research paper about customer service

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Providing Excellent Customer Service Is Therapeutic: Insights from an Implicit Association Neuromarketing Study

Gemma anne calvert.

1 Nanyang Business School, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore; gs.ude.utn@CAMIL

Abhishek Pathak

2 School of Business, 4 Nethergate, University of Dundee, Dundee DD1 4HN, UK; [email protected]

Lim Elison Ai Ching

Geraldine trufil.

3 Split Second Research Limited, London E1 8FA, UK; [email protected] (G.T.); [email protected] (E.P.F.)

Eamon Philip Fulcher

This paper reports the results of a combined biometric and implicit affective priming study of the emotional consequences of being the provider or receiver of either positive or negative customer service experiences. The study was conducted in two stages. Study 1 captured the moment-by-moment implicit emotional and physiological responses associated with receiving and providing good customer service. Study 2 employed an affective priming task to evaluate the implicit associations with good and poor customer service in a large sample of 1200 respondents across three Western countries. Our results show that both giving and receiving good customer service was perceived as pleasurable (Study 1) and at the same time, was implicitly associated with positive feelings (Study 2). The authors discuss the implications of the research for service providers in terms of the impact of these interactions on employee wellbeing, staff retention rates and customer satisfaction.

1. Introduction

Customer satisfaction is a vital goal for all businesses because it leads to increased sales and customer re-patronage, which ultimately boosts profits. To this end, managing customer experiences across the customer–employee touchpoints plays a critical role, given that most businesses involve some level of direct contact (e.g., face-to-face or voice-to-voice) between employees (especially those working at the consumer interface) and customers. Yet delivering high quality and effective customer service is not a straightforward or easily managed process. Customer–employee interactions have a significant emotional component that often confounds training strategies. While it is understood that positive customer service results in better marketing outcomes, much less is known about the emotional impact on those responsible for delivering that service.

Service employees often hide their true inner feelings and maintain a pleasant facial and bodily display in a bid to please their customers and/or gain control over employee–customer interactions [ 1 , 2 ]. Indeed, companies often train their service employees to act in a friendly manner since the display of positive emotions is associated with favourable consequences, such as increased customer satisfaction, customer re-patronage, and positive word-of-mouth [ 3 ]. Such acting requires significant effort on the part of the employees and can cause employees to suffer emotional burn-out if they are required to “put on” displayed emotions for long periods of time [ 4 , 5 ]. Furthermore, consumers do not always appreciate employee friendliness, and may even construe it negatively as being disrespectful [ 6 ]. Indeed, consumers are increasingly adept at discerning the expressive behaviour of service providers. For instance, they are more likely to be moved by the authenticity of an employee’s smile rather than the extent of it [ 7 , 8 ]. The somewhat artificial nature of these exchanges, coupled with the constant requirement to suppress negative emotions and “appear” friendly and understanding, makes it extremely difficult to disentangle true emotions associated with positive and negative customer–staff interactions and those which individuals presume they should experience.

Measuring the emotional consequences associated with customer experience is further complicated by the fact that it involves multiple moments of contact between an organisation and a customer. These may include the feelings evoked when walking into a shop, the way in which the customer is treated by frontline service employees in-store, as well as post-purchase follow-up customer service. Furthermore, the ability of individuals to introspect and comment on the nature of these subjective emotional responses, particularly during dynamic social interactions, is highly variable and often inaccurate [ 9 , 10 ]. The relationship (and perceptions thereof) between the employee-customer interaction has traditionally been measured using surveys [ 11 ] (may not be accurate always, and we propose an alternate method in this the current paper.

Extant scholarly researchers as well as companies interested in assessing service quality mostly employ explicit, self-reported measures. However, this approach captures only a partial picture of the multitude of responses in consumers’ brains. Neuroscience research has shown that a vast amount of human behaviour is driven and influenced by emotional and cognitive responses that occur below conscious awareness [ 12 , 13 , 14 ]. At the conscious level, customers tend to know what they want and also how they wish to be treated. But important implications of good and poor customer service can also play out at the subconscious or implicit level of cognition [ 15 , 16 ]. The same is true for those responsible for providing that service, where multiple conscious and subconscious emotional factors impinge on the effectiveness of customer interactions.

Although it is well known that the quality of customer–employee interaction is crucial for organisations and the importance of customer service has been studied for many years now, the literature is scarce on the consequences of poor (or good) service on employees [ 17 , 18 ]. Poor customer–employee interaction can lead to employee stress and is a potential health risk [ 19 ], which can cost up to $ 300 billion in losses cumulatively to organisations the world over American Institute of Stress (2014). Employees who are regularly tasked to maintain positive interactions with customers have also been reported to show excessive emotional burden, exhaustion and absenteeism [ 20 , 21 ]. Similarly, customer mistreatment (and consequent stress) can compromise both short term and long-term employee well-being [ 22 ] and result in emotional exhaustion [ 23 ].

Recent research has also shown that positive customer behaviour during service interactions has a cross over positive effect on the employee [ 24 ]. Similarly, stressful customer interactions can have a negative impact on the affective state of employees [ 25 ].

In order to develop a deeper understanding of the implicit consequences of customer service on providers and receivers, this research examined the implicit emotional responses associated with receiving and providing excellent service. Specifically, the paper investigated 1) the perception of both giving and receiving good vs. bad customer service, 2) and the implicit associations (or feelings) which people associate with the experience of giving or receiving good vs. bad customer service. By doing so, this research contributes to the services literature by demonstrating how the positive benefits of excellent customer service can impact not only on customers, but also on service providers themselves. Such positive outcomes, if made explicit, can clearly be exploited in a positive way so as to increase employee job satisfaction and reduce staff turnover rates. Furthermore, this research also contributes to the field by proposing a new research approach that captures customers’ subconscious responses in order to gain a more comprehensive understanding of the subliminal effects of positive customer–employee interactions.

2. Background

Over the past decade, techniques that have emerged from the fields of neuroscience and psychology, such as functional MRI, electroencephalography (EEG), eye-tracking, biometrics, facial decoding and implicit association testing, have been engaged by brand owners to capture these vital subconscious responses in order to define and predict consumer behaviour with much greater accuracy (for a recent review, see [ 9 ]). This approach has been referred to as “neuromarketing” [ 26 ] and numerous commercial practitioners of this burgeoning industry now exist. In recent years, commercial entities have paid particular attention to neuromarketing methods that are scalable, cost-effective and offer fast turnaround times [ 27 ].

One methodology that satisfies these criteria is the use of implicit reaction time tests [ 28 ]. The mainstay of many cognitive psychology experiments since the 1970s, implicit reaction time paradigms measure individuals spontaneous or ‘gut instinct’ responses. Commercial adaptations of these paradigms permit marketers to capture these vital subconscious consumer responses online, without the need for verbal feedback or even respondents’ awareness of their reactions. Implicit measures have now been used in a variety of settings to extract people’s implicit emotions and attitudes to a wide range of different issues, including racial prejudice, sexual preferences, alcoholism, mental health, and consumer attitudes (see [ 29 ] for an overview). Importantly, the implicit responses obtained in these studies were shown to be more predictive of respondents’ subsequent behaviour than their explicit verbal responses obtained at the same time and are therefore, in many instances, more accurate indicators of their emotional responses to specific concepts and scenarios.

Several recent implicit reaction time paradigms have been shown to have high reliability and validity [ 30 , 31 , 32 , 33 ]. These approaches rely on a simple behavioural response—a very rapid key press to the presentation of a stimulus, which is made following a simple decision about the stimulus. There are several distinct implicit paradigms, each with specific strengths and weaknesses, and the choice of task depends on the research question being addressed [ 29 ].

In the current study, we employed two implicit reaction time tests. The first was the Impulse Test recently developed and shown to measure the emotions evoked as respondents view dynamic material (e.g., while watching a television advertisement, movie trailer or video footage [ 34 ]. The second was an affective semantic priming task [ 35 , 36 ] that assesses the strength of implicit association between a set of emotional words and specific concepts, in this case, good and poor customer service. The rationale for employing two distinct implicit tests was that in the first case, we were able to identify the immediate emotions elicited by positive customer service interactions (both from the perspective of the provider and the receiver) and relevant in short-term memory, and in the second case, we were able to capture the more deep-seated emotions associated with positive as well as negative customer interactions that are stored in long-term memory.

Physiological responses (heart and breathing rate and electrodermal changes) were also measured during the Impulse test to determine if positive customer service interactions (both providing and receiving) impact the levels of arousal. Arousal, one of the components of emotional responding, is associated with stress, anxiety and fear [ 37 ], and physiological manifestations of arousal include increased blood pressure, heart rate, sweating and hyperventilation [ 38 ]. We hypothesized that the act of simply observing positive customer–staff interactions would result in reduced arousal and therefore stress levels, similarly to that experienced when engaging in other everyday pleasures.

This study was conducted in two stages. Study 1 was designed with two objectives in mind: first, the study served to identify the nature of the immediate emotions elicited in real time as respondents viewed videos of people receiving or providing excellent customer service compared with viewing other positive scenarios (e.g., everyday pleasurable activities such as enjoying time with friends), and secondly, we wanted to examine the physiological responses (heart and breathing rate, and electrodermal response) to the customer service scenarios depicted in the videos. In Study 2, we examined the more deeply held emotions (i.e., those maintained in long term memory) associated with customer service interactions (positive and negative) in a larger population (N = 1200) across three countries that individuals have either delivered or received.

3.1. Study 1: Laboratory Based Study

3.1.1. participants.

Twenty participants (thirteen females (two left-handed) and seven males (all right-handed) with mean age of 27 years) were recruited from Bristol, UK (via flyers in exchange for vouchers) and given small incentives to take part in a study to measure their immediate physiological and psychological responses to different emotional scenarios in real-time, including footage depicting individuals providing or receiving customer service (sample size is similar to other studies of comparable nature, e.g., [ 39 ]).

3.1.2. Materials

Three distinct video clips, each one minute in duration, were professionally created specifically for this study:

Video 1 (Condition 1: Control): was made up of footage of everyday pleasures (unrelated to customer service) shown from the first person perspective, such as eating crisps, going for a walk in the park.

Video 2 (Condition 2: Providing excellent customer service): constituted footage of four different scenarios in which service staff were filmed delivering excellent customer service and the footage shown from the service provider’s perspective. The scenarios were as follows: (i) a booking agent is seen giving a customer tickets to a previously sold out play at the theatre and knowing she has had a hard time recently, the booking agent has gone one step further and arranged for her to go to the opening night party as well, (ii) a travel agent helps a couple, who have been separated for six months due to work, to plan their dream honeymoon, giving them personalised recommendations on where to visit and restaurants to eat out at, (iii) a groom leaves his wedding rings in the back of a taxi the day before the wedding. The taxi driver returns to the hotel where he dropped off the groom off, re-uniting him with the rings and thus saving the day, and (iv) a woman collapses in a restaurant while on holiday after which a fellow customer, a doctor, tries to help but her friend is very distressed and does not speak the local language. The waitress steps in to translate what the doctor is saying and accompanies them all to hospital.

Video 3 : (Condition 3: Receiving excellent customer service): shows scenarios featuring excellent customer service and are the same scenarios as those used in Condition 2 but re-filmed and shown from the customer’s perspective.

3.1.3. Protocol

Only one subject at a time participated in the experiment. Each participant was greeted by the experimenter who explained that the purpose of the study was to gain a better understanding of customer service interactions. After obtaining informed consent (FREC-EF02-PSY-16-1-2013), physiological electrodes were applied and subjects were seated in front of a computer screen. Heart and breathing rate as well as skin conductance measures were collected as subjects viewed the video clips. The experimental videos were shown on a computer screen and participants’ responses were recorded using the computer keyboard. The order of presentation of the three videos was counterbalanced across subjects.

BIOPAC physiological equipment was used in the collection of data. In order to measure heart rate, one electrode was placed on the medial surface of each leg just above the ankle. A third electrode was placed on the right anterior forearm at the wrist. Once electrodes were attached, participants were asked to remain still while the system parameters were calibrated. Data was recorded at a rate of 200 times a second. Heart rate was measured as the milliseconds between heart beats and was analyzed as the average heart-rate per two seconds (400 datapoints).

Skin conductance data was collected through two electrodes attached to the middle and ring finger of the non-dominant hand. The index finger was avoided as it was used in the reaction time task. Participants were given the opportunity to practice key pressing with minimal movement of the hand, so as not to disturb recording. Respiratory cycle was recorded through a respiratory transducer attached around the chest below the armpits and over the shirt. It was adjusted so that it was slightly tight at the point of maximal expiration.

During the acquisition of biometric data, subjects were also asked to carry out an implicit reaction time test (the Impulse test) while viewing the experimental videos. The Impulse test consists of two stages—a baseline phase and an experimental phase. In the baseline phase of the current task, participants were exposed to a set of emotional words (see Table 1 , presented one at a time and in randomised order in the centre of the computer screen). Each word was presented four times, and on each occasion, the words were displayed on the screen until the correct key was pressed or 2 s had elapsed. The next word was presented 2 s after the previous word. The selection of emotional words most relevant to the content shown in our three videos was determined in a prior pilot study in which 16 words (8 positive and 8 negative) were identified from a cohort of 50 words as being ranked most closely to the emotions elicited in the videos and categorised consistently as of positive or negative valence.

Emotional words used during the Impulse test.

On each trial, an emotional word appeared briefly on the computer screen and subjects were instructed to categorise them according to their emotional valence by pressing the “I” key on the keyboard if the word was positive in nature and the “E” key if the word was negative (key mapping was counterbalanced between the subjects). A reminder of which key corresponded to which emotional valence “Positive” or “Negative” remained on the computer screen in the top left and right corners throughout the two phases. Subjects were asked to respond as quickly and as accurately as possible.

The baseline trials and the experimental trials were identical, except that a video was played in the background during the experimental trials. The baseline phase of the Impulse test served both as a means of training the subjects to respond within a very short timeframe (to clear contamination from conscious brain processes) and also to familiarise the participants with the task. Responses that were deemed too slow to be classified as pre-cognitive were followed by a brief warning tone and the visual warning “too slow”. Following successful completion of the training phase, subjects were informed via instructions on the computer that the experimental phase was about to begin. The design was similar to the practice phase, however, during this phase, the words appeared superimposed on the dynamic footage (the three videos are described in the Materials section). Respondents were instructed to continue classifying the words as positive or negative in terms of emotional valence and to press the corresponding keys on the computer keyboard.

Our previous research has shown that the speed and accuracy of classification of these words reflect the feelings that a participant has towards the content of the movie or television clip [ 34 ]. By comparing reaction times to classify positive and negative emotional words during the training (baseline) and experimental phase, it is possible to infer the nature of the internal feelings elicited in the viewer by the video content every 2 s. Specifically, we have found that positive emotions elicited by the footage shown, speeds responses to positive words and slows them to negative ones. The reverse holds true for aspects of the footage that elicits negative emotions—responses to negative words are sped up and responses to positive words are slowed. In both cases, RTs were computed against the responses recorded during the baseline and training phase, for each participant. To understand this approach in the context of semantic priming studies, in the current study, the video content acts as the “priming” stimulus, with the emotional words being the targets.

3.1.4. Analysis

The physiological analysis focused on the emotional peaks detected whilst watching each video. We hypothesized that during each emotionally provocative video, there were likely to be fluctuations in arousal, as determined by changes in electro-dermal response, breathing rate and heart rate. We also hypothesized that these physiological indices would be accompanied by changes in implicit psychological emotional responses detected using the Impulse test.

Physiological Responses

For the physiological data, the maximum values for each physiological measure (heart rate, breathing rate and skin conductance) were first computed by extracting the peak response recorded every 2 s during both the training and experimental phase of the Impulse test and the results from all individuals averaged and tested for statistical significance using paired T-tests at each time point (see Figure 1 ).

This graph shows the heart rate of one representative participant when they were carrying out the baseline test (blue line) and the test with the movie clip in the background (red line). The resulting data computed for this participant is the difference between the blue and red heart rate values every two seconds. When the value of a point on the red line is larger than the value of the corresponding point on the blue line (e.g., at t = 6), it shows that the participant’s heart rate increased as a result of watching this part of the movie clip. Conversely, at t = 28, the participant’s heart rate shows a decrease. These values were computed for each participant and then averaged and subjected to statistical analysis.

Impulse Test

Reaction time data obtained during the training and experimental phases of the Impulse test were first subjected to pre-processing, including removal of outliers so that responses that were impossibly quick (<250 ms) and those that were so slow as to invoke conscious processing (>1200 ms), were removed. The data were then analysed following the method outlined by Fazio and Olson [ 36 ]. For all trials of each word presented in each video, a facilitation index (FI) was computed. For all congruent responses (e.g., classifying “delightful” as “Positive”) obtained for each word across all trials, the FI was computed by subtracting the reaction times during the experimental phase from those obtained during the baseline phase. For incongruent responses to each word (e.g., classifying the word “lonely” as “Negative”), the FI calculation was reversed such that reaction times obtained during the baseline phase were subtracted from the reaction times obtained during the experimental phase. Thus, an FI greater than zero implies a response that is congruent with the emotion word set and a FI less than zero implies a response incongruent (or opposite) with the word set. This approach allowed us to take into account both the congruency (or subjective accuracy) of responses as well as the reaction times. The dependent variable was, for each moment of each video (every two seconds), the percentage of participants whose FI indicated that the footage at each time-point was either congruent or incongruent with a positive emotion or negative emotion. The averaged data were then tested for each condition for statistical significance using the binomial test that computes the probability of obtaining a specific count in one direction (e.g., a positive emotional response) against the total number of observations (the number of positive and negative responses).

3.1.5. Results

Physiological measures.

Condition 1: (Everyday pleasures) While viewing a video depicting everyday pleasures, breathing rate dropped from 16.3 cycles to 15.4 cycles per minute); heart rate remained stable at 76.1BPM in both cases; and a non-significant increase in electrodermal response from 0.171 to 0.252 was recorded.

Condition 2: (Providing good customer service) was associated with an average increase in heart rate from 76.0 BPM during the baseline phase to 87.4 BPM while the video was shown in the background ( p < 0.01). Breathing rate decreased from 16.7 cycles per minute during the baseline to 10.2 cycles per minute while viewing the video, and a significant increase in electrodermal response from 0.114 to 0.335 ( p < 0.001) was recorded.

Condition 3: (Receiving good customer service). A statistical comparison of physiological measures revealed that viewing footage of others receiving excellent customer service resulted in a significant increase in electrodermal response from 0.164 to 0.308 ( p < 0.01) and a significant decrease in heart rate from 71.4 to 80.6 BPM ( p < 0.05). There were no significant differences in breathing rate for condition 3 (17.2 to 16.8).

The control condition (viewing everyday pleasures) elicited an FI of −3.15, showing that that there was a slightly shorter mean response latency to negative attributes than to positive attributes. However, this FI did not differ from zero ( p > 0.05). Viewing footage of individuals receiving excellent customer service elicited an FI of +36.9, which reveals a significant increase in response latency to positive attributes ( p < 0.001). Viewing footage of individuals providing excellent customer service yielded the largest increase in FI of +53.8 ( p < 0.001). Paired t-tests revealed that providing excellent customer service elicited a greater association with positive emotions than either receiving excellent service ( p < 0.05) or viewing everyday pleasures ( p < 0.001).

3.1.6. Discussion and Conclusion

We believe that this is the first demonstration that viewing instances of positive customer service interactions from the perspective of both the recipient and the service provider has a positive impact on physiology and emotional well-being. Specifically, viewing footage of people delivering or receiving excellent customer service resulted in a significant increase in arousal levels, as evidenced by the increase in galvanic skin response and a significant decrease in heart rate (compared to viewing scenarios of everyday pleasures), indicating that positive customer service interactions can have a stress-reducing and calming impact on the service provider and surrounding viewers.

The results of the Impulse reaction time study showed that participants were faster at correctly classify positive word targets than negative ones when viewing footage of people providing good service compared to receiving it, or while viewing footage of every day pleasures. This is an intriguing finding as we would have hypothesized that people would adopt a self-interested stance and would instinctively attach greater positive valence to receiving good service than watching examples of people providing good service. Receiving good service was perceived with the same level of positive emotional engagement as viewing every day pleasures, highlighting the growing significance of customer service in people’s lives today.

The results of Study 1 raised further questions relating to the generalizability of these findings across different countries, age groups and gender. Therefore, in the next study, we sought to extend these findings by investigating the implicit emotional feelings associated with both positive, as well as negative, customer service interactions in a larger population using a web-based implicit affective priming task designed to uncover the strength of emotional association that people hold about positive and negative customer service interactions.

3.2. Study 2: Online Study

3.2.1. participants.

Participants (N = 1200) from three countries (UK, Canada and Australia; N = 400 from each country, 50% males) were recruited through a research participation recruitment company (Research Now) and were given small incentives to complete the tests. All the participants had normal to corrected vision, were native English speakers between 18 and 60 years and completed an online consent form prior to participation (the sample size is adequate for the chosen experimental design, since the study is a four (providing excellent or poor customer service vs. receiving excellent or poor customer service) by two (excellent service vs. poor service) design and is similar to other studies of comparable nature, e.g., [ 35 , 40 ].

3.2.2. Materials

The web-based survey included three components: (i) demographic questions to confirm age, gender, handedness and previous employment in a service industry, (ii) a consent form, and (iii) an implicit affective priming task. The survey was programmed in Javascript so that as soon as participants entered the survey, the test would automatically and immediately be downloaded onto their pc/laptop so that reaction times could be captured using the internal timing devices on the pc/laptop, which are far more sensitive than if running a program of this nature across the internet. On completion of the survey, the individual datasets were then uploaded back onto the server for analysis and without being apparent to the participant.

The affective priming task consisted of a series of emotional word primes ( Table 2 ) and target statements ( Table 3 ). The emotional word primes were selected following an explicit pilot test in 150 people (50 from each country) during which respondents were asked to classify attributes (from a set of 60; including those used in Study 1) into those most likely to be experienced in the context of extremely pleasurable experiences, peace of mind experiences, everyday experiences, and negative experiences. Of these, 35 were consistently classified and used as primes in the implicit test. The brief statements used as targets (e.g., “being helpful”, “feeling relieved”) were generated in consultation with service industry consultants and refer to the behaviours that were most often experienced in the context with excellent or poor service scenarios ( Table 3 ).

Emotional prime words used in the affective priming task.

Emotional words used to create brief statements used in Test A (Providing) and Test B (Receiving). All target words using in Test A were presented prefixed with the word “being” (e.g., “being helpful”, “being friendly”), whereas those used for Test B were pre-fixed with the word “feeling” (e.g., “feeling relieved”, “feeling neglected”).

3.2.3. Protocol

On entering the survey, respondents were asked to confirm their age, gender and handedness. They were also asked if there were currently employed, and/or did voluntary work and whether their current or any past employment involved “providing service of some form to service users, such as clients, customers or patients”. If they answered “no” to the last question, they were thanked for participating but informed that they were not eligible for the study.

On completing the inclusion criteria questions and subsequent consent form, participants were then asked to classify each of the 35 emotion words (pre-selected for inclusion in the implicit test) as extremely pleasurable experiences, peace of mind experiences, mundane experiences and negative experiences.

Participants were then instructed that they would be asked to perform a reaction time task that would measure how quickly and accurately they could classify a series of short phrases (see Table 3 ) that would be presented in the centre of the computer screen. There were two tasks designed to identify emotions implicitly associated with providing excellent or poor customer service (Test A) or receiving excellent or poor customer service (Test B). Participants were randomly assigned to one of the two tasks.

Before the experimental trials, participants were given 24 practice trials during which they were asked to discriminate whether short phrases which were either positive or negative (e.g., “being helpful”, “being impolite” in the case of test A— providing excellent or poor service) and (e.g., “feeling special”, “feeling neglected” in the case of test B— receiving excellent or poor customer service) were synonymous with either “excellent service” or “poor service” and to press the “E” or “I” key on the computer keyboard corresponding to each option. The practice trials served as a learning phase during which respondents were able to learn the association between each target and the correct key press so that they would not need to focus on which key to press during the main test.

The keys were allocated to “excellent service” or “poor service” and were counterbalanced for each participant, and once assigned, remained so for the duration of the task. If a response was incorrect, the error message “Try again!” appeared near the lower part of the screen; if two keys were pushed at the same time, the message “Please press only one key at a time” was displayed; if no key was pushed within two seconds, the cue “Warning: Please press E or I” appeared. The next trial proceeded after a 1500 ms inter-trial interval. Participants were instructed to respond as quickly as possible but to avoid making a mistake.

Following practice trials, participants were told that the main trials were about to begin and would be very similar as the practice phase but this time a word or “prime” was presented for 500 ms, immediately before the short phrase targets. Each prime was presented four times in total, twice before a phrase associated with “excellent service” and twice before a phrase associated with “poor service” to ensure a sufficient number of trials of each type. Prior testing has shown that with an N = 1200, this number of trials is sufficient to be able to detect a statistical difference if it exists. The task was identical to that conducted during the practice trials, which was to discriminate whether the targets (e.g., “being” or “feeling” a positive or negative emotion) that appeared immediately after the primes (see Table 2 ) were associated with “excellent service” or “poor service” and to respond as quickly and as accurately as possible by pressing the key corresponding to each option.

3.2.4. Analysis

Data were first subjected to analysis to remove outliers, including response times that were impossibly fast (<250ms) or those that occurred after the permitted time window. Reaction times were then computed for each word attribute and for each participant. A difference score was computed being the mean reaction time when the prime was presented before ‘poor service’ minus the mean reaction time when the prime was presented before ‘excellent service’. This was also done separately for Tests A (Providing) and B (Receiving). Positive difference scores indicated that a prime was more strongly associated with “excellent service” than with “poor service”. Negative difference scores indicated the reverse. Difference scores greater than zero were recoded as +1 and difference scores less than zero were recoded as −1 (scores at zero were not included in the subsequent analyses). For each attribute, we then computed the percentage number of 1 s, this value would reflect the percentage of participants who more strongly associated the prime with excellent service than with poor service.

3.2.5. Results

The results focus on the comparison of emotional attributes that were both significantly associated with providing versus receiving positive and negative customer service, as well as the overall number of positive and negative emotions attributed to each condition. Here, we first report the results for the entire group (averaged across all countries).

Providing Excellent Customer Service

The analysis of reaction times recorded when participants classified the targets subsequent to emotional primes in Test A (Providing customer service) found that (collapsed across all countries) providing excellent service was associated with fastest responses to feeling “calm” and “proud” ( p < 0.001). Other emotional word attributes that were found to be strongly associated with providing excellent service included feeling “fair”, “engaged”, “loved” and “pleased”, “nice”, “okay” and “ecstatic” ( p < 0.05). A total of nine positive emotion words were found to be implicitly associated with providing excellent customer service.

Receiving Excellent Customer Service

Receiving excellent service (Test B) was found to be associated with faster responses when preceded by the primes “energised”, “happy” and “proud” ( p < 0.001). Other emotions that were also strongly associated with receiving excellent customer service were “calm”, “satisfactory”, “nice”, “fair” and “okay” ( p < 0.05), attributes that were previously categorised as being experienced when engaging in everyday pleasures, such as meeting friends.

A comparison of significant associations across the two tests (see also Figure 2 ) revealed that only providing excellent service was associated with “pleased” and “ecstatic”, whereas receiving excellent service elicited significant associations with the attributes “energised”, “happy”, “thrilled”, “excited”, “fine” and “fortunate”.

Emotional attributes associated with providing versus receiving excellent customer service (Y-axis shows the percentage of people significantly associating primes with the receipt and provision of excellent service).

Providing Poor Customer Service

Providing poor customer service was significantly associated with the emotional attributes, “lonely”, “nervous”, “sad” and “annoyed”.

Receiving Poor Customer Service

Receiving poor customer service was significantly associated with these same four emotional attributes and additionally, with feeling “ignored”. Receiving poor service was more strongly associated with the attributes “sad” and “annoyed” than was providing poor service (see also Figure 3 ).

Emotional attributes associated with providing versus receiving poor customer service (Y-axis shows the percentage of people significantly associating primes with the receipt and provision of poor service).

Gender Differences

The statistical comparison of males and females collapsed across all countries found that while females associated more positive attributes with receiving excellent customer service, males associated more positive attributes with providing excellent customer service (both ps < 0.01). Specifically, females associated receiving excellent service with feeling “happy”, “energised”, “over-joyed”, “proud”, “thrilled”, “exhilarated”, “loved”, “nice”, “expected”, and “fair”. Receiving poor service was more significantly associated with feeling “nervous”, “sad” and “lonely”. By comparison, providing excellent service was associated with feeling “proud”, “calm”, “pleased”, “fair”, and “engaged”, whereas providing poor service was associated with feel “sad”, “annoyed” and “lonely”.

Males were faster to associate the provision of positive customer service with feeling “energised”, “calm”, “engaged”, “proud”, “thrilled” and “nice”. Providing poor service made them feel “nervous”. Receiving excellent customer service was associated with feeling “satisfactory”, “calm”, “okay”, “satisfied”, “ecstatic”, ”engaged”, “relief” and “nice”. Receiving poor customer service was associated with feeling “annoyed”, “regular” and “lonely”.

Age Differences

Respondents aged between 18 and 35 years associated more positive attributes with receiving than providing excellent customer service ( p < 0.001), including “OK, fair, confident, nice, satisfactory, engaged, energised, thrilled, calm, ecstatic, exhilarated, content, happy, pleasant”. Receiving poor service was associated with feeling “annoyed”, “sad” and “lonely”. Providing excellent service was associated with feeling “calm”, “engaged” and “proud” and “OK”; providing poor service made them feel “sad”, “ignored” and “nervous”.

In stark contrast, respondents in the older age group (36+) associated more positive attributes with providing rather than receiving excellent customer service ( p < 0.001). Specifically, providing excellent service was more closely associated with feeling “proud” and “calm”, “excited”, “pleased”, “nice” and “fair”. Providing poor service made them feel more “annoyed” and “sad”. Receiving excellent service made the older group feel “proud” and “calm”, poor service interactions made them feel “nervous”, “lonely”, “ignored”, “regular” and “sad”.

Cross-Cultural Differences

There were also a number of interesting cross-cultural differences in terms of the emotions most closely associated with providing and receiving good and poor customer service.

United Kingdom (least Impacted by Customer Service- Expectations much Lower)

Comparison of the statistical effect sizes between countries revealed that while respondents in the United Kingdom showed a positive association between giving or receiving amazing service, the effect was lower than that recorded for Canada and Australia.

Canada (Focused on “Providing”)

It was noteworthy that Canadians felt more “thrilled”, “content” and “pleased” when providing rather than receiving excellent service. Receiving, rather than giving amazing service was, on the other hand, more associated with a positive association with the emotions, “exhilarated”, “energised”, “happy”, “loved”, “relieved”, “pleasant” and “fine” ( p < 0.05).

Australia (Receiving is More Emotionally Important than Giving)

Australians were found to associate the provision of amazing service with a sense of “calm” ( p < 0.05), compared to receiving the same level of service. Australians were statistically more likely to feel “fortunate”, “thrilled”, “happy” and “appreciated” when receiving excellent service compared to when they were providing it.

3.2.6. Conclusions

In study 2, we demonstrated the implicit association of positive and negative feelings with proving and receiving good customer service across a large general populace. We also show the generalizability of our results across three cultures, ages and genders. Specifically, we demonstrated that, (1) providing and receiving excellent customer service was strongly associated with certain emotions (feeling “calm”, “proud”, “fair”, “engaged”, “loved”, “pleased”, “nice”, “okay”, “ecstatic”, “energised”, “happy” and “satisfactory”), and (2), providing and receiving poor customer service was strongly associated with certain emotions (feeling “lonely”, “nervous”, “sad”, “annoyed” and “ignored”), (3) females associated providing and receiving excellent customer service with certain emotions (“happy”, “energised”, “over-joyed”, “proud”, “thrilled”, “exhilarated”, “loved”, “nice”, “expected”, “fair”, “calm”, “pleased” and “engaged”), (4) females associated providing and receiving poor customer service with the emotions “nervous”, “sad”, “lonely” and “annoyed”, (5) males associated providing and receiving excellent customer service with the emotions “energised”, “calm”, “engaged”, “proud”, “thrilled”, “nice”, “satisfactory”, “okay”, “satisfied”, “ecstatic” and “relief”, (6) males associated providing and receiving poor customer service with the emotions (“nervous”, “annoyed”, “regular” and “lonely”). We also found that younger respondents associated more positive attributes with receiving, rather than providing, excellent customer service, whereas older respondents associated more positive attributes with providing rather than receiving excellent customer service. Among cross-cultural differences, we found that in (1), UK respondents showed a weak association between giving or receiving an amazing service and their expectations were lower (compared to Canada and Australia), (2) Canadian respondents showed a stronger association for providing rather than receiving excellent service and (3), Australian respondents showed a stronger association for receiving rather than providing excellent service).

4. General Discussion

In the current study, we exploited two implicit reaction time tasks. The first, the recently developed Impulse test, is a novel implicit reaction time paradigm that measures the moment-to-moment shifts in emotions when, for example, people are viewing dynamic videos or footages [ 34 ]. The second is a task based on affective priming, a very well established implicit paradigm that was developed out of cognitive psychology in the 1980s [ 41 , 42 , 43 ] and has been recently adapted for use in commercial neuromarketing studies [ 35 ]. Both implicit tasks are ideal for capturing the complex, often subconscious, emotions associated with receiving and providing customer service of varying quality in order to understand the subtle impact of these customer–staff interactions on emotional well-being. Major advantages of using these methods are that they are indirect and are not as susceptible to the response biases associated with explicit responses (e.g., self-reported measures) and that they can reveal the moment-to-moment scores during a video clip, rather than a post test score.

Our results show that people do not only find receiving excellent customer service as pleasurable but providing excellent service is equally satisfying. We corroborate these results using both physiological measures (study 1) and an implicit reaction time paradigm (study 2). We also provide evidence that both giving and receiving excellent service can actually reduce stress and anxiety levels amongst both consumers and service providers and have a positive impact on their wellbeing. These results were shown to hold true across three countries, demonstrating that giving and receiving excellent customer service can induce a sense of pride, calmness and of being loved.

Our data additionally revealed some age and gender differences. Specifically, our results reveal that younger individuals (18–35 years) exhibit more positive emotions when receiving than giving good customer service, whilst the opposite was the case for older participants. In thinking about being served, relatively more focus is placed on oneself (vs. others); in thinking about providing service, relatively more focus is placed on others (vs. oneself). Therefore, our results suggest that younger people tend to focus more on themselves (vs. others), whereas older individuals focus more on others (vs. themselves). This pattern of findings is consistent with Freund Blanchard-Fields’ [ 44 ] observation that older adults are more altruistic (i.e., focusing on the needs of others rather than on themselves) than younger adults, and tend to behave in ways that benefit others rather than themselves (e.g., donating money to a good cause rather than keeping it for themselves). By contrast, younger adults tend to focus on maximizing their personal gains over the interests of other people. Collectively, these findings add to the existing knowledge about customer service by underscoring the importance of age differences when it comes to customers and service providers. Future research may test the altruism explanation for the observed effects due to age differences.

Analysis of gender differences revealed that females tend to prefer receiving (vs. providing) excellent service, whereas the reverse is true for males. At first glance, this finding appears somewhat contradictory to past research that suggested that women are generally communal, warm, and nurturing, whereas men tend to be more competitive and goal-oriented [ 45 , 46 ]. However, we interpret this finding in the light of other research which showed that men and women place a different emphasis on different aspects of service. While men are usually more concerned about the core aspect of the service (e.g., the haircut received at a hair salon), women generally pay more attention to the relational aspects of service (e.g., how well one gets along with the hairstylist) [ 47 ]. It is also likely that the core (relational) aspects of service are more salient when thinking about giving (receiving) excellent customer service because the focus is on helping the recipient resolve their problem (core aspect); in thinking about receiving service, it is easier to think about how one would feel about being served (relational aspect). Applying this to the gender differences that we found, it is possible that men preferred giving (vs. receiving) excellent service because it is more closely aligned with their goal-oriented tendency. Women, on the other hand, preferred receiving (vs. giving) excellent service as they were drawn towards its more highly salient relational aspects of service as they imagine themselves being served. Future research may follow this lead to explicitly examine the underlying processes driving the results that we observed through the implicit tests.

4.1. Theoretical and Methodological Contributions

To the best of our knowledge, this research is the first to employ two implicit tests, targeting both individual and group level responses, in order to yield a comprehensive view of the payoffs of good customer service. This current research also contributes to retailing research, which tends to focus on explicit data, by adding the implicit angle to understand how customer service impacts individuals at a subconscious level.

4.2. Implications for Managers and Organizations

Past research on customer service is heavily focused on understanding how customer service affects the customer and how satisfied customers in turn reward organizations with increased sales, patronage, and higher profits. Service personnel, who often shoulder the “burden” of delivering customer service that yields benefits to customers and organizations, appear to gain the least from the exchange. Our current research augments this stream of literature by focusing on what customer service means to service providers. Managerially, the observation that older people exhibit a preference for providing good customer service suggests that companies might wish to consider employing more mature individuals on the front line (albeit with due consideration of the physical requirements related to standing in-stores for long hours) because they may be more naturally inclined to servicing the needs of others. In addition, we believe that our results gain credibility from the fact that for the implicit reaction time test, the primes chosen (e.g., pleasant experiences) were selected by real consumers and the targets (e.g., “being helpful”) were chosen in consultation with service industry consultants.

Our study found that service providers also benefit from delivering good customer service in the form of enhanced emotional well-being and inoculation against negative, damaging emotions. To some extent, understanding that delivering good customer service is emotionally lifting to the service providers helps to resolve the pressure of having to engage in acting to please customers. In the emotional labour literature, researchers identified two levels of acting—surface (where the employee displays false emotions that s/he does not feel, only to please customers) and deep (where the employee feels the emotions that she/he displays to customers)—that service personnel use when dealing with customers. However, both surface and deep acting have potential problems. Surface acting is often perceived as fake and distancing to customers; on the other hand, deep acting places considerable emotional strain on the service provider. Based on our results, service providers can be coached to focus on understanding how delivering good service makes them feel and the subsequent emotional payoffs they can gain from it. This may help to reduce employee burn-out and turnover whilst maintaining happy customers and a healthy bottom-line. Therefore, training employees to focus on how good customer service benefits themselves creates a positive feedback loop that benefits customers, service providers, and organizations alike.

Author Contributions

G.A.C.: Design, interpretation and co-drafting of the original manuscript; E.P.F.: Design and co-drafting of original manuscript; G.T.: Design, testing and analysis; A.P.: Literature review, interpretation and editing of manuscript; L.E.A.C.: Literature review, interpretation and editing of manuscript.

This research received no external funding.

Conflicts of Interest

The authors declare no conflict of interest.

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AI-based chatbots in customer service and their effects on user compliance

• Research Paper
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• Published: 17 March 2020
• Volume 31 , pages 427–445, ( 2021 )

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• Martin Adam   ORCID: orcid.org/0000-0001-9369-7203 1 ,
• Michael Wessel   ORCID: orcid.org/0000-0002-2611-9689 2 &
• Alexander Benlian   ORCID: orcid.org/0000-0002-7294-3097 1  

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Communicating with customers through live chat interfaces has become an increasingly popular means to provide real-time customer service in many e-commerce settings. Today, human chat service agents are frequently replaced by conversational software agents or chatbots, which are systems designed to communicate with human users by means of natural language often based on artificial intelligence (AI). Though cost- and time-saving opportunities triggered a widespread implementation of AI-based chatbots, they still frequently fail to meet customer expectations, potentially resulting in users being less inclined to comply with requests made by the chatbot. Drawing on social response and commitment-consistency theory, we empirically examine through a randomized online experiment how verbal anthropomorphic design cues and the foot-in-the-door technique affect user request compliance. Our results demonstrate that both anthropomorphism as well as the need to stay consistent significantly increase the likelihood that users comply with a chatbot’s request for service feedback. Moreover, the results show that social presence mediates the effect of anthropomorphic design cues on user compliance.

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Introduction

Communicating with customers through live chat interfaces has become an increasingly popular means to provide real-time customer service in e-commerce settings. Customers use these chat services to obtain information (e.g., product details) or assistance (e.g., solving technical problems). The real-time nature of chat services has transformed customer service into a two-way communication with significant effects on trust, satisfaction, and repurchase as well as WOM intentions (Mero 2018 ). Over the last decade, chat services have become the preferred option to obtain customer support (Charlton 2013 ). More recently, and fueled by technological advances in artificial intelligence (AI), human chat service agents are frequently replaced by conversational software agents (CAs) such as chatbots, which are systems such as chatbots designed to communicate with human users by means of natural language (e.g., Gnewuch et al. 2017 ; Pavlikova et al. 2003 ; Pfeuffer et al. 2019a ). Though rudimentary CAs emerged as early as the 1960s (Weizenbaum 1966 ), the “second wave of artificial intelligence” (Launchbury 2018 ) has renewed the interest and strengthened the commitment to this technology, because it has paved the way for systems that are capable of more human-like interactions (e.g., Gnewuch et al. 2017 ; Maedche et al. 2019 ; Pfeuffer et al. 2019b ). However, despite the technical advances, customers continue to have unsatisfactory encounters with CAs that are based on AI. CAs may, for instance, provide unsuitable responses to the user requests, leading to a gap between the user’s expectation and the system’s performance (Luger and Sellen 2016 ; Orlowski 2017 ). With AI-based CAs displacing human chat service agents, the question arises whether live chat services will continue to be effective, as skepticism and resistance against the technology might obstruct task completion and inhibit successful service encounters. Interactions with these systems might thus trigger unwanted behaviors in customers such as a noncompliance that can negatively affect both the service providers as well as users (Bowman et al. 2004 ). However, if customers choose not to conform with or adapt to the recommendations and requests given by the CAs this calls into question the raison d’être of this self-service technology (Cialdini and Goldstein 2004 ).

To address this challenge, we employ an experimental design based on an AI-based chatbot (hereafter simply “chatbot”), which is a particular type of CAs that is designed for turn-by-turn conversations with human users based on textual input. More specifically, we explore what characteristics of the chatbot increase the likelihood that users comply with a chatbot’s request for service feedback through a customer service survey. We have chosen this scenario to test the user’s compliance because a customer’s assessment of service quality is important and a universally applicable predictor for customer retention (Gustafsson et al. 2005 ).

Prior research suggests that CAs should be designed anthropomorphically (i.e., human-like) and create a sense of social presence (e.g., Rafaeli and Noy 2005 ; Zhang et al. 2012 ) by adopting characteristics of human-human communication (e.g., Derrick et al. 2011 ; Elkins et al. 2012 ). Most of this research focused on anthropomorphic design cues and their impact on human behavior with regard to perceptions and adoptions (e.g., Adam et al. 2019 ; Hess et al. 2009 ; Qiu and Benbasat 2009 ). This work offers valuable contributions to research and practice but has been focused primarily on embodied CAs that have a virtual body or face and are thus able to use nonverbal anthropomorphic design cues (i.e., physical appearance or facial expressions). Chatbots, however, are disembodied CAs that predominantly use verbal cues in their interactions with users (Araujo 2018 ; Feine et al. 2019 ). While some prior work exists that investigates verbal anthropomorphic design cues, such as self-disclosure, excuse, and thanking (Feine et al. 2019 ), due to limited capabilities of previous generations of CAs, these cues have often been rather static and insensitive to the user’s input. As such, users might develop an aversion against such a system, because of its inability to realistically mimic a human-human communication. Footnote 1 Today, conversational computing platforms (e.g., IBM Watson Assistant) allow sophisticated chatbot solutions that delicately comprehend user input based on narrow AI. Footnote 2 Chatbots built on these systems have a comprehension that is closer to that of humans and that allows for more flexible as well as empathetic responses to the user’s input compared to the rather static responses of their rule-based predecessors (Reeves and Nass 1996 ). These systems thus allow new anthropomorphic design cues such as exhibiting empathy through conducting small talk. Besides a few exceptions (e.g., Araujo 2018 ; Derrick et al. 2011 ), the implications of more advanced anthropomorphic design cues remain underexplored.

Furthermore, as chatbots continue to displace human service agents, the question arises whether compliance and persuasion techniques, which are intended to influence users to comply with or adapt to a specific request, are equally applicable in these new technology-based self-service settings. The continued-question procedure as a form of the foot-in-the-door compliance technique is particularly relevant as it is not only abundantly used in practice but its success has been shown to be heavily dependent on the kind of requester (Burger 1999 ). The effectiveness of this compliance technique may thus differ when applied by CAs rather than human service agents. Although the application of CAs as artificial social actors or agents seem to be a promising new field for research on compliance and persuasion techniques, it has been hitherto neglected.

Against this backdrop, we investigate how verbal anthropomorphic design cues and the foot-in-the-door compliance tactic influence user compliance with a chatbot’s feedback request in a self-service interaction. Our research is guided by the following research questions:

RQ1 : How do verbal anthropomorphic design cues affect user request compliance when interacting with an AI-based chatbot in customer self-service?

RQ2: How does the foot-in-the-door technique affect user request compliance when interacting with an AI-based chatbot in customer self-service?

We conducted an online experiment with 153 participants and show that both verbal anthropomorphic design cues and the foot-in-the-door technique increase user compliance with a chatbot’s request for service feedback. We thus demonstrate how anthropomorphism and the need to stay consistent can be used to influence user behavior in the interaction with a chatbot as a self-service technology.

Our empirical results provide contributions for both research and practice. First, this study extends prior research by showing that the computers-are-social-actors (CASA) paradigm extends to disembodied CAs that predominantly use verbal cues in their interactions with users. Second, we show that humans acknowledge CAs as a source of persuasive messages and that the degree to which humans comply with the artificial social agents depends on the techniques applied during the human-chatbot communication. For platform providers and online marketers, especially for those who consider employing AI-based CAs in customer self-service, we offer two recommendations. First, during CAs interactions, it is not necessary for providers to attempt to fool users into thinking they are interacting with a human. Rather, the focus should be on employing strategies to achieve greater human likeness through anthropomorphism, which we have shown to have a positive effect on user compliance. Second, providers should design CA dialogs as carefully as they design the user interface. Our results highlight that the dialog design can be a decisive factor for user compliance with a chatbot’s request.

Theoretical background

The role of conversational agents in service systems.

A key challenge for customer service providers is to balance service efficiency and service quality: Both researchers and practitioners emphasize the potential advantages of customer self-service, including increased time-efficiency, reduced costs, and enhanced customer experience (e.g., Meuter et al. 2005 ; Scherer et al. 2015 ). CAs, as a self-service technology, offer a number of cost-saving opportunities (e.g., Gnewuch et al. 2017 ; Pavlikova et al. 2003 ), but also promise to increase service quality and improve provider-customer encounters. Studies estimate that CAs can reduce current global business costs of $1.3 trillion related to 265 billion customer service inquiries per year by 30% through decreasing response times, freeing up agents for different work, and dealing with up to 80% of routine questions (Reddy 2017b ; Techlabs 2017 ). Chatbots alone are expected to help business save more than $8 billion per year by 2022 in customer-supporting costs, a tremendous increase from the $20 million in estimated savings for 2017 (Reddy 2017a ). CAs thus promise to be fast, convenient, and cost-effective solutions in form of 24/7 electronic channels to support customers (e.g., Hopkins and Silverman 2016 ; Meuter et al. 2005 ).

Customers usually not only appreciate easily accessible and flexible self-service channels, but also value personalized attention. Thus, firms should not shift towards customer self-service channels completely, especially not at the beginning of a relationship with a customer (Scherer et al. 2015 ), as the absence of a personal social actor in online transactions can translate into loss of sales (Raymond 2001 ). However, by mimicking social actors, CAs have the potential to actively influence service encounters and to become surrogates for service employees by completing assignments that used to be done by human service staff (e.g., Larivière et al. 2017 ; Verhagen et al. 2014 ). For instance, instead of calling a call center or writing an e-mail to ask a question or to file a complaint, customers can turn to CAs that are available 24/7. This self-service channel will become progressively relevant as the interface between companies and consumers is “gradually evolving to become technology dominant (i.e., intelligent assistants acting as a service interface) rather than human-driven (i.e., service employee acting as service interface)” (Larivière et al. 2017 , p. 239). Moreover, recent AI-based CAs have the option to signal human characteristics such as friendliness, which are considered crucial for handling service encounters (Verhagen et al. 2014 ). Consequently, in comparison to former online service encounters, CAs can reduce the former lack of interpersonal interaction by evoking perceptions of social presence and personalization.

Today, CAs, and chatbots in particular, have already become a reality in electronic markets and customer service on many websites, social media platforms, and in messaging apps. For instance, the number of chatbots on Facebook Messenger soared from 11,000 to 300,000 between June 2016 and April 2019 (Facebook 2019 ). Although these technological artefacts are on the rise, previous studies indicated that chatbots still suffer from problems linked to their infancy, resulting in high failure rates and user skepticism when it comes to the application of AI-based chatbots (e.g., Orlowski 2017 ). Moreover, previous research has revealed that, while human language skills transfer easily to human-chatbot communication, there are notable differences in the content and quality of such conversations. For instance, users communicate with chatbots for a longer duration and with less rich vocabulary as well as greater profanity (Hill et al. 2015 ). Thus, if users treat chatbots differently, their compliance as a response to recommendations and requests made by the chatbot may be affected. This may thus call into question the promised benefits of the self-service technology. Therefore, it is important to understand how the design of chatbots impacts user compliance.

Social response theory and anthropomorphic design cues

The well-established social response theory (Nass et al. 1994 ) has paved the way for various studies providing evidence on how humans apply social rules to anthropomorphically designed computers. Consistent with previous research in digital contexts, we define anthropomorphism as the attribution of human-like characteristics, behaviors, and emotions to nonhuman agents (Epley et al. 2007 ). The phenomenon can be understood as a natural human tendency to ease the comprehension of unknown actors by applying anthropocentric knowledge (e.g., Epley et al. 2007 ; Pfeuffer et al. 2019a ).

According to social response theory (Nass and Moon 2000 ; Nass et al. 1994 ), human-computer interactions (HCIs) are fundamentally social: Individuals are biased towards automatically as well as unconsciously perceiving computers as social actors, even when they know that machines do not hold feelings or intentions. The identified psychological effect underlying the computers-are-social-actors (CASA) paradigm is the evolutionary biased social orientation of human beings (Nass and Moon 2000 ; Reeves and Nass 1996 ). Consequently, through interacting with an anthropomorphized computer system, a user may perceive a sense of social presence (i.e., a “degree of salience of the other person in the interaction” (Short et al. 1976 , p. 65)), which was originally a concept to assess users’ perceptions of human contact (i.e., warmth, empathy, sociability) in technology-mediated interactions with other users (Qiu and Benbasat 2009 ). Therefore, the term “agent”, for example, which referred to a human being who offers guidance, has developed into an established term for anthropomorphically designed computer-based interfaces (Benlian et al. 2019 ; Qiu and Benbasat 2009 ).

In HCI contexts, when presented with a technology possessing cues that are normally associated with human behavior (e.g., language, turn-taking, interactivity), individuals respond by exhibiting social behavior and making anthropomorphic attributions (Epley et al. 2007 ; Moon and Nass 1996 ; Nass et al. 1995 ). Thus, individuals apply the same social norms to computers as they do to humans: In interactions with computers, even few anthropomorphic design cues Footnote 3 (ADCs) can trigger social orientation and perceptions of social presence in an individual and, thus, responses in line with socially desirable behavior. As a result, social dynamics and rules guiding human-human interaction similarly apply to HCI. For instance, CASA studies have shown that politeness norms (Nass et al. 1999 ), gender and ethnicity stereotypes (Nass and Moon 2000 ; Nass et al. 1997 ), personality response (Nass et al. 1995 ), and flattery effects (Fogg and Nass 1997 ) are also present in HCI.

Whereas nonverbal ADCs, such as physical appearance or embodiment, aim to improve the social connection by implementing motoric and static human characteristics (Eyssel et al. 2010 ), verbal ADCs, such as the ability to chat, rather intend to establish the perception of intelligence in a non-human technological agent (Araujo 2018 ). As such, static and motoric anthropomorphic embodiments through avatars in marketing contexts have been found predominantly useful to influence trust and social bonding with virtual agents (e.g., Qiu and Benbasat 2009 ) and particularly important for service encounters and online sales, for example on company websites (e.g., Etemad-Sajadi 2016 ; Holzwarth et al. 2006 ), in virtual worlds (e.g., Jin 2009 ; Jin and Sung 2010 ), and even in physical interactions with robots in stores (Bertacchini et al. 2017 ). Yet, chatbots are rather disembodied CAs, as they mainly interact with customers via messaging-based interfaces through verbal (e.g., language style) and nonverbal cues (e.g., blinking dots), allowing a real-time dialogue through primarily text input but omitting physical and dynamic representations, except for the typically static profile picture. Besides two exceptions that focused on verbal ADCs (Araujo 2018 ; Go and Sundar 2019 ), to the best of our knowledge, no other studies have directly targeted verbal ADCs to extend past research on embodied agents.

Compliance, foot-in-the-door technique and commitment-consistency theory

The term compliance refers to “a particular kind of response — acquiescence—to a particular kind of communication — a request” (Cialdini and Goldstein 2004 , p. 592). The request can be either explicit, such as asking for a charitable donation in a door-to-door campaign, or implicit, such as in a political advertisement that endorses a candidate without directly urging a vote. Nevertheless, in all situations, the targeted individual realizes that he or she is addressed and prompted to respond in a desired way. Compliance research has devoted its efforts on various compliance techniques, such as the that’s-not-all technique (Burger 1986 ), the disrupt-then-reframe technique (Davis and Knowles 1999 ; Knowles and Linn 2004 ), door-in-the-face technique (Cialdini et al. 1975 ), and foot-in-the-door (FITD) (Burger 1999 ). In this study, we focus on FITD, one of the most researched and applied compliance techniques, as the technique’s naturally sequential and conversational character seems specifically well suited for chatbot interactions.

The FITD compliance technique (e.g., Burger 1999 ; Freedman and Fraser 1966 ) builds upon the effect of small commitments to influence individuals to comply. The first experimental demonstration of the FITD dates back to Freedman and Fraser ( 1966 ), in which a team of psychologists called housewives to ask if the women would answer a few questions about the household products they used. Three days later, the psychologists called again, this time asking if they could send researchers to the house to go through cupboards as part of a 2-h enumeration of household products. The researchers found these women twice as likely to comply than a group of housewives who were asked only the large request. Nowadays, online marketing and sales abundantly exploit this compliance technique to make customers agree to larger commitments. For example, websites often ask users for small commitments (e.g., providing an e-mail address, clicking a link, or sharing on social media), only to follow with a conversion-focused larger request (e.g., asking for sale, software download, or credit-card information).

Individuals in compliance situations bear the burden of correctly comprehending, evaluating, and responding to a request in a short time (Cialdini 2009 ), thus they lack time to make a fully elaborated rational decision and, therefore, use heuristics (i.e., rules of thumb) (Simon 1990 ) to judge the available options. In contrast to large requests, small requests are more successful in convincing subjects to agree with the requester as individuals spend less mental effort on small commitments. Once the individuals accept the commitment, they are more likely to agree with a next bigger commitment to stay consistent with their initial behavior. The FITD technique thus exploits the natural tendency of individuals to justify the initial agreement to the small request to themselves and others.

The human need for being consistent with their behavior is based on various underlying psychological processes (Burger 1999 ), of which most draw on self-perception theory (Bem 1972 ) and commitment-consistency theory (Cialdini 2001 ). These theories constitute that individuals have only weak inherent attitudes and rather form their attitudes by self-observations. Consequently, if individuals comply with an initial request, a bias arises and the individuals will conclude that they must have considered the request acceptable and, thus, are more likely to agree to a related future request of the same kind or from the same cause (Kressmann et al. 2006 ). In fact, previous research in marketing has empirically demonstrated that consumer’s need for self-consistency encourages purchase behavior (e.g., Ericksen and Sirgy 1989 ).

Moreover, research has demonstrated that consistency is an important factor in social exchange. To cultivate relationships, individuals respond rather affirmatively to a request and are more likely to comply the better the relationship is developed (Cialdini and Trost 1998 ). In fact, simply being exposed to a person for a brief period without any interaction significantly increases compliance with the person’s request, which is even stronger when the request is made face-to-face and unexpectedly (Burger et al. 2001 ). In private situations, individuals even decide to comply to a request simply to reduce feelings of guilt and pity (Whatley et al. 1999 ) and to gain social approval from others to improve their self-esteem (Deutsch and Gerard 1955 ). Consequently, individuals also have external reasons to comply, so that social biases may lead to nonrational decisions (e.g., Chaiken 1980 ; Wessel et al. 2019 ; Wilkinson and Klaes 2012 ). Previous studies on FITD have demonstrated that compliance is heavily dependent on the dialogue design of the verbal interactions and on the kind of requester (Burger 1999 ). However, in user-system interactions with chatbots, the requester (i.e., the chatbot) may lack crucial characteristics for the success of the FITD, such as perceptions of social presence and social consequences that arise by not being consistent. Consequently, it is important to investigate whether FITD and other compliance techniques can also be applied to written information exchanges with a chatbot and what unique differences might arise by replacing a human with a computational requester.

Hypotheses development and research model

Effect of anthropomorphic design cues on user compliance via social presence.

According to the CASA paradigm (Nass et al. 1994 ), users tend to treat computers as social actors. Earlier research demonstrated that social reactions to computers in general (Nass and Moon 2000 ) and to embodied conversational agents in particular (e.g., Astrid et al. 2010 ) depend on the kind and number of ADCs: Usually, the more cues a CA displays, the more socially present the CA will appear to users and the more users will apply and transfer knowledge and behavior that they have learned from their human-human-interactions to the HCI. Applied to our piece of research, we focus on only verbal ADCs, thus avoiding potential confounding nonverbal cues through chatbot embodiments. As previous research has shown that few cues are sufficient for users to identify with computer agents (Xu and Lombard 2017 ) and virtual service agents (Verhagen et al. 2014 ), we hypothesize that even verbal ADCs, which are not as directly and easily observable as nonverbal cues like embodiments, can influence perceived anthropomorphism and thus user compliance.

H1a: Users are more likely to comply with a chatbot’s request for service feedback when it exhibits more verbal anthropomorphic design cues.

Previous research (e.g., Qiu and Benbasat 2009 ; Xu and Lombard 2017 ) investigated the concept of social presence and found that the construct reflects to some degree the emotional notions of anthropomorphism. These studies found that an increase in social presence usually improves desirable business-oriented variables in various contexts. For instance, social presence was found to significantly affect both bidding behavior and market outcomes (Rafaeli and Noy 2005 ) as well as purchase behavior in electronic markets (Zhang et al. 2012 ). Similarly, social presence is considered a critical construct to make customers perceive a technology as a social actor rather than a technological artefact. For example, Qiu and Benbasat ( 2009 ) revealed in their study how an anthropomorphic recommendation agent had a direct influence on social presence, which in turn increased trusting beliefs and ultimately the intention to use the recommendation agent. Thus, we argue that a chatbot with ADCs will increase consumers’ perceptions of social presence, which in turn makes consumers more likely to comply to a request expressed by a chatbot.

H1b: Social presence will mediate the effect of verbal anthropomorphic design cues on user compliance.

Effect of the foot-in-the-door technique on user compliance

Humans are prone to psychological effects and compliance is a powerful behavioral response in many social exchange contexts to improve relationships. When there is a conflict between an individual’s behavior and social norms, the potential threat of social exclusion often sways towards the latter, allowing for the emergence of social bias and, thus, nonrational decisions for the individual. For example, free samples often present effective marketing tools, as accepting a gift can function as a powerful, often nonrational commitment to return the favor at some point (Cialdini 2001 ).

Compliance techniques in computer-mediated contexts have proven successful in influencing user behavior in early stages of user journeys (Aggarwal et al. 2007 ). Providers use small initial requests and follow up with larger commitments to exploit users’ self-perceptions (Bem 1972 ) and attempt to trigger consistent behavior when users decide whether to fulfill a larger, more obliging request, which the users would otherwise not. Thus, users act first and then form their beliefs and attitudes based on their actions, favoring the original cause and affecting future behavior towards that cause positively. The underlying rationale is users’ intrinsic motivation to be consistent with attitudes and actions of past behavior (e.g., Aggarwal et al. 2007 ). Moreover, applying the social response theory (Nass et al. 1994 ), chatbots are unconsciously treated as social actors, so that users also feel a strong tendency to appear consistent in the eyes of other actors (i.e., the chatbot) (Cialdini 2001 ).

Consistent behavior after previous actions or statements has been found to be particularly prevalent when users’ involvement regarding the request is low (Aggarwal et al. 2007 ) and when the individual cannot attribute the initial agreement to the commitment to external causes (e.g., Weiner 1985 ). In these situations, users are more likely to agree to actions and statements in support of a particular goal as consequences of making a mistake are not devastating. Moreover, in contexts without external causes the individual cannot blame another person or circumstances for the initial agreement, so that having a positive attitude toward the cause seems to be one of the few reasons for having complied with the initial request. Since we are interested in investigating a customer service situation that focusses on performing a simple, routine task with no obligations or large investments from the user’s part and no external pressure to confirm, we expect that a user’s involvement in the request is rather low such that he or she is more likely to be influenced by the foot-in-the-door technique.

H2: Users are more likely to comply with a chatbot’s request for service feedback when they agreed to and fulfilled a smaller request first ( i.e. , foot-in-the-door effect).

Moderating effect of social presence on the effect of the foot-in-the-door technique

Besides self-consistency as a major motivation to behave consistently, research has demonstrated that consistency is also an important factor in social interactions. Highly consistent individuals are normally considered personally and intellectually strong (Cialdini and Garde 1987 ). While in the condition with few anthropomorphic design cues, the users majorly try to be consistent to serve personal needs, this may change once more social presence is felt. In the higher social presence condition, individuals may also perceive external, social reasons to comply and appear consistent in their behavior. This is consistent with prior research that studied moderating effects in electronic markets (e.g., Zhang et al. 2012 ). Thus, we hypothesize that the foot-in-the-door effect will be larger when the user perceives more social presence.

H3: Social presence will moderate the foot-in-the-door effect so that higher social presence will enhance the foot-in-the-door effect on user compliance.

Research framework

As depicted in Fig.  1 , our research framework examines the direct effects of Anthropomorphic Design Cues ( ADCs ) and the Foot-in-the-Door ( FITD ) technique on User Compliance. Moreover, we also examine the role of Social Presence in mediating the effect of ADCs on User Compliance as well as in moderating the effect of FITD on User Compliance.

Research methodology

Experimental design.

We employed a 2 (ADCs: low vs. high) × 2 (FITD: small request absent vs. present) between-subject, full-factorial design to conduct both relative and absolute treatment comparisons and to isolate individual and interactive effects on user compliance (e.g., Klumpe et al. 2019 ; Schneider et al. 2020 ; Zhang et al. 2012 ). The hypotheses were tested by means of a randomized online experiment in the context of a customer-service chatbot for online banking that provides customers with answers to frequently asked questions. We selected this context, as banking has been a common context in previous IS research on, for example, automation and recommendation systems (e.g., Kim et al. 2018 ). Moreover, the context will play an increasingly important role for future applications of CAs, as many service requests are based on routine tasks (e.g., checking account balances and blocking credit cards), which CAs promise to conveniently and cost-effectively solve in form of 24/7 service channels (e.g., Jung et al. 2018a , b ).

In our online experiment, the chatbot was self-developed and replicated the design of many contemporary chat interfaces. The user could easily interact with the chatbot by typing in the message and pressing enter or by clicking on “Send”. In contrast to former operationalizations of rule-based systems in experiments and practice, the IBM Watson Assistant cloud service provided us with the required AI-based functional capabilities for natural language processing, understanding as well as dialogue management (Shevat 2017 ; Watson 2017 ). As such, participants could freely enter their information in the chat interface, while the AI in the IBM cloud processed, understood and answered the user input in the same natural manner and with the same capabilities as other contemporary AI applications, like Amazon’s Alexa or Apple’s Siri – just in written form. At the same time, these functionalities represent the necessary narrow AI that is especially important in customer self-service contexts to raise customer satisfaction (Gnewuch et al. 2017 ). For example, by means of the IBM Watson Assistant, it is possible to extract intentions and emotions from natural language in user statements (Ferrucci et al. 2010 ). Once the user input has been processed, an answer option is automatically chosen and displayed to the user.

Manipulation of independent variables

Regarding the ADCs manipulation, all participants received the same task and dialogue. Yet, consistent with prior research on anthropomorphism that employed verbal ADCs in chatbots (e.g., Araujo 2018 ), participants in the high ADCs manipulation experienced differences in form of presence or absence of the following characteristics, which are common in human-to-human interactions but have so far not been scientifically considered in chatbot interactions before: identity, small talk and empathy:

Identity: User perception is influenced by the way the chatbot articulates its messages. For example, previous research has demonstrated that when a CA used first-person singular pronouns and thus signaled an identity, the CA was positively associated with likeability (Pickard et al. 2014 ). Since the use of first-person singular pronouns is a characteristic unique to human beings, we argue that when a chatbot indicates an identity through using first-person singular pronouns and even a name, it not only increases its likeability but also anthropomorphic perceptions by the user.

Smalltalk: A relationship between individuals does not emerge immediately and requires time as well as effort from all involved parties. Smalltalk can be proactively used to develop a relationship and reduce the emotional distance between parties (Cassell and Bickmore 2003 ). The speaker initially articulates a statement as well as signals to the listener to understand the statement. The listener can then respond by signaling that he or she understood the statement, so that the speaker can assume that the listener has understood the statement (Svennevig 2000 ). By means of small talk, the actors can develop a common ground for the conversation (Bickmore and Picard 2005 ; Cassell and Bickmore 2003 ). Consequently, a CA participating in small talk is expected to be perceived as more human and, thus, anthropomorphized.

Empathy: A good conversation is highly dependent on being able to address the statements of the counterpart appropriately. Empathy describes the process of noticing, comprehending, and adequately reacting to the emotional expressions of others. Affective empathy in this sense describes the capability to emotionally react to the emotion of the conversational counterpart (Lisetti et al. 2013 ). Advances in artificial intelligence have recently allowed computers to gain the ability to express empathy by analyzing and reacting to user expressions. For example, Lisetti et al. ( 2013 ) developed a module based on which a computer can analyze a picture of a human being, allocate the visualized emotional expression of the human being, and trigger an empathic response based on the expression and the question asked in the situation. Therefore, a CA displaying empathy is expected to be characterized as more life-like.

Since we are interested in the overall effect of verbal anthropomorphic design cues on user compliance, the study intended to examine the effects of different levels of anthropomorphic CAs when a good design is implemented and potential confounds are sufficiently controlled. Consequently, consistent with previous research on anthropomorphism (e.g., Adam et al. 2019 ; Qiu and Benbasat 2009 , 2010 ), we operationalized the high anthropomorphic design condition by conjointly employing the following design elements (see the Appendix for a detailed description of the dialogues in the different conditions):

The chatbot welcomed and said goodbye to the user. Greetings and farewells are considered adequate means to encourage social responses by users (e.g., Simmons et al. 2011 )

The chatbot signaled a personality by introducing itself as “Alex”, a gender-neutral name as previous studies indicated that gender stereotypes also apply to computers (e.g., Nass et al. 1997 ).

The chatbot used first-person singular pronouns and thus signaled an identity, which has been presented to be positively associated with likeability in previous CA interactions (Pickard et al. 2014 ). For example, regarding the target request, the chatbot asked for feedback to improve itself rather than to improve the quality of the interaction in general.

The chatbot engaged in small talk by asking in the beginning of the interaction for the well-being of the user as well as whether the user interacted with a chatbot before. Small talk has been shown to be useful to develop a relationship and reduce the emotional and social distance between parties, making a CA appear more human-like (Cassell and Bickmore 2003 ).

The chatbot signaled empathy by processing the user’s answers to the questions about well-being and previous chatbot experience and, subsequently, providing responses that fit to the user’s input. This is in accordance with Lisetti et al. ( 2013 ) who argue that a CA displaying empathy is expected to be characterized as more life-like.

Consistent with previous studies on FITD (e.g., Burger 1999 ), we used the in the past highly successful continued-questions procedure in a same-requester/no-delay situation: Participants in the FITD condition are initially asked a small request by answering one single question to provide feedback about the perception of the chatbot interaction to increase the quality of the chatbot. As soon as the participant finished this task by providing a star-rating from 1 to 5, the same requester (i.e., the chatbot) immediately asks the target request, namely, whether the user is willing to fill out a questionnaire on the same topic that will take 5 to 7 min to complete. Participants in the FITD absent condition did not receive the small request and were only asked the target request.

The participants were set in a customer service scenario in which they were supposed to ask a chatbot whether they could use their debit card abroad in the U.S. (see Appendix for the detailed dialogue flows and instant messenger interface). The experimental procedure consisted of 6 steps (Fig.  2 ):

A short introduction of the experiment was presented to the participants including their instruction to introduce themselves to a chatbot and ask for the desired information.

In the anthropomorphism conditions with ADCs, the participants were welcomed by the chatbot. Moreover, the chatbot engaged in small talk by asking for the well-being of the user (i.e., “How are you?”) and whether the user has used a chatbot before (i.e., “Have you used a chatbot before?”). Dependent on the user’s answer and the chatbot’s AI-enabled natural language processing and understanding, the chatbot prompted a response and signaled comprehension and empathy.

The chatbot asked how it may help the user. The user then provided the question that he or she was instructed to: Whether the user can use his or her debit card in the U.S. If the user just asked a general usage of the debit card, the chatbot would ask in which country the user wants to use the debit card. The chatbot subsequently provided an answer to the question and asked if the user still has more questions. In case the user indicated that he or her had more, he or she would be recommended to visit the official website for more detailed explanations via phone through the service team. Otherwise, the chatbot would just thank the user for being used.

In the FITD condition, the user was asked to shortly provide feedback to the chatbot. The user then expresses his or her feedback by using a star-rating system.

The chatbot posed the target request (i.e., dependent variable) by asking whether the user is willing to answer some questions, which will take several minutes and help the chatbot to improve itself. The user then selected an option.

After the user’s selection, the chatbot instructed the user to wait until the next page is loaded. At this point, the conversation stopped, irrespective of the user’s choice. The participants then answered a post-experimental questionnaire about their chatbot experience and other questions (e.g., demographics).

Experimental procedure (As stated in the FITD hypothesis, we intend to investigate whether users are more likely to comply to a request when they agreed to and fulfilled a smaller request first. As such, to avoid counteracting effects in the analysis, we will consider only participants who have agreed and fulfilled the initial small request (and thus remove participants who did not).)

Dependent variables, validation checks, and control variables

We measured User Compliance as a binary dependent variable, defined as a point estimator P based on

where n denotes the total number of unique participants in the respective condition who finished the interaction (i.e., answering the chatbot’s target request for voluntarily providing service feedback by selecting either “Yes” or “No”). x k is a binary variable that equals 1 when the participant complied to the target request (i.e., selecting “Yes”) and 0 when they denied the request (i.e., selecting “No”).

Moreover, in addition to our dependent variable, we also tested demographic factors (age and gender) and the following other control variables that have been identified as relevant in extant literature. The items for Social Presence (SP) and Trusting Disposition were adapted from Gefen and Straub ( 2003 ), Personal Innovativeness from Agarwal and Prasad ( 1998 ), and Product Involvement from Zaichkowsky ( 1985 ). All items were measured on a 7-Point Likert-type scale with anchors majorly ranging from strongly disagree to strongly agree . Moreover, we measured Conversational Agents Usage on a 5-point-scale ranging from never to daily. All scales exhibited satisfying levels of reliability (α > 0.7) (Nunnally and Bernstein 1994 ). A confirmatory factor analysis also showed that all analyzed scales exhibited satisfying convergent validity. Furthermore, the results revealed that all discriminant validity requirements (Fornell and Larcker 1981 ) were met, since each scale’s average variance extracted exceeded multiple squared correlations. Since the scales demonstrated sufficient internal consistency, we used the averages of all latent variables to form composite scores for subsequent statistical analysis. Lastly, two checks were included in the experiment. We used the checks to ascertain that our manipulations were noticeable and successful. Moreover, we assessed participants’ Perceived Degree of Realism on a 7-point Likert-type scale with anchors ranging from strongly disagree to strongly agree (see Appendix (Tables 1 , 2 , 3 , 4 and 6 ) (Figures 3 , 4 , 5 , 6 and 7 )

Results for the dependent variable User Compliance

Mediation analysis

Analysis and results

Sample description.

Participants were recruited via groups on Facebook as the social network provides many chatbots for customer service purposes with its instant messengers. We incentivized participation by conducting a raffle of three Euro 20 vouchers for Amazon. Participation in the raffle was voluntary and inquired at the end of the survey. 308 participants started the experiment. Of those, we removed 32 (10%) participants who did not finish the experiment and 97 (31%) participants more, as they failed at least one of the checks (see Table 5 in Appendix). There were no noticeable technical issues in the interaction with the chatbot, which would have required us to remove further participants. Out of the remaining 179 participants, consistent with previous research on the FITD technique to avoid any counteracting effects (e.g., Snyder and Cunningham 1975 ), we removed 22 participants who declined the small request. Moreover, we excluded four participants who expressed that they found the experiment unrealistic. The final data set included 153 German participants with an average age of 31.58 years. Moreover, participants indicated that they had moderately high Personal Innovativeness regarding new technology (x̄ = 4.95, σ = 1.29), moderately high Product Involvement in bank product (x̄ = 5.10, σ = 1.24), and moderately low Conversational Agent Usage experience (x̄ = 2.25, σ = 1.51). Table 1 summarizes the descriptive statistics of the used data.

To check for external validity, we assessed the remaining participants’ Perceived Degree of Realism of the experiment. Perceived Degree of Realism reached high levels (x̄ = 5.58, σ = 1.11), thus we concluded that the experiment was considered realistic. Lastly, we tested for possible common method bias by applying the Harman one-factor extraction test (Podsakoff et al. 2003 ). Using a principal component analysis for all items of the latent variables measured, we found two factors with eigenvalues greater than 1, accounting for 46.92% of the total variance. As the first factor accounted for only 16.61% of the total variance, less than 50% of the total variance, the Harman one-factor extraction test suggests that common method bias is not a major concern in this study (Figure 3 ).

Main effect analysis

To test the main effect hypotheses, we first performed a two-stage hierarchical binary regression analysis on the dependent variable User Compliance (see Table 2 ). We first entered all controls (Block 1), and then added the manipulations ADCs and FITD (Block 2). Both manipulations demonstrated a statistically significant direct effect on user compliance ( p  < 0.05). Participants in the FITD condition were more than twice as likely to agree to the target request (b = 0.916, p < 0.05, odds ratio = 2.499), while participants in the ADCs conditions were almost four times as likely to comply (b = 1.380, p  < 0.01, odds ratio = 3.975). Therefore, our findings show that participants confronted with the FITD technique or an anthropomorphically designed chatbot are significantly more inclined to follow a request by the chatbot.

Mediation effect analysis

For our mediation hypothesis, we argued that ADCs would affect User Compliance via increased Social Presence . Thus, we hypothesized that in the presence of ADCs , social presence increases and, hence, the user is more likely to comply with a request. Therefore, in a mediation model using bootstrapping with 5000 sampled and 95% bias-corrected confidence interval, we analyzed the indirect effect of our ADCs on User Compliance and selection through Social Presence . We conducted the mediation test by applying the bootstrap mediation technique (Hayes 2017 model 4). We included both manipulations (i.e., ADCs and FITD) and all control variables in the analysis.

To analyze the process driving the effect of ADCs on User Compliance , we entered Social Presence as our potential mediator between ADCs and User Compliance . For our dependent variable User Compliance , the indirect effect of ADCs was statistically significant, thus Social Presence mediated the relationship between ADCs and User Compliance : indirect effect = 0.6485, standard error = 0.3252, 95% bias-corrected confidence interval (CI) = [0.1552, 1.2887]. Moreover, ADCs were positively related with Social Presence (b = 1.2553, p  < 0.01), whereas the direct effect of our ADCs became insignificant (b = 0.8123, p  > 0.05) after adding our mediator Social Presence to the model. Therefore, our results demonstrate that Social Presence significantly mediated the impact of ADCs on User Compliance : ADCs increased Social Presence and, thus, increased User Compliance (Figure 4 ).

Moderation effect analysis

We suggest in H3 that Social Presence will moderate the effect of FITD on User Compliance . To test the hypothesis, we conducted a bootstrap moderation analysis with 5000 samples and a 95% bias-corrected confidence interval (Hayes 2017 , model 1). The results of our moderation analysis showed that the effect of FITD on User Compliance is not moderated by Social Presence such that there was no significant interaction effect of Social Presence and FITD on User Compliance (b = 0.2305; p  > 0.1). Consequently, our findings do not support H3.

This study sheds light on how the use of ADCs (i.e., identity, small talk, and empathy) and the FITD, as a common compliance technique, affect user compliance with a request for service feedback in a chatbot interaction. Our results demonstrate that both anthropomorphism as well as the need to stay consistent have a distinct positive effect on the likelihood that users comply with the CA’s request. These effects demonstrate that even though the interface between companies and consumers is gradually evolving to become technology dominant through technologies such as CAs (Larivière et al. 2017 ), humans tend to also attribute human-like characteristics, behaviors, and emotions to the nonhuman agents. These results thus indicate that companies implementing CAs can mitigate potential drawbacks of the lack of interpersonal interaction by evoking perceptions of social presence. This finding is further supported by the fact that social presence mediates the effect of ADCs on user compliance in our study. Thus, when CAs can meet such needs with more human-like qualities, users may generally be more willing (consciously or unconsciously) to conform with or adapt to the recommendations and requests given by the CAs. However, we did not find support that social presence moderates the effect of FITD on user compliance. This indicates that effectiveness of the FITD can be attributed to the user’s desire for self-consistency and is not directly affected by the user’s perception of social presence. This finding is particularly interesting because prior studies have suggested that the technique’s effectiveness heavily depends on the kind of requester, which could indicate that the perceived social presence of the requester is equally important (Burger 1999 ). Overall, these findings have a number of theoretical contributions and practical implications that we discuss in the following.

Contributions

Our study offers two main contributions to research by providing a novel perspective on the nascent area of AI-based CAs in customer service contexts.

First, our findings provide further evidence for the CASA paradigm (Nass et al. 1994 ). Despite the fact that participants knew they were interacting with a CA rather than a human, they seem to have applied the same social rules. This study thus extends prior research that has been focused primarily on embodied CAs (Hess et al. 2009 ; Qiu and Benbasat 2009 ) by showing that the CASA paradigm extends to disembodied CAs that predominantly use verbal cues in their interactions with users. We show that these cues are effective in evoking social presence and user compliance without the precondition of nonverbal ADCs, such as embodiment (Holtgraves et al. 2007 ). With few exceptions (e.g., Araujo 2018 ), potentials to shape customer-provider relationships by means of disembodied CAs have remained largely unexplored.

A second core contribution of this research is that humans acknowledge CAs as a source of persuasive messages. This is not to say that CAs are more or less persuasive compared to humans, but rather that the degree to which humans comply with the artificial social agents depends on the techniques applied during the human-chatbot communication (Edwards et al. 2016 ). We argue that the techniques we applied are successful because they appeal to fundamental social needs of individuals even though users are aware of the fact that they are interacting with a CA. This finding is important because it potentially opens up a variety of avenues for research to apply strategies from interpersonal communication in this context.

Implications for practice

Besides the theoretical contributions, our research also has noteworthy practical implications for platform providers and online marketers, especially for those who consider employing AI-based CAs in customer self-service (e.g., Gnewuch et al. 2017 ). Our first recommendation is to disclose to customers that they are interacting with a non-human interlocutor. By showing that CAs can be the source of persuasive messages, we provide evidence that attempting to fool customers into believing they are interacting with a human might not be necessary nor desirable. Rather, the focus should be on employing strategies to achieve greater human likeness through anthropomorphism by indicating, for instance, identity, small-talk, and empathy, which we have shown to have a positive effect on user compliance. Prior research has also indicated that the attempt of a CAs to provide a human-like behavior is impressive for most users, helping to lower user expectations and leading to more satisfactory interactions with CAs (Go and Sundar 2019 ).

Second, our results provide evidence that subtle changes in the dialog design through ADCs and the FITD technique can increase user compliance. Thus, when employing CAs, and chatbots in particular, providers should design dialogs as carefully as they design the user interface. Besides focusing on dialogs that are as close as possible to human-human communications, providers can employ and test a variety of other strategies and techniques that appeal to, for instance, the user’s need to stay consistent such as in the FITD technique.

Limitations and future research

This paper provides several avenues for future research focusing on the design of anthropomorphic information agents and may help in improving the interaction of AI-based CAs through user compliance and feedback. For example, we demonstrate the importance of anthropomorphism and the perception of social presence to trigger social bias as well as the need to stay consistent to increase user compliance. Moreover, with the rise of AI and other technological advances, intelligent CAs will become even more important in the future and will further influence user experiences in, for example, decision-makings, onboarding journeys, and technology adoptions.

The conducted study is an initial empirical investigation into the realm of CAs in customer support contexts and, thus, needs to be understood with respect to some noteworthy limitations. Since the study was conducted in an experimental setting with a simplified version of an instant messaging application, future research needs to confirm and refine the results in a more realistic setting, such as in a field study. In particular, future studies can examine a number of context specific compliance requests (e.g., to operate a website or product in a specific way, to sign up for or purchase a specific service or product). Future research should also examine how to influence users who start the chatbot interaction but who just simply end the questionnaire after their inquiry has been solved, a common user behavior in service contexts that does not even allow for the emergence of survey requests. Furthermore, our sample consisted of only German participants, so that future researchers may want to test the investigated effects in other cultural contexts (e.g., Cialdini et al. 1999 ).

We revealed the effects only based on the operationalized manipulations, but other forms of verbal ADCs and FITD may be interesting for further investigations in the digital context of AI-based CAs and customer self-service. For instance, other forms of anthropomorphic design cues (e.g., the number of presented agents) as well as other compliance techniques (e.g., reciprocity) may be fathomed, maybe even finding interacting observations between the manipulations. For instance, empathy may be investigated on a continuous level with several conditions rather than dichotomously, and the FITD technique may be examined with different kinds and effort levels of small and target requests. Researchers and service providers need to evaluate which small requests are optimal for the specific contexts and whether users actually fulfil the agreed large commitment.

Further, a longitudinal design approach can be used to measure the influence when individuals get more accustomed to chatbots over time, as nascent customer relationships might be harmed by a sole focus on customers self-service channels (Scherer et al. 2015 ). Researchers and practitioners should cautiously apply our results, as the phenomenon of chatbots is relatively new in practice. Chatbots have only recently sparked great interest among businesses and many more chatbots can be expected to be implemented in the near future. Users might get used to the presented cues and will respond differently over time, once they are acquainted to the new technology and the influences attached to it.

AI-based CAs have become increasingly popular in various settings and potentially offer a number of time- and cost-saving opportunities. However, many users still experience unsatisfactory encounters with chatbots (e.g., high failure rates), which might result in skepticism and resistance against the technology, potentially inhibiting that users comply with recommendations and requests made by the chatbot. In this study, we conducted an online experiment to show that both verbal anthropomorphic design cues and the foot-in-the-door technique increase user compliance with a chatbot’s request for service feedback. Our study is thus an initial step towards better understanding how AI-based CAs may improve user compliance by leveraging the effects of anthropomorphism and the need to stay consistent in the context of electronic markets and customer service. Consequently, this piece of research extends prior knowledge of CAs as anthropomorphic information agents in customer-service. We hope that our study provides impetus for future research on compliance mechanisms in CAs and improving AI-based abilities in and beyond electronic markets and customer self-service contexts.

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Adam, M., Wessel, M. & Benlian, A. AI-based chatbots in customer service and their effects on user compliance. Electron Markets 31 , 427–445 (2021). https://doi.org/10.1007/s12525-020-00414-7

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Article publication date: 1 February 1989

Although significant advances have been made in customer service research, a majority of this research has concentrated on defining and measuring the importance of customer service in isolation from the other components of the marketing mix. In order to achieve a competitive advantage from customer service, it is necessary to establish service levels as part of the firm′s overall marketing strategy. This monograph reviews the development of customer service; evaluates past customer service research; presents a methodology for integrating customer service and marketing strategy, and provides some suggestions for future research.

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Sterling, J.U. and Lambert, D.M. (1989), "Customer Service Research: Past, Present and Future", International Journal of Physical Distribution & Materials Management , Vol. 19 No. 2, pp. 2-23. https://doi.org/10.1108/EUM0000000000306

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ORIGINAL RESEARCH article

Service quality and customer satisfaction in the post pandemic world: a study of saudi auto care industry.

• 1 College of Business Administration, Prince Mohammad Bin Fahd University, Khobar, Saudi Arabia
• 2 Department of Management Sciences, University of Baluchistan, Quetta, Pakistan

The aim of this research is to examine the impact of service quality on customer satisfaction in the post pandemic world in auto care industry. The car care vendor in the study made effective use of social media to provide responsive updates to the customers in the post pandemic world; such use of social media provides bases for service quality and customer satisfaction. The study examined the relationship between service quality and customer satisfaction using the SERVQUAL framework. According to the findings, empathy, reliability, assurance, responsiveness, and tangibles have a significant positive relationship with customer satisfaction. Our findings suggest that it is critical for workshops to recognize the service quality factors that contribute to customer satisfaction. Findings also suggest that empathy, assurance, reliability, responsiveness, and tangibles contribute to customer satisfaction. Auto repair industry must regularly provide personal attention, greet customers in a friendly manner, deliver cars after services, notify customers when additional repairs are required, and take the time to clarify problems to customers. Furthermore, workshops must screen and hire courteous staff who can clearly communicate the services required to customers both in-person and online and effectively communicate the risks associated with repairs. Service quality seems to be aided by prompt services.

Introduction

The previous studies on the effect of pandemic have focused on the behavior related to preventative measures to protect the health of the customers; however, less attention has been paid to the influence of pandemic on customer outcomes. To fill this gap, the SERVQUAL framework was employed to examine the changes in customers’ social media behaviors that have occurred since the pandemic was declared ( Mason et al., 2021 ). In the post pandemic world, the parameters for customer satisfaction have changed considerably ( Monmousseau et al., 2020 ; Srivastava and Kumar, 2021 ; Wu et al., 2021 ). Pandemic has made personal interaction more challenging ( Brown, 2020 ). To be less vulnerable to becoming severely ill with the virus, customers prefer touchless digital mediums of communications. For example, Mason et al. (2021) concluded that pandemic has altered customers’ needs, shopping and purchasing behaviors, and post purchase satisfaction levels. Keeping in view the public healthcare concerns, the governmental pandemic mitigation policies also promotes touchless mediums for shopping; therefore, the role of social media as a communication tool stands to increase at a time when social distancing is a common practice; social media provides avenues for buyers to interact with sellers without physical contact. Thus, the use of social media gains critical importance, especially after the pandemic ( Mason et al., 2021 ), and the businesses may find new opportunities to gain competitive advantage through their use of effective social media strategies.

The car care industry uses traditional means of customer communications. The company in this study made use of social media in improving their service quality through effective and safe communication with their customers. The use of social media to provide updates to customers played a significant role in improving service quality and satisfaction ( Ramanathan et al., 2017 ). The company in the study used Snapchat to provide updates on the work, thus minimizing the customers’ need to physically visit the car care facility. This use of social media gave a significant boost to the responsiveness aspect of the service quality.

Service quality and customer satisfaction are important aspects of business since a company’s growth is largely dependent on how well it maintains its customers through service and how well they keep their customers satisfied ( Edward and Sahadev, 2011 ). According to Chang et al. (2017) ; customer satisfaction is expected to result from good service efficiency, which will improve customer engagement and interrelationship. González et al. (2007) asserted that customer satisfaction is linked to high service quality, which makes businesses more competitive in the marketplace. This study uses the SERVQUAL framework to define service quality. This framework uses five dimensions to account for service quality, namely, tangibles, reliability, responsiveness, assurance, and empathy. Identifying issues in service and customer satisfaction can lead to high service quality. Furthermore, service quality can be characterized by analyzing the variations between planned and perceived service. Service quality and customer satisfaction have a positive relationship.

Recognizing and meeting customer expectations through high levels of service quality help distinguish the company’s services from those of its rivals ( Dominic et al., 2010 ). Social media plays a critical role in shaping these service quality-related variables. Specifically, in the context coronavirus disease 2019 (COVID-19), where customers hesitated to visit auto workshops physically, the importance of online platforms such as auto workshops’ social media pages on Instagram and Facebook has increased, where customers try to get information and book appointment. For example, responsiveness is not only physical responsiveness but also digital means of communication. The car care company in this study uses social media as mode of communication with their customers due to physical interaction restriction caused by the pandemic.

Service quality becomes a critical element of success in car care industry because customer contact is one of the most important business processes ( Lambert, 2010 ). Saudi Arabia is one of the Middle East’s largest new vehicle sales and auto part markets. Saudi Arabia’s car repair industry has grown to be a significant market for automakers from all over the world. As a result, the aim of this research was to see how service quality affects customer satisfaction in the Saudi auto repair industry.

This aim of this research was to answer the following research questions:

(i) What is the contribution of individual dimensions of SERVQUAL on customer perceived service quality of car care industry in Saudi Arabia?

(ii) What is the impact of perceived service quality on customer satisfaction in car care industry in Saudi Arabia?

Literature Review

The concept of service has been defined since the 1980s by Churchill and Surprenant (1982) together with Asubonteng et al. (1996) , who popularized the customer satisfaction theory through measuring the firm’s actual service delivery in conformity with the expectations of customers, as defined by the attainment of perceived quality, and that is meeting the customers’ wants and needs beyond their aspirations. With this premise, Armstrong et al. (1997) later expanded the concept of service into the five dimensions of service quality that comprised tangibles, reliability, responsiveness, assurance, and empathy.

Extant literature on service delivery focuses on the traditional emphasis on the contact between the customer and service provider ( Mechinda and Patterson, 2011 ; Han et al., 2021 ). Doucet (2004) explained that the quality in these traditional settings depends on the design of the location and the behavior of the service provider. More recently, the proliferation of the internet has led to the emergence of the online service centers. In these cases, communication both in-person and online plays a critical role in the quality of service rendered. It follows that service quality in hybrid settings depends on quality of communications on social media as well as the behavioral interactions between the customer and the service provider ( Doucet, 2004 ; Palese and Usai, 2018 ). These factors require subjective assessments by the concerned parties, which means that different persons will have varied assessments of the quality of service received.

SERVQUAL Dimensions

Service quality has been described with the help of five quality dimensions, namely, tangibles, reliability, responsiveness, assurance, and empathy. Definitions relating to these variables have been modified by different authors. The relationship between various dimensions of service quality differs based on particular services.

The tangible aspects of a service have a significant influence on perception of service quality. These comprise the external aspects of a service that influence external customer satisfaction. The key aspects of tangibility include price, ranking relative to competitors, marketing communication and actualization, and word-of-mouth effects ( Ismagilova et al., 2019 ), which enhance the perception of service quality of customers ( Santos, 2002 ). These aspects extend beyond SERVQUAL’s definition of quality within the car care industry settings. Thus, we proposed the following hypothesis:

Hypotheses 1a: Tangibles are positively related with perceived service quality.

Reliability

Reliability is attributed to accountability and quality. There are a bunch of precursors that likewise aid basic methodology for shaping clients’ perspectives toward administration quality and reliability in the car care industry in Saudi ( Korda and Snoj, 2010 ; Omar et al., 2015 ). A portion of these predecessors is identified with car repair benefits and includes the convenient accessibility of assets, specialist’s expertise level and productive issue determination, correspondence quality, client care quality, an exhibition of information, client esteem, proficiency of staff, representatives’ capacity to tune in to client inquiries and respond emphatically to their necessities and protests, security, workers’ dependability, more limited holding up time and quickness, actual prompts, cost of administration, accessibility of issue recuperation frameworks, responsibility, guarantees, for example, mistake-free administrations, generally association’s picture and workers’ politeness, and responsiveness. Despite the innovative changes happening in the car care industry and the instructive degree of car administrations suppliers in Saudi Arabia, car care suppliers in the territory are taught about the need to continually refresh their insight into the advancements in the area of vehicle workshops and the components of administration. Thus, we argued that reliability is important to enhance the perception of service quality of customers.

Hypotheses 1b: Reliability is positively linked with perceived service quality.

Responsiveness

Responsiveness refers to the institution’s ability to provide fast and good quality service in the period. It requires minimizing the waiting duration for all interactions between the customer and the service provider ( Nambisan et al., 2016 ). Nambisan et al. (2016) explained that responsiveness is crucial for enhancing the customers’ perception of service quality. Rather, the institution should provide a fast and professional response as to the failure and recommend alternative actions to address the customer’s needs ( Lee et al., 2000 ). In this light, Nambisan summarizes responsiveness to mean four key actions, i.e., giving individual attention to customers, providing prompt service, active willingness to help guests, and employee availability when required. These aspects help companies to enhance the customers’ perception of service quality. Therefore, we proposed the following hypothesis:

Hypotheses 1c: Responsiveness is positively linked with perceived service quality.

Assurance refers to the skills and competencies used in delivering services to the customers. Wu et al. (2015) explains that employee skills and competencies help to inspire trust and confidence in the customer, which in turn stirs feelings of safety and comfort in the process of service delivery. Customers are more likely to make return visits if they feel confident of the employees’ ability to discharge their tasks. Elmadağ et al. (2008) lists the factors that inspire empathy as competence, politeness, positive attitude, and effective communication as the most important factors in assuring customers. Besides, other factors include operational security of the premises as well as the proven quality of the service provided to the customers. Thus, the assurance has significant contribution in the perception of service quality.

Hypotheses 1d: Assurance is positively related with perceived service quality.

Empathy refers to the quality of individualized attention given to the customers. The service providers go an extra mile to make the customer feel special and valued during the interaction ( Bahadur et al., 2018 ). Murray et al. (2019) explains that empathy requires visualizing the needs of the customer by assuming their position. Murray et al. (2019) lists the qualities that foster empathy as including courtesy and friendliness of staff, understanding the specific needs of the client, giving the client special attention, and taking time to explain the practices and procedure to be undertaken in the service delivery process. Therefore, we proposed the following hypothesis:

Hypotheses 1e: Empathy is positively related with perceived service quality.

Perceived Service Quality and Customer Satisfaction

Customer satisfaction refers to the level of fulfillment expressed by the customer after the service delivery process. This is a subjective assessment of the service based on the five dimensions of service quality. Customer satisfaction is important due to its direct impact on customer retention ( Hansemark and Albinsson, 2004 ; Cao et al., 2018 ; Zhou et al., 2019 ), level of spending ( Fornell et al., 2010 ), and long-term competitiveness of the organization ( Suchánek and Králová, 2019 ). Susskind et al. (2003) describes that service quality has a direct impact on customer satisfaction. For this reason, this research considers that five dimensions of service quality are the important antecedents of customer satisfaction.

Service quality refers to the ability of the service to address the needs of the customers ( Atef, 2011 ). Customers have their own perception of quality before interacting with the organization. The expectancy-confirmation paradigm holds that customers compare their perception with the actual experience to determine their level of satisfaction from the interaction ( Teas, 1993 ). These assessments are based on the five independent factors that influence quality. Consequently, this research considers service quality as an independent variable.

This study attempts to quantify perceived service quality though SERVQUAL dimensions. We proposed that customers place a high premium on service quality as a critical determinant of satisfaction. Moreover, it is argued that satisfaction prompts joy and reliability among customers in Saudi Arabia. These discoveries infer that the perception of service quality is significantly related to satisfaction, and quality insight can be applied across different cultures with negligible contrasts in the result. Car care industry in Saudi Arabia has grave quality problems. To rectify this situation, it is essential to apply quality systems as tools for development. The SERVQUAL is one of these system options. It is used to gauge the service quality using five dimensions that have been time-tested since 1982. Thus, the significance of SERVQUAL in car care industry in Saudi Arabia cannot be overemphasized. The study further suggests that the SERVRQUAL dimension increases the perceived service quality, which in turn increases customer satisfaction. Thus, we proposed the following hypothesis:

Hypothesis 2: The perceived service quality of car care customers is positively linked with their satisfaction.

Methods and Procedures

In this study, we employed a cross-sectional research design. Using a paper-pencil survey, data were collected form auto care workshops situated in the Eastern Province of Saudi Arabia. According to the study by Newsted et al. (1998) , the survey method is valuable for assessing opinions and trends by collecting quantitative data. We adapted survey instruments from previous studies. The final survey was presented to a focus group of two Ph.D. marketing scholars who specialized in survey design marketing research. The survey was modified keeping in view the recommendations suggested by focus group members. We contacted the customers who used social media to check the updates and book the appointment for their vehicle’s service and maintenance. We abstained 130 surveys, 13 of which were excluded due to missing information. Therefore, the final sample encompassed 117 (26 female and 91 male) participants across multiple age groups: 10 aged less than 25 years, 46 aged between 26 and 30 years, 28 aged between 31 and 35 years, 21 aged between 36 and 40 years, and 12 aged older than 40 years (for details, refer to Table 1 ). Similarly, the averaged participants were graduates with more than 3 years of auto care service experience.

Table 1. Demographic information.

We measured service quality dimensions using 20 indicators. Customer satisfaction of the restaurant customers was assessed using 4-item scale (for detail, refer to Table 2 ). In this research, the 5-point Likert scale from 1 = strongly disagree to 5 = strongly agree was used.

Table 2. Constructs and items included in the questionnaire.

Control Variables

Following the previous research, customer’s gender and age were controlled to examine the influence of service quality dimensions on customer satisfaction.

Data Analysis and Results

For data analysis and hypotheses testing, we employed the structural equation modeling (SEM) based on the partial least squares (PLS) in Smart-PLS. Smart-PLS 3 is a powerful tool, which is used for the confirmatory factor analysis (CFA) and SEM ( Nachtigall et al., 2003 ). Research suggests that CFA is the best approach to examine the reliability and validity of the constructs. We employed SEM for hypotheses testing because it is a multivariate data analysis technique, which is commonly used in the social sciences ( González et al., 2008 ).

Common Method Bias

To ensure that common method bias (CMB) is not a serious concern for our results, we employed procedural and statistical and procedural remedies. During data collection, each survey in the research contained a covering letter explaining the purpose of the study and guaranteed the full anonymity of the participants. Moreover, it was mentioned in the cover letter that there was no right and wrong questions, and respondents’ answers would neither be related to their personalities nor disclosed to anyone. According to Podsakoff et al. (2003) , the confidentiality of the responses can assist to minimize the possibility of CMB. Furthermore, CMB was verified through the Harman’s single-factor test ( Podsakoff et al., 2003 ). All items in this research framework were categorized into six factors, among which the first factor explained 19.01% of the variance. Thus, our results showed that CMB was not an issue in our research. Moreover, using both tolerance value and the variance inflation factors (VIFs), we assessed the level of multicollinearity among the independent variables. Our results indicate that the tolerance values for all dimensions of service quality were above the recommended threshold point of 0.10 ( Cohen et al., 2003 ), and VIF scores were between 1.4 and 1.8, which suggested the absence of multicollinearity; thus, it is not a serious issue for this study.

Measurement Model

We performed CFA to analyze the reliability and validity of the constructs. The measurement model was assessed by examining the content, convergent, and discriminant validities. To assess the content validity, we reviewed the relevant literature and pilot test the survey. We used item loadings, Cronbach’s alpha, composite reliability (CR), and the average variance extracted (AVE) ( Fornell and Larcker, 1981b ) to assess the convergent validity. The findings of CFA illustrate that all item loadings are greater than 0.70. The acceptable threshold levels for all values were met, as the value of Cronbach’s alpha and CR was greater than 0.70 for all constructs ( Fornell and Larcker, 1981b ), and the AVE for all variables was above 0.50 ( Tabachnick and Fidell, 2007 ; see Table 3 ). Thus, these findings show acceptable convergent validity.

Table 3. Item loadings, Cronbach’s alpha, composite reliability, and average variance extracted.

To analyze the discriminant validity, we evaluated the discriminant validity by matching the association between correlation among variables and the square root of the AVE of the variables ( Fornell and Larcker, 1981a ). The results demonstrate that the square roots of AVE are above the correlation among constructs, hence showing a satisfactory discriminant validity, therefore, indicating an acceptable discriminant validity. Moreover, descriptive statistics and correlations are provided in Table 4 .

Table 4. Descriptive statistics and correlations.

Structural Model and Hypotheses Testing

After establishing the acceptable reliability and validity in the measurement model, we examined the relationship among variables and analyzed the hypotheses based on the examination of standardized paths. The path significance of proposed relations were calculated using the SEM through the bootstrap resampling technique ( Henseler et al., 2009 ), with 2,000 iterations of resampling. The proposed research framework contains five dimensions of service quality (i.e., tangibles of the auto care, reliability of the auto care, responsiveness of the auto care, assurance of the auto care, and empathy of the auto care) and customer satisfaction of auto care. The results show that five dimensions of service quality are significantly related to customer’s perception of service quality of auto care; thus, hypotheses 1a, 1b, 1c, 1d, and 1e were supported. Figure 1 shows that the service quality of auto care is a significant determinant of customer satisfaction of auto care industry (β = 0.85, p < 0.001), supporting hypothesis 2. The result in Figure 1 also shows that 73.8% of the variation exists in customer satisfaction of auto care.

Figure 1. Results of the research model tests. *** p < 0.001.

The main purpose of this research was to assess the relationship between service quality and customer satisfaction in the post pandemic world in Saudi Arabia. This study was designed to examine how satisfaction of auto care customers is influenced by service quality, especially, when pandemic was declared, and due to health concerns, the customers were reluctant to visit workshops physically ( Mason et al., 2021 ). It appears that after the pandemic, customers were increasingly using online platforms for purchasing goods and services. This study reveals how customers of auto repair in Saudi perceive service quality and see how applicable SERVQUAL model across with five dimensions, including tangibles, responsiveness, reliability, assurance, and empathy measure service quality. The findings of this research show that five dimensions of SERVQUAL are positively related to the service quality perception of auto care customers in Saudi Arabia. Moreover, service quality perceptions are positively linked with customer satisfaction. These results indicate that auto care customers view service quality as an important antecedent of their satisfaction. The findings indicate that the customers perceive the service quality as a basic service expectation and will not bear the extra cost for this criterion. In this research, the positive connection between service quality and customer satisfaction is also consistent with previous studies (e.g., González et al., 2007 ; Gallarza-Granizo et al., 2020 ; Cai et al., 2021 ). Thus, service quality plays a key role in satisfying customers. These findings suggest that service organizations, like auto repair industry in Saudi Arabia could enhance satisfaction of their customers through improving service quality. Because of pandemic, people are reluctant to visit auto care workshops, and they try to book appointment through social media; so, by improving the quality of management of their social media pages, the workshops can provide accurate information for monitoring, maintaining, and improving service quality ( Sofyani et al., 2020 ). More specifically, social media, which allows individuals to interact remotely, appears to be gaining significant importance as a tool for identifying customers’ products and service needs. Increasingly, customers are also increasingly engaging with retailers through social media to search and shop for product and services options, evaluate the alternatives, and make purchases.

Furthermore, the research on the customer service quality can be held essential since it acts as a means for the promotion of the competitiveness of an organization. Precisely, the knowledge about the customers’ view concerning service quality can be used by organizations as a tool to improve their customer services. For example, knowledge of the required customer service would help in the facilitation of training programs oriented toward the enlightenment of the overall employees on the practices to improve and offer high-quality customer services. Besides, information concerning customer services would be essential in decision-making process concerning the marketing campaigns of the firm, hence generating competitive advantage of the organization in the marketplace. Findings show that customers demand more from auto repair, so the company must work hard to increase all service quality dimensions to improve customer satisfaction. Thus, organizations ought to venture in customer services initiatives to harness high-quality services.

Managerial Implications

The findings of this research indicate a strong association between SERVQUAL dimensions and perceived service quality. Perception of higher service quality leads to higher level of customer satisfaction among Saudi car care customers. In particular, the results indicate high scores for reliability, empathy, tangibles, and responsiveness. These are clear indications that the immense budgetary allocation has enabled these institutions to develop capacity. Nevertheless, the lack of a strong human resource base remains a key challenge in the car care industry. The effective use of social media plays a critical role in the responsiveness dimension of service quality. Companies need to develop their digital and social media marketing strategies in the post pandemic world to better satisfy their customers.

Saudi Arabia requires a large and well-trained human resource base. This requires intensive investment in training and development. Most of these workers have a limited contract, which reduced their focus on long-term dedication. Consequently, the government should provide longer-term contracts for workers in this critical sector. The contracts should include training on tailored courses to serve the identified needs in effective communication with the customers using digital media. We suggested that the auto car care workshops should provide training to their workers, particularly, on service technicians to enhance their skills that will help to deliver fast and reliable service to their auto customers.

Moreover, the auto car care workshops also provide customer care- or customer handling-related training especially for the service marketing personnel who handles customer directly for them to better understand the customer needs and expectations. This can be done at least once a year. This will help auto care workshops to improve their service quality.

Limitation and Future Research Direction

This research is not without limitations. First, the findings of this study are based on data collected from a single source and at a single point of time, which might be subjected to CMB ( Podsakoff et al., 2003 ). Future research can collect data from different points of time to validate the findings of this research. Second, this research was carried out with data obtained from Saudi auto car care customers; the findings of this research might be different because the research framework was retested in a different cultural context. Therefore, more research is needed to improve the understanding of the principles of service quality and customer satisfaction, as well as how they are evaluated, since these concepts are critical for service organizations’ sustainability and development. A greater sample size should be used in a similar study so that the findings could be applied to a larger population. Research on the effect of inadequate customer service on customer satisfaction, the impact of customer retention strategies on customer satisfaction levels, and the impact of regulatory policies on customer satisfaction is also recommended. Third, because most of the participants participated in this research are men, future studies should obtain data from female participants and provide more insights into the difference between male and female customers’ satisfaction levels. Moreover, due to limitation of time, the sample was collected from the eastern province. Consequently, further research should include a larger and more representative sample of the Saudi population. Because of the non-probability sampling approach used in this research, the results obtained cannot be generalized to a wide range of similar auto repair services situations, even though the methodology used in this study could be extended to these similar situations. Since the sample size considered is not that large, expectations could vary significantly. When compared with the significance of conducting this form of analysis, the limitations mentioned above are minor. Such research should be conducted on a regular basis to track service quality and customer satisfaction levels and, as a result, make appropriate changes to correct any vulnerability that may exist.

Data Availability Statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

Ethics Statement

Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements. The patients/participants provided their written informed consent to participate in this study.

Author Contributions

SZ helped in designing the study. ZH helped in designing and writing the manuscript. MAA helped in data collection and analysis and writing the manuscript. SUR repositioned and fine-tuned the manuscript, wrote the introduction, and provided feedback on the manuscript.

This study was received funding from University Research Fund.

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.

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Keywords : auto care, customer satisfaction, service quality, Saudi Arabia, pandemic (COVID-19)

Citation: Zygiaris S, Hameed Z, Ayidh Alsubaie M and Ur Rehman S (2022) Service Quality and Customer Satisfaction in the Post Pandemic World: A Study of Saudi Auto Care Industry. Front. Psychol. 13:842141. doi: 10.3389/fpsyg.2022.842141

Received: 23 December 2021; Accepted: 07 February 2022; Published: 11 March 2022.

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Copyright © 2022 Zygiaris, Hameed, Ayidh Alsubaie and Ur Rehman. 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: Zahid Hameed, [email protected]

Disclaimer: 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.

Customer Satisfaction and Service Research Paper

Extract (summary), introduction, customer service, how and why it is important, impact of customer service on sales, factors that enhance better customer service.

The goal of every organization is to provide proper services to its customers. This will help attract them and ensure that they maintain them. This is necessary in order to maintain the sales and ensure profitability and sustainability of the business.

Employees are required to understand the needs of their customers. This will put them in a position to match the products of the company with their needs. When the needs of the customers are met, they get satisfied (customer satisfaction) and this is what keeps them coming back for more. Therefore, customer service is important for the success of every business.

Providing customer service is quite a simple task, however, providing efficient customer service is another story all together. This requires proper skills. Organizations can ensure that its employees are well equipped with these skills through providing them with proper training. This may be in the provision of courses that would impart these skills and knowledge to them.

This way, the organization will be able to maintain its customers, make numerous sales and make profits constantly. The main objective of this paper is to look at the importance of effective customer service in the organization’s success.

A vivid definition of customer service will be provided. The importance of customer service will also be evaluated. The impact that customer service has on sales in a business will be looked at. Some of the factors that enhance better customer service will also be discussed.

Proper customer service, which is the act of providing services to the customer during the whole transaction process, is important for the success of every business. This involves providing the services before, during and after the customer has purchased the good or service.

Effective customer service is meant to ensure customer satisfaction in order to be able to retain the customer base. This is necessary to maintain the number of sales that the business makes and consequently, continue to make consistent profits.

In order to ensure that the customer service is effective, the organizations require to have well trained customer service providers. This can be achieved through the training of the employees (Pollitt, 2008). In addition, all new employees should also be introduced to the training in order to ensure that all the customer service staff is competent and understand how to handle their customers well.

The future profitability of a company is greatly determined by its effectiveness to deliver customer satisfaction and providing quality real-time training to staff members, which will influence the success of the business.

Customer service is generally the provision of quality service to the consumer of the organization’s products. It entails a series of activities during all stages of the consumer’s purchasing process. The main aim of providing customer service is to ensure customer satisfaction.

Price (2011) likes to think about customer service in different perspectives. He believes that it must be thought of as a leadership issue. He believes that one of the most important roles of a manager is to establish an environment of trust.

Another way of viewing it is as a marketing issue. Customer service is a way of reaching and keeping customers. It should be made to be part of the organizations marketing strategy.

Pollitt points out that being honest to the customers even when the mistake was the company’s is a recovery factor for the customer. Research indicates that telling the customers the truth of the matter when a problem is encountered creates trust. After such encounters, the customers become even more loyal since they can trust the company (business). Reinforcing this trust is the work of the leader.

Making customer service the main agenda of the company is a very vital move. Such organizations are set to achieve a great competitive advantage. This is because the companies that deliver effective customer services are recognized by the customers. When they receive services from other organizations that do not match up the services received from such companies, they will always create preferences hence customer loyalty.

The importance of effective customer service starts at the company’s mission statement. It should be realistic rather than well developed. It should be public relations-related. When it is realistic and genuine, it will provide the foundation to the development of the operational principles.

This way, the company’s core values will be reflected. This way, the customers will be able to relate to them and identify with them. Consequently, this will enhance customer loyalty and the success of the business.

In the current market, nine out of every ten businesses fail after some years of operation (Schlocker, 2004). Schlocker (2004) agrees with John Dijulius that customer service is what makes the difference between the successful businesses and those that fail.

Superior customer service is the necessary ingredient in the operation of the business. Such organizations take time to evaluate and enhance the experiences of the customer. This is done with the main aim of enhancing client loyalty.

The main goal of every business is to make profits and this is made possible when the organization makes sales. Charan (2010) believes that people need to think differently when it comes to making sales.

There are situations where an organization constantly loses sales even when it is providing good products and after putting a lot of effort on the services. In such situations, the organization needs to reconsider its goals and the ways of achieving them. It is then to reinvent the strategies to employ while selling them.

Triest, Bun, Raaij, and Vernooij (2008) studied the factors that enhanced customer retention and customer profitability. As they student certain service providers, they concluded that those customers who received free equipment during their previous visits came back for the same services. In other words, retention rates were higher. Therefore, the businesses could make more sales and more profits.

However, these authors argued that this was only applicable for those businesses that had large number of customers. It did not have any effect on the businesses that attracted a smaller number of customers. Essentially, this means that effective customer service is important in order for the business to be more profitable as it retains its customer base.

According to the authors, targeting on marketing expenses that were customer-specific was effective in retaining the customers. This was as opposed to the development of new customers into larger numbers or deriving more profits from them. This was a smart marketing procedure that involved incurring extra costs in the business in order to make more revenue from the customers.

Other similar studies have proved that such marketing decisions positively impact other marketing decisions. These include the pricing of services, customer loyalty, and the frequency of contracting customer, among others.

By offering free equipment, the businesspersons were able to strengthen the relationship with the consumers in order to make them avoid opportunistic behavior, which could negatively affect customer retention initiatives.

The salespeople should not only be people who take orders. They should also be ambassadors. This involves acquiring social skills that would enable them to learn about the needs of their customers. Having a good understanding about the product is also important. This would enable them to present them together with other services in a way that would match the specific needs of the consumers.

Creating value for the customers is very important in creating customer loyalty and ensuring that they will always come for the products (increase sales). The customers will differentiate such salesperson and will be regular customers. Therefore, a salesperson needs to acquire new knowledge and skills so as to be respected and supported by the teammates (Charan, 2010).

In order for employees at any organization to understand how to conduct effective customer service, they require to acquire social skills that will enable them to learn customer needs. This would enable them to understand how to match the customer needs with the products and services they offer (Charan, 2010).

Pollitt (2008) emphasizes on staff training as a factor in enhancing better (effective) customer service. This explains why the passengers on Stena’s Caledonia ferry like the services provided. The staff is provided with training that helps them provide the best customer services. This type of training was referred to as the ‘experiential’ training. It mostly targeted the workers from the catering units.

Those from the lowest ranks to the ones in senior positions were included in the training. It was a course that lasted for one day. All the employees who attended the training provided positive views about the training. They believed that it was helpful. The organization also had a policy that ensured that all new employees had to undergo that particular training.

One of the most important goals of an organization should be to provide customer service that would make the organization stand out from the rest. In order to achieve this, the employees need to be aware of the emotions and needs of the customer. They should also be able to deal with them appropriately and this calls for proper training in customer service and relations.

Experiential training may be provided to the employees in order to develop the necessary skills. This is different from the chalk-and-talk training, which is less effective. This is because experiential training enables them to develop skills by putting them in scenarios that resemble those in real life.

They would be able to go through self-discovery and identify themselves with the needs of the company. Consequently, they would be able to develop new skills that they would incorporate in the corporate culture.

The success of the world-class companies selected in Japan and Brazil was also attributed to training (Da Silva, Tadashi, & Kikuo, 2005). The companies had initiated training programs that raised the awareness about total quality management. This training also emphasized on teamwork in order to ensure that the customer satisfaction is made a team business.

With such training, the employees will also develop an interest and need to improve the organization and to satisfy the needs of the customers at the same time. The success of these world-class organizations is also attributed to the policy of training all new customers. This means that both the new and old employees have the same skills in terms of customer service. The contracted employees are also not left out in the training.

Customer service should also be delivered in a way that depicts respect and humility. Different people from different cultures have their own way of providing customer service. For example, the Japanese have a very different culture from the westerners. This cuts across the business sector and specifically in terms of customer service.

The difference between Japanese culture and westernized culture in terms of customer service is that the Japanese believe in the demonstration of respect and humility through words. The Japanese also believe that one should carry out his duties to the best of his abilities. This seems hypocritical to the westerners. Therefore, the westerners should embrace this in order to enhance customer satisfaction.

Customer service is a vital tool for any organization. It determines the success or failure of an organization. Those organizations that provide excellent services are recognized by their customers and are able to make sales continuously. In order for organizations to ensure efficient customer service, they are required to provide training to all its employees. This would ensure customer satisfaction and the overall success of the company.

Charan, R. (2010). Profitable growth. Leadership Excellence, 27(11), 3-5.

Da Silva, J., Tadashi, O., & Kikuo, N. (2005). Look through and beyond the TQM horizon: Lessons learned from world-class companies. The TQM Magazine, 17(1), 67-85.

Pollitt, D. (2008). Experiential training ensures customer service in ship-shape at Stena. Training & Management Development Methods, 22(3), 557-561.

Price, B. (2011). Being a customer service leader. The American Salesman, 56(3), 21-24.

Schlocker, D. (2004). Secret service: Hidden systems that deliver unforgettable customer service. Journal of Applied Management and Entrepreneurship , 9(1), 159-162.

Triest, S., Bun, M., Raaij, E., & Vernooij, M. (2008). The impact of customer-specific marketing expenses on customer retention and customer profitability. Journal of Applied Management and Entrepreneurship , 9(1), 159-162.

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Research on Artificial Intelligence Customer Service on Consumer Attitude and Its Impact during Online Shopping

Chenzhuoer Li 1 , Runjie Pan 2 , Huiyu Xin 3 and Zhiwen Deng 4

Published under licence by IOP Publishing Ltd Journal of Physics: Conference Series , Volume 1575 , 5th Annual International Conference on Information System and Artificial Intelligence [ISAI2020] 22-23 May 2020, Zhejiang, China Citation Chenzhuoer Li et al 2020 J. Phys.: Conf. Ser. 1575 012192 DOI 10.1088/1742-6596/1575/1/012192

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1 Virginia Polytechnic Institute and State University, College of Engineering, 24060

2 Corresponding Author, University of Notre Dame, College of Science, 46637

3 Inner Mongolia Agricultural University, College of Foreign Language, 010018

4 Sichuan University, College of Business,610065

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Currently, AI customer service is gaining popularity at a high rate, with over 92% of online shoppers having experience with AI customer service. The question is: what attitudes do consumers have towards AI customer service? A randomly selected sample of 670 consumers was surveyed and the study found that 71.5% of consumers accept or at least do not resist AI customer service. The main reasons AI customer service is so popular are that it is fulltime responsive, absolutely neutral, more objective, and represents a future trend. Nevertheless, 28.5% of consumers are still resistant to AI chatbot, mainly because they are not as relevant, effective, and smooth as a human customer service agent. Besides, there are prevalent obstacles to seamlessly bridge AI chatbots with human agents. In terms of explicitly specified AI chatbots versus concealed AI chatbots, merchants should have them specified since consumers have strong antipathy with AI chatbots disguising as human agents. Furthermore, there are differences in attitudes towards AI customer service across age and educational background. Accordingly, we recommend that, in the context of the overall improvement of service quality, to slow down the pace of AI replacing human agents, to do so in a step-by-step and orderly manner, and to give consumers adequate choice for human agents versus AI chatbots. Finally, to fully promote AI customer service, it is an essential measure to increase its media coverage and publicity.

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