case study on road construction

Road construction and its socio-economic and health impact: a case study of Atonsu lake road

• Open access
• Published: 06 July 2023
• Volume 1 , article number  6 , ( 2023 )

Cite this article

You have full access to this open access article

• Lyndon N. A. Sackey 1 ,
• Jeremiah Quartey 1 ,
• Augustus N. N. Nortey 1 ,
• Afia Tiwaa Obeng 1 ,
• Abigail Amoakoatta Okyere 1 &
• Phebe Y. Kayoung 1  

6717 Accesses

3 Altmetric

Explore all metrics

The construction of roads has become very popular in our age due to heightened modernization, industrialization and the various benefits reaped from proper road systems. However, construction processes massively contribute to environmental pollution and negatively impact socio-economic activities, necessitating this study. The aim of this paper is to assess the impact of road construction and socioeconomic and health impact using the Atonsu lake road construction as a case study. A mixed research method was employed in the research work. The quantitative method was used for primary data collection through the distribution of questionnaires, which surveyed the perception of inhabitants on the construction activity, and its health and socioeconomic effects. Through a qualitative method, data from the Kumasi south hospital was used to assess the impact of the activity on health. The income levels of inhabitants before and during the construction process were compared to the minimum wage in Ghana to analyze the impact on their socioeconomic lives. The research indicated that road construction has adversely impacted the health of Atonsu lake road inhabitants but saw a decline in the number of cases recorded at the hospital due to restrictions associated with COVID-19 and its accompanying stigmatization, which prevented people from reporting to the hospital. There was also a significant impact on the income levels of the inhabitants, which has a significant correlation with the frequency of client patronage before and during the construction of the road. Findings reinforce the need to greatly consider including effective dust abatement practices and a phase-by-phase implementation of road construction projects to reduce the negative impacts associated with the process.

Similar content being viewed by others

Environmental Sustainability: Impact of Construction Activities

Sustainable Road Infrastructure in Rural Areas in South Africa—A Preliminary Study

Reviewing the Negative Impacts of Building Construction Activities on the Environment: The Case of Congo

Avoid common mistakes on your manuscript.

1 Introduction

Large-scale spatial planning and urban development initiatives like road infrastructure have become increasingly popular in cities worldwide [ 1 ]. These projects improve connectivity [ 2 ], increase cities’ competitiveness, and attract investment [ 1 , 3 ]. Roads are constructed to aid in the flow of products and services [ 1 ] and increase economic stability and quality of life [ 4 ]. A road is a way or route connecting two locations on land that has been paved or renovated to allow travel by vehicles like cars, motorcycles, and horses. They contribute significantly to the nation's economic growth and advancement and offer important social benefits [ 5 , 6 ]. Design, construction, repair, and maintenance of roads are all parts of the complex of operations that make up road construction. Any nation's level of economic growth may be inferred from the quality of its road construction, which is also a crucial element in projecting a favorable image of the nation overseas [ 7 ] stated that several consistent efforts had been made to address the lack of road infrastructure, resulting in a massive increase in the number of road projects [ 8 ] across Ghana in recent years. Despite the many positive impacts, road construction activities are known to produce enormous amounts of dust into the environment resulting in air pollution [ 9 ]. Usually, in Ghana, roads are constructed based on political gains, the springing up of private residential facilities, and industrial establishments [ 2 ]. The study of road traffic, stone thickness, road alignment, and slopes led to the development of systems for building roads that used larger stones set in a regular, compact pattern and covered with smaller stones to create a solid layer [ 10 ]. Asphalt and concrete are promising and are widely used in modern-day road construction [ 11 ]. Roads have a significant role in economic growth and development and have significant social advantages. They are of critical importance to making a nation grow and prosper. A road network is essential for ensuring access to social, health, education, and employment services, and for other reasons related to the battle against poverty. Roads facilitate access to new locations and promote social and economic advancement. Because of these factors, road infrastructure is the most significant public asset [ 12 ].

Air pollution caused by road construction harms the environment, degrading the region’s air quality [ 13 ]. The degraded air resulting from road construction mainly contains silica, among other compounds [ 14 , 15 ]. When inhaled into the human body, silica can lead to lung cancer and other respiratory tract infections such as silicosis, cough, cold, etc. [ 14 , 16 ]. These diseases impact human health greatly and can have even worsening effects on people with underlying health conditions such as asthma, which may lead to the loss of life [ 17 ]. On the other hand, road construction is linked to environmental pollution and risks, which impact people's health and well-being in urban and rural areas [ 16 ].

Also, the varying implications of road construction activity on residents, commuters, traders, hawkers, and on-site workers on the road strongly correlate with the place's socioeconomic activity [ 1 , 2 ]. Traders along the stretch of road construction activity are displaced to make way for the construction to go on as when the road is completed, it will improve living conditions [ 1 ] and trading conditions; but the displacement of traders and hawkers during road construction greatly impacts their socio-economic lives [ 2 ]. According to a recent report by the World Resources Institute (a Maharashtra government knowledge partner), building dust is responsible for 71% of Mumbai's air pollution [ 2 ]. Air, water, and noise pollution result from these pollutants, causing irreversible damage to human health, with a concerning link between pollutants and cancer [ 18 ]. The formation of dust from vehicle movement, transport of building materials, and noise created by operating machines are the main types of environmental pollution associated with the construction of highways [ 19 ]. Breathing these specks of dust can damage the lungs and health. In Fig.  1 , dust particles are deposited in the respiratory system based on their size [ 20 ]. As mentioned, the main dust-related diseases affecting construction workers and residents are; Lung cancer, Silicosis, Chronic obstructive pulmonary disease (COPD) and Asthma.

A study area Map of Atonsu lake road showing major towns along the road

Various methods, such as roads, are employed to assess construction projects’ impact. An example is the Environmental Impact Assessment (EIA) [ 21 ]. Khanani et al. [ 1 ] and [ 2 ] assessed the socioeconomic aspect of road construction, while our research looked at the socioeconomic and health impact of road construction. The greatest difficulties in road development and construction come from what seems to be the city's unplanned urban growth, which has evolved in response to the city’s dense population and precedes the creation of numerous road networks [ 21 ]. As a result, there is already intense competition for land use in Ghana, with various residential communities and commercial buildings battling for available space with the operations of mechanics, artisans, markets, car parks, churches, taxi ranks, salons, and food vendors [ 21 ]. The location of Atonsu lake road will improve the connectivity of the adjoining towns within the stretch, bringing about competitiveness and attracting investment. However, the delay in its construction and the nature of the road could impact human health and socioeconomic activities. The aim of this paper is to assess the impact of road construction in Ghana on Traders and inhabitants living along highways, using the construction of Atonsu lake road as a case study. The research will help decision-makers and developers know the challenges that ensue when projects of such nature delay completion.

2 Research methodology

2.1 study area.

The study area is situated in the center of the Ashanti region within the boundaries of the Atonsu lake road in the Asokwa Municipal District and Bosomtwe District. It lies within the latitude 6˚40′39″ N and longitude 1˚35′2″ W with a total land size of 25.31 km 2 and a population of over 125,642 according to the 2021 population and housing census. Atonsu lake road was chosen because it’s a major road that connects many towns where socioeconomic activities occur and its construction has also taken too long. This study used five major towns along the lake road: Atonsu, Agogo, Esereso, Feyiase, and Aputuogya. These towns were chosen since they comprise the hub of commercial activities along the route, with market centers, bus terminals, filling stations, hospitals, and schools. Every day, people commute in and out of these areas to go about their daily routines, making them highly susceptible to both the health and socio-economic effects of road construction.

2.2 Sample size and sampling technique

A mixed research method was employed in the research work. The quantitative method was used for primary data collection through the distribution of questionnaires, which surveyed the perception of inhabitants on the construction activity, and its health and socioeconomic effects. Through a qualitative method, data from the Kumasi south hospital was used to assess the impact of the activity on health. This was done by using records of inhabitants who had visited the facility and reported of respiratory-related disease within the period of the road construction. The random sampling technique was used in this study to disseminate questionnaires. Regarding the populace of the Asokwa metropolitan assembly, 400 individuals participated in the survey using Slovin’s formula [ 22 ]. This sample size will give us sufficient data to be evaluated and generalized to the whole population [ 23 ].

where N is the total population, e is the margin error.

The population of the Asokwa municipality was used as given by the 2021 Population and Housing Census report. And a margin of error used was 0.05 since that was the p-value used throughout our analysis of results.

2.3 Survey instruments

Questionnaires and key informant interviews were used for the primary data collection in the field [ 24 ]. 400 questionnaires were randomly distributed to road users, including traders, residents, commercial drivers, onsite workers, and hawkers, within the study area to assess the impact of road construction on socioeconomic and health impact. These respondent types were used because they comprise the people who live alongside and use the road and conduct business activities on the stretch. All 400 questionnaires were retrieved as respondents were assisted to fill and return on the spot. The questionnaire was in two sections: Section I and II. Section I: focused on the demographic characteristics of the respondents, such as gender, marital status, level of education, and occupation. Section II: centered mainly on the road and its impacts on the health and socio-economic lives of the respondents in three sub-sections (A, B, C), where ‘A’ asks questions about the Road construction and its inception, ‘B’ focuses on assessing the health status of respondents and their respective hospitals visited and ‘C’ evaluated the socio-economic impact of the Road construction activities on the respondents. ‘A’ and some parts of ‘B’ were developed on a Likert rating scale measuring respondents’ opinions by asking how much they agreed or disagreed with a particular statement. While ‘C’ and the other part of ‘B’ are a mix of binary choice, multiple-choice and open-ended questions, allowing respondents to freely share their perceptions and opinions and provide precise responses to the subject. A hypothesis was drawn from the responses generated from the questionnaire, which will be validated in the later part of this study. A survey was conducted at the various health facilities through key informant interviews with the records department of the hospitals along the Atonsu lake road. Responses from the questionnaire provided specific details of the hospitals to visit. The survey provided information on how these hospitals’ operations have been impacted by the activities of the road construction and the kinds of health problems reported at the hospital since the construction of the road began.

Secondary data from the hospital’s statistical unit was obtained to determine the number and respiratory-related diseases reported to the health facility during the several phases of the construction. The diseases reported over the previous years of the road construction phase to the current phase will be studied to enhance our data analysis process.

The survey was conducted according to established ethical guidelines, and consent was obtained from the participant. The Humanities and Social Sciences (HuSSREC) of Kwame Nkrumah University of Science and Technology approved of this research.

2.4 Data analyses

The data collected from these surveys were analyzed using the Statistical Package for Social Sciences (SPSS) Model (Version 20) and XLSTAT (Version 2018).

3.1 Socio-demographic information

As shown in Table 1 , a total of 400 respondents were interviewed during the research, there were more males than females. Out of this number, 53.75% were married, 41% were single and 5.25% were divorced. With respect to the age variable, the highest number of respondents were between 26 and 35, representing 31.3% and the lowest were respondents above 61, representing 13,3%. Considering the educational levels of the people interviewed, most of them have secondary level 54.3%, with only 4% who had various postgraduate programs. This indicates that it is a highly educated community. Concerning occupations, they were categorized into trade, technical, professional, transport services [drivers and conductors (mates)] and others (students and Unemployed) here, the highest number of the respondents are in trading 47.0%, 18.75% various professional jobs and 5.75% into technical jobs.

3.2 Perception of road

As shown in Table 2 , out of the 400 people interviewed, 84.75% agreed that they were given prior notice before the construction, whiles 15.25% disagreed with having prior notice. Most traders (63.0%) disagreed with allowing traders to relocate temporarily. A large number of people, 52.25%, disagreed with the contractor doing regular dust abatement.

3.3 Perception of the population on health

As shown in Fig.  2 , 81% of the respondents agreed with claims of high levels of noise pollution, while 19% disagreed. Most of the respondents confirmed having difficulty breathing. 67.75% agreed to have experienced adverse effects of the construction on their health, while 32.35% disagreed. A majority agreed to develop eye irritations and most of them reported this at the hospital. 59.25% were unaffected by the high noise level and 40.75% agreed to have experienced the effects of noise on their health. Most respondents reported symptoms of respiratory tract infection.

Perception of respondents on health effects of road construction activity in the area

3.4 Trend of upper respiratory tract infections from Agogo hospital

Figure  3 shows that over 2800 people reported to the hospital with RTIs in 2018. This, however, saw a drop in 2019, which recorded a total of 1856 cases. In 2020 we saw a steep reduction, which amounted to a total of 526 cases being recorded. In 2021 we saw a steep decline, with the total number of cases recorded as 613 cases.

Impact of road construction activities on the health of road users within the study area

3.5 Socioeconomic impact

The socioeconomic impact of the construction activity of the area focused mainly on how it has affected the income levels of inhabitants. The results showed that road construction strongly correlated with the area's socioeconomic activities, such as the frequency with which clients patronize the goods and services of service providers [ 25 ]. To find out if the income levels of the traders were affected, data on the range of income levels before and during the construction process was taken. Also, data on the frequency of clients’ patronage was taken to determine the socioeconomic impact of road construction on traders. To ascertain if these variables (income levels and clients’ patronage before and during the road construction) are significant with each other, a cross-tabulation Chi-square test was run at a confidence level of 95% which yielded a p-value of 0.00 each for before and during, showing high significance.

From the analysis, many respondents earn between GHC 50–400 and GHC 400–800, indicating 65 and 53 of the total questionnaires administered. Also, for income levels between GHC 801–1200, a total of 38 respondents was recorded. Of the respondents earning > GHC 1200, there were 28 respondents.

From the analysis, Table 4 assesses the relationship between the income levels of respondents and the frequency of client patronage during the construction process, a total of 165 of the sample size, were earning between GHC 50–400 and a total of 51 of the respondents earned between GHC 400–800. For income levels between GHC 800–1200, a total of 29 respondents were recorded and for income levels > GHC 1200, a total of 13 respondents were recorded. The results indicated that there are more responses ending in less than GHC 800.

4 Discussion of findings

4.1 socio-demographic information.

In the study area, there were more males than females and socioeconomically, this could cause a lot of social vices in the area [ 26 ]. The data indicated that 47% of the respondents are into trading and the displacement of the majority of them, as a result of the road construction, could lead to unemployment. Also, 24.5% worked in the technical and transportation sectors; hence, the road construction delay and the road's bad nature could affect their incomes. Most of the inhabitants are youth; between 26 and 35 years, the road construction and the delay due to financial challenges could affect economic activities. This could affect the livelihoods of these youth within the catchment area.

4.2 Perception on road

The majority of the traders whose opinions were collected during the survey at the markets on the Atonsu lake road believed they had received appropriate notice of the road construction before it started. However, there were no other locations or provisions for them to temporarily relocate during the road construction. This meant that most of the displaced market traders effectively went out of business or had to scale down in their trade size since most of them had to compete for space or even perch with other unaffected traders. From the interviews with the traders along the roadside, it was recorded that some traders lost their containers, and stores and resorted to using a small table shaded by an umbrella stand to trade, whiles some had to put a cloth on the floor to sell their items. This indicates that in addition to losing their business place, they were continuously exposed to hot and humid weather. Most traders discussed how they had lost customers because certain customers chose to support specific stall layouts and structures. Although it has been theorized that the location of a trader's choice of trade in a market does not directly correlate with the trader's survival, location is still a key factor in determining whether a deal is successful or not. It has been confirmed by the decrease in earnings from the traders as they moved [ 2 ]. Due to the regular switching of positions and absence due to road construction activities, customers who frequently relied on positions to locate a trader could no longer do so. As the construction and demolition exercises were extremely disruptive and chaotic to typical shopping activities, some customers would hunt for new dealers to buy from, while others would be discouraged from attending the market and visiting alternate markets. The traders said that, in addition to the complaints, the contractor was present on the site every day until the project was completed. The disruption and chaos caused by the road construction, such as the noise and dust, prevented the dealers from taking a day off. Additionally, the construction was completed earlier than expected. This indicates that many things changed in their environment since some could not return to their original positions and others' health was affected [ 27 ]. The fact that the contractor barely performed dust abatement meant that the air they breathed could affect their health, and the majority of the traders complained that it made their products look unappealing because dust accumulated on them. An interview with the drivers revealed that they had to spend significantly more money having their cars washed because they now had to visit the washing bay daily, impacting their revenue. Several also stated that some passengers refused to board their vehicle because the seats were covered with dust or the vehicles lacked air conditioning, forcing them to breathe dust in the air [ 19 ]. Market vendors whose operations are close to road construction are displaced, particularly women, who lack alternatives and experience negative effects on their ability to make a living as traders. Instead of reducing informality, road construction initiatives that don't consider the predicament of traders frequently end up escalating challenges and inconveniences [ 27 ].

4.3 Perception on health

A health assessment suggested that more of the population experienced adverse health effects from the construction, associating their symptoms with eye irritations and RTIs. The movement of vehicles and transportation of construction materials contributed to the formation of dust clouds [ 28 ], which resulted in difficulty in breathing, as most of the population agreed. According to a greater percentage of the residents, headaches, coughs, sore throats, catarrh, among others, were more prevalent among them during the construction’s climax phase due to their consistent exposure to dust. In their research, Ghanney et al. [ 29 ], these symptoms are associated with respiratory tract infections, which addresses the effects of dust exposure on street sweepers. However, some residents failed to report their complications to the hospital because they couldn’t afford the cost, especially in their current state of low sales and reduced income levels. Meanwhile, the analyzed data acquired from Agogo Hospital showed a contrary report that construction activities’ air pollution greatly impacts human health. This data shows a greater number of RTI cases reported in 2018, which was before the construction of the Atonsu lake road. During the construction period (2019–2021), there was a reduction in the number of cases, with 2020 noted as the year with very few cases reported, which contrasts with our hypothesis. This contrast can be linked to the impact of the COVID-19 pandemic, which was on the rise in 2020 [ 30 ]. We can associate the reduction in the number of RTI cases in this period to a number of factors that followed the pandemic. One major factor was the fear of being stigmatized with Covid-19 when you visit the hospital with symptoms of respiratory infections because they are very similar to that of COVID-19 [ 31 ]. Most people resorted to treating mild coughs, catarrh, fever, etc., traditionally by preparing herbal drinks with neem tree, Hibiscus leaves, “pr3kese” a local spice that is known to have various health benefits. Induced quarantine by the government lessened frequent plying of the roads and kept people indoors, primarily reducing interactions and exposure to dust from the road, which can be seen as an appositive aspect of the pandemic [ 1 ]. Some residents talked about frequently inhaling warm water and wearing nose masks to protect them from the dust instead of the COVID-19 virus when the ban on quarantine was lifted. The fear of contracting the virus also made people adopt measures such as frequent hand washing, regular use of sanitizer, avoiding contact with infected areas, etc., which protected them from the Covid-19 virus and other viruses that could cause respiratory infections. [ 32 ], elaborated on a category of Noise-Induced Hearing Loss (NIHL) which was most widespread in hearing loss associated with a blast overpressure, known as blast-induced hearing loss. Residents around the construction site complained of extreme noise pollution, especially when contractors had to blast rocks for construction. The discomfort associated with this activity was difficult to bear; however, most of the population did not experience any health complications related to the noise. They attested to the fact that advance notice was given to all residents to evacuate their homes for some days when the blasting exercise was about to take place. This can account for why most of them were not affected health-wise by the noise since the distance from the blast is a major factor in determining the effect of noise on human health [ 33 ].

4.4 Socio-economic impact

4.4.1 income and frequency of clients cross tabulation, before the construction process.

In our bid to understand the relationship and significance of frequency on the income levels of the people, we run a cross-tabulation Chi-square analysis at a confidence level of 95%. This yielded a significance value of P < 0.00, indicating that the relationship is very significant in Tables 3 and 4 . This revealed that the income levels of the people in the Atonsu lake road area before the construction primarily ranged from GHC 50.00–800.00. This is seen in the total number of people with such income levels, i.e. 192 out of 400. This represents almost half the sample size. Hence, this indicates that road construction has impacted their income levels. Also, the results during the construction process, revealed that patronage frequency was very low for more than 110 of the sample size, and ranged between GHC 50.00–400.00 income levels. This represents a sharp decline in the frequency and income levels recorded before. According to [ 34 , 35 ], the minimum wage in Ghana is GHC 13.53/day and the minimum monthly salary is GHC 365.31. This is consistent with most respondents’ earnings (GHC 50.00–400.00). However, this could have been better if the road construction activity was critically checked to reduce its impact on their socio-economic lives.

5 Conclusion and future perspective

From the study, the main health complication associated with road construction activity is Upper Respiratory Tract Infections (URTI). This decreased in frequency in the number of cases recorded due to the rise of COVID-19 at the time and its accompanying restrictions and stigmatization. Also, the income levels of the people showed to be very significant with the rate at which people engaged in business activities, as more people moved from earning between GHC 50–800 to earning between GHC 50–400. Although income levels were reduced, it is still consistent with the minimum wage in Ghana, it could have been better if not for the impact of the road construction. Nonetheless, we recommend that contractors invest more in dust abatement procedures, by employing the services of adequate water tankers. Appropriate reallocation schemes should be used, such as proper market developments and affordable housing schemes. Also, a clear separation between developed and undeveloped areas is necessary to avoid the relocation of residents owing to road extension projects. The local government authorities and traditional leaders should also properly enforce the legislation to prohibit construction on roadways, which would later be demolished to make space for expansion projects when the region is expanded and the current road infrastructure is at capacity. Road maintenance should be done regularly throughout the nation to maximize the longevity and durability of roads. Finally, further studies can be conducted on other health pollutants relating to road construction, its harmful effects, and the age groups affected more.

Availability of data and materials

They are available upon request.

Khanani RS, Adugbila EJ, Martinez JA, Pfeffer K. The impact of road infrastructure development projects on local communities in peri-urban areas: the case of Kisumu, Kenya and Accra Ghana. Int J Commun Well-Being. 2021;4(1):33–53.

Article   Google Scholar  

Adugbila EJ, Martinez JA, Pfeffer K. Road infrastructure expansion and socio-spatial fragmentation in the peri-urban zone in Accra Ghana. Cities. 2023;133:104154.

Labi S, Faiz A, Saeed TU, Alabi BNT, Woldemariam W. Connectivity, accessibility, and mobility relationships in the context of low-volume road networks. Transp Res Rec. 2019;2673(12):717–27.

Mostafa HM. Road maintenance in Africa: approaches and perspectives. E3S Web Conf. 2018;38:01005.

Ghosh PK, Dinda S. Revisited the relationship between economic growth and transport infrastructure in India: an empirical study. Indian Economic J. 2022;70(1):34–52.

Ng CP, Law TH, Jakarni FM, Kulanthayan S. Road infrastructure development and economic growth. In IOP conference series: materials science and engineering. Bristol: IOP Publishing; 2019.

Google Scholar  

Pheng LS, Hou LS. The Economy and the Construction Industry. Constr Qual Econ. 2019,9:21–54.

Edriss AK, Chiunda C. Interfaces between road infrastructure and poverty in Africa: the case of Malawi, 1994–2013. J Soc Economics Res. 2017;4(1):9–21.

Wijeyesekera DC, Bakar I, Lim SM, Abidin NZ. Dust emissions from unpaved ground surfaces. ARPN J Eng Appl Sci. 2016;11:16.

Amakye SY, Abbey SJ, Booth CA, Oti J. Road pavement thickness and construction depth optimization using treated and untreated artificially-synthesized expansive road subgrade materials with varying plasticity index. Materials. 2022;15(8):2773.

Article   CAS   Google Scholar  

Lay M, Gordon B, Fred J. Road. Encyclopedia Britannica. 2022.

World Highways. “Asphalt Paving, Compaction & Testing” Asphalt Paving, Compaction & Testing|World Highways. 2015.

Giunta M. Assessment of the environmental impact of road construction: modelling and prediction of fine particulate matter emissions, Building and Environment, 2020. 176.

Guo J, Lin W, Li H, Zhang Z, Qin X. Numerical simulation study on spatial diffusion behavior of non-point source fugitive dust under different enclosure heights. Int J Environ Res Public Health. 2023;20(5):4361.

Harrison J, Dawson L. Occupational health: meeting the challenges of the next 20 years. Safety and health at work. 2016;7(2):143–9.

Gharpure A, Heim JW, Vander Wal RL. Characterization and hazard identification of respirable cement and concrete dust from construction activities. Int J Environ Res Public Health. 2021;18(19):10126.

Tan S, Chen S. Macrophage autophagy and silicosis: current perspective and latest insights. Int J Mol Sci. 2021;22(1):453.

Guzder J. Reflections on the privacy of self and the drive to create in the context of dislocation. In Privacy. New York: Routledge; 2019.

Book   Google Scholar  

Barikayeva N, Nikolenko D, Ivanova J. About forecasting air pollution in the construction of highways. IOP Conf Ser Mater Sci Eng. 2018;463(4):042016.

Subramanian N, Abhyankar EV. (2019). Construction dust causes, effects and remedies. New Building Materials and Construction World.

Ikioda F. The impact of road construction on market and street trading in Lagos. J Trans Geogr. 2016;55:175–81.

Langat DCR. Microcredit and its relationship to small and medium enterprises growth in Konoin Subcounty, Kenya. Int J Adv Res. 2018;6(4):961–8.

Park W, Kim R, Roh S, Ban H. Analysis of major environmental impact categories of road construction materials. Sustainability. 2020;12(17):6951.

Glasow AP. Fundamentals of survey research methodology. Bedford: MITRE Product; 2005.

Zucker DM. How to do case study research. In teaching research methods in the social science. New York: Routledge; 2016.

Nanor JN. Assessment of the effects of quarrying activities on some selected communities in the lower Manya Krobo District (Master of Philosophy Thesis, University of Ghana). 2011.

Zuo J, Rameezdeen R, Hagger M, Zhou Z, Ding Z. Dust pollution control on construction sites: awareness and self-responsibility of managers. J Clean Prod. 2017;166:312–20.

Habybabady RH, Sis HN, Paridokht F, Ramrudinasab F, Behmadi A, Khosravi B, Mohammadi M. Effects of dust exposure on the respiratory health symptoms and pulmonary functions of street sweepers. Malaysian J Med Sci MJMS. 2018;25(6):76.

Ghanney EB, Mijinyawa Y, Ana G. Meteorological and air pollution assessment from road use and construction in the eastern and greater Accra regions (Ghana). J Environ Earth Sci. 2022;12(3):25–39.

Hamid A, Akhtar S, Atique SA, Huma Z, Mohay Uddin SG, Asghar S. Ambient air quality & noise level monitoring of different areas of Lahore (Pakistan) and its health impacts. Polish J Environ Stud. 2019;28:2.

Pruthi Sandhya. COVID-19, cold, allergies and the flu: what are the differences? Mayo Foundation for Medical Education and Research (MFMER). 2022.

Kenu E, Frimpong J, Koram K. Responding to the COVID-19 pandemic in Ghana. Ghana Med J. 2020;54(2):72–3.

Esson J, Gough KV, Simon D, Amankwaa EF, Ninot O, Yankson PW. Livelihoods in motion: linking transport, mobility and income-generating activities. J Trans Geogr. 2016;55:182–8.

Wage indicator, minimum wage News, 2023. https://mywage.org/ghana/salary/minimum-wages . Accessed 4 Mar 2023.

Download references

There was no funding for this research work.

Author information

Authors and affiliations.

Department of Environmental Science, Faculty of Biosciences, Kwame Nkrumah University of Science and Technology, PMB, Kumasi, Ghana

Lyndon N. A. Sackey, Jeremiah Quartey, Augustus N. N. Nortey, Afia Tiwaa Obeng, Abigail Amoakoatta Okyere & Phebe Y. Kayoung

You can also search for this author in PubMed   Google Scholar

Contributions

LNAS, JQ, ANNN, ATO, AAO, PKK design of the experiment, JQ, ANNN, ATO, AAO data collection, LNAS, PKK Supervision, LNAS, JQ, ANNN, ATO, AAO, PKK Analysis of data.

Corresponding author

Correspondence to Lyndon N. A. Sackey .

Ethics declarations

Ethics approval and consent to participate.

The experiment was conducted according to established ethical guidelines, and consent was obtained from the participant. The Humanities and Social Sciences (HuSSREC) of Kwame Nkrumah University of Science and Technology approved of this research. The study complies with all regulations relating to research, including experimentation on human subjects via interviews.

Consent for publication

Since this study is not attempting to re-publish/publish any third party or author's previously published material, this section does not apply.

Competing interests

The authors declare no competing interests.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Sackey, L.N.A., Quartey, J., Nortey, A.N.N. et al. Road construction and its socio-economic and health impact: a case study of Atonsu lake road. Discov Environ 1 , 6 (2023). https://doi.org/10.1007/s44274-023-00009-x

Download citation

Received : 01 May 2023

Accepted : 20 June 2023

Published : 06 July 2023

DOI : https://doi.org/10.1007/s44274-023-00009-x

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Road construction
• Health impact
• Find a journal
• Publish with us
• Track your research

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• My Account Login
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Open access
• Published: 25 March 2022

Evaluating the impact of highway construction projects on landscape ecological risks in high altitude plateaus

• Chao Li 1 , 2 ,
• Jingxiao Zhang 1 ,
• Simon P. Philbin 3 ,
• Xu Yang 4 ,
• Zhanfeng Dong 5 ,
• Jingke Hong 6 &
• Pablo Ballesteros-Pérez 7  

Scientific Reports volume  12 , Article number:  5170 ( 2022 ) Cite this article

7465 Accesses

14 Citations

4 Altmetric

Metrics details

• Environmental sciences

In China and other countries, many highway projects are built in extensive and high-altitude flat areas called plateaus. However, research on how the materialisation of these projects produce a series of ecological risks in the landscape is very limited. In this research, a landscape ecological risk analysis model for high-altitude plateaus is proposed. This model is based on the pattern of land uses of the surrounding area. Our study includes buffer analysis, spatial analysis, and geostatistical analysis. We apply the model to the Qumei to Gangba highway, a highway section located in the southeast city of Shigatse at the Chinese Tibet autonomous region. Through global and local spatial autocorrelation analysis, the spatial clustering distribution of ecological risks is also explored. Overall, our study reveals the spatial heterogeneity of ecological risks and how to better mitigate them. According to a comparison of the risk changes in two stages (before and after the highway construction), the impact of highway construction on the ecological environment can be comprehensively quantified. This research will be of interest to construction practitioners seeking to minimize the impact of highway construction projects on the ecological environment. It will also inform future empirical studies in the area of environmental engineering with potential affection to the landscape in high-altitude plateaus.

Similar content being viewed by others

Heat health risk assessment in Philippine cities using remotely sensed data and social-ecological indicators

FSC-certified forest management benefits large mammals compared to non-FSC

Disappearing cities on US coasts

Introduction.

Since the beginning of the twenty-first century, the Chinese government has implemented specific construction plans for highways in the Tibet plateau. This has resulted in a major increase in the size and capacity of the highway network in this region 1 . However, the complex and special geological environment of the Tibet region has not been adequately considered in the construction process creating many negative effects. The progressive destruction of vegetation during highway construction has caused significant landscape changes along the highway route resulting in a fragmented landscape. At the same time, waste discharges and exhaust gases during the construction process have eroded the soil and will surely create further soil erosion and water pollution problems 2 . Recent research has been mainly focused on evaluating the impact of highway construction on urban areas 3 , 4 , 5 , lakes and river basins 6 , 7 and nature reserves 8 , 9 . However, hardly any research has investigated the impact of highway construction in ecosystems at high altitudes in the Plateau. In the case of Tibet, the complex terrain, climatic conditions and the difficulty of data acquisition, has resulted in very limited research.

The Tibet plateau is a densely distributed area of nature reserves and an important ecological security barrier between China and the wider continent of Asia. It plays an important role in climate regulation, soil and water conservation, biodiversity protection and carbon accumulation. However, due to the fragility of the very cold environment and its sensitivity to external disturbances, the overall landscape pattern of such areas can be easily fragmented (i.e. acquire poor stability and resilience to external changes). Consequently, intensive highway construction will likely result on major negative impacts on the biodiversity and landscape patterns of this area.

At present, methods for ecological risk assessment include various modelling approaches from diverse fields like physics, chemistry and biology. Many of them involve simulation as well as other risk measurement methods, such as the expert judgment. Physics, chemistry and biological-based simulation involve developing a model in order to observe and test the envisaged impact of events on the ecological properties of the ecosystem, including biological life. The general risk measurement method is used to estimate the importance of the risk, which is broken down in probability and severity. When there are many system property uncertainties or just different opinions on the ecological value of some of the system components, the expert judgment method can also become an alternative method. Similarly, ecological risk assessment methods based on remote sensing technologies and geographic information systems are becoming increasingly common. These technologies are also used to process and analyze changes in the ecological environment 10 , 11 . In terms of ecological risk evaluation indicators, there tends to be two main aspects analyzed: heavy metal pollution in soils and landscape pattern changes. Landscape ecological risk assessment pays more attention to spatio-temporal heterogeneity. Understanding this heterogeneity can help decision-making for regional risk prevention and improve landscape management 12 , 13 . However, empirical studies that confirm the advantages and application of these models are extremely limited.

This research study builds on existing research and adopts the Qumei to Gangba highway section in the southeast city of Shigatse. This city is located in the Tibet autonomous region of China. The study considers the 10-km buffer zone along the highway in a high-altitude plateau area and develops a landscape ecological risk assessment model based on the landscape pattern. The spatial and temporal distribution of the landscape ecological risks along the highway are evaluated before and after the highway construction. This analysis reveals the characteristics and extensive impacts of highway construction on the landscape pattern and the landscape ecological risks of the area. It will also provide an improved understanding of the technical support required for the post-construction stage of ecological restoration in these high-altitude areas.

Literature review

The impact of infrastructure construction on landscape patterns.

Engineering construction activities deeply affect the regional landscape and the level of biological activity, including human life. On the microscopic scale, construction activities frequently result in heavy metal pollution, which change the structure of the surface soil and affects the migration of species 14 . On the landscape scale, construction activities often lead to long-term fragmentation.

Based on GIS and the buffer analysis method, Minxi et al. 15 used several landscape metrics to quantitatively study the impact of hydropower projects construction on landscape structure changes. Yang et al. 16 investigated the process of hydropower facility development and the ecological characteristics of a river basin. Then, they systematically evaluated the impact of cascade hydropower development on the river landscape. Chen et al. 17 adopted the West–East gas pipeline project in China as the research object, and studied its impact on the landscape pattern by comparing the changes of landscape indicators along its route.

In terms of research on the impact of highway construction on the landscape pattern, Qianqian et al. 18 used remote sensing data to compare the pre- and post-construction stages in a 500-m buffer zone along the highway. Yong et al. 19 analysed a 15-km buffer zone on both sides of the Yuyi expressway (Chongqing section). With the help of ArcGIS technology and landscape ecology methods, these researchers explored gradient differences of land use and landscape pattern evolution. Keken et al. 20 monitored the land cover typologies in Czech Republic’s highways for nearly 60 years and studied the impact of road construction and operation on changes in landscape structure. Huang and Ting 21 studied the impact of road construction on landscape fragmentation and evaluated their influence and environmental variables. Mothorpe et al. 22 studied the impact of the American intercontinental highway construction on land use, and provided technical support for future agricultural land protection plans. Huang et al. 23 investigated Taiwan’s township roads and showed that road construction led to varying degrees of isolation and fragmentation on the overall landscape pattern.

The above researches provide an effective method for in-depth evaluation of the changes of regional landscape pattern in the process of engineering construction, but it does not consider the vulnerability and particularity of plateau landscape under extremely complex geological conditions. Therefore, with the help of the above research methods, it is necessary to evaluate the evolution characteristics of landscape pattern in the process of highway construction in high-altitude Plateau, and the research results can provide differentiated governance schemes for landscape restoration in similar regions.

The impact of infrastructure construction on ecological risks

With the rapid development of infrastructure development, the ecological impact of these works has caused higher stress levels in the surrounding environment. Many Chinese scholars have focused on theory and methods development of landscape ecological risks assessment. Consequently, a research framework of landscape ecological risk assessment has already been developed.

However, the landscape factors that have been considered are mainly focused on the quantification and analysis of landscape patterns. These research results have generally been used to characterize landscape ecological risks indirectly, though. In this vein, different scholars have selected relevant indicators, methods and models and applied them to different regions and for different evaluation purposes. For example, Jian et al. 24 proposed environmental protection measures for tunnel construction by evaluating the ecological risks and provided a reference for the construction of similar geotechnical projects. Wang 25 studied the ecological environment along a high-speed railway project and put forward several measures to prevent its disturbance. He and Xiong 26 selected several indicators and analyzed their impact on the ecological environment with the aim of reducing ecological risks. Jing et al. 27 verified the impact of the construction of a cross-sea bridge on the water quality and ecological environment of the surrounding sea. Jianhua et al. 28 used multi-scale and multi-source remote sensing data to monitor and analyze the ecological environment and socio-economic impacts along a railway project. Fang 29 analyzed the main ecological environmental problems and the main influencing factors of metal mine construction projects. Then, some methods for ecological environment assessment were proposed for those mine projects.

In terms of the impact of highway construction on ecological risks, many researchers have also adopted different study perspectives (from micro and macro frameworks, and from single roads to whole road networks). Bian et al. 30 assessed the ecological and health risks of the surrounding areas of a highway project by analyzing the persistence of heavy metals in the soil. Limin et al. 31 quantitatively studied the gradient changes of the landscape pattern in different buffer zones of roads according to an ad-hoc landscape pattern index. Liang and Nianlai 32 adopted an index evaluation method to analyze the impact of highway construction on the surrounding ecological environment. Specifically, they focused on how to alleviate the impact of highway construction to maintain the sustainable use of local natural resources. Ting and Zongmin 33 proposed an ecological environment impact assessment index system for highway construction. And more recently, Igondova et al. 34 proposed another ecological impact assessment method for roads construction. In this case, though, their method included an ecological risk assessment index which could be applied in quantitative research studies.

Research on landscape ecological risk assessment methods

Landscape ecological risk assessment frequently encompasses two methods: those based on risk sources, and those based on sink and landscape patterns. The so-called early landscape ecological risk assessment is one of the former methods, but it is not applicable when the regional ecological stress factors are not clear 35 , 36 . Evaluation methods based on landscape patterns directly evaluate landscape ecological risks from spatial patterns on a regional scale. In this regard, ecological risk assessment methods based on land use and cover changes have become a research hotspot 37 .

In the process of ecological risk assessment, the construction of landscape ecological risk indices based on landscape patterns or land mosaic patterns have become prominent too 38 . The risk level of the landscape can also be measured from the existence of external forces (i.e. rapid urbanization) and the internal pressure capacity of the landscape 39 . In terms of evaluation indicators, the expert scoring method is frequently used as research method. The sorting normalization method is also used as well, but the assignment method is conditioned by some subjective weight normalization which can affect the eventual assessment of different evaluation indicators 40 , 41 . As a systematic method, a multi criteria decision making (MCDM) method can reduce the interference of decision-makers' subjective judgments on decision-making, and is widely used in various fields of ecological risk assessment 42 , 43 . Among the MCDM methods, the analytic hierarchy process (AHP) method and the technique for order preferences by similarity to ideal solutions (TOPSIS) method are commonly used methods. Peng et al. 44 used AHP to determine the weight of each factor affecting wetland ecological risk, and established a risk assessment model. Based on the improved AHP, Zhang et al. 45 combined the fuzzy comprehensive evaluation (FCE) method and applied the improved AHP to the ecological environment impact assessment of expressways, and concluded that the improved method has good objectivity and reliability, applicability. Luan et al. 46 used TOPSIS method to conduct multi criteria decision making analysis on environmental pollution caused by land cover change, and the research results provided scientific guidance for regional environmental management and planning. In addition, the combination of AHP and TOPSIS method has become an important method for ecological risk assessment 47 , 48 .

Recently, landscape ecological risk assessment methods usually accommodate multi-element ecological risk assessment. However, the selection of evaluation indicators remains subjective. Also, there is a lack of quantitative standards for ecological risks. Most of the evaluations are based on qualitative analysis, whereas quantitative analysis still is in an exploratory stage. Consequently, a comprehensive ecological risk assessment system needs to be established as soon as possible. Namely, a standard method for ecological risk assessment should be determined to provide a theoretical basis for further ecological environmental management and risk prevention measures. This method will be applied to highway construction projects, unlike many prior studies which have focused on cities or river basins.

Research area and research methods

General situation of the study area.

The extensive repair work for the highway maintenance of the Qumei to Gangba highway section commenced in early 2019. This highway is located in the southeast city of Shigatse, in the Chinese Tibet autonomous region. The route is 145.64 km long and runs through three counties and seven towns. The terrain has a high altitude in the middle and low altitude at both ends. The highway runs along riverbed terraces and at the foot of mountain slopes. The average altitude of the highway is around 3850–4750 m above sea level.

The geomorphology of the area where most of the highway is located is a plateau valley landform with some mid-mountain landforms. Wide river valley areas are mostly U-shaped valleys and narrow V-shaped river valleys. The landforms are mainly developed as modern riverbeds, floodplains and river terraces accumulating and cutting out structural landforms. High terraces are generally developed in the valley area, with high mountains on both sides of the valley and steep slopes. The main source of replenishment for the river is rainfall water. Most of the highway track is located at the foot of the mountain slope where the topography is relatively even.

The area where the route is located has a continental climate. The main features are dryness and lower levels of oxygen due to altitude, sufficient sunshine, and a wide temperature difference between day and night. Meteorological records from the Chinese Meteorological Bureau from recent years show that the annual average temperature of Sajia County is 5.5 °C, and the annual precipitation is 35 mm. The Sangzizhu area has a dry climate and thin air, with an average annual temperature of 4.9 °C and an average annual rainfall of 430 mm. The terrain of Gamba County is complex with large vertical changes. The highest point is 6783 m above sea level, whereas the lowest is 4375 m above sea level (a height difference of 2.408 m), and the annual average temperature is 1.5 °C. We used ArcGIS software to extract the vector boundary of some counties in Shigatse region, and superimposed the vector data of highway from Qumei to Gamba in the software. Finally, we got the location of the highway (Fig.  1 ).

Location of the highway section from Qumei to Gamba.

Model construction

Buffer analysis.

A highway is a linear structure, and its impact on the ecological environment is generally located on both sides of the highway. Buffer analysis is an analysis tool for studying the ecological and environmental effects of roads and other linear structures. Based on this method, the spatial variation of the impact of roads on a certain indicator can be studied by comparing the spatial differences of related indicators in buffer zones. This method has been widely used in the fields of ecology and pollution evaluation 49 . Like previous research, on the basis of Fig.  1 , this study uses the highway as the baseline and uses the buffer analysis tool built in ArcGIS10.8 to generate a 10-km buffer zone on both sides. The influence process of highway construction on the landscape pattern and ecological risk is discussed indirectly by using the differences measured in each index and buffer zones (see Fig.  2 ).

10-km buffer zone of the highway from Qumei to Gamba.

Construction of the ecological risk index

Ecological risk refers to the probability of which a regional ecosystem can remain stable in response to external disturbances (including natural and/or human activities). A landscape ecological risk model is a method that quantifies ecological risks by considering internal and external factors of the ecosystem. Hence, an ecological risk index model evaluates the ecological risk status of a region from the landscape characteristics such as the landscape disturbance index that characterizes the degree of external disturbance. It also uses the landscape vulnerability index to describe the ability of the ecosystem to maintain stability.

The landscape ecological risk index along the highway is composed of two parts, namely the landscape disturbance index and landscape vulnerability index. The Landscape disturbance index ( E i ) includes three factors: the landscape fragmentation index ( C i ), the landscape separation index ( S i ) and the landscape dominance index ( Di ). These indices are weighted to interpret some system results.

Landscape disturbance index ( E i )

The landscape disturbance index can reflect the disturbance degree of different landscape types. We select here a landscape fragmentation index, landscape separation index and landscape dominance index to build the Landscape disturbance index 50 .

Landscape fragmentation index ( C i )

Landscape fragmentation is a process in which the regional landscape structure gradually tends to be complex, heterogeneous and discontinuous under the action of external factors. The landscape fragmentation index has important ecological significance in measuring the loss of biodiversity. This index is calculated as:

In ( 1 ), n i is the number of patches of landscape type i and A i is the total area of landscape type i .

Landscape separation index ( S i )

The landscape separation index is used to describe the degree of separation between landscape patches and quantify the connection between various ecosystems. Its expression is:

In ( 2 ), A is the total area of the landscape.

Landscape dominance index ( D i )

The degree of landscape dominance is the difference in the areas of various patches. It describes the degree in which the overall landscape is dominated by the main landscape types. The greater the landscape dominance grows (or falls), the higher the increase (decrease) in area ratio differences of every landscape type. The calculation formula is:

In ( 3 ), R i is the ratio of the number of risk evaluation units with landscape type i respect to the total number of risk evaluation units; F i is the ratio of the number of patches with landscape type i to the total number of patches in the evaluation unit; L i is the ratio of the area of landscape type i to the total area of the evaluation unit.

After calculating the three indices of C i , S i and D i according to formulae ( 1 )–( 3 ), a normalization has to be performed. This research assigns the following weights for the fragmentation, separation and dominance indices: 0.5, 0.3, and 0.2, respectively. The calculation formula of the landscape disturbance index for each land cover type of each risk assessment unit is obtained as follows:

Landscape vulnerability index ( F i )

The landscape vulnerability index refers to the ability of the regional ecosystem to resist external disturbances. This is the internal factor that characterizes ecological risks. This index is closely related to the stage of the landscape in the process of natural alternation. According to classification of land uses, the landscape of the study is divided into six main types: cultivated land, wood land, grass land, water land, construction land, and unused land. Also, based on previous studies and the actual conditions of the Tibet region (Yanxu et al. 2015; Qiran and Hui 2014), the expert scoring method is used to determine the value of the landscape vulnerability along the highway. The value of landscape vulnerability index for each land type is deemed as follows: unused land is 6, water land is 5, cultivated land is 4, grass land is 3, wood land is 2, construction land is 1, and then normalized to obtain various types of landscape vulnerability indexes. The values above then become 0.2857, 0.2381, 0.1905, 0.1429, 0.0952, and 0.0476, respectively.

Landscape ecology risk index ( ERI k )

In order to connect the internal composition of the landscape pattern with the regional ecological risk status, and combine it with the above indices, this study uses the area proportions of each landscape type. This way, a landscape ecological risk index model is built. This index model can be used to describe the relative ecological properties loss of a certain sample area. The latter fully reflect the changes in ecological risks caused by the change of landscape pattern. The specific construction of the model is as follows:

In ( 5 ), ERI k is the ecological risk index value of the kth risk assessment unit; A i is the area of land cover type i in the kth risk assessment unit; A is the area of the kth risk assessment unit; E i and F i are the value of landscape disturbance index and landscape vulnerability index of land cover type i in the kth risk assessment unit, respectively.

Spatialization of ecological risks

Division of the evaluation unit

According to the scope of the study area and the sampling workload, we proposed a method for combining point grid evaluation units with the area vector evaluation units. If the grid is too large, it cannot reflect the spatial difference. If the size is too small, the landscape type is too single and the calculation is too large. Referring to previous studies, the grid should be 2–5 times of the average patch area 51 , 52 . Therefore, on the basis of considering the actual situation and workload of the research area, a square of 2 km × 2 km was used as the smallest area (unit) to calculate the landscape comprehensive index. The sampling method was equidistant for all squares. This process can be easily performed with ArcGIS. This way, 820 different risk units were analyzed, and the comprehensive ecological risk index was calculated for each of them. Then, the ecological risk level at the center point of each 2 × 2 km 2 sample area was used as the representative location of the index evaluation.

Spatial autocorrelation analysis

Global spatial autocorrelation is a description of the spatial characteristics interrelation of several attribute values of an entire region 53 . It is used to test whether the value of a spatial variable is related to the value of the same variable in the adjacent space. This study uses Moran's I coefficient to reflect the similarity of the attribute values of spatially adjacent regional units. The formula for calculating the global Moran’s I coefficient is:

In ( 6 ), W ij represents the spatial connection matrix between spatial unit i and j with i  ≠  j ; n is the total number of spatial units; X i is the attribute value of the spatial unit i ; X j is the attribute value of spatial unit j ; and \(\overline{X}\) is the attribute average value of all spatial units. The value of I ranges from − 1 to 1. When I  = 0, it means that the space autocorrelation is irrelevant. When I takes a positive (negative) value, there is a positive (negative) correlation.

Local spatial autocorrelation analysis can also be applied when: it is necessary to consider if there is a local spatial aggregation of high or low values of observations; when we want to find out which regional unit contributes more to the global spatial autocorrelation; and when we want to find to what extent the global assessment of the spatial autocorrelation conceals some abnormal local conditions. This study used the local autocorrelation LISA index to analyze the spatial aggregation of high and low values of the regional ecological risk index. Then, we explored the abnormal areas of the ecological risk distribution by identifying potential high or low “hot spots” with significant ecological risks. The formula for the LISA index is as follows:

Data source and processing

The basic data used in this study mostly encompassed remote sensing image data, vector data of the highway and administrative area, as well as land use and land cover data.

Remote sensing image data. The large and medium-level repair of the highway maintenance works on the Qumei to Gamba section of the highway took place between early 2019 and October 2020. In addition, because the characteristics of ground classes in high altitude areas of the plateau are often not obvious, the accuracy of selected training samples may not be guaranteed if low-resolution images are used, which may reduce the accuracy of classification. This study selected Sentinel-2 remote sensing images taken in October 2016, October 2018, and October 2020. The data was acquired from the European Space Agency’s (ESA) website with a resolution of 10 m. This raw source data went through some image processing such as orthorectification, registration, and band fusion. The preprocessed data as a data source for supervised classification (Table 1 ).

The vector data of the highway and administrative area. The administrative area data was mainly gathered from the administrative boundary data of the Shigatse area, including the administrative boundaries and administrative centers of the township-level regions. The vector data of the highway from Qumei to Gamba section of the highway was also collected. This data was sourced from the Resource and Environmental Science and Data Center of the Chinese Academy of Sciences ( https://www.resdc.cn/ ).

Land use and land cover data. With the support of ENVI5.3 software and ArcGIS10.8, a support vector machine algorithm was used to supervise and classify the preprocessed remote sensing images. The sentinel-2 image data of different phases were also automatically interpreted and the accuracy of the data remained always above 90% (Table 1 ). Finally, we took cultivated land, forest land, grassland, water area, construction land and unused land as the main landscape types in this study.

Analysis and results

Analysis of landscape pattern changes.

According to the land use of the study area and the six-type land classification of the Chinese Academy of Sciences (cultivated land, wood land, grass land, etc.), the overall landscape pattern of the study area was analyzed. It can be observed in Fig.  3 that grass land, wood land and unused land were the main types of land use. This is common because of the topography of the Tibetan plateau region. Construction land was mainly distributed in several towns and villages such as the Qumei township, and along the highway. Cultivated land was distributed in large extensions around residential areas. The area of water land was the smallest, mainly distributed on both sides of the highway.

Map of land usages in the study area from 2016 to 2020.

In order to fully show the influence law of highway construction on the landscape pattern, therefore, we estimated the land use transfer matrix along the highway in 2016–2018 and 2018–2020. By comparing the land use type transfer before and after highway construction, the influence of highway construction on landscape pattern was quantitatively evaluated. The calculation results are shown in Tables 2 and 3 respectively.

In the process of land type transfer, the main types of land type transfer are unused land to grassland (98.17 km 2 ) and grassland to forest (105.48 km 2 ). Unused land and grassland were turned out, accounting for 19.01% and 9.62% of their respective areas in 2016, respectively. Meanwhile, woodland, unused land and water area accounted for 20.19%, 13.85% and 13.80% of their respective areas in 2018, respectively. However, due to the small total area of water area, the converted area was less than 1 km 2 . It can be concluded from the transfer of land use types from 2016 to 2018 that the area of unused land was reduced before road construction, and the vegetation coverage was increased overall. Essentially, the overall transfer area of land use types was very small, and this transfer scenario was relatively simple.

It can be seen from Table 3 that the transfer of land use types is significantly more complicated after highway construction. The bidirectional transfer between grassland and unused land and between grassland and forest land is the main type of transfer. Among them, 203.50 km 2 of unused land was transferred from grassland, followed by 140.45 km 2 of unused land from grassland to woodland. Meanwhile, unused land and forest land were the main sources of grassland transfer, with 49.26 km 2 and 46.60 km 2 respectively, but their area was much smaller than that of grassland transfer.

Compared with the land use transfer before highway construction, it can also be seen that during highway construction, the transfer proportion of all land types increased significantly. The proportion of grassland and water area transferred out is more than 20%, and the area of water area, unused land and construction land transferred out account for 51.47%, 32.08% and 30.69% of the total area respectively.

According to the above analysis, it can be inferred that in the process of highway construction, grassland was damaged and polluted, and a large part of grassland was transferred to unused land, and the change of landscape pattern was more obvious than before highway construction, and the change of landscape pattern was more obvious after highway construction.

Due to the differences in the distribution of land use types, the landscape also had a significant change over time. As can be deduced, the major changes involved the grass land, unused land and wood land (Fig.  4 ). Initially, grassland was the most abundant landscape type, and it accounted for more than half of the total area of study. Wood land increased by 3.65% in 2016–2018, and by 3.27% in 2018–2020. Conversely, grass land decreased by 2.74% and 8.85% across the two periods analyzed. The unused land showed opposite trends in both periods (first a decrease of 1.08% before the highway construction, then an increase of 5.24% after the highway construction).

Changes in various landscapes (land use types) along the highway in 2016–2018 and 2018–2020.

In order to study the changes of landscape patterns quantitatively, we calculated the landscape ecological risk index with Fragstats4.2 software (see Table 4 ). The landscape indices of different landscape (land use) types also showed significant changes. Before and after the highway was constructed, the ecological risk index of cultivated land and construction land was the smallest. The reason was that the distribution of cultivated land and construction land was relatively concentrated, so the integrity of the patch improved. Unused land was highly fragmented and had the highest risk index, which was mainly related to the nature of land use in the landscape type. Combining the landscape indices of various landscapes, the ecological risk index along the highway in 2016, 2018, and 2020 was also calculated (with Formula 5 ). After its calculation, the ecological risk index of the three phases were 0.2316, 0.2217, 0.2822, respectively. Judging from the overall changes in the four years of the time span, the ecological risk index of the buffer zone did not change significantly before the highway was constructed. However, afterwards, the ecological risk index increased much more than in the previous period (a differential increment of 0.0605 and total increase of 27.29%). This variation indicated that the ecological risk index along the route showed a steeper upward trend after the highway was constructed.

Analysis of the temporal and spatial changes of the ecological risk index

Distribution characteristics of ecological risk index.

Based on the grid model and the Kriging interpolation method performed with the geostatistical analyst module of ArcGIS software, the ecological risk index of each risk assessment unit was spatially interpolated. This allowed us to create the ecological risk index spatial distribution map along the highway (see Fig.  5 ).

The distribution of ecological risk index along the highway in 2016, 2018, and 2020.

In order to better discriminate the ecological risk changes in the areas along the highway and further study the impact of project construction, we created five ecological risk index value bins, namely: low risk area (0 ≤ ERI < 0.2), sub-low risk area 0.2 ≤ ERI < 0.4), medium risk area (0.4 ≤ ERI < 0.6), sub-high risk area (0.6 ≤ ERI < 0.8) and high risk area (0.8 ≤ ERI ≤ 1.0). An ecological risk level distribution map was drafted (see Fig.  6 ). It can be seen therefore that during the construction of the highway, the ecological risk level changed significantly. This was mainly manifested as a generalized shift from a lower level of risk to a higher level of risk in most areas.

Distribution of ecological risk levels in 2016, 2018, and 2020.

Time series changes of the ecological risk index

In Table 5 , the analysis highlights that the proportion of area occupied by the low risk area was the largest in the three years of the study (51.35%, 57.71%, and 36.65%, respectively). The area of low risk increased slightly before highway construction, then decreased sharply during the construction period (a decrease of 21.07%). The area change of the medium risk area was in second place (it increased by 10.58% during the construction of the highway). The area of high risk had the smallest proportion, but the maximum area appears in 2020, when reached the 2.76% of the total area. The sub-high risk area had the smallest amount of change in the three phases (area changes remained below 1% in the two periods). In general, before the road was constructed, areas with low ecological risk increased, while areas with high ecological risk slightly decreased. However, after the highway was constructed, the opposite change occurred. This indicated that the ecological security status during the construction of the highway affected the surrounding area to some extent.

Based on the previous classification of ecological risk grades, the analysis of ecological risk grade transfer changes helps to identify further local differences. Hence, with the help of a spatial statistical analysis method, the ecological risk transfer matrix of the 10-km buffer zone in two periods could be calculated (see Tables 6 , 7 ).

In Table 6 we can see that the changes in the ecological risk exhibited the characteristics of a higher level of risk shifting to adjacent lower risks from 2016 to 2018. The total area of the reduced ecological risk level area was 250.85 km 2 , while the area with increased ecological risk level was just 0.26 km 2 . This indicates that the ecological security situation along the highway improved during this period. In the process of ecological risk transfer and transformation encompassing all levels, the dominant area transfer occurred from sub-low risk to low risk, with an area of 183.83 km 2 accounting for 73.21% of the total transferred area. Overall, it can be observed that the ecological environment along the highway was generally better before the road was constructed.

In Table 7 we can see that the changes in ecological risk grade between 2018 and 2020 were still dominated by the transfer of adjacent risk levels. In this time span, the area of transfer across risk levels was minimal. During the period of highway construction, the ecological risk changes were mainly based on the transfer of low-level risks to adjacent high-risks. The total area of the areas with elevated risk levels was 1071.34 km 2 , which accounted for 37.10% of the total area. The area with reduced risk levels was 12.47 km 2 , which was far less than the total area with increased risk. These results highlight that the overall ecological risk along the road rose during the construction of the highway and the overall ecological security situation showed a downward trend.

Spatial autocorrelation analysis of the ecological risk index

Global spatial autocorrelation analysis.

With the aid of the “Geoda” software, we calculated the global Moran’s I index value of the ecological risk index in 820 2 × 2 km 2 sample areas along the highway in 2016, 2018 and 2020. Namely, this calculation was used to verify the spatial pattern and significance of the ecological risk index of the entire study area.

The Moran’s I index in 2016, 2018 and 2020 was 0.954, 0.952 and 0.955, respectively. The index in the three phases was also positive, and its change trend not very obvious. However, this indicates that the ecological risk index of the area along the highway had a moderately strong positive correlation with the spatial distribution (i.e., adjacent plots had mutual influence and showed a high degree of spatial similarity). In the time series, the spatial clustering of plots with similar land use showed first a trend of ecological index decrease, and then, an increase. This indicates that the overall spatial differentiation of the landscape ecological risk intensity increased slightly along the route during the construction of the highway.

Local spatial autocorrelation analysis

The global autocorrelation analysis mainly considers the overall distribution of the ecological risk index. However, the local spatial autocorrelation helps to discriminate more fine-grained (local) change characteristics and spatial patterns. The LISA graph of local autocorrelation was used in this case to analyze the ecological index risk plots around the highway. Rook's adjacency weight matrix was also used to calculate the local autocorrelation results along the highway from 2016 to 2020 (see Fig.  7 ).

Local spatial autocorrelation diagrams of the ecological risk index.

It can be observed in Fig.  7 that the types of the spatial distribution of the ecological risk index in the three phases was mainly of high–high aggregation and low–low aggregation. The low–low aggregation areas of ecological risk were mainly distributed in the northern and southeastern parts of the study area. This indicates that the ecological risk intensity in this region was low, and the ecological risk intensity of adjacent areas was also low. The latter may have happened because the area had more wood land and this ecosystem was more stable. The high–high aggregation areas of ecological risk were mainly concentrated in the central and southern part of the study area. This highlights that the ecological risk grade of these areas was high, and the ecological risk grade of adjacent areas was also high. This probably happened because the area had more unused land and low vegetation coverage. Finally, it can also be seen that the number of high–high concentration plots increased significantly from 2018 to 2020. This may have happened because grass land was extensively destroyed during the highway construction process, which further increased the area of unused land.

At present, studies on the impact of engineering construction on ecological risk are mainly focused on large-scale hydropower projects and urban roads in developed areas, while there is still a lack of systematic research on ecological risk assessment in high-altitude Plateaus. The process which highways impact the ecological environment is quite complex. This study has adopted the macro perspective of the landscape pattern and enabled the development of an ecological risk model. According to a comparison of the risk changes in two stages (before and after the highway construction), the impact of highway construction on the ecological environment has been quantified. Although there are certain limitations in this study, the analysis results are consistent with the actual survey situation for the highway.

Regarding extant research on the impact of highway construction on the ecological environment, most researchers have focused on time-based studies over an extended time period 20 , 54 . The research reported here adopted the time period corresponding to the highway works maintenance program. Remote sensing data analyzed in the study were selected from the same month of each year with a unified time scale. Furthermore, the landscape pattern and ecological risk indicators before and after highway construction were compared to study the impact of highway construction on the ecological environment. At the same time, due to the complex terrain in Tibet and the abrupt land features, in order to improve the classification accuracy, Sentinel-2 remote sensing images with a resolution of 10 m were selected. These images were combined with actual field surveys and, in some cases, incoherent data were corrected.

The analysis of landscape pattern before and after highway construction identified that the landscape pattern changes were more pronounced during the construction period than before construction. However, the overall landscape pattern as well as the types of main land uses along the highway did not change. This is in line with the conclusions of Gang, HuiJun, and Guang 55 on wetlands in arid areas, and Haihang et al.’s 56 on urban areas. The analysis of the ecological risk index before the highway construction scenario highlights that the average ecological risk index of the constructed highway is significantly higher than before. Although this is similar to the research study of Shiliang et al. 57 , it is fundamentally different to the conclusions of other researchers like Mo et al. 52 . A likely cause of this difference may be that the impact of construction on ecological risks of urban roads is different at the county-level and township roads, that is, urban areas may have more diversified risk sources.

For the convenience of discussion, we compared the differences between the relevant references and this study in methods, locations and main results in the form of tables (Table 8 ). It can be seen that some scholars have analyzed the ecological risk changes of river basins by establishing ecological risk models. The results show that in the process of urbanization, the ecological environment quality of these areas is declining, which is similar to the research conclusion of this paper 58 , 59 . Yuan et al. 58 also analyzed the relationship between flood feature values and landscape patterns through multiple linear regression methods, which provided useful information for regional landscape planning and watershed flood control planning. Different from the above references, this study quantitatively studies the changes of various landscape indicators during highway construction, which can provide specific reference for regional landscape governance. At the same time, Research on the impact of infrastructure construction on ecological risk levels identifies that the transfer of ecological risks mostly involved the transfer between adjacent risk grades (i.e., cross-risk transfer rarely occurred). This is similar to the conclusions of Jie et al. 40 on the ecological risks of the entire Qinghai-Tibet Plateau landscape. Furthermore, the research on the spatial heterogeneity identified that the ecological risk index of the three phases along the highway had a high degree of positive correlation with the spatial distribution. This spatial distribution was mainly of high-high aggregation and low-low aggregation. Particularly, the area with high-high aggregation increased significantly during the construction period. This is similar to the spatial distribution characteristics of the ecological risk index obtained by Fengjiao and Xiao 60 and Xie et al. 59 . However, their research objects and methods were quite different.

Relevant references also reported changes in regional landscape patterns and ecological risks caused by highway construction, which is similar to the method used in this study 52 , 61 . By analyzing the changes in the landscape pattern, these two references concluded that the landscape type with the largest area increase was construction land, while the area of unused land increased the most in the study. This may be caused by the large differences in population, economy, topography and other factors in the study area, which is located at extremely high altitude. It is worth mentioning that the highway is a single linear project in this study, so the research method of buffer zone is also adopted. Oliveira et al. 62 considered social and environmental factors, and used buffer and landscape index analysis to analyze the changes in the landscape pattern of the Rio Doce State Park in Brazil. They believed that the substantial reduction of farmland area should be given enough attention. Different from this reference, this study established a landscape ecological risk model and studied the aggregation effect of ecological risks through autocorrelation analysis. In addition, although some literatures do not establish ecological risk models, they take other factors such as social and economic into consideration. Through regression analysis, they studied the relationship between landscape pattern and socio-economic factors qualitatively or quantitatively, which had a certain positive effect on the development of ecological economy 63 , 64 , and is also some of the shortcomings of this study. By synthesizing social, historical, economic, environmental and other factors, constructing an ecological risk assessment model under the influence of multiple factors, thus laying the foundation for the establishment of a scientific and practical ecological development model, may be a valuable future research direction.

Changes in the landscape pattern of land use will inevitably lead to changes in regional ecological functions. Therefore, studying ecological risk changes from the perspective of its landscape structure helps to objectively reflect the ecological risk pattern of highways (and probably other linear infrastructures as well).

Conclusions

Combining the information of land use and land cover data with a Chinese highway vector data, this research study has evaluated the impact of highway construction on the landscape. As a result, an ecological risk model for a high-altitude plateau area has been proposed using a geographic information system combined with statistical analysis. The following conclusions are obtained from the Qumei to Gangba highway section (Tibet autonomous region), where this model has been implemented:

From 2016 to 2020, the major land use type in the buffer zone along the highway was grassland, accounting for more than 52% of the surrounding area. This land use was followed by woodlands and unused lands. The overall trend of land use change was a decrease in grassland area. Conversely, the area of woodland, cultivated land, construction land and water-based land increased. The type of transfer mainly involved the conversion of grassland to woodland, and a balanced mutual conversion between grassland and unused land. This means that before the highway construction, the area of grassland and unused land transferred to each other was almost the same. However, after highway construction, the area of grassland converted to unused land was comparatively much larger, whereas he mutual transfer area of other land use types was negligible.

The average values of the ecological risk indices at 2016, 2018 and 2020 were 0.2316, 0.2217 and 0.2822. This indicates that the ecological risk intensity of the study area also showed different trends before and after the highway construction. Before the highway construction, the ecological risk slightly reduced. Whereas after the road construction, the ecological risk increased significantly.

During the study period, the transfer of ecological risks mainly involved transfers between adjacent risk levels (cross-risk transfers seldom occurred). However, before the highway construction, the ecological risks were mainly transferred to the lower-level risk level. After the construction project, the ecological risks were mainly transferred to a higher risk level.

Global autocorrelation analysis performed with the Moran index indicated that the ecological risk index along the highway had a high degree of positive correlation with the spatial distribution. In other words, adjacent land uses interacted with each other and showed a high degree of spatial similarity. In terms of time series, the spatial agglomeration of land plots with similar ecological risk levels did not show an obvious trend. Based on the local autocorrelation analysis, though, it was found that the spatial distribution of ecological risk index was dominated by high–high aggregation and low–low aggregation. The areas of high-high aggregation increased significantly during the highway construction period and this evidences that the highway construction had an important influence on the spatial distribution of ecological risks.

This study has qualitatively and quantitatively analyzed the process and ecological effects of highway construction on the ecological environment from the perspective of the landscape pattern. It has also provided some new approaches for the study of infrastructure-related ecological risks in high-altitude plateaus. The study has mainly considered the impact assessment of a single highway, but have neglected other roads along the route. Similarly, the corresponding relationship between different buffer distances and landscape ecological risk has not been discussed. Those simplifications will be analysed in further research work, but we find it is highly unlikely that they could have affected the major conclusions from this study.

Due to the fragility of the plateau landscape in Tibet and the complexity of the geological conditions, how to carry out a quantitative analysis of the impact of construction roads on the ecological environment for this type of area has become the key to ecological environmental assessment. This study constructed a plateau high-altitude landscape ecological risk assessment model and analyzed the impact of highway construction on ecological risks dynamically. Its research results provided technical support for the construction of differentiated ecological restoration programs, and also provided a new research perspective and research foundation for ecological risk assessment of engineering construction projects in high-altitude plateau.

Tsering, D. Transport development in Tibet since the democratic reform in 1959. J . Tibetan Stud. 76–85 (2019).

Yan, X. et al. Relationships between heavy metal concentrations in roadside topsoil and distance to road edge based on field observations in the Qinghai-Tibet Plateau, China. Int. J. Environ. Res. Public Health. 10 (3), 762–765 (2013).

CAS   PubMed   PubMed Central   Google Scholar  

Berling-Wolff, S. & Jianguo, W. U. Modeling urban landscape dynamics: A case study in Phoenix, USA. J. Urban Ecosyst. 7 (3), 215–240 (2004).

Google Scholar  

Jianzhou, G., Yansui, L. & Beicheng, X. Spatial heterogeneity of urban land-cover landscape in Guangzhou from 1990 to 2005. J. Geogr. Sci. 19 (2), 213–224 (2009).

Pan, L., Zhang, H. & Liu, A. Analysis of threshold of road networks effecting landscape fragmentation in Chongqing. J. Ecol. Sci. 34 (5), 45–51 (2015).

CAS   Google Scholar  

Paukert, C. P., Pitts, K. L., Whittier, J. B. & Oldenc, J. D. Development and assessment of a landscape-scale ecological threat index for the Lower Colorado River Basin. J. Ecol. Indic. 11 (2), 304–310 (2011).

Li, H., Yu, Q., Li, N., Wang, J. & Yang, Y. Study on landscape dynamics and driving mechanisms of the Shudu Lake catchment wetlands in Northwest Yunnan. J . West China Forest. Sci. 42 (3), 34–39 (2013).

Yunqing, H., Jinxi, W. & Hong, J. The dynamics of land cover change pattern and landscape fragmentation in Jiuzhaigou Nature Reserve, China. J . Proc. SPIE Int. Soc. Opt. Eng. 7498 , 74983P (2009).

Hu, L. et al. Landscape pattern in Nanwenghe nature reserve and its driving forces. J . Protect. Forest Sci. Technol. 0 (7), 18–21 (2015).

Li, X. et al. Land use/cover and landscape pattern changes in Manas River Basin based on remote sensing. J . Int. J. Agric. Biol. Eng. 13 (5), 141–152 (2020).

Andrejs, R. & Merkurjevs, J. Software tool implementing the fuzzy AHP method in ecological risk assessment. J . Inform. Technol. Manag. Sci. 20 (1), 34–39 (2017).

Peng, J., Dang, W., Liu, Y., Zong, M. & Hu, X. Research progress and prospect of landscape ecological risk assessment. J. Acta Geogr. Sin. 70 (04), 664–677 (2015).

Xu, Y., Fu, B. & Lü, H. Research on landscape pattern and ecological processes based on landscape models. J. Acta Ecol. Sin. 30 (1), 212–220 (2010).

Forman, R. Road ecology: A solution for the giant embracing us. J. Landsc. Ecol. 13 (4), 3–5 (1998).

Minxi, W., Shiliang, L., Baoshan, C. & Min, Y. Impacts of hydroelectric project construction on nature reserve and assessment. J. Acta Ecol. Sin. 28 (4), 1663–1671 (2008).

Yang, K., Deng, X., Xue-Ling, L. I. & Wen, P. Impacts of hydroelectric cascade exploitation on river ecosystem and landscape: A review. J. Acta Ecol. Sin. 22 (5), 1359–1367 (2011).

Chen, L. D., Wang, J. P., Jiang, C. L. & Zhang, H. P. Quantitative study on effect of linear project construction on landscape pattern along pipeline. J. Sci. Geogr. Sin. 30 (2), 161–167 (2010).

Qianqian, H., Luomeng, C. & Shanlin, W. Impact of expressway on land use and landscape pattern: A case study of Putan Guai to Chenghao section of Inner Mongolia Provincial Highway 103. J. Environ. Protect. Sci. 35 (05), 58–61 (2009).

Huang, Y., Li, Y. & Ying, H. Responses of Chongqing-Yi Expressway to land use change and landscape pattern. J. Nat. Resourc. 30 (09), 1449–1460 (2015).

Keken, Z., Sebkova, M. & Skalos, J. Analyzing land cover change—The impact of the motorway construction and their operation on landscape structure. J . Geogr. Inform. Syst. 6 (5), 559–571 (2014).

Mengna, H. & Ting, M. Assessing the impacts of China’s road network on landscape fragmentation and protected areas. J. Geo-inform. Sci. 21 (8), 1183–1195 (2019).

Mothorpe, C., Hanson, A. & Schnier, K. The impact of interstate highways on land use conversion. J. Ann. Reg. Sci. 51 (3), 833–870 (2013).

Wu, C.-F., Lin, Y.-P., Chiang, L.-C. & Huang, T. Assessing highway’s impacts on landscape patterns and ecosystem services: a case study in Puli Township, Taiwan. J. Landsc. Urban Plan. 128 , 60–71 (2014).

Jia, L., Lei, T. & Yan, S. H. Environmental impact analysis and control measures in tunnel construction. J. Appl. Mech. Mater. 90–93 , 3250–3253 (2011).

ADS   Google Scholar  

Wang, M. Analysis of high-speed railway construction on ecological environment impact and environmental protection contribution. J. Railway Constr. Technol. https://doi.org/10.3969/j.issn.1009-4539.2015.04.019 (2015).

Article   Google Scholar  

He, Y. & Xiong, C. Environmental impact of waste slurry in pile foundation construction of high-speed railway bridges and its countermeasures. J. Adv. Mater. Res. 383–390 , 3690–3694 (2011).

Jing, C. et al. Influence of cross-sea bridge project on water quality and ecological environment of nearby sea and its tracking, monitoring and verification. J. Ocean Dev. Manag. 37 (10), 96–100 (2020).

Jianhua, X., Mingquan, W., Shijian, Z. & Zheng, N. Remote sensing monitoring of ecological and economic impacts of major Railway construction along the Belt and Road. J. Sci. Technol. Eng. 20 (11), 9 (2020).

Fang, L. On ecological environment impact assessment of metal mine construction project. J. Nonferrous Metals (Min. Sect.). 64 (03), 58–60 (2012).

Bian, B., Lin, C. & Wu, H. S. Contamination and risk assessment of metals in road-deposited sediments in a medium-sized city of China. J. Ecotoxicol. Environ. Saf. 112 , 87–95 (2015).

Limin, Y., Yanhai, Z., Rongzu, Q. & Xisheng, H. The influence of regional road construction on landscape ecology on both sides: A case study of Jiangle County, Fujian Province. J. Sichuan Agric. Univ. 33 (2), 159–165 (2015).

Liang, Z. & Nianlai, C. Analysis on the impact of Jinwu Expressway on ecological environment based on comprehensive index evaluation method. J. Environ. Sustain. Dev. 44 (3), 137–139 (2019).

Ting, W. & Zongmin, W. Study on eco-environmental impact assessment system of highway construction. J. Resourc. Econom. Environ. Protect. 3 , 129–132. (2015).

Igondova, E., Pavlickova, K. & Majzlan, O. The ecological impact assessment of a proposed road development (the Slovak approach). J. Environ. Impact Assessm. Rev. 59 , 43–54 (2016).

Chen, L., Fu, B. & Zhao, W. Source-sink landscape theory and its ecological significance. J. Front. Biol. China 3 (2), 131–136 (2008).

Wu, J. et al. Spatial differentiation of landscape ecological risk in opencast mining area. J. Acta Ecol. Sin. 33 (12), 3816–3824 (2013).

Wang, J., Cui, B., Liu, J., Yao, H. & Juan, H. The effect of land use and its change on ecological risk in the Lancang River watershed of Yunnan Province at the landscape scale. J. Acta Sci. Circumstan. 2 , 269–277 (2008).

Article   CAS   Google Scholar  

Xie, H. Regional eco-risk analysis based on landscape structure and spatial statistics. J. Acta Ecol. Sin. 28 (10), 5020–5026 (2008).

Jinggang, L. I., Chunyang, H. E. & Xiaobing, L. I. Landscape ecological risk assessment of natural/semi-natural landscapes in fast urbanization regions——A case study in Beijing, China. J. Nat. Resourc. 23 (1), 33–47 (2008).

Jie, W., Wanqi, B. & Guoxing, T. Temporal and spatial characteristics of landscape ecological risk in Qinghai-Tibet Plateau. J. Resour. Sci. 42 (9), 1739–1749 (2020).

Xuegong, X., Huiping, L., Zaiyi, F. & Rencang, B. Ecological risk assessment of wetland area in Yellow River Delta. J. Acta Sci. Nat. Univ. Pekinensis. 01 , 111–120 (2001).

Malekmohammadi, B. & Blouchi, L. Ecological risk assessment of wetland ecosystems using multi criteria decision making and geographic information system. J. Ecol. Indic. 41 , 133–144 (2014).

Campos, P., Paz, T., Lenz, L., Qiu, Y. & Paz, I. Multi-criteria decision method for sustainable watercourse management in urban areas. J. Sustain. 12 (16), 6493–6514 (2020).

Peng, L. et al. Research on ecological risk assessment in land use model of Shengjin Lake in Anhui province, China. J. Environ. Geochem. Health. 41 (6), 2665–2679 (2019).

Zhang, D., Yang, S., Wang, Z., Yang, C. & Chen, Y. Assessment of ecological environment impact in highway construction activities with improved group AHP-FCE approach in China. J. Environ. Monit. Assess. 192 (7), 451–469 (2020).

Luan, B. et al. Evaluating green stormwater infrastructure strategies efficiencies in a rapidly urbanizing catchment using SWMM-based topsis. J. Clean. Prod. 223 , 680–691 (2019).

Ramya, S. & Devadas, V. Integration of GIS, AHP and TOPSIS in evaluating suitable locations for industrial development: A case of Tehri Garhwal district, Uttarakhand, India. J . Clean. Prod. 238 , 117872 (2019).

Koc, K., Ekmekciolu, M. & Zger, M. An integrated framework for the comprehensive evaluation of low impact development strategies. J . Environ. Manag. 294 , 113023 (2021).

Xiumei, T., Yu, L., Yanmin, R., Yuchun, P. & Xingyao, H. Study on change of land use and ecosystem service value along expressway. J. China Agric. Univ. 21 (2), 132–139 (2016).

Fei, Z., Shanjiang, Y. & Dongfang, W. Ecological risk assessment due to land use/cover changes (LUCC) in Jinghe County, Xinjiang, China from 1990 to 2014 based on landscape patterns and spatial statistics. J. Environ. Earth. Sci. 77 (13), 491 (2018).

Rangel-Buitrago, N., Neal, W. J. & de Jonge, V. N. Risk assessment as tool for coastal erosion management. J. Ocean Coast. Manag. 186 , 105099 (2020).

Mo, W., Wang, Y., Zhang, Y. & Zhuang, D. Impacts of road network expansion on landscape ecological risk in a megacity, China: A case study of Beijing. J. Sci. Total Environ. 574 , 1000–1011 (2017).

ADS   CAS   Google Scholar  

Getis, A. & Ord, J. K. The analysis of spatial association by use of distance statistics. J. Springer Berlin Heidelberg. 24 (3), 189–206 (2010).

Yingxue, Z., Wenbo, M., Yong, W. & Dafang, Z. Impact of land use change on landscape pattern around expressways in Beijing. J. Geo-Inform. Sci. 19 (001), 28–38 (2017).

Gang, Z., HuiJun, G. & Guang, Z. Changes of wetland landscape pattern in arid inland area of Northwest China: A case study of inner flow area in Junggar, Xinjiang. J. Arid Land Resourc. Environ. 28 (8), 77–82 (2014).

Haihang, W., Qianhui, Z., Jiayao, Z. & Chunguo, Z. Analysis on dynamic change of landscape pattern of land use in Zhushan County. J. Forest Resourc. Manag. 6 , 76–83 (2018).

Shiliang, L., Zhifeng, Y., Baoshan, C. & Shu, G. Impact of road on landscape and ecological risk assessment: A case study of Lancang River Basin. J. Chin. J. Ecol. 8 , 897–901 (2005).

Yuan, Y. et al. Flood-landscape ecological risk assessment under the background of urbanization. J . Water. 11 (7), 1418 (2019).

Xie, H., Wang, P. & Huang, H. Ecological risk assessment of land use change in the Poyang lake Eco-economic zone, China. J. Int. J. Environ. Res. Public Health. 10 (1), 328–346 (2013).

Fengjiao, X. & Xiao, L. Ecological risk pattern in coastal areas of Jiangsu Province based on land use change. J. Acta Ecol. Sin. 38 (20), 7312–7325 (2018).

Mann, D., Anees, M. M., Rankavat, S. & Joshi, P. K. Spatio-temporal variations in landscape ecological risk related to road network in the Central Himalaya. J. Hum. Ecol. Risk Assess. https://doi.org/10.1080/10807039.2019.1710693 (2020).

Oliveira, B. R. D., Costa, E. L. D., Carvalho-Ribeiro, S. M. & Maia-Barbosa, P. M. Land use dynamics and future scenarios of the Rio Doce State Park buffer zone, Minas Gerais, Brazil. J. Environ. Monit. Assessm. 192 (1), 39.1–39.12 (2020).

Li, Y., Sun, Y. & Li, J. Heterogeneous effects of climate change and human activities on annual landscape change in coastal cities of mainland China. J . Ecol. Indic . https://doi.org/10.1016/j.ecolind.2021.107561 (2021).

Dadashpoor, H., Azizi, P. & Moghadasi, M. Land use change, urbanization, and change in landscape pattern in a metropolitan area. J. Sci. Total Environ. 655 (10), 707–709 (2019).

Download references

Acknowledgements

This research is supported by the Branch of China Road and Bridge Corporation (Cambodia) Technology Development Project (No.2020-zlkj-04); National Social Science Fund Projects (No.20BJY010); National Social Science Fund Post-financing Projects (No.19FJYB017); Sichuan-Tibet Railway Major Fundamental Science Problems Special Fund (No.71942006); Qinghai Natural Science Foundation (No. 2020-JY-736); List of Key Science and Technology Projects in China’s Transportation Industry in 2018-International Science and Technology Cooperation Project (Nos. 2018-GH-006 and 2019-MS5-100); Emerging Engineering Education Research and Practice Project of Ministry of Education of China (No. E-GKRWJC20202914); Shaanxi Social Science Fund (No. 2017S004); Xi’an Construction Science and Technology Planning Project (Nos. SZJJ201915 and SZJJ201916); Shaanxi Province Higher Education Teaching Reform Project (No. 19BZ016); Fundamental Research for Funds for the Central Universities (Humanities and Social Sciences), Chang’an University (Nos. 300102239616, 300102281669 and 300102231641).

The Branch of China Road and Bridge Corporation (Cambodia) Technology Development Project (No. 2020-zlkj-04), National Social Science Fund Projects (No. 20BJY010), National Social Science Fund Post-financing Projects (No. 19FJYB017), Sichuan-Tibet Railway Major Fundamental Science Problems Special Fund (No. 71942006), Qinghai Natural Science Foundation (No. 2020-JY-736), List of Key Science and Technology Projects in China’s Transportation Industry in 2018-International Science and Technology Cooperation Project (Nos. 2018-GH-006 and 2019-MS5-100), Emerging Engineering Education Research and Practice Project of Ministry of Education of China (No. E-GKRWJC20202914), Shaanxi Social Science Fund (No. 2017S004), Xi’an Construction Science and Technology Planning Project (Nos. SZJJ201915 and SZJJ201916), Shaanxi Province Higher Education Teaching Reform Project (No. 19BZ016), Fundamental Research for Funds for the Central Universities (Humanities and Social Sciences), Chang’an University (Nos. 300102239616, 300102281669 and 300102231641).

Author information

Authors and affiliations.

School of Economics and Management, Chang’an University, Xi’an, 710061, Shaanxi, China

Chao Li & Jingxiao Zhang

School of Civil Engineering, University of Science and Technology Liaoning, Liaoning Anshan, 114051, China

Nathu Puri Institute for Engineering and Enterprise, London South Bank University, London, UK

Simon P. Philbin

Harbin Normal University, Harbin, 150500, Heilongjiang, China

Institute of Eco-Environmental Policy and Management, Chinese Academy of Environmental Planning, Beijing, 100012, China

Zhanfeng Dong

Chongqing University (CQU), Chongqing, 400044, China

Jingke Hong

Departamento de Proyectos de Ingeniería, Universitat Politècnica de València, Camino de Vera s/n, 46022, Valencia, Spain

Pablo Ballesteros-Pérez

You can also search for this author in PubMed   Google Scholar

Contributions

C.L. wrote the main content of the manuscript. J.Z. determined the research content and research method of the manuscript. S.P.P. modified the grammatical structure of the manuscript. X.Y. did the calculations for part of the manuscript. Z.D. finished the data collection. J.H. made important revisions to the manuscript. P.B.-P. helped perform the analysis with constructive discussions.

Corresponding author

Correspondence to Jingxiao Zhang .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cite this article.

Li, C., Zhang, J., Philbin, S.P. et al. Evaluating the impact of highway construction projects on landscape ecological risks in high altitude plateaus. Sci Rep 12 , 5170 (2022). https://doi.org/10.1038/s41598-022-08788-8

Download citation

Received : 22 December 2021

Accepted : 07 March 2022

Published : 25 March 2022

DOI : https://doi.org/10.1038/s41598-022-08788-8

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

By submitting a comment you agree to abide by our Terms and Community Guidelines . If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Sign up for the Nature Briefing: Anthropocene newsletter — what matters in anthropocene research, free to your inbox weekly.

• Reference Manager
• Simple TEXT file

People also looked at

Original research article, causes and effects of contract management problems: case study of road construction.

• Institute of Construction Economics and Management, Faculty of Civil Engineering, Brno University of Technology, Brno, Czechia

Contract management is a crucial component of any project. As construction projects are complex and difficult to manage, adequate attention must be given to the related contract management issues. Inexpert management can bring about serious unfavourable consequences that can even result in a project failure. This study aims to explore a specific case study: A private road construction project implemented in the Czech Republic. The analysis consists in identifying potential problems and discussion of their implications. The problem is investigated on three levels: economic, technical and legal. The paper also considers contrasting attitudes of the contracting parties (buyer and supplier), e.g., from the point of view of the causes of problems. Several recommendations are formulated on the basis of the research findings. The results of this study have an ambition to improve contract management capabilities in the construction sector in order to prevent the occurrence of similar problems in future and contribute to our understanding of long-term effects of contract management problems throughout the life cycle.

Introduction

Construction projects typically involve a high degree of complexity. In the theory, complexity is understood as the number and heterogeneity of different interrelated elements ( Burke and Morley, 2016 ). Taking into consideration that construction projects 1) involve a high number of stakeholders, are 2) subject of frequent change orders, 3) of a long-term nature, and 4) affected by various influencing factors such as location, inflation, schedule targets, constrained budget, etc., it is difficult to understand, foresee and keep the under control ( Vidal et al., 2011 ; Vařbuchta et al., 2017 ; Kermanshachi and Safapour, 2019 ). In order to cope with the project complexity, the project itself should be supported with good-quality technical, economic, and contractual documentation. Unfortunately, many projects suffer from disputes between the parties involved, leading up to adverse consequences such as significant delays, loss of quality in follow-up work, or lack of future cooperation ( Lu et al., 2015 ). To imagine, National Construction Contracts and Law Survey reported that 30 percent of companies in the Great Britain had been involved in at least one dispute in the previous 12 months ( RIBA Enterprises, 2013 ). Such disputes are often caused by a misunderstanding of the contractual terms and conditions as well as violation of obligations, no matter if real or only perceived by one of the parties. Given regular occurrence of disputes in construction projects, good negotiating skills are becoming crucial ( Chow et al., 2012 ).

Research problem and aim of the paper

This paper deals with contract management problems and their influence on the construction and operation of a private road. Despite the fact that a wide body of knowledge on causes of claims, dispute resolution techniques, time and costs overruns, and project performance in general is available, there is a lack of studies that monitor these issues from a long-term perspective. In the case of the construction industry, this is essential because the duration of the life cycle of buildings is expected to be in the tens of years. At the same time, it is necessary to be aware that sooner or later the consequences of the decisions made in the early stages of the project will be felt. Although we know what the most common causes of disputes are and how they can be resolved, it is usually unclear to what extent the consequences of failing to resolve the dispute may increase in the future.

Accordingly, this study aims to investigate causes and effects of dispute in different phases of the life-cycle of a building facility. Therefore, the study addresses how contract management problems resulting from insufficient project preparation may affect not just the construction phase, but also the operation phase of the building facility’s life cycle. The single-case study analysed in this research points out how a long-term dispute can negatively affect the operation of an owner’s business; how it, for many years, has been tying contractor to a project which, from his point of view, had already been finished long ago; and especially how the continuously growing complexity of the problem significantly complicates its resolution.

Literature review

Project management literature provides a substantial body of knowledge concerning the assessment of a construction project’s success. The main success criteria are time, cost, and quality, also known as the “iron triangle” ( Ljevo et al., 2017 ). These criteria usually act as contradictive objectives and can be considered as interdependent parameters in a building project ( Hu and He, 2014 ). This mutual interdependency was analysed by many researchers, e.g. in terms of time and cost for water supply systems ( Zujo et al., 2017 ) and the balance of cost, time and quality for reinforced concrete ( Hosseini et al., 2017 ). The aspect of project cash flow is also crucial as it allows the assessment of working capital requirements ( Maravas and Pantouvakis, 2012 ).

The above-mentioned factors are crucial in construction disputes as well. Ilter (2012) deals with three categories of disputes, namely: extension of time, payments, and quality of works clearly corresponding to the iron triangle. Furthermore, study of Ilter (2012) identifies the relations between dispute categories with dispute factors such as late instructions by the employer, inadequate/incomplete specifications or unclear contractual terms. It should be emphasised that the contract is among the most important components of the construction project ( Safa et al., 2017 ) and project documentation forms an integral part of the contract. This importance is documented by Leśniak et al. (2018) , who point out that problems with project documentation are among the main causes of delays in both Poland and Slovakia. Disputes may arise for various reasons, in addition to usual ones between client and contractor such as cost and time overruns for ongoing projects ( Nahidi et al., 2017 ; Johnson and Babu, 2020 ; Shoar et al., 2022 ; Subramanya et al., 2022 ), disputes may also be related to inadequate cost estimations for repairing damages caused by large scale natural disasters, such as floods or windstorms ( Hanak and Korytarova, 2014 ).

Construction disputes may be destructive for projects ( Ilter and Dikbas, 2009 ), therefore efforts should be made to prevent them in the first place. This issue is highly topical within the research community; e.g., Lee et al. (2016) found 140 articles dealing with dispute prevention. In this relation, Molenaar et al. (2000) developed a structural equation model for predicting of construction contract disputes. As presented by Naji et al. (2020) , structural equation modelling enables to determine a regression model for the dispute occurrence as an output variable in terms of the dispute causes as real variable. However, since it is not possible to prevent all disputes, it is subsequently necessary to resolve them. In the case of systematic violations of one party’s obligations, a judicial decision is typically needed ( Yaskova and Zaitseva, 2017 ). This solution is commonplace in modern construction projects ( Biering et al., 2016 ); however, it may take long ( Dziadosz et al., 2015 )—disputes can drag on for many years, which is why parties also consider alternative dispute resolution (hereinafter referred as ADR) methods, an option that arose as an alternative to lengthy and costly processes of arbitration and litigation ( Cheung, 1999 ). The use of ADR (such as negotiation, arbitration or adjudication) depends on the nature of claims that are to be decided and also on the parties’ perception of fairness and outcomes of win and losses in claims ( Lee et al., 2016 ). The list of factors that affect the selection and use of ADR provided by Lee et al. (2016) is comprehensive, involving–apart from fairness and outcomes–e.g., bindingness, cost, confidentiality, control over the proceedings, lawyer’s influence, perception of risk, and complexity of disputes. Regarding related costs, disputes resolution carries explicit costs such as lawyer’s fees, court fees, consultant costs etc., however, other types of costs (so-called hidden costs) should also be considered, e.g., reduced project working efficiency, damaged reputation, or the aspect of future cooperation ( Lu et al., 2015 ).

The frequency of disputes occurrence was analysed by Ilter and Dikbas (2009) . They have revealed that design and build causes 8 precent more disputes in contrary to the build method and also that the frequency is positively correlated with the size of the contractor. According to Tazelaar and Snijders (2010) there is an 84 percent probability that at least some problem will occur within the project and 81 percent probability that the problem will be discussed successfully with the other party. However, if the problem involves a delayed payment or claim of damage, then there is 10 percent probability that the case will lead to arbitration or other legal steps.

The case study analysed in this paper deals with road construction. Road construction projects also involve the iron triangle; however, it should be noted that problems and risks are higher due to the duration and size of such projects, as well as unforeseen economic and other conditions such as material and energy prices. In the case of road construction, increased energy costs influence material costs and may slow down projects significantly ( Hashem Mehany and Guggemos, 2015 ). An example of the procedure of contractor’s claims management in a road works project is provided by Rybka et al. (2017) . Mishmish and El-Sayegh (2018) have reported causes of claims in road construction projects in the UAE. Based on their findings, the most likely causes consist in variations initiated by the client or engineer, delays caused by the contractor (e.g., as a consequence of lack of resources and machinery on the construction site), and inadequate site investigation before bidding.

Providing sufficient background materials for each dispute is crucial. Typically, contractors lack documents such as adequate photographic evidence, time sheets, site diaries and revised drawings to pursue their claims ( Vidogah and Ndekugri, 1998 ). Therefore, an experienced supervisor ( Kongsong and Pooworakulchai, 2018 ) as well as the use of modern technical devices and solutions on the construction site ( Banaszek et al., 2017 ; Acosta et al., 2019 ) are essential.

Materials and methods

The dispute analyzed in this case study was settled in court. Since authors of the paper participated in the preparation of the expert opinion for the court, they had at disposal complete documentation from the court file. Detailed documentation that has been available for the selected case study has been carefully studied. This documentation includes the following: contract for work, technical documents including initial road design, relevant documents provided by both parties to the dispute, and materials obtained during personal investigation of the site. All sensitive information and materials are published in an anonymised form (incl. location, time, name of the parties involved, the amount of costs, name of the technology used). The article contains only the facts that are relevant to the achievement of the paper’s objective, i.e., to identify dispute factors and the related consequences.

After examining the textual and graphical documentation in the court file (analysis no. 1), an additional set of information was obtained during personal investigation of the site that took place in 2018 (analysis no. 2). Due to the long duration of the dispute, 6 years passed before the revision expert opinion was ordered and processed. On the other hand, it enables to explore evidentiary material covering the whole six-year period. This investigation primarily involved physical documentation of visible damages, the extent of which progressively evolved over time (when compared to previous evidence available in the court file). Subsequently, the disputed matters were discussed with both parties (investor and supplier) in order to obtain the widest possible material for the subsequent assessment of responsibility for the occurrence of defects. When all the defects have been identified, the causes of problems were investigated. Then, cause-effect relations were assigned and graphically presented in multi-dimensional diagram. In addition, the entire analysis has been performed in the context of the iron triangle (i.e., time, cost, and quality issues). The case study research methodology is graphically presented in Figure 1 . Based on the findings, several lessons learnt are provided at the end of the manuscript.

FIGURE 1 . Case study research methodology.

Regarding scientific methods use, analytical-synthetic cognitive procedures have been applied to achieve an understanding of the qualitative data. Of these, a causal analysis was particularly important as it helps identify causes of phenomena. It is crucial to ensure objective and deep insight into the problem, especially in situations when observer just see certain process, but its manifestations are dependent on a very complex causal chain of causes and effects ( Molnar et al., 2012 , p. 22). For graphical interpretation for casual models, different types of casual diagrams are used, e.g., mind mapping and casual loop diagrams. Mind maps provides nonlinear graphical interpretation of data and casual loop diagrams are used to analyse qualitative data ( Milen et al., 1997 ). Generally speaking, casual diagrams help to predict how the system would respond to hypothetical interventions ( Pearl, 2000 ). For this reason, casual diagram was used as a graphical tool to present and understand causes and effects in analysed case study and, in the second stage, to facilitate the formulation of lessons learned. Project life cycle as well as the perspectives of both parties to the dispute in view of dispute categories are considered within the performed analysis.

Case study of a road construction project

The subject of the analysis consists in construction of a road on a privately-owned plot of land and its connection to the existing public asphalt road. Specifically, the road was to be used for transport to and from company premises. The road thus enables the entrance to the investor’s premises, parking and the connection of the public road to the storage hall. The investor needed to bring the premises into operation quickly and, for this reason, it began to consider a change in the originally envisaged technological solution for the road. The investor and the contractor reached an agreement where the contractor proposed to use a non-standard construction process which promised to shorten the construction period and reduce price. The technology lacked binding rules in the Czech Republic and there was no demonstrable experience with its use in other projects in the country. The basic characteristics of the project are provided in Table 1 and a cross-section drawing is shown in Figure 2 .

TABLE 1 . Basic characteristics of the analysed project.

FIGURE 2 . Cross section drawing of the road.

The investor and the contractor entered into a contract for work, but the contract unfortunately contained serious shortcomings consisting, e.g., in the absence of proper project documentation concerning the new technological solution attached to the contract as its integral part. All the above-mentioned facts subsequently led to disagreements and disputes between the contractual parties.

The road was built by the contractor, but defects and faults appeared during handover, resulting in the investor’s refusal to accept the road and its request for a repair of these defects and faults (consisting, e.g., of incorrectly implemented drainage). Although the work was neither officially accepted nor paid for, the investor started using it for its business activities, which involved heavy freight traffic on the road which had not been designed for that purpose. Consequently, the defects and faults deteriorated further, manifesting as faults on the road near the drainage sites, ruts in the covering layer, cracks and unevenness in the road and area deformations. Figures 3 – 5 show examples of defects on the analysed road and view on its structure.

FIGURE 3 . Cracks and deformations.

FIGURE 4 . Road surface irregularities.

FIGURE 5 . View of the road structure.

Since the parties were unable to agree on a solution to their dispute, they referred the matter to the court. As part of the investigation of the causes of the defects and faults and the liability for them, the following factors were identified: inadequate preparation of the ground plane, incorrectly implemented drainage, uneven thickness of the asphalt layer, partially insufficient compaction of the underlying structure, insufficient binding between the covering and the supporting layer, and overloading the road by heavy freight traffic.

The situation was further worsened by the increasing number and scope of faults as time progressed, the fact that there was no building diary, as well as the absence of as-built documentation. Selected most serious faults and defects were provisionally repaired by the investor on the spot, yet documentation was again not made with respect to these repairs. As a result, the entire dispute became fairly complex, especially with regard to the assignment of liability for the individual defects and faults.

Figure 6 provides a lucid two-dimensional overview of the above facts. The individual factors at play and their consequences are divided based on their time sequence into three life cycle stages, i.e., preparation, construction and operation. The second dimension consists in dispute categories (time, payment and quality). Colours indicate the decisions/activities/requirements of the parties in the dispute (blue = investor; orange = contractor; colour gradient = both).

FIGURE 6 . Causes and effects diagram.

The previous analysis showed that the project failure was caused by four main general factors: 1) selection of the contractor, 2) selection of the technology, 3) insufficient documentation, and 4) unsuitable use of the structure. The interaction of these factors made solving the dispute by agreement of the parties practically impossible.

The contractor selection process should generally be conducted in a way that results in implementation of the work by a construction company that has sufficient technical, managerial and economic qualifications to deliver the work in the required quality. Although the entire process of selecting the contractor was not part of the analysis, the authors note that a proper verification of the contractor’s qualifications is crucial in this regard. Only qualified contractors should be selected to implement the contract, which means contractors who are competitive, competent and capable ( Lam et al., 2010 ). A part of the qualifications should have consisted in documented (and verified by the investor) references proving that the contractor was competent and capable.

The above requirement for submission of references is also related to the selection of the technology to be used. The investor did not verify if other projects using this technology had been implemented in the Czech Republic. This fact is especially important since this construction technology was not tried and proven in the Czech Republic and lacked relevant generally binding standards.

The dispute escalated and was difficult to resolve particularly due to the absence of relevant documents. This means both design documents for construction and as-built documentation. Since the contract for work concluded in this particular case study did not contain the usual provisions concerning construction contracts and the investor was not experienced in this area, no building diary was made during the construction and the investor did not arrange for adequate supervision of the work. These factors significantly hindered the possibility for determining qualitative shortcomings of the construction, e.g., in relation to bad binding of the covering and supporting layers since these structures are not visible.

Finally, another important factor consisted in the fact that the investor started using the road and overloaded it with heavy freight vehicles for which the surface was not designed. This brought about a situation where both parties to the dispute bore some responsibility for the occurrence of certain defects and faults. For instance, as regards the road cracks, it is not clear to what extent they were caused by, e.g., insufficient drainage of the site as opposed to heavy traffic. Determining the exact degree of liability for the individual defects and faults is thus nearly technically impossible, taking into consideration the fact that the scope of the faults grew as the time progressed.

Finally, several lessons learnt from the analysis of the case study can be presented. Firstly, it is necessary to choose a technical solution suitable to the structure’s operational requirements. In this relation, a detailed project documents must be drawn up.

Secondly, the contractor selection process should take place on the basis of sufficient qualifications. The qualification requirements should enable a selection from a sufficient number of bidders with the aim of ensuring sufficient competition within the selection procedure and, simultaneously, exclude from the procedure such potential contractors that lack the qualifications for successful completion of the project or who have previously developed reference projects that had quality issues.

Thirdly, contractual provisions in the contract for work should be consulted with experts in construction contract management in order to minimise the possibility of disputes in the course of the project’s implementation and afterwards.

Fourthly, handover of the construction site to the contractor has to be properly recorded in order to ensure that the investor has met all its obligations as agreed in the contract for work.

Fifthly, during the course of the construction, the investor should arrange for oversight of the works by a supervisor; keeping a building diary including photographic documentation by the contractor is also necessary. These measures enable timely identification of low-quality work and achieving appropriate remedy; potentially, the same documents can serve as evidence for determination of the scope and liability for defects appearing during operation, which is especially important with regards to structures that are covered and cannot be visually inspected.

Sixthly, defects and shortcomings found during delivery of the completed work should be recorded with participation of both contractual parties and the supervisor. The defects and faults should be classified into two categories based on their severity, i.e., defects preventing the use of the work and defects not preventing the use of the work. This categorisation should be supported by the provisions of the contract for work; material defects preventing proper use of the work are generally considered to constitute grounds for non-acceptance of the work by the investor. A list of these lessons is provided in Table 2 showing the relationships between the problem, the measures adopted, and their desired effects.

TABLE 2 . Recommendations resulting from the case study analysis.

As a result, the impact of this dispute is negative mainly for the investor, but also for the supplier. For investor, the effects consist mainly in the limited possibility to use built communication and in additional incurred costs for carrying out local repairs. Since the supplier consistently and completely rejects its liability for defects, its main burden consists of attending court hearings and the related costs of legal representation.

This study aimed to identify dispute factors and the related consequences on a case study involving the construction of a road to commercial premises. The subject of the analysis involved a critical evaluation of the interaction of individual factors both in terms of the dispute categories and the life cycle of the project. The mutual interactions are depicted in casual diagram ( Figure 6 ), which shows the process in which a dispute becomes increasingly more complex and thus more difficult to resolve by reaching a mutually acceptable compromise solution.

Presented research is not without limitations. As this is a case study of one particular project, the observations and conclusions reached herein cannot be generalised to the entire construction sector. However, due to the high level of complexity of the analyzed case in the perspective of the life cycle, substantial implications can be derived not only for practice but also for theory.

This paper provides two main managerial implications. Firstly, the discussion of the case study brings several recommendations on how to avoid potential problems based on lessons learned from the situation that occurred in the studied project. Secondly, the conducted analysis shows that in case of protracted disputes arising from insufficient documentation, determining the party responsible for defects becomes extremely difficult.

From a theoretical perspective, performed analysis contributes to the current body of knowledge by highlighting potential undesirable growth in project complexity in relation to inexpert and controversial steps of the parties to the dispute. Furthermore, the findings presented extend our understanding of the long-term effects of contract management problems within individual stages of the project life cycle on both parties involved in the dispute and within iron triangle dimensions.

In order to reach generalisable findings in the area of transport construction projects, further project case studies should be analysed; in aggregate, they would have the potential to identify recurring negative scenarios, project inflection points and possibilities for general improvement in the area of contract management.

Data availability statement

The data analyzed in this study is subject to the following licenses/restrictions: business case of dispute. Requests to access these datasets should be directed to [email protected] .

Author contributions

All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.

This paper has been written with the support of a research grant FAST-S-22-7970 “Economic and managerial processes in civil engineering”.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Acosta, L. M., Torres, A., Krejza, Z., Gibert, V., and Serrat, C. (2019). Exploring technological alternatives to the visual inspection method in the built environment. IOP Conf. Ser. Earth Environ. Sci. 222, 012027–12110. doi:10.1088/1755-1315/222/1/012027

CrossRef Full Text | Google Scholar

Banaszek, A., Banaszek, S., and Cellmer, A. (2017). Possibilities of use of UAVS for technical inspection of buildings and constructions. IOP Conf. Ser. Earth Environ. Sci. 95 (3), 032001–6. doi:10.1088/1755-1315/95/3/032001

Biering, C., Hanus, J. P., and Verma, R. “Day in court - teaching contract disputes in construction management,” in Proceedings of the ASEE Annual Conference and Exposition , New Orleans, USA , 2016-June , 1–11. paper ID 16249. doi:10.18260/p.26643

Burke, C. M., and Morley, M. J. (2016). On temporary organizations: A review, synthesis and research agenda. Hum. Relat. 69 (6), 1235–1258. doi:10.1177/0018726715610809

Cheung, S. (1999). Critical factors affecting the use of alternative dispute resolution processes in construction. Int. J. Proj. Manag. 17 (3), 189–194. doi:10.1016/S0263-7863(98)00027-1

Chow, P. T., Cheung, S. O., and Yiu, T. W. (2012). A cusp catastrophe model of withdrawal in construction project dispute negotiation. Automation Constr. 22, 597–604. doi:10.1016/j.autcon.2011.12.006

Dziadosz, A., Tomczyk, A., and Kapliński, O. (2015). Financial risk estimation in construction contracts. Procedia Eng. 122, 120–128. doi:10.1016/j.proeng.2015.10.015

Hanak, T., and Korytarova, J. (2014). 10.5937/jaes12-6098 = Risk zoning in the context of insurance: Comparison of flood, snow load, windstorm and hailstorm. Istraz. i Proj. za privredu 12 (2), 137–144. doi:10.5937/jaes12-6098

Hashem Mehany, M. S., and Guggemos, A. (2015). Risk management for asphalt road construction and maintenance under performance-based contracts. Int. J. Constr. Educ. Res. 11 (4), 292–315. doi:10.1080/15578771.2014.990121

Hosseini, S. A., Akbarpour, A., Ahmadi, H., and Aminnejad, B. (2017). Balance of cost, time, and quality related to construction projects regarding the reinforced concrete of underground structures using a meta-heuristic algorithm. Archives Civ. Eng. 63 (4), 103–121. doi:10.1515/ace-2017-0043

Hu, W., and He, X. (2014). An innovative time-cost-quality tradeoff modeling of building construction project based on resource allocation. Sci. World J. 2014, 1–10. doi:10.1155/2014/673248

PubMed Abstract | CrossRef Full Text | Google Scholar

Ilter, D., and Dikbas, A. “An investigation of the factors influencing dispute frequency in construction projects,” in Proceedings of the COBRA 2009 - Construction and Building Research Conference of the Royal Institution of Chartered Surveyors , Cape Town, South Africa , 10-11 September 2009 , 1496–1504.

Google Scholar

Ilter, D. (2012). Identification of the relations between dispute factors and dispute categories in construction projects. Int. J. Law Built Env. 4 (1), 45–59. doi:10.1108/17561451211211732

Johnson, R. M., and Babu, R. I. I. (2020). Time and cost overruns in the UAE construction industry: A critical analysis. Int. J. Constr. Manag. 20 (5), 402–411. doi:10.1080/15623599.2018.1484864

Kermanshachi, S., and Safapour, E. (2019). Identification and quantification of project complexity from perspective of primary stakeholders in us construction projects. J. Civ. Eng. Manag. 25 (4), 380–398. doi:10.3846/jcem.2019.8633

Kongsong, W., and Pooworakulchai, C. (2018). Improving for construction contract management of government construction projects. Int. J. Civ. Eng. Technol. 9 (7), 253–260.

Lam, K. C., Tao, R., and Lam, M. C. (2010). A material supplier selection model for property developers using Fuzzy Principal Component Analysis. Automation Constr. 19 (5), 608–618. doi:10.1016/j.autcon.2010.02.007

Lee, C. K., Yiu, T. W., and Cheung, S. O. (2016). Selection and use of alternative dispute resolution (ADR) in construction projects - past and future research. Int. J. Proj. Manag. 34 (3), 494–507. doi:10.1016/j.ijproman.2015.12.008

Leśniak, A., Piskorz, G., Spišáková, M., and Mačková, D. (2018). Causes of delays in construction works resulting from the provisions of the contract in Poland and Slovakia. Sci. Rev. Eng. Environ. Sci. 27 (1), 71–81. doi:10.22630/PNIKS.2018.27.1.7

Ljevo, Ž., Vukomanović, M., and Rustempašić, N. (2017). Analysing significance of key quality factors for management of construction projects. Gradjevinar 69 (5), 359–366. doi:10.14256/JCE.1723.2016

Lu, W., Zhang, L., and Pan, J. (2015). Identification and analyses of hidden transaction costs in project dispute resolutions. Int. J. Proj. Manag. 33 (3), 711–718. doi:10.1016/j.ijproman.2014.08.009

Maravas, A., and Pantouvakis, J. P. (2012). Project cash flow analysis in the presence of uncertainty in activity duration and cost. Int. J. Proj. Manag. 30 (3), 374–384. doi:10.1016/j.ijproman.2011.08.005

Milen, D. R., Schriefer, A., Lehder, D. Z., and Dray, S. M. “Mind maps and causal models: Using graphical representations of field research data,” in CHI EA '97 CHI '97 Extended Abstracts on Human Factors in Computing Systems , Atlanta, Georgia , March 1997 ( ACM ), 265–266.

Mishmish, M., and El-Sayegh, S. M. (2018). Causes of claims in road construction projects in the UAE. Int. J. Constr. Manag. 18 (1), 26–33. doi:10.1080/15623599.2016.1230959

Molenaar, K., Washington, S., and Diekmann, J. (2000). Structural equation model of construction contract dispute potential. J. Constr. Eng. Manag. 126 (4), 268–277. doi:10.1061/(ASCE)0733-9364(2000)126:4(268)

Molnar, Z., Midleova, S., Rezankova, H., Brixi, R., and Kalina, J. (2012). Pokrocile metody vedecke prace (Advanced methos of scientific work) . Czech Republic: VŠE . 978-80-7259-064-3.

Nahidi, S., Fountas, G., Sarvani, S. P., Sarwar, M. T., and Anastasopoulos, P. C. (2017). Project discrepancies in roadway construction and preservation: A statistical analysis of public–private partnership contract types in the US. Front. Built Environ. 3. doi:10.3389/fbuil.2017.00015

Naji, K. K., Mansour, M. M., and Gunduz, M. (2020). Methods for modeling and evaluating construction disputes: A critical review. IEEE Access 8, 45641–45652. doi:10.1109/ACCESS.2020.2976109

Pearl, J. (2000). Causality: Models, reasoning, and inference . Cambridge University Press .

RIBA Enterprises, (2013). National construction contracts and Law Survey 2013. Available at: https://www.thenbs.com/knowledge/nbs-national-construction-contracts-and-law-survey-2013 .

Rybka, I., Bondar-Nowakowska, E., Pawluk, K., and Połoński, M. (2017). Risk of contractors' claims on the example of road works. IOP Conf. Ser. Mat. Sci. Eng. 245 (7), 072009–9. doi:10.1088/1757-899X/245/7/072009

Safa, M., Shahi, A., Haas, C. T., and Hipel, K. W. (2017). Construction contract management using value packaging systems. Int. J. Constr. Manag. 17 (1), 50–64. doi:10.1080/15623599.2016.1167369

Shoar, S., Chileshe, N., and Edwards, J. D. (2022). Machine learning-aided engineering services' cost overruns prediction in high-rise residential building projects: Application of random forest regression. J. Build. Eng. 50, 104102. doi:10.1016/j.jobe.2022.104102

Subramanya, K., Kermanshachi, S., and Pamidimukkala, A. (2022). Evaluation of E-Ticketing technology in construction of Highway projects: A systematic review of adoption levels, Benefits, Limitations and Strategies. Front. Built Environ. 8. doi:10.3389/fbuil.2022.890024

Tazelaar, F., and Snijders, C. (2010). Dispute resolution and litigation in the construction industry. Evidence on conflicts and conflict resolution in The Netherlands and Germany. J. Purch. Supply Manag. 16 (4), 221–229. doi:10.1016/j.pursup.2010.08.003

Vařbuchta, P., Kovářová, H., Hromádka, V., and Vítková, E. (2017). Risk variables in evaluation of transport projects. IOP Conf. Ser. Mat. Sci. Eng. 236 (1), 012112–012117. doi:10.1088/1757-899X/236/1/012112

Vidal, L., Marle, F., and Bocquet, J. (2011). Measuring project complexity using the analytic hierarchy process. Int. J. Proj. Manag. 29 (6), 718–727. doi:10.1016/j.ijproman.2010.07.005

Vidogah, W., and Ndekugri, I. (1998). Improving the management of claims on construction contracts: Consultant's perspective. Constr. Manag. Econ. 16 (3), 363–372. doi:10.1080/014461998372385

Yaskova, N., and Zaitseva, L. (2017). Application of alternative dispute resolution in the field of construction projects. IOP Conf. Ser. Earth Environ. Sci. 90 (1), 012182–012184. doi:10.1088/1755-1315/90/1/012182

Zujo, V., Car-Pušić, D., Zileska-Pančovska, V., and Cecez, M. (2017). Time and cost interdependence in water supply system construction projects. Technol. Econ. Dev. Econ. 23 (6), 895–914. doi:10.3846/20294913.2015.1071292

Keywords: construction project, contract management, road construction, project documentation, dispute

Citation: Hanák T and Vítková E (2022) Causes and effects of contract management problems: Case study of road construction. Front. Built Environ. 8:1009944. doi: 10.3389/fbuil.2022.1009944

Received: 02 August 2022; Accepted: 26 September 2022; Published: 07 October 2022.

Reviewed by:

Copyright © 2022 Hanák and Vítková. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Tomáš Hanák, [email protected]

This article is part of the Research Topic

Insights: Frontiers in Built Environment

• LOGIN & Help

Carbon Footprint Estimation in Road Construction: La Abundancia–Florencia Case Study

• Civil and Environmental Engineering
• Grainger College of Engineering
• Center for South Asian and Middle Eastern Studies

Research output : Contribution to journal › Article › peer-review

The environmental impact of road construction and rehabilitation can be associated with the increase of greenhouse gas (GHG) emissions, which are highly related to climate change. Consequently, departments of transportation have recently focused on the development and implementation of tools to evaluate the performance of projects and minimize GHG emissions. An example is the use of life cycle assessment (LCA) to analyze and quantify the environmental impact of a product, system, or process, from cradle to grave. In this regard, the present case study quantifies the carbon footprint associated with the construction of the La Abundancia-Florencia highway, located in the province of San Carlos in Costa Rica. The analysis is also intended to generate consciousness both in the public and private sectors on the environmental impacts of road construction. After an LCA study, it was determined that the construction of the hot mix asphalt (HMA) layer generates a carbon footprint of 65.8 kg of CO2e per km of road. In addition, it was evident that HMA production generates the greatest environmental impact, among all the considered LCA production and construction stages, with a GHG contribution of 38% to 39% from bitumen only. Consequently, special attention to HMA production is required in order to minimize GHG emissions.

• Asphalt mixtures
• Carbon footprint
• Life cycle analysis

ASJC Scopus subject areas

• Geography, Planning and Development
• Renewable Energy, Sustainability and the Environment
• Management, Monitoring, Policy and Law

Online availability

• 10.3390/su11082276 License: CC BY

Library availability

Related links.

• Link to publication in Scopus
• Link to citation list in Scopus

Fingerprint

• road construction Social Sciences 100%
• Carbon footprint Engineering & Materials Science 81%
• life cycle assessment Social Sciences 76%
• Greenhouse gases Engineering & Materials Science 66%
• Environmental impact Engineering & Materials Science 62%
• environmental impact Social Sciences 61%
• Gas emissions Engineering & Materials Science 50%
• Asphalt Engineering & Materials Science 48%

T1 - Carbon Footprint Estimation in Road Construction

T2 - La Abundancia–Florencia Case Study

AU - Espinoza, Marianela

AU - Campos, Noelia

AU - Yang, Rebekah

AU - Ozer, Hasan

AU - Aguiar-Moya, José P.

AU - Baldi, Alejandra

AU - Loría-Salazar, Luis G.

AU - Al-Qadi, Imad L

N1 - Funding Information: The present study is based on the results obtained during the analysis carried out by TEST, Inc. Special thanks extend to the companies Constructora Herrera and Eurofinsa for the information provided to carry out the study.This research received no external funding. Publisher Copyright: © 2019 by the authors. Copyright: Copyright 2019 Elsevier B.V., All rights reserved.

PY - 2019/4/16

Y1 - 2019/4/16

N2 - The environmental impact of road construction and rehabilitation can be associated with the increase of greenhouse gas (GHG) emissions, which are highly related to climate change. Consequently, departments of transportation have recently focused on the development and implementation of tools to evaluate the performance of projects and minimize GHG emissions. An example is the use of life cycle assessment (LCA) to analyze and quantify the environmental impact of a product, system, or process, from cradle to grave. In this regard, the present case study quantifies the carbon footprint associated with the construction of the La Abundancia-Florencia highway, located in the province of San Carlos in Costa Rica. The analysis is also intended to generate consciousness both in the public and private sectors on the environmental impacts of road construction. After an LCA study, it was determined that the construction of the hot mix asphalt (HMA) layer generates a carbon footprint of 65.8 kg of CO2e per km of road. In addition, it was evident that HMA production generates the greatest environmental impact, among all the considered LCA production and construction stages, with a GHG contribution of 38% to 39% from bitumen only. Consequently, special attention to HMA production is required in order to minimize GHG emissions.

AB - The environmental impact of road construction and rehabilitation can be associated with the increase of greenhouse gas (GHG) emissions, which are highly related to climate change. Consequently, departments of transportation have recently focused on the development and implementation of tools to evaluate the performance of projects and minimize GHG emissions. An example is the use of life cycle assessment (LCA) to analyze and quantify the environmental impact of a product, system, or process, from cradle to grave. In this regard, the present case study quantifies the carbon footprint associated with the construction of the La Abundancia-Florencia highway, located in the province of San Carlos in Costa Rica. The analysis is also intended to generate consciousness both in the public and private sectors on the environmental impacts of road construction. After an LCA study, it was determined that the construction of the hot mix asphalt (HMA) layer generates a carbon footprint of 65.8 kg of CO2e per km of road. In addition, it was evident that HMA production generates the greatest environmental impact, among all the considered LCA production and construction stages, with a GHG contribution of 38% to 39% from bitumen only. Consequently, special attention to HMA production is required in order to minimize GHG emissions.

KW - Asphalt mixtures

KW - Carbon footprint

KW - Emissions

KW - Life cycle analysis

UR - http://www.scopus.com/inward/record.url?scp=85066843152&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85066843152&partnerID=8YFLogxK

U2 - 10.3390/su11082276

DO - 10.3390/su11082276

M3 - Article

SN - 2071-1050

JO - Sustainability

JF - Sustainability

• View Record

TRID the TRIS and ITRD database

CASE STUDIES OF EFFECT OF ROADS ON DEVELOPMENT

A SERIES OF CASE STUDIES WAS CONDUCTED IN LATIN AMERICA TO INDICATE THE IMPACTS OF ROAD CONSTRUCTION ON ECONOMIC DEVELOPMENT. THE COUNTRIES INCLUDED IN THE CASE STUDY WORK WERE EL SALVADOR, GUATEMALA, NICARAGUA, VENEZUELA, AND BOLIVIA. IN ADDITION, ANALYSIS WAS MADE OF A NUMBER OF OTHER CASES PREVIOUSLY STUDIED BY OTHER ORGANIZATIONS IN INDIA, THAILAND, NORTH BORNEO, UGANDA, AND PERU. IN EVERY CASE THE EXTENT OF NEW TRAFFIC GENERATED DEPENDED MAINLY ON THE AVAILABILITY OF EASILY EXPLOITABLE NATURAL RESOURCES. THE LOWEST LEVELS OF TRAFFIC, OMITTING THE EARTH ROADS IN UGANDA AND NORTH BORNEO FOR WHICH TRAFFIC ESTIMATES ARE LACKING, WERE ASSOCIATED WITH HIGHWAYS TRAVERSING A TERRITORY POOR IN RESOURCES. THE HIGHEST TRAFFIC VOLUMES WERE FAIRLY CONSISTENTLY ASSOCIATED WITH RISING NET RECEIPTS TO PRODUCERS OF AGRICULTURAL PRODUCTS. NO ADEQUATE DETAILS OF ACTUAL OR POSSIBLE PROFIT PROSPECTS WERE PROVIDED, BUT THE INFERENCE IS CLEAR THAT THEY CREATED A POWERFUL INDUCEMENT TO RAISE OUTPUT AND SELL A GREATER PROPORTION OF IT IN LOCAL, SECTIONAL, OR WORLD MARKETS. EXAMPLES ARE GIVEN IN GUATEMALA, BOLIVIA AND INDIA WHERE THE HIGHWAY IS BEST CONSTRUED AS A RESPONSE TO A DEVELOPMENT THAT WOULD PROBABLY HAVE OCCURRED IN ANY EVENT, ALTHOUGH NOT NECESSARILY IN THE SAME MANNER NOR TO THE SAME EXTENT. THE EXAMPLES SUGGEST THAT, GIVEN A RELATIVELY STATIC OR DETERIORATING SITUATION BEFORE THE NEW TRANSPORTATION CAPACITY, ALONG WITH FEW READILY EXPLOITABLE NATURAL RESOURCES, THE TASK OF INITIATING SUSTAINABLE GROWTH IS BOTH MORE DIFFICULT AND PROTRACTED, WHICH IMPLIES THE NECESSITY OF COMBINING TRANSPORT INVESTMENT WITH OTHER POLICIES IF IMPORTANT CHANGES ARE TO OCCUR. THE THREE COUNTRIES WITH THE SLOWEST RATE OF OVERALL GROWTH COINCIDE WITH THESE RELATIVELY UNSUCCESSFUL CASES. THIS SUGGESTS THAT WHERE THERE IS A GENERAL LACK OF DYNAMISM THERE IS ALSO A GREATER PROBABILITY THAT A SPECIFIC INVESTMENT WILL NOT BECOME MUCH OF A SUCCESS.

• Record URL: http://onlinepubs.trb.org/Onlinepubs/hrr/1966/115/115-002.pdf
• Distribution, posting, or copying of this PDF is strictly prohibited without written permission of the Transportation Research Board of the National Academy of Sciences. Unless otherwise indicated, all materials in this PDF are copyrighted by the National Academy of Sciences. Copyright © National Academy of Sciences. All rights reserved.
• Wilson, George W
• Publication Date: 1966
• Media Type: Digital/other
• Features: References; Tables;
• Pagination: pp 10-18
• Monograph Title: Transportation and economic development
• Highway Research Record
• Issue Number: 115
• Publisher: Highway Research Board

Subject/Index Terms

• TRT Terms: Agriculture ; Economic development ; Field studies ; Highways ; Improvements ; Natural resources ; Road construction ; Traffic volume ; Transportation ; Transportation planning ; Trip generation
• Uncontrolled Terms: Capacity
• Geographic Terms: Latin America
• Subject Areas: Economics; Society; Transportation (General);

Filing Info

• Accession Number: 00201142
• Record Type: Publication
• Files: TRIS, TRB
• Created Date: Nov 21 1994 12:00AM

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to  upgrade your browser .

Enter the email address you signed up with and we'll email you a reset link.

• We're Hiring!
• Help Center

Road Construction Equipment Management: A Case Study on Selected Industry

2016, International Journal of Engineering Technology and Sciences

The major share of capital and equipment intensive operation goes to the road sector and the hydro – electric power projects. The construction sector in Ethiopia is developing at a fast rate and its capital budget is increasing from year to year. One of the reasons for this high growth is the number of new construction projects underway and those in the pipeline. In addition, the hydro-electric power projects the government has given a great emphasis to increase the current installed power of 780Mw to a total of 10,000Mw in the coming few years. These hydro-power projects are known for using a great deal of high investment heavy machineries. Therefore, the construction equipment management plays a great role in finalizing the projects with fewer budgets and no time over run. Considering the higher operation, maintenance and investment cost of construction equipment, it is important to have a carefully optimized decision making model that will help in the sizing and selection of the ...

Related Papers

Construction Equipment Management Practice

Abstract The construction industry is a sector that relies on the use of construction equipment. Especially contractors who are engaged in road construction primarily demand high utilization of construction equipment. Construction equipment owned by contractors also constitutes the greatest portion of assets owned by them. To obtain the benefit from equipment and to utilize effectively these assets which have high economic value, contractors are required to have a well-developed system and guideline that directs equipment management practice in the right way. The practice followed by contractors in Ethiopia in the management of construction equipment is not being clearly known and studies regarding it are limited. However, problems related to construction management are increasing as the construction industry keeps on growing. Contractors are experiencing frequent downtime, less productivity but high operation cost and workplace accident related to construction equipment. The main objective of this research is thus to study the general equipment management practice followed by high-grade level contractors (from grade one up to three) who are engaged in road construction and identify significant causes of problems related to the management of construction equipment. A structured questionnaire was prepared and distributed for 52 grade one up to three contractors who are in the Addis Ababa region of Ethiopia. Out of these, responses of 33 contractors were obtained. The sample size is determined by using the kish equation for 94% confidence of interval. The collected data were analyzed using SPSS 16 statistical software package producing frequencies, percentages, and cross-tabulation charts. RII ranking is done to identify the most significant causes of equipment management problems. The finding obtained from this research indicates that only limited contractors (12.1%) have well-documented equipment management guideline. The practice of record-keeping of costs of operation and maintenance is not on the satisfactory level and preventive maintenance is also not the popular practice among contractors. Most of the time equipment maintenance is undertaken when it is breakdown. The Equipment management practice of contractors is highly influenced by the limitation of the financial capacity of contractors and most of the cause of the problem is due to inappropriate management practice they follow. A significant difference in the management of equipment is observed across grade levels; some grade one contractors who developed equipment management guidelines relatively have shown better equipment management practice.

Journal of emerging technologies and innovative research

Ghanasham Sarode

Abebaw worku

Modern construction, characterized by effective and efficient utilization of construction equipment to accomplish numerous construction activities. Equipment may range from simple hand tools or apparatus to heavy-duty construction equipment. As a high level of productivity is important to any company’s success and survival, this paper help to fill the gap created by the absence of proper equipment management on the construction sites and helps to examine the overall performance of heavy-duty construction equipment. This study also examines the major contributing factors for productivity loss on the case study federal road construction projects to find important interventions for changes; this is because machinery management have high influence on productivity, cost and quality. Three federal roads where involved in this study, Namely, Mazoria-Durame-Hadero, Hadero-Durgi and Alaba-Alemgebeya-Hulbarek road projects in the southern regional state of Ethiopia. The assessment involved in this study was field observation and measurement to quantify downtime and the actual productivity and desk study to identify main factors contributing for productivity loss. In the entire study site, the OEE index show low percentage of productivity in between 55% to 68%. Out of the three primary component rates of OEE index only quality rate have a higher performance, which is about 90% and above. However, the performance rate in the entire study site shows lower performance(less than 76%). Due to this weak performance of the construction equipment productivity, the contractors forced to incur an additional cost from 1 – 2 % of the total monthly running cost allocated for the equipment. Out of the four main contributing factors for equipment productivity loss (machine factor, human factor, management factor and work factor) the management problem ranked first. Although there was low construction equipment productivity in the entire study site, the Resident Engineers (RE) do not have any compliant on the contractor regarding to their poor Performance.

jayaram sankar

International Journal of Advanced Technology in Engineering and Science (IJATES), www.ijates.com, ISSN (online): 2348 – 7550, Journal Impact Factor (2014): 1.012

Prof. (Dr.) Jayeshkumar Pitroda

Purchasing with cash, financing through a loan, renting and leasing are four most common ways which are mainly affected by different construction equipment selection factors. For having the best result in profit for a construction industry choosing the best alternative for obtaining equipment is one of the most important issues. The optimum acquisition strategy comes from accurate estimates of revenues and cost and also some non-financial factors that effect on selection of appropriate equipment. The purpose of this paper is to evaluate these factors. The identification of the factors that effect on equipment selection has been carried out using different literatures and by interviewing from experts in construction. This paper has been planned to deal with identification of factors affecting equipment selection, developing a framework for assessing the factors affecting equipment selection. A framework has been developed, which will be used for the future research in this area.

Mearg Ngusse

cuong pham phu

Mechanization and automation constitute an essential stage in the production and operation of any company, as one of the determinants of increase in labor productivity and decrease in product price, while significantly contributing to shortening of the lead time. Businesses are, therefore, able to quickly put projects into operation, improving economic efficiency, quality, and aesthetics, which speeds up the national economic growth. For the construction industry to be the most effective, modern construction equipment is a necessity. It is one of the five main resources of a construction project. Thus, effective construction equipment management contributes to the success of a project and benefits the relevant construction companies economically. This paper presents the critical risk factors affecting equipment management and proposes suitable solutions. The questionnaire-based survey with experienced experts in the construction sector on the management of the likelihood and consequ...

IRJET Journal

Construction equipment are the major resources in infrastructure projects. Construction equipment occupy major portion of project cost, but improper utilization of such resources lead to loss of productivity, ultimately affecting profit. Thus, there is need to optimize these operations to reduce the cost. The present research attempt to design the optimized equipment fleet by studying existing fleet and using optimization for the highway project. It includes an economic analysis of equipment fleet with respect to time and cost. To perform these optimization, production capacity and cost of equipment is taken into consideration. To validate the results, case study of four laning of Sangli-Solapur Section of NH 166 is taken.

Ahmad Jrade

Optimizing equipment selection in heavy earthwork operations is a critical key in the success of any construction project. The objective of this research incentive was geared towards developing a computer model to assist contractors and construction managers in estimating the cost of heavy earthwork operations. Economical operation analysis was conducted for an equipment fleet taking into consideration the owning and operating costs involved in earthwork operations. The model is being developed in a Microsoft environment and is capable of being integrated with other estimating and optimization models. In this study, Caterpillar® Performance Handbook [5] was the main resource used to obtain specifications of selected equipment. The implementation of the model shall give optimum selection of equipment fleet not only based on cost effectiveness but also in terms of versatility. To validate the model, a case study of an actual dam construction project was selected to quantify its degree...

International Journal of Engineering Research & Technology (IJERT)

IJERT Journal

https://www.ijert.org/study-on-factors-affecting-equipment-management-and-its-effect-on-productivity-in-building-construction https://www.ijert.org/research/study-on-factors-affecting-equipment-management-and-its-effect-on-productivity-in-building-construction-IJERTV9IS040176.pdf Construction equipment is one of the important resources of modern day construction in the building sites. Equipment selection is an important factors in the implementation of many construction projects. Equipment managers are habitually called upon to make economical decisions involving the machines in their charge. Their duties includes repairs, rebuilds, and maintenance. Around 30-40% of construction cost overrun is caused by inappropriate supervision of equipments. The purpose of this paper is to identify the various factors affecting equipment management which effects the productivity in construction sites. The main goal of the research study is to provide essential information about factors affecting equipment management to the project management teams who enable the project's success. The questionnaire was categorized into the profile of respondents and the factors in three different groups. This profile were created to collect the information such as job position, experience and contact information. Factors affecting equipment productivity were ranked on the basis of relative importance index method. Based on analysis, the factors which affect equipment productivity are late inspection, condition of sites, operators efficiency and availability of skilled operators.

RELATED PAPERS

Abstract and Applied Analysis

Nazmiye Yılmaz

Skrivena javna potrošnja: sadašnjost i budućnost poreznih izdataka

Predrag Bejaković

Evidencias en Odontología Clínica

Sara Valencia

Electroanalysis

Qiantao Cai

Journal of proteome research

Jörgen Ekström

Carlos Jimenez

Henryk Josiński

Jual Gazebo Gresik

Jual Rumah Joglo Di Jogja

Dzakiyah Widyaningrum

Daniel Quiroz

yulinarti setianingrum

Science & Technology

Nguyen Thi Cam Tien

Putu Eka Sudaryatma

The Journal of Humanistic Counseling

Catalysis Communications

g v s sarma

Shahin Kavousi

New Microbes and New Infections

Andreas Burkovski

Doo Woong Lee

Jesus cuero

Transplantation

Bjorn Winkens

ROSA ROSARIO

World Journal of Gastroenterology

Eleni Jelastopulu

The Pakistan Development Review

Biotechnology and Applied Biochemistry

Behnam Rasekh

Rahmat Setiawan

RELATED TOPICS

•   We're Hiring!
•   Help Center
• Find new research papers in:
• Health Sciences
• Earth Sciences
• Cognitive Science
• Mathematics
• Computer Science
• Academia ©2024

Case Study: The Amazonian Road Decision

The proposed Pucallpa–Cruzeiro do Sul will connect the Amazon’s interior to urban centers and export markets in Peru and Brazil. However, critics are worried that the road will also create new opportunities for illegal logging and infringe on the territory of indigenous communities and wildlife.

Biology, Geography, Human Geography

Loading ...

On the western edge of the Amazon River, there is a proposal to construct a road. This road would connect the remote town of Cruzeiro do Sul, Brazil, with the larger city of Pucallpa, Peru. The construction of the road has become a subject of contentious debate. Proponents of the road claimed that it would provide an efficient way for rural farmers and tradesmen to get their goods to city markets. They claimed it would also allow loggers to more easily transport timber from the depths of the Amazon rainforest to sawmills. From the sawmills in Pucallpa, goods could be transported to Peru’s Pacific coast and shipped to international buyers. Critics of the Pucallpa-Cruzeiro do Sul road, however, argue that it would cut right through traditional territories of the Ashéninka, an indigenous people of eastern Peru. Many leaders fear the road will increase access to previously undeveloped rainforest, threatening the ecosystem and the Ashéninka way of life. Large trees, such as mahogany, for example, will catch the eye of illegal loggers because of their high market value. The great mahogany trees also serve as protection to the Ashéninka from the outside world and are essential for the health of the Amazonian rainforest. The trees provide shelter, food, and nesting grounds that sustain the vast biodiversity within the ecosystem, an ecosystem the Ashéninka have come to depend on for their own food, shelter, and life sustenance. Geography The Amazon Basin is located in South America, covering an area of seven million square kilometers (2.7 million square miles). Nearly 70 percent of the basin falls within Brazil with remaining areas stretching into parts of Peru, Ecuador, Bolivia, Colombia, Venezuela, and Guyana. The Amazon’s massive drainage basin is made of dozens of smaller watersheds , including the Tamaya. Its watershed lies at the headwaters of the Purus and Juruá Rivers, near the border of Peru and Brazil. The Ashéninka people have lived in this region for centuries, surviving on game, fish, and cultivated crops, such as yucca roots, sweet potato, corn, coffee, and sugar cane. Background The rainforest surrounding the Amazon is the largest on the entire planet. In addition to 33 million human inhabitants, including 385 distinct Indigenous groups, it hosts the greatest diversity of plant and animal life in the world. More than two million species of insects are native to the region, including many tree-living species and hundreds of spiders and butterflies. Primates are abundant—including howler, spider, and capuchin monkeys—along with sloths, snakes, and iguanas. Brightly colored parrots, toucans, and parakeets are just some of the region’s native birds. Many of these species are unique to the Amazon rainforest, which means they cannot be found anywhere else in the world. At a global level, the Amazon rainforest helps to regulate climate and acts as a carbon sink for greenhouse gases . At a national level, the Amazon is considered a source of energy and income, based on production and commercialization of raw materials. Some of the most valued tree species in the world thrive in the rainforest. Mahogany is one of the most valuable resources from the Amazon forest. The tree’s rich, red grain and durability make it one of the most coveted building materials in the world. A single mahogany tree can fetch thousands of U.S. dollars on the international market. Even though logging is prohibited in much of the Amazon River, it is legal in some areas in large part because the sale of the wood is so lucrative. The high demand for mahogany has left many of Peru’s watersheds—such as the Tamaya—stripped of their most valuable trees. Without large trees, and their roots, the watershed risks heavy flooding and soil erosion. Conflict The Pucallpa-Cruzeiro do Sul road is part of a larger development plan to link South America’s remote, isolated economies through new transportation, energy, and telecommunications projects. Tension exists between communities that favor developing the rural economies of the Amazon Basin and those who favor preserving its forested areas and diversity of life. The Initiative for the Integration of the Regional Infrastructure of South America (IIRSA) is a proposal for the construction of several highways throughout the continent, five of them within the western Amazon Basin. The Pucallpa-Cruzeiro do Sul road is one such proposed highway. Supporters of the Pucallpa-Cruzeiro do Sul road say international demand for Amazonian resources could help develop the rural economies that are scattered throughout the basin. In addition to providing a route of access for rural goods to enter the global market, the road will allow members of rural communities to access better health care, education, and welfare. This could lead to improved living conditions, healthier lifestyles, and longer life spans. Conservationists are concerned that infrastructure such as the Pucallpa-Cruzeiro do Sul road will devastate an already weakened Amazonian ecosystem, as road access is highly correlated with  deforestation . In Brazil, for instance, 80 percent of deforestation occurs within 48.28 kilometers (30 miles) of a road. Critics argue that the construction of a road along the Brazil-Peru corridor will provide easier access for loggers to reach mahogany and other trees. Indigenous communities like the Ashéninka will also be affected. These communities have largely chosen to maintain a traditional way of life, and conservationists are concerned that the Pucallpa-Cruzeiro do Sul road may expose them to disease and land theft. Identification of Stakeholders Indigenous Communities:  Members of the Ashéninka community are trying to protect the forest and their native lands. Yet, like other Indigenous communities in the area, they are in turmoil, largely divided between those favoring conservation and those seeking greater economic opportunities. While the Ashéninka want to preserve their culture and connections to the forest, they also need access to things like clothes, soap, and medicine. The road could establish trade routes that make these goods more accessible. However, isolated peoples could be exposed to disease and land theft. Wildlife:  The proposed Pucallpa-Cruzeiro do Sul road runs through Serra do Divisor National Park, Brazil, and other reserves that are home to threatened and rare species, including mammals, reptiles, and birds. For some of these species, such as the spider monkey and red howler monkey, the construction of the road could make their populations vulnerable to fragmentation and more visible to hunters. As mahogany and other canopy giants are removed, any wildlife that relies on the trees for shelter, nesting, or food will need to relocate. Amazonian Ecosystem:  In addition to the detrimental effects to the flora and fauna in the area, the construction of the Pucallpa-Cruzeiro do Sul road could accelerate erosion, reduce water quality, and increase deforestation for agriculture and timber extraction. Tropical forest accounts for 40 percent of the global terrestrial carbon sink. A reduced number of trees could exacerbate global warming. Fewer forests means larger amounts of greenhouse gases entering the atmosphere. Logging Companies:  If a road is constructed, loggers will have easier access to mahogany and other trees, allowing them to generate more income and provide a higher standard of living for their families and communities. A higher standard of living might include expanded educational opportunities, improved healthcare facilities, and the chance to participate in political debate. Residents of Rural Communities:  The Pucallpa-Cruzeiro do Sul road would allow local farmers and business people to transfer goods from the Amazonian interior to Peru’s Pacific coast. Right now, merchants who want to travel between Cruzeiro do Sul and Pucallpa must do so by plane. A reliable road would improve basic infrastructure, transportation, and communication for greater commercial and social integration between Peru and Brazil, which meets part of the larger objective of the Initiative for the Integration of Regional Infrastructure in South America. International Consumers:  The global demand for mahogany makes it a multimillion dollar business. Mahogany is used to create bedroom sets, cabinets, flooring, and patio decks throughout the world, mostly in the United States and Europe. Conflict Mitigation Groups are seeking to mitigate conflict in the Pucallpa-Cruzeiro do Sul road conflict through dialogue and alternate infrastructure plans. Environmental conservation groups have suggested that the Pucallpa-Cruzeiro do Sul road be removed from the list of approved projects until the community engages in greater communication surrounding two aspects of the project. First, conservationists are seeking more information on the environmental impact of the construction. This discussion involves local environmental groups, government representatives, and businesses. Second, conservationists are seeking full consent to the project from indigenous communities. Some critics of the Pucallpa-Cruzeiro do Sul road argue that roads are not the only option for the Pucallpa business community to extend its commerce. Traditional river systems are already in place. These critics think the fluvial network should be explored as a viable alternative to road construction. The Upper Amazon Conservancy is working with indigenous peoples to help protect their native territories. One initiative involves organizing community “vigilance committees” that consist of members of indigenous peoples who help park services by patrolling the edges of national parks and keeping illegal loggers out.

Media Credits

The audio, illustrations, photos, and videos are credited beneath the media asset, except for promotional images, which generally link to another page that contains the media credit. The Rights Holder for media is the person or group credited.

Research Manager

Educator reviewer, expert reviewer, last updated.

October 19, 2023

User Permissions

For information on user permissions, please read our Terms of Service. If you have questions about how to cite anything on our website in your project or classroom presentation, please contact your teacher. They will best know the preferred format. When you reach out to them, you will need the page title, URL, and the date you accessed the resource.

If a media asset is downloadable, a download button appears in the corner of the media viewer. If no button appears, you cannot download or save the media.

Text on this page is printable and can be used according to our Terms of Service .

Interactives

Any interactives on this page can only be played while you are visiting our website. You cannot download interactives.

Related Resources

Paper Information

• Paper Submission

Journal Information

• About This Journal
• Editorial Board
• Current Issue
• Author Guidelines

International Journal of Construction Engineering and Management

p-ISSN: 2326-1080    e-ISSN: 2326-1102

2021;  10(4): 101-115

doi:10.5923/j.ijcem.20211004.02

Received: Apr. 27, 2021; Accepted: Sep. 8, 2021; Published: Sep. 26, 2021

Assessment of the Factors Influencing Performance of Road Construction Projects in Uganda: A Case Study of Ministry of Works and Transport

S. Seninde , L. Muhwezi, J. Acai

Department of Civil and Environmental Engineering, Faculty of Engineering, Kyambogo University, Kampala, Uganda

Copyright © 2021 The Author(s). Published by Scientific & Academic Publishing.

The road construction projects in Uganda suffer from many problems and complex issues in performance such as; cost, time, scope and quality. The aim of this study was to assess the factors influencing performance of road construction projects in Uganda. The study adopted a descriptive research design and data were collected using questionnaires from 147 purposively selected respondents from construction companies, consultancy firms, and government. Relevant literature was reviewed to establish actual factors influencing performance of road construction projects in Uganda. Data were coded and entered into statistical packages for social scientists (SPSS) version 25. Data were analyzed descriptively using statistical correlation and regression analysis, and Relative Importance Index (RII) was used to rank the identified factors. The research study revealed five most significant and influential factors on the performance of road construction projects in Uganda and these included; contractors, clients/owners, contractor’s ability to mobilize to site, availability of funds/ cash flows, and site instructions and quality control; and three least influential factors; inadequate mobilization of resources, inadequate geotechnical and hydrological studies, and lack of equipment. The study concluded that contract management, Project stake holders’ factors and project financing factors significantly influence the performance of road construction projects in Uganda.

Keywords: Assessment, Performance, Road construction projects, Relative importance index

Cite this paper: S. Seninde, L. Muhwezi, J. Acai, Assessment of the Factors Influencing Performance of Road Construction Projects in Uganda: A Case Study of Ministry of Works and Transport, International Journal of Construction Engineering and Management , Vol. 10 No. 4, 2021, pp. 101-115. doi: 10.5923/j.ijcem.20211004.02.

Article Outline

1. introduction, 2. literature review, 2.1. key concepts of project performance, 2.2. problem of performance in construction industry, 2.3. construction management and performance, 2.4. information technology and construction projects performance, 2.5. factors affecting performance of managers, 2.6. factors affecting cost and time performance, 2.7. factors affecting road construction performance, 3. research methodology, 3.1. research design and approach/strategy, 3.2. study population, 3.3. sample size, 3.4. area of study, 3.5. data collection methods, 3.6. data collection instruments, 3.7. validity of the instruments, 3.8. reliability of the instrument, 3.9. data analysis, 3.10. attainment of research objectives, 3.10.1. establishing the factors influencing the performance of road construction projects, 3.10.2. establishing the extent of impact of the factors on performance of road construction projects, 3.10.3. establishing the relationship between the factors influencing performance and the performance of road construction projects, 3.10.4. developing a frame work to improve performance of road construction projects, 4. findings and discussions, 4.1. demographics of the respondents, 4.2. empirical findings, 4.2.1. establishing factors influencing the performance of road construction projects in uganda, 4.2.2. ranking of the main factors influencing the performance of road construction projects, 4.2.3. extent of impact of the main factors influencing performance of road construction projects, 4.2.4. extent of impact of the sub-factors of all the main factors influencing the performance of road construction projects, 4.2.5. most influential and impacting factors on performance of road construction projects in uganda, 4.2.6. correlation analysis of the main factors influencing performance of road construction projects in uganda, 4.2.7. a framework to improve the performance of road construction projects in uganda, 5. conclusions and recommendations, 5.1. conclusions, 5.2. recommendations, 6. limitations of the research, acknowledgements.