Article The Effect of ATM Service Quality on Customer Satisfaction and Customer Loyalty: An Empirical Analysis Global Business Review 20(5) 1155–1178, 2019 © 2019 IMI Reprints and permissions: in.sagepub.com/journals-permissions-india DOI: 10.1177/0972150919846965 journals.sagepub.com/home/gbr Wajeeha Aslam1 Ayesha Tariq1 Imtiaz Arif1 Abstract This study examines the impact of automated teller machine (ATM) service quality on customer satisfaction and its effect on customer loyalty. The data were collected from 360 ATM users in Karachi, Pakistan, using a structured questionnaire. After the data screening process and the removal of outliers, 322 responses were found useable. To identify the dimensions of ATM service quality and their relationship with customer satisfaction and customer loyalty, exploratory factor analysis, confirmatory factor analysis and structural equation modelling (SEM) were used. The findings indicate that (a) fulfilment, reliability, ease of use, and security and privacy are the major dimensions of ATM service quality, (b) dimensions such as convenience and responsiveness are positively insignificantly correlated with customer satisfaction and (c) customer satisfaction significantly influences customer loyalty. This study suggests concrete strategies for bank managers to improve customer experience with ATM and identifies the issues to be resolved in order to improve ATM service quality. Keywords Customer satisfaction, customer loyalty, service quality, ATM, structural equation modelling Introduction In the course of last 20 years, an increase in employment costs and advancement in technology has convinced service providers towards exploring technology-based service opportunities that empower clients in the direction of yielding self-governing services (Dabholkar, 1996; Lin & Chang, 2011). Technology is one of the most significant drivers in many service sectors in terms of attracting more 1 Department of Business Administration, Iqra University Town, Gulshan-e-Iqbal, Karachi, Pakistan. Corresponding author: Wajeeha Aslam, Department of Business Administration, Iqra University Town, Block-2, Gulshan-e-Iqbal, Karachi 75300, Pakistan. E-mail: wajeeha_aslam_87@live.com 1156 Global Business Review 20(5) customers, providing better services and improving transaction execution (Boon-itt, 2015). Service providers want the consumers to use technology because it increases services processes, enhances proficiency of services, offers efficient assistance to customers and multiplies services delivery alternatives (Curran & Meuter, 2005). Self-service technologies (SSTs) are ‘high-tech edges which aid customers in creating self-regulating services of uninterrupted employee participation in service’. It is considered as a substitute for banks that are responsible for cash deposit and withdrawal as well as over the counter transactions (Iberahim, Taufik, Adzmir, & Saharuddin, 2016). SSTs are intentionally intended towards advancing excellence to fulfil the needs of the customers (Zhao, Mattila, & Eva Tao, 2008). Automated service quality has turned into a viable tool because of its ability to easily duplicate a bank product, but not its level of service. Therefore, by accepting the consequences of automated service quality, reimbursements are offered to banks in terms of enhancing the level of service quality, gaining competitive advantages, expanding their market share, increasing their innovation ability and finally improving the bank performance (Al-Hawari, 2011). Meuter, Ostrom, Roundtree, and Bitner (2000), and Lin and Chang (2011) suggested automated teller machines (ATMs), check-in machines and automated ticketing, telephone banking and online services as examples of SSTs and stated that customers who take advantage of SSTs appreciate service surrounded by extra flexible time frames plus additional channels. Bitner (2001) stated that service providers correspondingly enhance efficiency as well as effectiveness over SSTs. ATM service quality is stated as ‘customer’s total assessment and verdict for quality of services delivered by means of ATM channel’ (Narteh, 2013). Lower labour cost, efficiency, more consumer involvement, standardization of service delivery, customer satisfaction and loyalty are the reasons for the introduction of ATMs in retail banking (Al-Hawari & Ward, 2006; Hsieh et al., 2012; Narteh, 2015). Service quality is an essential requirement for creating and sustaining a satisfactory relationship with customers in a traditional banking context (Sureshchandar, Rajendran, & Anantharaman, 2002). Rod, Ashill, Shao, and Carruthers (2009) observed a direct association between automated service quality and customer satisfaction. According to Day (2003), Wong and Zhou (2006), Olorunniwo, Hsu, and Udo (2006), and Aslam and Frooghi (2018), service quality has been found as an important determinant to attain customer loyalty and satisfaction. According to Parasuraman, Zeithaml, and Berry (1988), advocated service quality is measured by variance concerning customer anticipations of a service provider’s performance and assessment of services they received. Lee and Lin (2005) and Gefen (2002) used the SERVQUAL model by modifying its dimensions to measure the service quality (Shachaf, Oltmann, & Horowitz, 2008). Several studies have been conducted to investigate the effect of the ATM service quality on customer satisfaction globally (Narteh, 2013, 2015; Proença & Rodrigues, 2011), but none of such studies have been conducted in Pakistan. Khan (2010) stated that ease of use, efficiency, reliability, privacy, responsiveness; convenience and efficiency are the factors of ATM service quality. However, his research ignored a vital ATM service quality dimension, that is, fulfilment, which has been assumed as a foremost automated quality dimension (Parasuraman, Zeithaml, & Malholtra, 2005; Wolfinbarger & Gilly, 2003) as well as customer loyalty (Ariff, Yun, Zakuan, & Ismail, 2013). Narteh (2015) determined security and privacy as one of the quality dimensions. Bearing in mind the significance of SSTs in the retail banking industry, there is a need to expand the study and explore some concerns (inconsistency in operations) of service quality that influence customer loyalty and customer satisfaction in retail banking sector of Karachi, Pakistan. Aslam et al. 1157 With the continuous acceptance of ATMs as a service delivery choice in retail banking, the research into the dimensions of service quality of ATM and their association with customer satisfaction and customer loyalty is an important requirement and this study aims to fulfil this research need. In Pakistan, banks are offering automated services to attain superior success in these vibrant environs. Banks must be able to deliver a high level of service quality to their customers to increase their costeffectiveness and attractiveness. This study attempts to observe the impact of the ATM service quality on customer satisfaction and its influence on customer loyalty. Furthermore, the study discovers issues that are to be focussed in order to improve service delivery through the ATMs. Findings from the assessment could also offer bank managers insights to increase and develop customer satisfaction and loyalty in retail banking for using ATMs. The next section reviews the related literature and presents the framework of the study and service quality dimensions with respect to customer satisfaction, and then objective and rationale of the study are discussed. Data source, sample frame and empirical model are incorporated in the section of methodology, followed by the section of data analysis. At the end, the paper presents the discussion, managerial implications and directions for future research. Review of Literature Conceptual Framework For predicting the acceptance of new technologies, Davis (1986) proposed the technology acceptance model (TAM) that is an adaptation of the theory of reasoned action (TRA) (Ajzen & Fishbein, 1980). TAM comprises subsequent conceptions: perceived ease of use (PEOU), perceived usefulness (PU), attitudes towards use and intention to use/actual use (King & He, 2006; Lin & Chang, 2011). TAM postulates that PEOU is a main element that affects acceptance of information system, whether directly or indirectly over PU. The aim of the TAM is to deliver a broad-spectrum description of the elements of acceptance of technology that is proficient in clarifying users’ behaviour towards technology (Davis et al., 1989). According to Kumar, Lall, and Mane, (2017), the TAM model states that if an application is perceived to be easy to use, it would have a greater level of acceptance. Sahi and Gupta (2013) argued that an application that is apparent to be stress free to use than another is more likely to be accepted by the users. For the adoption of innovation, both PEU and PU have been used and the influence of PU on system utilization is found more significant (Lucas, Swanson, & Zmud, 2008; Robey, 1979). Wang, Butler, Hsieh, and Hsu (2008) also discovered the casual impact of ease of use (EOU) on PU, and noticed that consumers are focussed to adopt an innovation primarily because technology is easy to use and secondarily for usefulness of the technology for them. Both the factors significantly affect customers’ attitude and intention to use SSTs, as consumers are expected to be more satisfied with SSTs, if they consider that using the system will increase their productivity and performance. Davis et al. (1989), Wang, Wang, Lin, and Tang (2003), and Pikkarainen, Pikkarainen, Karjaluoto, and Pahnila (2004) have revealed that PEOU is the main element of acceptance by user and it has a significant impact on the proposed system use. While acknowledging the robustness and supremacy of the TAM, they continue towards extending the model with external determinants critical to technology adoption and use (Dimitriadis & Kyrezis, 2010; Wu & Lederer, 2009). Bolton and Drew (1991) suggested that customer satisfaction causes service quality. Bitner, Ostrom, and Meuter (2002) and Proença and Rodrigues (2011) acknowledged ease of access and convenience to services as reimbursements of SSTs that encourage customer satisfaction; however, 1158 Global Business Review 20(5) out-of-order hardware and software cause dissatisfaction. Perceived service quality is assumed to have an indirect positive effect on loyalty via satisfaction (Eakuru & Matt, 2008). In previous studies, dimensions of ATM service quality are found to be significantly related to customer satisfaction (Narteh, 2015). In the current study, we have applied the TAM theory to support the relationship of ATM service quality with customer satisfaction and customer loyalty. Hence, based on the previous research (Khan, 2010; Narteh, 2015), we have extended the model of ATM perceived service quality with the added construct of Customer Loyalty (Ariff et al., 2013; Eakuru & Matt, 2008; Ribbink et al., 2004). The service quality hypothesis development is discussed in the next section. Self Service Technology SSTs are ‘high-tech edges which aid customers in creating self-regulating services of uninterrupted employee participation in service’. It is considered as a substitute for banks, which is responsible for cash deposit and withdrawal as well as over the counter-transactions (Iberahim et al., 2016). Makarem, Mudambi, and Podoshen (2009) said that, by attractive SSTs, the firm’s crucial purpose is to deliver superior value to customers at convenient times and at cheaper costs in order to satisfy and retain customers. In the past two decades, the introduction of SSTs in business world has resulted in an overabundance of academic research (Agnihothri, Sivasubramaniam, & Simmons, 2002; Hsieh et al., 2012; Joseph & Stone, 2003; Lee & Allaway, 2002; Snellman & Vihtkari, 2003). The results of these studies suggest that customers assess technology-based service innovations more confidently, if the assumed innovation has the features of high expectedness, controllability, and outcome attractiveness. Though, like all other man-made inventions, SSTs sometimes do fail, and while interacting with technology-based service delivery systems, customer frustration is also evident (Parasuraman, 2000). The frustration has been largely accredited to the lack of readiness and confidence on the part of customers in operating tech-based service delivery interfaces (Ganguli & Roy, 2010). In spite of these problems, SSTs have become enduring features of retail banking service delivery and an examination into their quality dimensions and how they affect customer satisfaction especially in emerging countries is critical for managing customer satisfaction and loyalty of retail banks. Customer Satisfaction According to Saleem and Rashid (2011), customer satisfaction is usually regarded as the degree to which a product or service delivered by a firm meets customer expectations. Molina, Martín-Consuegra, and Esteban (2007) claimed that satisfaction results from the feelings consumers attain throughout and later the consumption process. According to Oliver (1980) and Meng, Tepanon, and Uysal (2008), the expectancy-disconfirmation paradigm is constructed on the intention that customers form expectancies about a product or service prior to consumption. However, Cronin and Taylor (1992) have debated that neither expectation nor disconfirmation has any influence on customer satisfaction due to the diverse definitions of customer expectations as well as the problems in its measurement. Aslam et al. 1159 Service Quality and Customer Satisfaction in Automated Channels Services function as the most prominent phenomena that customers can experience and perceive, and service quality can be assessed based on the interactions of customers with service providers, technology interface and physical evidence (Hanaysha, 2016). Day (2003), Wong and Zhou (2006), Olorunniwo et al. (2006), and Gursoy and Swanger (2007) postulated that service quality is related to customer satisfaction and loyalty. Parasuraman et al. (1988) propose that service quality is measured by the difference between customer expectations of service provider’s performance and their evaluation of the service they received. Various models have been established in the previous studies to measure service quality. The SERVQUAL model, proposed by Parasuraman et al. (1988), and the alternative SERVPERF model by Cronin and Taylor (1992) have acknowledged extensive research consideration and solicitation in the service quality texts. According to Cronin and Taylor (1992), the SERVQUAL model, in spite of its shortcomings, seems to have attained a recognized status with service quality research. The model is built on the statement that service quality is dependent on five major factors of reliability, tangibles, empathy, assurance and responsiveness (Parasuraman et al., 1988). Lee and Lin (2005) and Gefen (2002) used the SERVQUAL model and altered its dimensions to measure service quality. In situations where machines are used to substitute employees in the service delivery process, new dimensions of service quality might be perceived as central by customers. The inference from these studies is that service quality dimensions in traditional services cannot be entirely valid to automated service environments. ATM Service Quality and Customer Satisfaction ATMs are electronic devices which let customers deposit, withdraw and transfer money, pay bills and perform other financial transactions without the assistance of a branch representative or a teller. From the prior research, it is evident that ATM is the electronic version of the brick-and-mortar banking hall and customers visit the ATM to make financial transactions, be it withdrawals, deposits or balance enquiry, as they would have done in the normal banking halls. Santos (2003) stated that ATM service quality is the customers’ overall evaluation and judgement of the excellence of services provided through ATM channels. Research shows that ATM quality dimensions are multi-dimensional (Katono, 2011; Khan, 2010; Narteh, 2013). Narteh (2013) identified several dimensions of ATM service quality, such as reliability, convenience, security and privacy, ease of use, fulfilment and responsiveness. Reliability Reliability is the capability to carry out the required service precisely and reliably (within the traditional service quality research) (Parasuraman et al., 1988). Wolfinbarger and Gilly (2003) claimed that reliability is the robust interpreter of customer satisfaction in electronic channels. The reliability dimension is critical because it embeds the active competency to perform the undertaken service dependably and accurately. In the ATM environment, reliability predicts the ability of the machine to function all the time, and provide error-free and consistent services. In online transactions, Stiakakis and Georgiadis (2009) found reliability as the essential benchmark of higher electronic service quality. Within ATMs, both Khan (2010) and Katono (2011) found reliability to be an essential ATM quality dimension which impacts customer satisfaction. 1160 Global Business Review 20(5) Convenience Convenience refers to the situation where work is simplified with no hassle (Aslam, Arif, & Farhat, 2017). Convenience is regarded as the site or location of the ATM and includes 24/7 accessibility of the services to the customers (Narteh, 2013, 2015). ATMs are conveniently located at bank branches, or off sites, such as shopping malls and college campuses. The bank’s ATM card is compatible with other banks ATM platforms and this makes it possible for customers to withdraw money from other ATMs at a small fee (Narteh, 2015). It lessens the troublesomeness involved in using ATMs and is found to be positively correlated with customer satisfaction (Al-Hawari et al., 2005). If the ATMs are conveniently located, it reduces the inconvenience involved with covering long distances in order to carry out bank transactions. Joseph and Stone (2003), Al-Hawari et al. (2005), Khan (2010), and Katono (2011) stated that convenience has been the most used dimension of ATM service quality and has been found to be positively correlated with customer satisfaction. Ease of Use Technology can be threatening to some customers, and therefore, one expects that ATMs should be intended to abridge the transactional process for customers. Davis et al. (1989) described the ease of use as the extent to which the potential user anticipates target system to be stress-free. If users feel that electronic banking is easy to use and free of stress, then the likelihoods of them using the system will be higher (Chong, Ooi, Lin, & Tan, 2010). This study uses the concept to mean the degree to which ATMs offer trouble-free transaction for the customer. Ease of use is a key element in defining the acceptance and use of various corporate information technologies such as online banking (Gounaris & Koritos, 2008). Researchers such as Al-Hawari et al. (2005) and Khan (2010) found that ease of use leads to customer satisfaction in case of ATM usage. Security and Privacy An ATM should also deliver customers with security and privacy. Security includes defence of customers from deception and monetary loss, whereas privacy is fortification of personal information (Zeithaml, Parasuraman, & Malhotra, 2002). Casaló, Flavián, and Guinaliu (2007) defined security as ‘the technical assurance that the legal obligation and practices concerning privacy will be met successfully’. In Bangladesh and Brazil, privacy and security were found to be of serious value and an important enabler for customers in online transactions (Hernandez & Mazzon, 2007; Jahangir & Begum, 2008; Kim, Kim, & Lennon, 2006). Similarly, Chong et al. (2010) found security and privacy as important factors in the adoption of Internet banking in Vietnam. Every customer expects protection for their money and personal information from their banks. In the studies of USA, Australia and Pakistan, security and privacy were considered as important ATM service quality dimensions (Al-Hawari et al., 2005; Joseph & Stone, 2003; Khan, 2010). Consequently, the current study assumes that security and privacy will be positively correlated with customer satisfaction. Fulfilment It is the degree to which the site’s assurances about order delivery and item readiness are encountered (Parasuraman et al., 2005). The fulfilment of websites has a noteworthy influence on total quality, satisfaction and loyalty intents (Wolfinbarger & Gilly, 2003). Previous studies related to ATM considered fulfilment as a quality dimension to measure consequence desirability or the degree to which the ATM performs outcomes to meet the customers’ expectations. This includes the genuineness of notes provided by the ATM (eradicate counterfeits), the amount provided to customers per transaction, and the ATM’s transactional charges imposed on customers. Narteh (2015) found availability of cash and the quality of bank notes to be important ATM service quality variables. Aslam et al. 1161 Responsiveness Like all technologies, ATMs are also sometimes disposed to service failures. Responsiveness measures the accomplishment of strategies which the banks introduce to get better services, when ATM services are undesirably established (Narteh, 2015). Responsiveness or recovery is a major determinant in many electronic service quality scales (Narteh, 2013, 2015; Parasuraman et al., 2005). With ATMs, response or recovery quality deals with the banks’ ability to handle customer complaints arising as an outcome of transactional failures as well as reimbursing customers in contradiction of losses experienced, such as money illegally withdrawn out of their accounts. Khan (2010) and Narteh (2015) stated that effective ATM response strategies anticipate customer satisfaction in Pakistan. Customer Satisfaction and Customer Loyalty The function of both customer satisfaction and perceived value is known as customer loyalty (Alhemoud, 2010). It is profoundly believed that commitment means to rebuy desired product/service dependably in prospect, thus causing repetitive same-brand/same-set purchasing, regardless of situational effects and marketing determinations ensuring possibility to cause switching behaviour (Al-Hawari, 2011). The degree to which a customer exhibits repeat purchasing behaviour from a service provider possesses a positive attitudinal disposition towards the provider, and considers using only this provider when a need for this service arises (Fianko et al., 2015). According to Fianko et al. (2015), a loyal customer may not necessarily be a satisfied customer. Oliver (1999) points out that satisfaction and loyalty are related. Satisfaction is, therefore, a function of relative level of expectation and perceived performance. Expectations are built on the basis of previous experience with the same or similar situations, statements made by friends, or other associates. A customer is said to be loyal to a brand that provides a satisfactory experience. Beerli, Martin, and Quintana (2004) stated that satisfaction has been shown to have its effect on customer loyalty and conclude that satisfaction together with personal switching costs is an antecedent of loyalty. Building on the existing literature revised above, the current study suggests that reliability, convenience, ease of use, security and privacy, responsiveness, and fulfilment are projected to be the chief dimensions of ATM service quality, which will impact customer satisfaction and influence customer loyalty. Objectives Due to the importance and increase in usage of SSTs, the objective of this study is to investigate the effect of ATM service quality on customer satisfaction and customer loyalty. Responsiveness, ease of use, reliability, convenience, fulfilment, and security and privacy have been taken as the dimensions of service quality. By considering these dimensions, customer satisfaction as well as the impact of customer satisfaction on customer loyalty has been assessed in the present study. Rationale of Studies The purpose of the study is to identify the service quality dimensions that help in increasing customer satisfaction, which leads to loyalty. Due to the increase in the usage of SSTs and the acceptance of ATMs 1162 Global Business Review 20(5) as service delivery choice in retail banking, there is a need to identify the factors that help in satisfying the customer. Methodology To foresee the ATM service quality impact on customer satisfaction and loyalty, primary data were collected through a self-administered questionnaire. The questionnaire was designed for use as a survey instrument to record the respondents’ experiences and perceptions about ATM service on a 5-point Likert-type scale that varied from ‘strongly disagree’ (1) to ‘strongly agree’ (5). The technique used for data collection and the sources from where the questionnaire was adapted are mentioned in data source. Under the sample frame, the target audience of this study was mentioned. Statistical tests which were applied on the data are mentioned under the heading of Data analysis tool. Data Source The items used for the survey instrument were adopted from earlier studies and the measurements taken are mentioned in Table 1. The Questionnaire was based on two parts: one was related to demographic profile of respondents and the other was based on constructs. After compilation of the questionnaire, it was circulated among the respondents in both hard copy and soft copy forms. Soft copy was shared with the respondents by sending a link of the questionnaire through e-mails and social media. A non-probability convenience sampling method was implemented. A total of 360 questionnaires were distributed, but 322 usable completed questionnaires were received. Table 1. Exploratory Factor Analysis Items Adapted Source Factor Loadings RESPONSIVENESS Cronbach’s alpha = 0.800 ATM contact person is available to set right the problems. Broken-down ATMs are fixed promptly. 0.66 Narteh (2015) 0.765 ATM cards are promptly replaced. 0.76 ATM banking settles complaints in a reasonable time. 0.672 EASE OF USE Cronbach’s alpha = 0.853 ATM provides clear instructions on usage. ATMs are easy to use for transactions. 0.765 Narteh (2015) 0.824 ATM language is easy to understand. 0.845 ATM provides graphics and adverts of bank services. 0.525 RELIABILITY Cronbach’s alpha = 0.764 (Table 1 Continued) 1163 Aslam et al. (Table 1 Continued) Items ATM functions all the time. ATM provides consistent services. I don’t find fake currency notes from my ATM. I never found my ATM out of cash. Adapted Source Factor Loadings Narteh (2015) 0.697 Jha et al. (2014) 0.608 0.703 0.731 CONVENIENCE Cronbach’s alpha = 0.828 ATMs are conveniently located in my city. ATMs of my bank are easily found at all useful places like hospitals, malls, airports &amp, stations, etc. I can locate my bank’s ATMs easily when I am out of station. ATM cards are compatible on other platforms. Narteh (2015) 0.634 0.693 Jha et al. (2014) 0.712 Narteh (2013) 0.73 FULFILMENT Cronbach’s alpha = 0.826 ATM provides fast services. ATM provides enough money during transactions. 0.685 Narteh (2015) 0.687 ATM satisfies most of my banking needs. ATM charges are reasonable. 0.615 Narteh (2013) 0.525 ATM gives instant money all the time. 0.618 SECURITY AND PRIVACY Cronbach’s alpha = 0.829 I have trust and confidence in the security of ATM banking. I feel safe during ATM transactions. 0.665 Narteh (2015) 0.746 I have confidence in the security of my personal information. I trust that ATM will not misuse my personal information. 0.805 Collier (2006) 0.787 CUSTOMER SATISFACTION Cronbach’s alpha = 0.821 My bank’s ATMs provide the service that I need. Overall I am very satisfied with the services an ATM provides me with. I like to encourage friends and relatives to use an ATM machine operated by this bank. I think that I made the correct decision to use this bank’s ATM. Cockrill, Goode, and Beetles (2009) Casaló, Flavián, and Guinaliu (2008) 0.736 0.674 0.596 0.734 (Table 1 Continued) 1164 Global Business Review 20(5) (Table 1 Continued) Adapted Source Items Factor Loadings CUSTOMER LOYALTY Cronbach’s alpha = 0.788 I have a positive emotional relation with the bank’s ATM I have chosen. I intend to remain a user of the bank’s ATM I have chosen. Eakuru and Matt (2008) 0.518 0.794 I would always recommend my bank’s ATM to someone who seeks my advice. Beerli et al. (2004) 0.79 Based on my experience, I am very likely to continue my relationship with this bank’s ATM in the next months. Casaló et al. (2008) 0.54 Source: The authors. Responsiveness Ease of Use Reliability Customer Satisfaction Customer Loyalty Convenience Fulfilment Security and Privacy Figure 1. Research Model Source: The authors. Sample Frame Data were collected from ATM users of different banks in Karachi, since this market segment is viewed as important for the continued advancement of the retail banking industry. Aslam et al. 1165 Data Analysis Tools Reliability analysis was performed to evaluate the internal consistency of the items. Exploratory factor analysis was performed using the option of varimax rotation in order to compile the construct using SPSS 22.0. After performing exploratory factor analysis, confirmatory factor analysis was performed to check all the model fitness criteria. To further test the hypothesized relationships among the latent variables, the structural equation modelling (SEM) was employed using IBM SPSS Amos 22.0. Empirical Model Founded on the aforementioned literature review, the study proposes a framework which guides the current research. Analysis Demographic Profile The gender composition of the respondents indicated that 57.8 per cent of the respondents were male, while 42.2 per cent of the respondents were female. Only 11.5 per cent of the respondents were 30–40 years old, and 2.8 per cent were above 40 years of age. As the data were collected from different universities of Karachi, the largest group of ATM users were from 20–30 years age group, that is 73.3 per cent followed by 12.4 per cent of the respondents belonging to under 20 years of age category. The education level of 47.2 per cent of the respondents was graduation, while 27 per cent and 25.8 per cent respondents were postgraduates and undergraduates, respectively. In addition, the survey of the ATM usage pattern revealed that about 47.8 per cent of the respondents use their cards once a week for transactions, 23.9 per cent twice a week, and 17.7 per cent and 10.6 per cent of the respondents reported that they use their ATM cards three to four times per week. Occupational distribution reflects that 54.7 per cent respondents were salaried employees, 37.3 per cent were students, while 8.1 per cent were selfemployed. The analysis of respondents’ reported monthly income revealed that only 13.4 per cent respondents earn PKR 50,000 per month or more, 37.3 per cent earn PKR 20,000–30,000 per month, while 28.9 per cent earn less than PKR 20,000. Finally, 19.9 per cent and 10.6 per cent respondents earn PKR 30,000–40,000 and PKR 40,000–50,000, respectively. The maximum number of people (71.1%) use ATM for cash withdrawal, 9.9 per cent use ATM for balance enquiry, 9.6 per cent use ATM for transfer funds, while 9.3 per cent it for bill payments; 12.4 per cent people use ATM due to its time saving nature, while 7.1 per cent like it for its faster transaction; 18.3 per cent respondents prefer it as it is easy for them to use, whereas 43.8 per cent people consider it as easy banking anytime/anywhere as they do not have to look around for their own bank’s branch every time to get cash or check their balance; 18.3 per cent customers consider it to be meeting all the mentioned features that lead to their needs fulfilment. Table 2 illustrates the demographic profile of respondents. 1166 Global Business Review 20(5) Table 2. Demographic Profile of Respondents Frequency Percentage Male 186 57.8 Female 136 42.2 Below 20 years 40 12.4 20–30 Years 236 73.3 30–40 Years 37 11.5 Above 40 Years 9 2.8 Under graduate 83 25.8 Graduate 152 47.2 Postgraduate and above 87 27 Once 154 47.8 Twice 77 23.9 Thrice 57 17.7 Four times 34 10.6 Student 120 37.3 Salaried employee 176 54.7 Self-employed 26 8.1 Less than PKR 20,000 93 28.9 PKR 20,000–30,000 88 37.3 PKR 30,000–40,000 64 19.9 PKR 40,000–50,000 34 10.6 Above 50,000 43 13.4 Cash withdrawal 229 71.1 Balance Enquiry 32 9.9 Transfer funds 31 9.6 Bill payments 30 9.3 Gender Age Qualification ATM usage per week Occupation Monthly income Purpose of using ATM Reason to prefer ATM (Table 2 Continued) 1167 Aslam et al. (Table 2 Continued) Frequency Percentage Easy banking any time any where 141 43.8 Easy to use 59 18.3 Faster transactions 23 7.1 Time saving 40 12.4 All of the above 59 18.3 Source: The authors. Descriptive Statistics Table 3 displays the means and standard deviations of the various variables used. These values describe the extent to which the sampled respondents agreed/disagreed with the statements used in the questionnaire. The descriptive statistics below indicate moderate-to-high mean values from the respondents. The highest mean was 4.17 (ATMs are easy to use for transactions and ATM language is easy to understand), whilst the lowest value was 3.09 (I never found my ATM out of cash). Hence, it is evident from Table 3 that majority of the respondents agreed that ATMs are easy to use for transactions and ATM language is easy to understand, although they sometimes found ATM out of cash. Table 3. Descriptive Statistics Variables Mean Std. Deviation ATM contact person is available to set right the problems. 3.35 1.116 Broken-down ATMs are fixed promptly. 3.25 1.141 ATM cards are promptly replaced. 3.43 1.066 ATM banking settles complaints in a reasonable time. 3.5 1.02 ATM provides clear instructions on usage. 4.02 0.925 ATMs are easy to use for transactions. 4.17 0.883 ATM language is easy to understand. 4.17 0.857 ATM provides graphics and adverts of bank services. 3.95 0.973 ATM functions all the time. 3.4 1.193 ATM provides consistent services. 3.59 1.044 I do not find fake currency notes from my ATM. 3.76 1.211 I never found my ATM out of cash. 3.09 1.287 ATMs are conveniently located in my city. 4.01 0.854 ATMs of my bank are easily found at all useful places like hospitals, malls, airports &amp; stations etc. 3.86 0.917 I can locate my bank’s ATMs easily when I am out of station. 3.85 0.907 (Table 3 Continued) 1168 Global Business Review 20(5) (Table 3 Continued) Variables Mean Std. Deviation ATM cards are compatible on other platforms. 3.88 0.867 4 0.818 ATM provides enough money during transactions. 3.8 0.889 ATM satisfies most of my banking needs. 3.9 0.771 ATM charges are reasonable. 3.64 0.964 ATM gives instant money all the time. 3.79 1.007 I have trust and confidence in the security of ATM banking. 3.81 0.969 I feel safe during ATM transactions. 3.48 1.023 I have confidence in the security of my personal information. 3.88 0.859 I trust that ATM will not misuse my personal information. 3.89 0.862 My bank’s ATMs provide the service that I need. 3.87 0.716 Overall I am very satisfied with the services an ATM provides me with. 3.96 0.823 I like to encourage friends and relatives to use an ATM machine operated by this bank. 3.99 0.797 I think that I made the correct decision to use this bank’s ATM. 3.87 0.833 I have a positive emotional relation with the bank’s ATM I have chosen. 3.75 0.865 I intend to remain a user of the bank’s ATM I have chosen. 3.75 0.849 I would always recommend my bank’s ATM to someone who seeks my advice. 3.82 0.864 Based on my experience, I am very likely to continue my relationship with this bank’s ATM in the next months. 3.96 0.777 ATM provides fast services. Source: The authors. Factor Adequacy, Reliability and Validity of Construct Scales To check the dimensionality of the instrument, all the items of the questionnaire were factor analyzed by using varimax rotation. The validation process was initiated using an initial exploratory analysis of reliability and dimensionality. The values of the Bartlett test of sphericity and the Kaiser–Meyer–Olkin (KMO) measure of sampling adequacy, which were 0.000 and 0.899 (>0.60), respectively, confirmed that there is a significant correlation among the variables (Hair, Anderson, Babin, & Black, 2010). The variables with loadings of at least 0.5 and factors with a reliability threshold of 0.7 (Hair, Black, Babin, Anderson, & Tatham, 2006) were incorporated into the analysis. Cronbach’s α statistics for the constructs range from 0.764 for reliability to 0.853 for ease of use, which advocates that scales are adequately reliable (Hair et al., 2010). Table 1 illustrates the overall factor loadings and reliability of the individual items. After exploring the eight factors through EFA, IBM AMOS 22 is used for confirmatory factor analysis to facilitate cross-validation of the model. During CFA, average variance extracted (AVE) and composite reliability (CR) were measured for the variables. The value of CR should be >0.7 and AVE should be >0.5 (Fornell & Larcker, 1981). Table 4 illustrates the values of AVE, CR and standardized factor loadings of CFA. 1169 Aslam et al. Table 4. Confirmatory Factor Loadings, Composite Reliability and Average Variance Extracted Constructs Responsiveness Ease of use Reliability Security and privacy Convenience Fulfilment Customer satisfaction Customer loyalty Items Standardized Loadings RES3 0.79 RES4 0.69 RES5 0.73 EOU1 0.89 EOU2 0.79 EOU4 0.88 REL1 0.86 REL2 0.85 REL4 0.69 SP1 0.93 SP3 0.88 SP4 0.81 CON2 0.74 CON3 0.81 CON4 0.76 FUL3 0.79 FUL4 0.79 FUL5 0.79 FUL7 0.82 CS2 0.72 CS3 0.75 CS4 0.71 CS5 0.83 CS6 0.78 CS7 0.75 CS8 0.75 CR AVE 0.782 0.545 0.888 0.727 0.843 0.644 0.904 0.759 0.814 0.594 0.875 0.637 0.774 0.534 0.86 0.605 Source: The authors. To check whether the variables are correlated, discriminant validity (test/measure?) was performed. The square roots of the AVE values are greater than corresponding correlations (Fornell & Larcker, 1981). It was observed that the variable is correlated with itself only. Table 5 illustrates the values of correlation among the variables and the squared value of AVE to check the discriminant validity. 1170 Global Business Review 20(5) Table 5. Discriminant Validity and Correlation CL EOU CS SP CON FUL RES CL 0.778 EOU 0.307 0.852 CS 0.696 0.489 0.731 SP 0.315 0.384 0.424 0.871 CON 0.351 0.583 0.511 0.474 0.771 FUL 0.378 0.489 0.595 0.484 0.701 0.798 RES 0.328 0.469 0.472 0.312 0.484 0.509 0.738 REL 0.335 0.461 0.513 0.356 0.47 0.54 0.569 REL 0.802 Source: The authors. Model Fitness To analyze the simultaneous effects of the variables included in the final construct, the model was further studied by SEM. A few items were excluded from the model in order to achieve model fitness. The items are as follows: ‘ATM banking settles complaints in a reasonable time’, ‘ATM language is easy to understand’, ‘I never found my ATM out of cash’, ‘I feel safe during ATM transactions’, ‘ATM cards are compatible on other platforms’, ‘ATM charges are reasonable’ and ‘I think that I made the correct decision to use this bank’s ATM’. From the results of various indices, the model showed good fitness. The value of χ2(CMIN/df) was (2.106) which is between the acceptable range of 3:1(Arif, Aslam, & Ali, 2016; Kline, 2011) and CMIN is (526.469), df is 250, and the probability level is (0.000). While goodness-of-fit index (GFI) is (0.892) and possible good range of GFI is 0–1, high values show better fit, and previously values greater than 0.90 were considered good (Hair et al., 2010). Trucker Lewis Index (TLI) was found to be (0.906), which also lies in the acceptable range of 0 to 1 (Arif, Afshan, & Sharif, 2016; Aslam, Batool, & Haq, 2016; Byrne, 2013) for better model fitness. The root mean square error of approximation is (0.059), which is less than 0.07 and shows good fit (Aslam et al., 2015; Byrne, 2013). The results indicated that the overall model was a good fit at 95 per cent level of confidence. The value of standardized root mean square residual (SRMR) for the default model is found to be 0.0496, and according to Hu and Bentler (1999), it must be less than 0.08. These various indices showed that the model fits the data perfectly. All the stated values are between acceptable regions for the default model. Table 6 demonstrates the model fitness for the SEM. Path Analysis As per the proposed model, the relation was built and checked after the model fit of SEM. The estimated relationship is shown in Table 7. Out of six service quality dimensions, four were found to be statistically significant, and thus, they supported five of the seven hypothesized relationships. The results show that customer satisfaction with ATM service quality is chiefly predicted by fulfilment, reliability, ease of use 1171 Aslam et al. and security and privacy, thus they are significant and H2, H3, H5 and H6 are supported. Although responsiveness and convenience had a positive correlation with customer satisfaction, they are statistically insignificant. Therefore, H1 and H4 are not supported. The R2-value between the dimensions of ATM service quality on customer satisfaction was found to be 0.44, which shows that 44 per cent of the variation in customer satisfaction could be predicted by dimensions of ATM service quality. There is strong support for the path from customer satisfaction to customer loyalty, so H7 is also supported. The R2-value was 0.46, which means that 46 per cent of the variation in customer loyalty was accounted for by customer satisfaction. Table 6. Model Fit Absolute fit Measures Recommended Value Model Value χ2 526.469 df 250 χ2/df <3a 2.106 Goodness-of-fit index (GFI) >0.8c 0.891 Root mean square error of approximation (RMSEA) <0.08b 0.059 Incremental fit index (IFI) >0.90a 0.929 Tucker–Lewis coefficient (TLI) >0.90a 0.906 Comparative fit index (CFI) >0.90a 0.927 Parsimony normed fit index (PNFI) >0.50a 0.671 Parsimony comparative fit index (PCFI) >0.50a 0.713 Sources: Bagozzi and Yi (1988); Browne and Cudeck (1993); Baumgartner and Homburg (1996), and Doll, Xia, and Torkzadeh (1994). a b c Table 7. Hypothesis Testing Path Coefficients S.E. C.R. p-Value Results Reliability → customer satisfaction 0.083 0.036 2.284 0.022 Supported Responsiveness → customer satisfaction 0.061 0.046 1.339 0.181 Unsupported Fulfilment → customer satisfaction 0.232 0.072 3.21 0.001 Supported Convenience → customer satisfaction 0.029 0.078 0.369 0.712 Unsupported Security and privacy → customer satisfaction 0.07 0.033 2.098 0.036 Supported Ease of use → customer satisfaction 0.093 0.043 2.186 0.029 Supported Customer satisfaction → customer loyalty 0.953 0.105 9.049 0.000 Supported Source: The authors. 1172 Global Business Review 20(5) Discussion The motive of the study was to examine the customer satisfaction as well as check the relationship of dimensions of ATM service quality and customer loyalty. The ATM service quality is found to be multidimensional, which is concordant with previous studies (Nateh, 2013, 2015). The study has delivered a comprehensive set of ATM quality dimensions and demonstrates that apart from convenience and responsiveness, dimensions such as fulfilment, security and privacy, ease of use, and reliability have a significant effect on customer satisfaction and this influences customer loyalty. The study has discovered that fulfilment is the most essential determining factor of customer satisfaction for ATM service quality. The findings are in accordance with previous studies (Narteh, 2015), which also found that ATM must provide fast services, precisely record transactions with receipts in order to meet the needs of the customers, ensure availability of adequate quality bank notes and enough cash in a sufficiently early manner, and create receipts to approve transactions. Second, the results showed that reliability is an important contributor of customer satisfaction of ATM services. To enhance customer satisfaction, ATMs must have technical and functional reliability and provide error-free services. The outcomes are similar to the results obtained by scholars (Narteh, 2013, 2015; Parasuraman et al., 2005) who also found that customers anticipate ATMs to function persistently, provide reliable services and create exact account records. The purpose of creating automated channels is to facilitate the clients, so that they can carry out their financial transactions during any period of the day. Third, security and privacy is another significant dimension of ATM service quality in predicting customer satisfaction. The results suggest that all customers anticipate security, confidence, and trust for their money as well as their personal information. Installation of CCTV cameras and the presence of security guards on on-site ATMs have increased the trust factor in customers during transactions. Moreover, the study has found that the ease of use has a significant impact on customer satisfaction. Even technology-savvy customers occasionally find technology use a bit intimidating, so customers anticipate the ATM to be effort free and less complex. The results are consistent with past studies (Narteh, 2013, 2015), which also found that the facility of an easy-to-understand language as well as user-friendly instructions are an important determinant for improving customers’ ATM experience. Furthermore, the study revealed that customer satisfaction has a strong influence on customer loyalty. Customer satisfaction leads to customer loyalty with an estimated value of 93 per cent. The results are consistent with previous studies (Beerli et al., 2004; Casaló et al., 2008; Eakuru & Mat, 2008; Kaura, Durga Prasad, & Sharma, 2015), which found that customer satisfaction will be created, if the customers’ anticipations about the services are met, as expectations are built on the basis of previous encounters with the same or similar situations and testimonials made by friends or other associates. Satisfaction is an essential criterion for loyalty, because satisfied customers are loyal, and therefore, they incline to select the same service providers. The results further show that responsiveness has an insignificant effect on customer satisfaction. This might be due to the reason that customers do not consider quick complaints compensations, prompt recovery of malfunctions of ATMs and replacement of ATM cards as much important as other dimensions. The results are concordant with earlier studies (Kumbhar, 2011; Wong, Rexha, & Phau, 2008) that responsiveness is not significantly associated with satisfaction in ATM services. Another reason for this insignificant result might be that if the ATM card gets trapped or damaged in the machine and customer makes complaints against it, the customer has confidence that the card would be returned to them only after displaying his identity. Convenience has a positive insignificant impact on customer satisfaction. The results are similar to the study of Mohammed (2012), which also concluded that convenience has no attentive effect on the Aslam et al. 1173 use of advanced IT banking services. Location of ATMs and compatibility of cards at other platforms are not the only reasons for creating customer satisfaction. Another reason might be e-banking channels that have resolved this issue, and customers feel comfortable in performing their transactions online. As this study has been conducted in Karachi city, where debit card use is very common at several shopping malls and restaurants, people can easily use their ATM cards anytime and anywhere. Conclusion Nowadays, SSTs have gained much popularity. SSTs are changing the way customers interact with the firm for service outcomes. This study reflects the consumer behaviour towards SSTs; mainly ATM service was focussed. For determining consumer behaviour, customer satisfaction and loyalty were considered. Different service quality dimensions (reliability, fulfilment, ease of use, convenience, security and privacy and responsiveness) were taken to assess customer satisfaction, which leads to loyalty. An adapted 5-point Likert-type scale questionnaire was used for the data collection. In total, 322 usable responses were gathered. Different statistical techniques such as EFA, CFA and SEM were implied. Reliability, content validity and discriminant validity were also examined. According to the results of path analysis, consumers get satisfied by the ATM service if it is reliable in terms of consistent service and availability of cash. Fulfilment and ease of use are also found to be the key factor, which helps in gaining satisfied customers. Consumers want to feel secure and want privacy while doing transactions; therefore, if the firm provides secure transaction facility, it can easily be able to get the satisfied customer. Managerial Implications This study delivers and exhibits the sustained importance of ATMs in the retail banking in Karachi. These identified dimensions will offer bank managers insights into what factors clients find to be most important in their ATM usage experience. The quality dimensions used in this study recognize the need for enhancement in ATM banking systems in order to offer value-added services to customers. In current study, continence has failed to establish a significant relation with customer satisfaction. This might be because mostly ATMs are used for cash withdrawal only and are under-utilized. A full range of bank services should be enabled through ATMs, which may add to the customer convenience and may contribute to the customer satisfaction. Banks should upgrade their ATM platforms to aid customers to receive all services, which are enabled through Internet banking, for instance, inter-bank transfer, payment of utility bills, cash deposit, making of pay-order, etc. These new services will probably attract more customers into the ATMs use and reduce the long queues in banking halls, which will help in building a robust and persistent relationship with customers. The banks should ensure that ATMs are there to fulfil the needs of customer belonging to all income classes. The ATM must provide notes of smaller denominations too, at times notes of small denomination finish quickly and customers may get ‘service denied’ message for lesser amounts. The resulting increase in customers’ inclination to use ATM for multidimensional features will also add to the demands on banks to promptly respond to meet the needs of customers. The focus of bank management should also be on delivering better interactivity, expanded assistance and increased ease of use through their ATM service, which will also ensure customer retention. 1174 Global Business Review 20(5) The service standards of ATMs can be improved through a two-way communication, that is, rapid response to customer queries about the ATM-associated services and regular maintenance at the ATMs to reduce failures, ensuring that all malfunctioning ATMs are fixed quickly. Banks should introduce new user-friendly, multilingual, biometric access-based, competitive systems and applications that will assist customers take the full advantage of the ATM service. Limitations of the Study and Future Recommendations This study is carried out in Karachi which limits the generalizability of the outcomes beyond the context of the study. Future studies must be conducted in other cities of Pakistan using random sampling in order to augment understanding of ATM quality dimensions and customer satisfaction. Future studies must investigate the relationship of additional dimensions of service quality with customer satisfaction, loyalty and retention in other SSTs (Internet banking and mobile banking), comparing the cross-cultural service quality of conventional commercial banks and Islamic banks. Acknowledgement The authors are grateful to the anonymous referees of the journal for their extremely useful suggestions to improve the quality of the article. Usual disclaimers apply. Declaration of Conflicting Interests The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article. Funding The authors received no financial support for the research, authorship and/or publication of this article. References Agnihothri, S., Sivasubramaniam, N., & Simmons, D. (2002). Leveraging technology to improve field service. International Journal of Service Industry Management, 13(1), 47–68. Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behaviour. Englewood Cliffs, NJ: Prentice-Hall. Al-Hawari, M. A. (2011). Automated service quality as a predictor of customers’ commitment: A practical study within the UAE retail banking context. Asia Pacific Journal of Marketing and Logistics, 23(3), 346–366. Al-Hawari, M., Hartley, N., & Ward, T. (2005). Measuring Banks' Automated Service Quality: A Confirmatory Factor Analysis Approach. Marketing bulletin, 16(1), 1–19. Al-Hawari, M., & Ward, T. (2006). The effect of automated service quality on Australian banks' financial performance and the mediating role of customer satisfaction. Marketing Intelligence & Planning, 24(2), 127–147. Alhemoud, A. M. (2010). Banking in Kuwait: A customer satisfaction case study. Competitiveness Review: An International Business Journal, 20(4), 333–342. Arif, I., Afshan, S., & Sharif, A. (2016). Resistance to adopt mobile banking in a developing country: Evidence from modified TAM model. Journal of Finance and Economics Research, 1(1), 23–38. Arif, I., Aslam, W., & Ali, M. (2016). Students’ dependence on smartphones and its effect on purchasing behavior. South Asian Journal of Global Business Research, 5(2), 285–302. Ariff, M. S. M., Yun, L. O., Zakuan, N., & Ismail, K. (2013). The impacts of service quality and customer satisfaction on customer loyalty in internet banking. Procedia-Social and Behavioral Sciences, 81, 469–473. Aslam et al. 1175 Aslam, W., & Frooghi, R. (2018). Switching behavior of young adult’s in cellular service industry: An empirical study of Pakistan. Global Business Review, 19(3), 635–649. Aslam, W., Arif, I., & Farhat, K. (2017). Smartphone dependence among students: Gender-based analysis. International Journal of Electronic Marketing and Retailing, 9(3), 269–287. Aslam, W., Batool, M., & Haq, Z. U. (2016). Attitudes and behaviour of the mobile phones users towards SMS advertising: A study in an emerging economy. Journal of Management Sciences, 3(1), 63–80. Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation model. Journal of Academy of Marketing Science, 16(1), 74–94. Baumgartner, H., & Homburg, C. (1996). Applications of structural equation modeling in marketing and consumer research: A review. International Journal of Research in Marketing, 13(2), 139–161. Beerli, A., Martin, J. D., & Quintana, A. (2004). A model of customer loyalty in the retail banking market. European Journal of Marketing, 38(1/2), 253–275. Bitner, M. (2001). Self-service technologies. Marketing Management, 10(1), 10. Bitner, M. J., Ostrom, A. L., & Meuter, M. L. (2002). Implementing successful self-service technologies. The Academy of Management Executive, 16(4), 96–108. Bolton, R. N., & Drew, J. H. (1991). A multistage model of customers’ assessments of service quality and value. Journal of Consumer Research, 17(4), 375–384. Boon-itt, S. (2015). Managing self-service technology service quality to enhance e-satisfaction. International Journal of Quality and Service Sciences, 7(4), 373–391. Browne, M.W., & Cudeck, R. (1993). Alternative ways of assessing model fit. Newbury Park, CA: SAGE Publications. Byrne, B. M. (2013). Structural equation modeling with EQS: Basic concepts, applications, and programming. New York: Routledge. Casaló, L. V., Flavián, C., & Guinaliu, M. (2007). The role of security, privacy, usability and reputation in the development of online banking. Online Information Review, 31(5), 583–603. ———. (2008). The role of satisfaction and website usability in developing customer loyalty and positive word-ofmouth in the e-banking services. International Journal of Bank Marketing, 26(6), 399–417. Chong, A. Y.-L., Ooi, K. B., Lin, B., & Tan, B. I. (2010). Online banking adoption: An empirical analysis. International Journal of Bank Marketing, 28(4), 267–287. Cockrill, A., Goode, M. M., & Beetles, A. (2009). The critical role of perceived risk and trust in determining customer satisfaction with automated banking channels. Services Marketing Quarterly, 30(2), 174–193. Cronin, J. J., Jr, & Taylor, S. A. (1992). Measuring service quality: A reexamination and extension. The Journal of Marketing, 56(3) 55–68. Curran, J. M., & Meuter, M. L. (2005). Self-service technology adoption: Comparing three technologies. Journal of Services Marketing, 19(2), 103–113. Dabholkar, P. A. (1996). Consumer evaluations of new technology-based self-service options: An investigation of alternative models of service quality. International Journal of Research in Marketing, 13(1), 29–51. Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management science, 35(8), 982–1003. Davis, F. D., Jr. (1986). A technology acceptance model for empirically testing new end-user information systems: Theory and results (Doctoral dissertation). Massachusetts Institute of Technology. Day, G. S. (2003). Creating a superior customer-relating capability. MIT Sloan Management Review, 44(3), 77. Dimitriadis, S., & Kyrezis, N. (2010). Linking trust to use intention for technology-enabled bank channels: The role of trusting intentions. Psychology & Marketing, 27(8), 799–820. Doll, W. J., Xia, W., & Torkzadeh, G. (1994). A confirmatory factor analysis of the end-user computing satisfaction instrument. MIS Quarterly, 18(4), 453–461. Eakuru, N., & Mat, N. K. N. (2008). The application of structural equation modeling (SEM) in determining the antecedents of customer loyalty in banks in South Thailand. The Business Review, Cambridge, 10(2), 129–139. Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3), 382–388. 1176 Global Business Review 20(5) Ganguli, S., & Roy, S. K. (2010). Service quality dimensions of hybrid services. Managing Service Quality: An International Journal, 20(5), 404–424. Gefen, D. (2002). Customer loyalty in e-commerce. Journal of the Association for Information Systems, 3(1), 2. Gounaris, S., & Koritos, C. (2008). Investigating the drivers of internet banking adoption decision: A comparison of three alternative frameworks. International Journal of Bank Marketing, 26(5), 282–304. Gursoy, D., & Swanger, N. (2007). Performance-enhancing internal strategic factors and competencies: Impacts on financial success. International Journal of Hospitality Management, 26(1), 213–227. Hair, J. F., Anderson, R. E., Babin, B. J., & Black, W. C. (2010). Multivariate data analysis: A global perspective (Vol. 7). Upper Saddle River, NJ: Pearson. Hair, J. F., Jr, Black, C. W., Babin, J. B., Anderson, R. E., & Tatham, L. R. (2006). Multivariate data analysis (6th ed.). Upper Saddle River, NJ: Prentice-Hall. Hanaysha, J. (2016). Testing the effect of service quality on brand equity of automotive industry: Empirical insights from Malaysia. Global Business Review, 17(5), 1060–1072. Hernandez, J. M., & Mazzon, J. A. (2007). Adoption of internet banking: Proposition and implementation of an integrated methodology approach. International Journal of Bank Marketing, 25(2), 72–88. Hsieh, Y. C., Roan, J., Pant, A., Hsieh, J. K., Chen, W. Y., Lee, M., & Chiu, H. C. (2012). All for one but does one strategy work for all? Building consumer loyalty in multi-channel distribution. Managing Service Quality: An International Journal, 22(3), 310–335. Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. Iberahim, H., Taufik, N. M., Adzmir, A. M., & Saharuddin, H. (2016). Customer satisfaction on reliability and responsiveness of self-service technology for retail banking services. Procedia Economics and Finance, 37, 13–20. Jahangir, N., & Begum, N. (2008). The role of perceived usefulness, perceived ease of use, security and privacy, and customer attitude to engender customer adaptation in the context of electronic banking. African Journal of Business Management, 2(2), 32. Joseph, M., & Stone, G. (2003). An empirical evaluation of US bank customer perceptions of the impact of technology on service delivery in the banking sector. International Journal of Retail & Distribution Management, 31(4), 190–202. Katono, I. W. (2011). Construction of an instrument to measure social valuation in an emerging market context. Education + Training, 53(5), 371–386. Kaura, V., Durga Prasad, C. S., & Sharma, S. (2015). Service quality, service convenience, price and fairness, customer loyalty, and the mediating role of customer satisfaction. International Journal of Bank Marketing, 33(4), 404–422. Khan, M. A. (2010). An empirical study of automated teller machine service quality and customer satisfaction in Pakistani banks. European Journal of Social Sciences, 13(3), 333–344. Kim, M., Kim, J. H., & Lennon, S. J. (2006). Online service attributes available on apparel retail web sites: An ES-QUAL approach. Managing Service Quality: An International Journal, 16(1), 51–77. King, W. R., & He, J. (2006). A meta-analysis of the technology acceptance model. Information & Management, 43(6), 740–755. Kumar, V. R., Lall, A., & Mane, T. (2017). Extending the TAM model: Intention of management students to use mobile banking: Evidence from India. Global Business Review. Retrieved from https://doi. org/10.1177/0972150916666991 Kumbhar, V. M. (2011). Factors affecting the customer satisfaction in e-banking: Some evidences form Indian banks. Management Research and practice, 3(4), 1–14. Lee, J., & Allaway, A. (2002). Effects of personal control on adoption of self-service technology innovations. Journal of Services Marketing, 16(6), 553–572. Lee, G. G., & Lin, H. F. (2005). Customer perceptions of e-service quality in online shopping. International Journal of Retail & Distribution Management, 33(2), 161–176. Aslam et al. 1177 Lin, J. S. C., & Chang, H. C. (2011). The role of technology readiness in self-service technology acceptance. Managing Service Quality: An International Journal, 21(4), 424–444. Lucas, H. C., Jr, Swanson, E. B., & Zmud, R. (2008). Implementation, innovation, and related themes over the years in information systems research. Journal of the Association for Information Systems, 8(4), 8. Makarem, S. C., Mudambi, S. M., & Podoshen, J. S. (2009). Satisfaction in technology-enabled service encounters. Journal of Services Marketing, 23(3), 134–144. Meng, F., Tepanon, Y., & Uysal, M. (2008). Measuring tourist satisfaction by attribute and motivation: The case of a nature-based resort. Journal of Vacation Marketing, 14(1), 41–56. Meuter, M. L., Ostrom, A. L., Roundtree, R. I., & Bitner, M. J. (2000). Self-service technologies: Understanding customer satisfaction with technology-based service encounters. Journal of Marketing, 64(3), 50–64. Mohammed, S. (2012). Factors affecting ATM usage in India: An empirical analysis. UTMS Journal of Economics, 3(1), 1. Molina, A., Martín-Consuegra, D., & Esteban, Á. (2007). Relational benefits and customer satisfaction in retail banking. International Journal of Bank Marketing, 25(4), 253–271. Narteh, B. (2013). Service quality in automated teller machines: An empirical investigation. Managing Service Quality: An International Journal, 23(1), 62–89. ———. (2015). Perceived service quality and satisfaction of self-service technology: The case of automated teller machines. International Journal of Quality & Reliability Management, 32(4), 361–380. Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 17(4), 460–469. Olorunniwo, F., Hsu, M. K., & Udo, G. J. (2006). Service quality, customer satisfaction, and behavioral intentions in the service factory. Journal of Services Marketing, 20(1), 59–72. Parasuraman, A. (2000). Technology Readiness Index (TRI) a multiple-item scale to measure readiness to embrace new technologies. Journal of service research, 2(4), 307–320. Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1988). SERVQUAL: A multiple item scale for measuring consumer perceptions of service quality. Journal of Retailing, 64(5), 21–40. Parasuraman, A., Zeithaml, V. A., & Malholtra, A. (2005). E-S-QUAL: A multiple-item scale for assessing electronic service quality. Journal of Service Research, 7(3), 213–235. Pikkarainen, T., Pikkarainen, K., Karjaluoto, H., & Pahnila, S. (2004). Consumer acceptance of online banking: An extension of the technology acceptance model. Internet Research, 14(3), 224–235. Proença, J. F., & Rodrigues, M. A. (2011). A comparison of users and non-users of banking self-service technology in Portugal. Managing Service Quality: An International Journal, 21(2), 192–210. Ribbink, D., Van Riel, A. C., Liljander, V., & Streukens, S. (2004). Comfort your online customer: Quality, trust and loyalty on the internet. Managing Service Quality: An International Journal, 14(6), 446–456. Robey, D. (1979). User attitudes and management information system use. Academy of Management Journal, 22(3), 527–538. Rod, M., Ashill, N. J., Shao, J., & Carruthers, J. (2009). An examination of the relationship between service quality dimensions, overall internet banking service quality and customer satisfaction: A New Zealand study. Marketing Intelligence & Planning, 27(1), 103–126. Sahi, G. K., & Gupta, S. (2013). Predicting customers’ behavioral intentions toward ATM services. Journal of Indian Business Research, 5(4), 251–270. Saleem, Z., & Rashid, K. (2011). Relationship between customer satisfaction and mobile banking adoption in Pakistan. International Journal of Trade, Economics and Finance, 2(6), 537. Santos, J. (2003). E-service quality: A model of virtual service quality dimensions. Managing Service Quality: An International Journal, 13(3), 233–246. Shachaf, P., Oltmann, S. M., & Horowitz, S. M. (2008). Service equality in virtual reference. Journal of the American Society for Information Science and Technology, 59(4), 535–550. Snellman, K., & Vihtkari, T. (2003). Customer complaining behaviour in technology-based service encounters. International Journal of Service Industry Management, 14(2), 217–231. 1178 Global Business Review 20(5) Stiakakis, E., & Georgiadis, C. K. (2009). E-service quality: Comparing the perceptions of providers and customers. Managing Service Quality: An International Journal, 19(4), 410–430. Sureshchandar, G. S., Rajendran, C., & Anantharaman, R. N. (2002). The relationship between service quality and customer satisfaction–a factor specific approach. Journal of Services Marketing, 16(4), 363–379. Wang, W., Butler, J. E., Hsieh, J. P. A., & Hsu, S. H. (2008). Innovate with complex information technologies: A theoretical model and empirical examination. Journal of Computer Information Systems, 49(1), 27–36. Wang, Y. S., Wang, Y. M., Lin, H. H., & Tang, T. I. (2003). Determinants of user acceptance of Internet banking: An empirical study. International Journal of Service Industry Management, 14(5), 501–519. Wolfinbarger, M., & Gilly, M. C. (2003). eTailQ: Dimensionalizing, measuring and predicting etail quality. Journal of Retailing, 79(3), 183–198. Wong, A., & Zhou, L. (2006). Determinants and outcomes of relationship quality: A conceptual model and empirical investigation. Journal of International Consumer Marketing, 18(3), 81–105. Wong, D. H., Rexha, N., & Phau, I. (2008). Re-examining traditional service quality in an e-banking era. International Journal of Bank Marketing, 26(7), 526–545. Wu, J., & Lederer, A. (2009). A meta-analysis of the role of environment-based voluntariness in information technology acceptance. MIS Quarterly, 33(2), 419–432. Zeithaml, V. A., Parasuraman, A., & Malhotra, A. (2002). Service quality delivery through web sites: A critical review of extant knowledge. Journal of the Academy of Marketing Science, 30(4), 362–375. Zhao, X., Mattila, A. S., & Eva Tao, L. S. (2008). The role of post-training self-efficacy in customers’ use of selfservice technologies. International Journal of Service Industry Management, 19(4), 492–505.