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Int. J. Human-Computer Studies 64 (2006) 926–938
www.elsevier.com/locate/ijhcs
Assessment of employees’ perceptions of servicequality and satisfaction with e-business
Jung-Yu Lai�
Institute of Electronic Commerce, College of Social Sciences and Management, National Chung Hsing University, No. 250, Kuo Kuang Rd.,
Taichung 402, Taiwan
Received 8 November 2005; received in revised form 21 February 2006; accepted 25 April 2006
Communicated by P. Pendharkar
Abstract
In a competitive environment of frequent and rapid change, electronic business (e-business), whose supply, production, and logistics
and distribution networks are enabled digitally, is increasingly dependent on electronic interconnections that are innovative in their
functionality. Conceivably, its ability to deliver functions and services is closely associated with and helpful for the completion of
employees’ tasks and jobs, leading to service quality being critically important for both the employees and e-business (EB). On the other
hand, since EB utilizes enterprise applications, user satisfaction, as a surrogate measure of information system (IS) or information
technology (IT) effectiveness/success is also important for enterprise applications success. Thus, this research attempts to extrapolate the
results of marketing research concerning customers’ perceptions of service quality and IS/IT research as to employees’ perceptions of
service quality with EB. First, we revise the SERVQUAL instrument to fit the new context of EB and measure employees’ perceived
service quality with EB. Based on a survey of 161 respondents practicing mostly in seven international electronic businesses in Taiwan, a
13-item EB-SERVQUAL instrument is proposed. This can be used to improve and diagnose the service quality of EB. Second, we
examine user satisfaction with enterprise applications and its causal link in relation to service quality with EB. The instrument and our
findings in this paper will be valuable to researchers and practitioners interested in designing, implementing, and managing EB.
r 2006 Elsevier Ltd. All rights reserved.
Keywords: E-business; Enterprise applications; Service quality; User satisfaction
1. Introduction
E-business (EB), an enterprise with the capability ofexchanging values (goods, services, money, and knowledge)digitally via a computer network (Hackbarth and Kettinger,2000; Jones et al., 2000), uses distributed informationtechnology (IT), knowledge management, and trust mechan-isms to transform key business processes and relationships withcustomers, suppliers, employees, business partners, regulatoryparties, and communities (Craig and Jutla, 2001). It is not onlyrapidly changing the way that companies buy, sell, and dealwith customers, but also changing the relationships with itsemployees (Abu-Musa, 2004). Apparently, the ability of an EBto deliver functions and services is closely associated with
e front matter r 2006 Elsevier Ltd. All rights reserved.
cs.2006.04.007
35 697208; fax: +886 4 22859497.
ess: [email protected].
completion of employees’ jobs and tasks. Conceivably, servicequality is important for the success of EB.A substantial body of research has focused on the
outcome of the service, i.e. the customers’ perceptions ofservice quality (Brown et al., 1993; Fisk et al., 1993; Teas,1993a, b; Deveraj et al., 2002; Zeithaml et al., 2002). Also, aheavy relevance of internal customers within the context ofthe service delivery process is frequently referred to in theliterature of marketers and organizational behaviourists(Berry and Parasuraman, 1992; Reynoso and Moores,1995; Finn et al., 1996). Unfortunately, there is a paucity ofpublished research on the staff perspective, especially forthe relationship between employees and EB. On the otherhand, an EB utilizes enterprise applications1 for doing
1Enterprise applications refer to systems that can coordinate activities,
decisions, and knowledge across many different functions, levels, and
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business that involves connectivity, transparency, sharing,and integration and has heralded many new opportunities forexpansion and enhancement of their markets, as well as theextension and broadening of their supply chains. Usersatisfaction, a surrogate measure of IS/IT effectiveness/success (Bailey and Pearson, 1983; Raymond, 1985; Dolland Torkzadeh, 1988; Melone, 1990; Klenke, 1992), seems tobe a critical factor for the success of enterprise applications.Thus, there exists a need to better understand service qualityof EB and user satisfaction with enterprise applications.
SERVAUAL, an instrument developed by marketingacademics (Parasuraman et al., 1985, 1988, 1991, 1993), ismodified and appropriate for measuring IS service qualityin prior studies (Kettinger and Lee, 1994; Kettinger et al.,1995; Pitt et al., 1995, 1997, 1998; Jiang et al., 2002). Thus,this paper aims to adapt and refine the original SERVQ-UAL to fit the EB context for assessing employees’ perceivedservice quality of EB. Additionally, user satisfaction withenterprise applications and its relationship with servicequality are also evaluated. From these analyses, severallessons are learned to guide and provide practitioners withmore insights as to how to improve service quality and usersatisfaction for employees. It was, therefore, decided toexplore the nature and characteristics of interdepartmentalrelationships in relation to the employees’ perceived servicequality of EB in addition to user satisfaction with enterpriseapplications. In what follows, significant arguments ofvarious studies on service quality are reviewed and discussed,particularly demonstrating that the original SERVQUALinstrument should be revised and refined to fit the EB context.This will be followed by a description of how important therole of employees’ perceived service quality is in the EBcontext. The following sections and various subsectionsdescribe the measurement of service quality with EB anduser satisfaction with enterprise applications and the stepsinvolved in scale adoption, refinement, and validation. Next,we examine whether there exists a causal relationship betweenservice quality with EB and user satisfaction with enterpriseapplications. The final section discusses applications andimplications for management.
2. Domain of service quality and user satisfaction within EB
2.1. The role that employees’ perceptions of service quality
plays in EB
In associating customer service affairs with organiza-tional matter, there are several contributions related todifferent kinds of services. For example, Edvardsson (1988)worked on aspects related to service development andservice design in mechanical engineering companies. Other
(footnote continued)
business units in a firm, including enterprise resource planning systems
(ERPS), supply chain management systems (SCMS), customer relation-
ship management systems (CRMS), knowledge management systems
(KMS), etc. (Kalakota and Robison, 2001; Laudon and Laudon, 2004).
authors emphasized the importance of the productionsystem that supports the encounters with the customer(Shostack, 1984, 1987). Due to the internal interactionswhich inevitably occur between departments in anycompany, organizational dynamics are of particularrelevance for both service production and its delivery(Reynoso and Moores, 1995). The concept of the internalcustomer, evolved originally through the idea of sellingjobs with the purpose of making the job more attractive forthe employees in the service sector (Sasser and Arbeit,1976), has been subsequently addressed in wider terms asinternal marketing by a number of researchers (Berry,1981; Parasuraman and Grewal, 2000; Colby and Para-suraman, 2003). Berry and Parasuraman (1992) pointedout that internal marketing is essential to service marketingsuccess, and it also attracts, develops, motivates, andretains the qualified employees’ excellent service deliverydemands. Later, because of the rapid infusion of technol-ogy into the process through which products and servicesare purchased and consumed, Parasuraman (2000) stressedthe pyramid model which incorporates technology as a newdimension into the two-dimensional triangle model andhighlights three new links (company–technology, techno-logy–employee, and technology–customer) that need to bemanaged well in order to maximize marketing effective-ness. EB, a dynamic set of technologies (e.g., enterpriseapplications), employees (internal customers), and businessprocesses that link companies, customers, and communitiesthrough the electronic exchange of goods, services,transaction, and information (Kalakota and Robison,2001; Chen and Ching, 2002; Abu-Musa, 2004; Laudonand Laudon, 2004), will herald service quality, delivered byEB and perceived by internal customers (herein referred asemployee), plays an increasingly larger role in EB, and hasbecome an increasingly critical issue for technologyimplementation and management.Employee research is as important to service quality
management in EB contexts as customer research is toservice sectors for the following reasons. First, employeesare themselves customers of internal service, and thus arethe only people who can assess internal service quality(Berry and Parasuraman, 1994). Because internal servicequality affects external service quality, measuring internalservice quality is essential. Second, employees can offerinsight into conditions that reduce service quality in anorganization. Employees experience the company’s servicedelivery system day after day. They see more thancustomers see and they see it from a different angle.Employee research helps reveal why service problemsoccur, and what companies might do to solve theseproblems. Third, employee research serves as an earlywarning system. Because of employees’ more intensiveexposure to the service delivery system, they often see thesystem breaking down before customers do (Berry andParasuraman, 1994). Fourth, competencies may be locatedin the knowledge and skills of key employees; it can be lostif employees leave the firm (King et al., 2001). This is
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crucially important for EB in knowledge-based economyowing to its high competitiveness. Fifth, EB is a dynamicset of technologies, applications, and business processes.The relationships with respect to employee–company,employee–technology, and employee–customer (Parasura-man, 2000; Parasuraman and Grewal, 2000; Zeithamlet al., 2002; Colby and Parasuraman, 2003) has shown thatthe role the employee plays in EB is very crucial. Thus,these cause a need to understand and manage employees’perceptions of service quality with EB.
2.2. Overview of SERVQUAL research
The customers’ perceptions of service quality havereceived fairly extensive attention from researchers andpractitioners. Based on exploratory research from market-ing academics, PZB (Parasuraman et al., 1985) first definedservice quality as the degree of discrepancy betweencustomers’ normative expectation for the service and theirperceptions of service performance. Subsequently,SERVQUAL, a 22-item scale for measuring service qualityis comprised of five dimensions: reliability, responsiveness,assurance, empathy, and tangibles, was empirically devel-oped and validated by PZB (Parasuraman et al., 1988).SERVQUAL which operationalizes service quality bysubtracting customers’ expectation scores from theirperception scores on the 22 items (P-E) has beenproductively used as the theoretical basis for manyempirical studies for measuring customers’ perceptions ofservice quality (Brown et al., 1993; Fisk et al., 1993; Teas,1993a, b; Deveraj et al., 2002; Zeithaml et al., 2002).Furthermore, PBZ (Parasuraman et al., 1991) indicatedthat the SERVQUAL instrument could be revised andrefined slightly to fit a wide range of contexts with its intactbasic content, structure, and length. Later, IS-adaptedSERVQUAL modified and refined by Kettinger and Lee(1994) was proposed for measuring employees’ perceivedservice quality with information systems functions (ISF)and has stimulated broad discussion among IS/ITresearchers (Kettinger and Lee, 1994; Kettinger et al.,1995; Pitt et al., 1995, 1997, 1998; Jiang et al., 2002).Recently, it has been applied in variety contexts, includingphysicians in privacy practice (Brown and Swartz, 1989),university (Kettinger and Lee, 1994; Kettinger et al., 1995),web service (Aladwani and Palvia, 2002; Li et al., 2002;Zeithaml et al., 2002), and electronic commerce(e-commerce) (Aladwani and Palvia, 2002; Deveraj et al.,2002; Li et al., 2002). Although the SERVQUAL instru-ment has stimulated debates concerning dimensionality(Carman, 1990; Finn et al., 1996), the need to measureexpectations (Babakus and Boller, 1992; Cronin andTaylor, 1992, 1994), the reliability and validity ofdifference-score formulation (Babakus and Boller, 1992;Brown et al., 1993), and the interpretation and operatio-nalization of expectations (Teas, 1993a, b, 1994). However,developers have presented counterarguments, clarifica-tions, and additional evidence to reaffirm the instrument’s
psychometric soundness and practical value for these issues(Parasuraman et al., 1991, 1993, 1994). Undoubtedly,SERVQUAL, with modification and refinement, is appro-priately applied in measuring employees’ perceived servicequality with EB.Jointly, this preliminary literature reviewed earlier
illustrates the fact that employees’ perceptions of servicequality are critically important for the success of EB.However, the construct lacks an appropriate operationa-lization and its measurement is still in infancy. With thisbackground, we extrapolate prior results related tomarketing research in the new context of EBand act on modifying, validating, and refining originalSERVQUAL to form an EB-SERVQUAL instrument formeasuring employees’ perceptions of service quality withEB.
2.3. User satisfaction and its relationship with service
quality
User information satisfaction (UIS) is defined as theextent to which users believe that the information system(IS) available to them meets their information requirements(Ives et al., 1983). The most frequently used instrument forcomputer user satisfaction (CUS) was developed by Baileyand Pearson (1983), who identified a list of 39 factors. Theinstrument was re-evaluated and refined by Ives et al.(1983), and later again by Baroudi and Orlikowski (1988).This resulted in a shortened list of 13 items, which can bebroadly grouped into three main dimensions: ‘‘informationproduct,’’ ‘‘EDP staff and services,’’ and ‘‘knowledge andinvolvement.’’ On the other hand, Doll and Torkzadeh(1988) developed a 12-item instrument comprising fivefactors for measuring end-user computing satisfaction(EUCS): content, accuracy, format, ease of use, andtimeliness. This EUCS instrument was a synthesis of theIves et al.’s (1983) measure of UIS, which is a widely used,well-validated generalized instrument (Doll and Torkza-deh, 1988; Doll et al., 1994, 1995). UIS is often used as asurrogate measure of management information systems(MIS) success/effectiveness (Bailey and Pearson, 1983;Raymond, 1985; Doll and Torkzadeh, 1988; Klenke,1992; Melone, 1990) and is related to other importantconstructs in systems analysis and design. EB alwaysimplements enterprise applications for doing business.Hence, user satisfaction with enterprise applications iscritically important for EB since enterprise applicationsconsists of complex IS/IT.As to the relationship between service quality and user
satisfaction, Pitt et al. (1995) suggested that service qualityprovides a superior indicator of user satisfaction andindicated that service quality can influence user satisfactionirrespective of whether a user interacts with one or multipleIS. This argument was supported by the revised IS successmodel (DeLone and McLean, 2003). In the revised D&MIS success model, quality has three major dimensions:information quality, systems quality, and service quality.
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Each should be measured—or controlled for—separately,because singularly or jointly, they will affect subsequentuser satisfaction (DeLone and McLean, 2003). Addition-ally, the link between service quality and customersatisfaction is also well established in the marketingliterature (Dabholkar, 1995; Dabholkar et al., 2000;Parasuraman and Grewal, 2000). It also partially sup-ported in the EC context (Deveraj et al., 2002). Therefore,this study attempts to explore user satisfaction withenterprise applications and its relationship with servicequality in addition to measuring service quality with EBand hypothesizes:
H1. Service quality with EB is associated with usersatisfaction with enterprise applications.
H2. A higher level of service quality with EB will lead to ahigher level of user satisfaction with enterprise applica-tions.
3. Measurement of service quality and user satisfaction
within EB
3.1. Modification of SERVQUAL within EB contexts
Zeithaml et al. (1990) claimed that SERVQUAL, withappropriate adaptation, can be used by department anddivisions within a company to ascertain the service qualitythey provide to employees in other departments anddivisions. This requires some efforts to refine SERVQUALfor measuring the employees’ perceptions of service qualitywith EB. Thus, we made several modifications. First, thefirst question was originally asked in terms of ‘‘up-to-dateequipment,’’ and later was reworded to ‘‘up-to-datehardware and software.’’ Because hardware and softwarecannot accurately reflect the dynamic set of applications,technologies, processes in EB. Hence, we changed thewording of the first question into ‘‘up-to-date informationtechnology.’’ Second, being innovative in attempting totreat employees with assurance means creating new ways ofbuilding trust and loyalty, lowering the costs of doingbusiness, increasing flexibility and opportunities for newtraining, improving employee care plans, and implement-ing aggressive reward systems. Hence, we changed thewording of the 15th question into ‘‘makes employees feelsafe when interacting with company,’’ the 16th questioninto ‘‘company will be consistently courteous with employ-ees,’’ and the 19th question into ‘‘provide convenientworking hours to employees.’’ Third, the rising popularityof the mobile workforce not only addresses employees’needs for flexibility but also reduces overhead costs, allowsemployees to work more hours at home and the road, andmost importantly is a good way to retain employees (Craigand Jutla, 2001), the 20th question was reworded into‘‘gives employees personal attention.’’ Finally, employeesrated managers on issues such as whether they discussed
work priorities, appreciated extra effort, and were visible(Berry and Parasuraman, 1994). Hence, we changed thewording of the 14th question into ‘‘makes employeesconfident with company.’’Minor wording adjustments were made in a few items to
clarify them in the EB context. Finally, the EB-adaptedSERVQUAL instrument was proposed and pre-testedthrough a serious of interviews with manager positions ofEB, doctoral students, and professors specializing in EB.Additional wording adjustments were made followingcareful examination of the results of pre-testing. The EB-adapted SERVQUAL instrument consists of two sections.The expected service section measures an employee’sexpected service level by using the 22 expected items andthe perceived section measures an employee’s perceivedlevel by using the 22 perceived items (Appendix A lists allthe expected and perceived items). The resulting gap scoreswere obtained by subtracting the 22 expected items fromthe 22 perceived items (P-E). All the respondents wereasked to rate each item on a five-point Likert scaleanchored from strongly disagree (1) to stronglyagree (5).
3.2. Development of user satisfaction with enterprise
applications
Instruments that assess both general UIS (Bailey andPearson, 1983; Ives et al., 1983), and application-specificUIS (Bailey and Pearson, 1983; Palvia, 1996; Piccoli et al.,2001), or EUCS (Doll and Torkzadeh, 1988), are widelyused by researchers. As a surrogate measure of ISsuccess in computing environments, user satisfaction hasbeen a heavily researched topic (e.g., Bailey andPearson, 1983; Ives et al., 1983; Palvia, 1996; Piccoli etal., 2001) and is perhaps the most widely used measureamong many assessments of IS success/effectiveness(DeLone and McLean, 2003). Thus, the user satisfactioninstrument is applicable for measuring user satisfactionwith enterprise applications (USEA). Two majorvariables, one is content (a key component of informationquality) and the other is ease of use (an importantcomponent of system quality), adapted from Doll andTorkzadeh’s inventory (1988) were modified tomeasure user satisfaction with enterprise applications.Also, since enterprise applications consist of complexIS/IT. Enterprise applications being reliable, predictable,and satisfying user needs will allow employees to feel asense of immediate gratification. Dependability, defined asthe ability to deliver functions and services that canjustifiably be relied on by users, is proposed in this studyand it is speculated that it will affect user satisfaction.Finally, two items measuring overall satisfaction weredeveloped by this study. Hence, the USEA instrument waspresented and all the items used in this study are listed inAppendix B.
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Table 1
Enterprise applications implemented in each e-business
TSMC UMC AUO CMO MXIC ASE
ERPS | | | | | |SCMS | | | | | |CRMS | | |KMS | | | | | |EIP | | | | | |
| The system implemented.
J.-Y. Lai / Int. J. Human-Computer Studies 64 (2006) 926–938930
4. Data sampling and model testing
4.1. Data collection and profiles
Data used in this paper were obtained from 161respondents mostly employed in six international semi-conductor manufacturing companies in Taiwan, includingthe Taiwan Semiconductor Manufacturing Corporation(TSMC), United Microelectronics Corporation (UMC),AU Optronics Corporation (AUO), Advanced Semicon-ductor Engineering Inc. (ASE), Chi-Mei OptoelectronicsCorporation (CMO), and Macronix International(MXIC). TSMC and UMC are the world’s top twodedicated semiconductor foundries. TSMC’s revenuesrepresent some 60% of the global foundry market share.It employed over 15,000 people worldwide and had a salesvolume greater than US$6.8 billion in 2004. UMCemployed over 10,500 people worldwide and had a salesvolume exceeding US$3.5 billion in 2004. AUO is Taiwan’slargest and the world’s third largest manufacturer of large-sized thin film transistor liquid crystal display panels (TFT-LCD). By the end of 2004, AUO had generated over US$5billion in sales revenues and now houses over 20,000employees throughout its global operations spreadingacross Taiwan, USA, Japan, Europe, South Korea, andChina. CMO is now one of the few important suppliers oflarge-sized LCD panels. It currently has 13,000 employeesand had a sales volume of over US$2.4 billion in 2004. ASEis the world’s largest independent providers of semicon-ductor packaging and testing services. It currently has24,000 employees worldwide and had a sales volumegreater than US$1.3 billon in 2004. MXIC is a semicon-ductor manufacturing company. It is an emerging inte-grated solutions provider for high-quality consumer-basedproducts worldwide utilizing non-volatile memory andother technologies. MXIC had over 3700 employees andgenerated a sales volume of over US$0.68 billion in 2004.
Each company has implemented their own enterpriseapplications. For instance, TSMC not only integratesERPS with manufacturing executive system (MES) andcomputer integrated manufacturing (CIM) systems, butalso links CRMS and SCMS together. As to CRM, TSMCsatisfies customers by means of TSMC-Online, TSMC-Direct, and TSMC-YES. TSMC-Online provides custo-mers real-time visibility of orders, work-in-process (WIP)materials, and shipping status in the production cycles. Italso helps customers place orders, review technicaldocumentation, and submit a general query anytime fromanywhere. TSMC-Direct is an integrated enterprise serviceon the Internet and allows customers to participate in themanufacturing processes until their orders are completed.In addition, it connects TSMC with vendors in supplychains. This enables collaboration and data sharing amongdownstream and upstream partners and reduces cycle timeof process design, simulating a customer-owned foundryand improving yield rate. In TSMC, in addition toenterprise systems (e.g., ERPS, SCMS, etc), there are
many systems helping employees in their completion ofwork. First, myTSMC is an integrated portal for employ-ees to access any resources they needed on intranet. UsingmyTSMC, employees can access engineering data andanalysed reports. Second, employees can retrieve valuableinformation and knowledge from KM repositories. Thiscan stimulate learning and sharing among employees andenable organizational learning. All the focal systems ofenterprise applications implemented in each firm aresummarized in Table 1.For each question, respondents were asked to circle the
response which best described their level of agreement withthe statements. Of the 250 surveys, 161 useful responseswere returned and thus the response rate was 63.4 percent.The respondents averaged 31.5 years in age and had 11.1years of experience in computer; the male-to-female ratiowas approximately 2.7 to 1. Fifty-six percent hadcompleted only one college or university degree; a further41 percent had completed postgraduate degrees.
4.2. Refinement of EB-adapted SERVQUAL
First, second-order confirmatory factor analysis (CFA)was used to achieve strong reliability and validity becausethe measurement model provides a reasonably goodapproximation with reality. The higher-order confirmatoryfactor analysis can be regarded as an extension of asubsequent common factor with oblique rotations, that is,correlations among the obtained factors from a first factoranalysis are entered into a second factor analysis toexamine the possibility of second-order factors (Marshand Hocevar, 1985, 1988). Here, we hypothesize that EB-adapted SERVQUAL is a second-order construct govern-ing the correlations among factors such as tangibles,reliability, responsiveness, assurance, and empathy. For asense of comparison, the gap scores of initial and EB-adapted SERVQUAL measures were subjected to second-order CFA using the CALIS procedure of SAS 8.1, aprocedure that provides estimates of parameters and testsof fit, similar to LISREL.Then, MacCallum’s (1986) and Anderson and Gerbing’s
(1988) guidelines are applied in a specification searchprocess to find a proper level of model fit. After examiningsquared multiple correlations (SMC), standardized resi-duals, and t-values, nine items (items 1–4, 9, 10, 16, 18, 19)
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Fig. 1. Four first-order factors and one second-order factor analysis for EB-SERVQUAL.
Table 2
Goodness-of-fit measures of the research model
Goodness-of-fit measure Threshold Model
Initial Refined
Chi-square/degree of freedom p3.00 2.12 1.57
Goodness-of-fit index (GFI) X0.90 0.81 0.93
Adjusted goodness-of-fit index (AGFI) X0.80 0.76 0.88
Normed fit index (NFI) X0.90 0.81 0.94
Non-normed fit index (NNFI) X0.90 0.87 0.97
Comparative fit index (CFI) X0.90 0.89 0.98
Root mean square residual (RMSR) p0.10 0.06 0.03
J.-Y. Lai / Int. J. Human-Computer Studies 64 (2006) 926–938 931
with lower than 0.5 of SMC were dropped to form therefined model. All the SMC of each remaining item satisfythe recommended level in the refined model (Fig. 1).Additionally, seven common goodness-of-fit indices usedto assess the adequate fit of the data are above therecommended value, suggesting a good fit with the data.Contrarily, the original model does not meet the threshold(Table 2).
Next, convergent validity was evaluated for the refinedmodel according to three criteria recommended by Fornelland Larcker (1981). (1) All indicator factor loadings (l)
should be significant, (2) Construct reliability in terms ofcomposite reliability (CR notated as r), internal consis-tency on the indicators measuring given factor, shouldexceed 0.80. CR is computed by taking the square of sumsfor standardized factor loadings divided by the square ofsums for standardized factor loadings and sums for errorvariance. (3) The average variance extracted (AVE) of eachconstruct should exceed 0.50. It assesses the amount ofvariance that is captured by the underlying factor inrelation to the amount of variance due to measurementerror. Following the calculations, the results show that thel-values for all items were significant at pp0:001, thecomposite reliability of each factor was: reliability ¼ 0.91;responsiveness ¼ 0.89; assurance ¼ 0.84; and empathy¼ 0.82, and all the AVE of each factor were higher than0.5, suggesting good reliability and convergent validity(Table 3).Additionally, the Cronbach’s alpha coefficient for each
factor was: reliability ¼ 0.88; responsiveness ¼ 0.87;assurance ¼ 0.84; and empathy ¼ 0.82. Then, multipleregression analysis with forward stepwise method for thesefactors with summed score of them are also examined andillustrated in Table 4. The ASS variable is more closelyrelated to the other variables, thus only three of them areselected in the final regression model.
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Table 3
Reliability of dimensions of refined EB-adapted SERVQUAL
Construct Composite reliability (r) Average variance extracted (AVE) Cronbach’s alpha
Reliability (REL) 0.91 0.72 0.88
Responsiveness (RES) 0.90 0.74 0.87
Assurance (ASS) 0.88 0.71 0.84
Empathy (EMP) 0.84 0.63 0.82
Table 4
Multiple regression analysis for refined EB-adapted SERVQUAL vari-
ables
Parameter estimate VIF t-value
REL 0.41��� 1.94 22.08
RES 0.38��� 2.14 19.39
EMP 0.35��� 1.77 19.58
VIF means variance inflation factor.���po0.001.
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Finally, average variance extracted is used to evaluatediscriminant validity (Fornell and Larcker, 1981). Forsatisfying the requirement for adequate discriminantvalidity, AVE must exceed g2 (squared canonical correla-tion) for all factors. Unlike the approach of Campbell andFiske (1959), this criterion is associated with modelparameters and recognizes that the measurement errorcan vary in magnitude across a set of methods (i.e.,indicators of constructs). As shown in Fig. 1, the resultssatisfy the requirement. Jointly, these suggest adequateconvergent and discriminant validity of the measurement.Thus, a validated refined EB-adapted SERVQUAL (EB-SERVQUAL) is proposed in this study.
4.3. Confirmatory analysis for USEA
CFA is used again to test one second-order USEA factorand its three one-order factors model. The results are: (1)seven common goodness-of-fit indexes (chi-square/degrees of freedom ¼ 1.13, GFI ¼ 0.98, AGFI ¼ 0.93,NFI ¼ 0.96, NNFI ¼ 0.99, CFI ¼ 0.99, RMSR ¼ 0.02)are above the recommended value; (2) all the coefficientsl and g are significant at po0:001, showing a good fit of thedata (Fig. 2); (3) multiple regression analysis with forwardstepwise method for USEA variables with overall usersatisfaction are also evaluated. As illustrated in Table 5, allthree variables are significant antecedents and ease of useplays the most important role in influencing overall usersatisfaction.
4.4. Relationship between EB- SERVQUAL and USEA
Based on the results described in Fig. 3, the correlationcoefficient between second-order EB-SERVQUAL and
USEA latent factor is significant at po0:01 (j ¼ 0:24).The results of this combined model also showadequate fit of the data. The seven common goodness-of-fit indexes were chi-square/degrees of freedom ¼ 1.36,GFI ¼ 0.89, AGFI ¼ 0.85, NFI ¼ 0.88, NNFI ¼ 0.96,CFI ¼ 0.96, and RMSR ¼ 0.03. These results support thecontention that service quality with EB is significantlyassociated with user satisfaction with enterprise applica-tions. Furthermore, the correlation coefficients betweenUSEAF and EB-SERVQUAL variables are evaluated. Assummarized in Table 6, some relations are statisticallystrong while others are not. These partially support that ahigher level of service quality with EB leads to a higherlevel of user satisfaction with enterprise applications.Hence, H1 is supported; nevertheless, H2 is partiallysupported.
5. Discussion and implications
Consistent with previous results on IS-adapted SERVQ-UAL (Kettinger and Lee, 1994; Jiang et al., 2002), fouritems were in complete deletion of the tangibles dimensiondue to their low reliability. This indicates that the tangiblesdimension is less relevant to employees’ perceptions ofservice quality with EB. Additionally, REL seems to havethe biggest influence on the summed score of EB-SERVQUAL based on the results of multiple regressionanalysis. We believe that the employee, a ‘‘pragmatic’’internal customer, will not be pleased by neat-appealing,up-to-date, and the excellent ‘‘appearance’’ of facilities.Contrarily, reliable service delivered by EB is the mostsignificant determinant. This implies that various support-ing departments (e.g., human resource, finance, purchase,IT) should keep internal customers (i.e., employees) inmind and provide good service for them at the right time inright place.Ease of use, an essential element of user satisfaction and
system quality, is indeed found to be the most significantfactor for USEA. It is critically important for enterpriseapplications because of their complex functions like: (1)retrieving diverse information. Information is stored indifferent repositories at different locations, it is challengingfor employees to search/retrieve the ‘‘right’’ information atthe ‘‘right’’ time in the ‘‘right’’ location; (2) collaborationamong interested groups. There is a need to encouragecollaboration in order to maximize the synthesis effects of
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Table 5
Multiple regression analysis with USEA variables with overall user
satisfaction
Parameter estimate VIF t-value
Content 0.27��� 1.39 3.66
Dependability 0.20�� 1.53 2.59
Ease of use 0.30��� 1.41 4.08
��po0.01.���po0.001.
Fig. 2. Three first-order factors and one second-order factor analysis for USEA.
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employees’ efforts and avoid complications due toenterprise applications’ complexity; (3) different kinds ofservice. Employees need enterprise applications to providedifferent kinds of service for daily jobs and tasks throughdifferent systems. Ease of use is a good way of makingcomplex interfaces transparent among systems through anintegrated service window with a single and simplemechanism.
According to Teas’s (1994) suggestions as well as Croninand Taylor’s (1992) findings, service quality appears to anantecedent of user satisfaction in the service marketingarea. Although DeLone and McLean (2003) suggest thatservice quality has a positive effect on user satisfaction,little evidence exists to support this causal link. Like priorresults on IS/IT research (Kettinger and Lee, 1994; Jiang etal., 2002), we only provide partial evidence for this causalrelationship in an EB context. Even so, we believe that EB-SERVQUAL has a positive influence on USEAF andsuggest that REL variable is the most significant ante-cedent of USEAF compared to other variables of EB-SERVQUAL.
6. Conclusions
SERVQUAL has demonstrated value as a diagnostic toolfor improving service quality in marketing or informationcontexts. The purpose of this research is to extrapolate theserelated results in the new context of EB and aims to develop avalidated and reliable EB-SERVQUAL instrument formeasuring employees’ perceptions of service quality withEB. We also partially support the causal relationship betweenservice quality with EB and user satisfaction with enterpriseapplications. These results and findings not only helppractitioners to improve service quality, but also providetheoretical foundations for future research.The major contributions of this paper are:
(1)
This study provides a confirmatory model describingthe primary dimensions of employees’ perceived servicequality with EB, i.e. reliability, responsiveness, assur-ance, and empathy. We also encourage practitionersand researchers to use it as a common framework foranalysing and comparing four variables and servicequality across several departments, businesses, andindustries.(2)
Following a variety of statistical tests presented toshow good reliability and validity of the scales, an EB-SERVQUAL instrument for measuring employees’perceived service quality with EB was successfullydeveloped.(3)
Among the four variables of EB-SERQUAL, reliabilityseems to have the most influence on service quality anduser satisfaction. This is very important for improvingservice quality.(4)
Although the proposition that higher level of servicequality leads to higher level of user satisfaction is only
ARTICLE IN PRESS
Fig. 3. Combined confirmatory factor analysis for EB-SERVQAL and USEA.
Table 6
Correlation coefficients between USEA and EB-SERVQUAL variables
Reliability Responsiveness Assurance Empathy
Content 0.07 0.06 0.10 0.08
Dependability 0.09 0.22�� 0.10 0.12
Ease of use 0.22�� 0.15 0.20� 0.12
Overall USEAF 0.19* 0.15 0.13 0.10
�po0.05.��po0.01
J.-Y. Lai / Int. J. Human-Computer Studies 64 (2006) 926–938934
partially proved, we suggest that practitioners canimprove user satisfaction by increasing servicequality.
(5)
Ease of use is the most important antecedent of overalluser satisfaction. User-friendliness is also important forthe success of enterprise applications and will increaseemployees’ perceptions of satisfaction.(6)
Content has a significant effect on user satisfaction withenterprise applications, so they must maximize theirusefulness by providing useful, integral, up-to-date, andconsistent information and knowledge to attract ‘prag-matic’ employees to get potential gains.(7)
Dependability was found to be a significant factorfor user satisfaction. Employees with higher depend-ability have higher perceptions of user satis-faction, which contribute to enterprise applicationssuccess.
ARTICLE IN PRESSJ.-Y. Lai / Int. J. Human-Computer Studies 64 (2006) 926–938 935
Appendix A. The initial EB-adapted SERVQUAL instrument
Expected service Section
Directions: The purpose of this study is to obtain a better understanding of an employee’s expected and perceived serviceprovided by EB. There are two sections in this survey. In this expected service section, we would like to deal with youropinions on the service delivered by an ‘‘excellent’’ EB. Based on your experiences as an employee, please think about thekind of excellent EB that will deliver excellent service. Please indicate the extent to which you think such EB will possess thefeature described by each statement. If you strongly agree that a feature is absolutely essential for an excellent EB, circle 5.Contrarily, if you strongly disagree that a feature is essential for an excellent EB, circle 1. If your feeling is less strong, circleone of the numbers in the middle.
Strongly
disagree
Strongly agree
Tangibles
E1.
An excellent EB will have up-to-date IT. 1 2 3 4 5E2.
The physical facilities of an excellent EB willbe visually appealing.
1
2 3 4 5E3.
Employees of an excellent EB will be neat-appealing.
1
2 3 4 5E4.
The appearance of the physical facilities ofan excellent EB will be in keeping with the
kinds of services provided.
1
2 3 4 5Reliability
E5.
When an excellent EB promises to dosomething by a certain time, it will do so.
1
2 3 4 5E6.
When employees have a problem, anexcellent EB will show a sincere interest in
solving it.
1
2 3 4 5E7.
An excellent EB will perform the serviceright the first time for employees.
1
2 3 4 5E8.
An excellent EB will provide their servicesfor employees at the time it promises to do
so.
1
2 3 4 5E9.
An excellent EB will insist on error-freehardware and software.
1
2 3 4 5Responsiveness
E10.
An excellent EB will tell employees exactlywhen services will be performed.
1
2 3 4 5E11.
An excellent EB will give prompt services toemployees.
1
2 3 4 5E12.
An excellent EB will always be willing to helpemployees.
1
2 3 4 5E13.
An excellent EB will never be too busy torespond to employees’ requests.
1
2 3 4 5Assurance
E14.
The behaviour of an excellent EB will instillconfidence in employees.
1
2 3 4 5E15.
Employees will feel safe when interactingwith an excellent e -business.
1
2 3 4 5E16.
An excellent EB will be consistentlycourteous with employees.
1
2 3 4 5E17.
An excellent EB will have the knowledge toanswer employees’ questions
1
2 3 4 5Empathy
E18.
An excellent EB will give employeesindividual attention.
1
2 3 4 5
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E19.
An excellent EB will provide convenientworking hours to employees.
1
2 3 4 5E20.
An excellent EB will give employees personalattention.
1
2 3 4 5E21.
An excellent EB will have employees’ bestinterests at heart.
1
2 3 4 5E22.
An excellent EB will understand employees’specific needs.
1
2 3 4 5Perceived service section
Directions: The following statements relate to your feelings about ABC EB (your own company). For each statement,please show the extent to which you believe your EB has the feature described by the statement. Once again, circling 5means that you strongly agree, and circling 1 means that you strongly disagree. You may circle any of the numbers in themiddle that show how strong your feelings are.
Strongly
disagree
Strongly
agree
Tangibles
P1.
ABC has up-to-date IT. 1 2 3 4 5P2.
The physical facilities at ABC are visuallyappealing.
1
2 3 4 5P3.
Employees of ABC are neat-appealing. 1 2 3 4 5P4.
The appearance of the physical facilities of ABC isin keeping with the kinds of services provided.
1
2 3 4 5Reliability
P5.
When ABC promises you to do something by acertain time, it does so.
1
2 3 4 5P6.
When you have a problem, ABC shows a sincereinterest in solving it.
1
2 3 4 5P7.
ABC performs the service right the first time foryou.
1
2 3 4 5P8.
ABC provides its services to you at the time itpromises to do so.
1
2 3 4 5P9.
ABC insists on error-free hardware and software. 1 2 3 4 5Responsiveness
P10.
ABC tells you exactly when services will beperformed.
1
2 3 4 5P11.
ABC gives prompt services to you. 1 2 3 4 5P12.
ABC is always willing to help you. 1 2 3 4 5E13.
ABC is never too busy to respond to yourrequests.
1
2 3 4 5Assurance
P14.
The behaviour of ABC instills confidence in you. 1 2 3 4 5P15.
You feel safe when interacting with ABC. 1 2 3 4 5P16.
ABC is consistently courteous with you. 1 2 3 4 5P17.
ABC has the knowledge to answer your questions. 1 2 3 4 5Empathy
P18.
ABC gives you individual attention. 1 2 3 4 5P19.
ABC has convenient working hours for you. 1 2 3 4 5P20.
ABC gives you personal attention. 1 2 3 4 5P21.
ABC has your best interests at heart. 1 2 3 4 5P22.
ABC understands your specific needs. 1 2 3 4 5
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Appendix B. User satisfaction instrument
Content
C1 Enterprise applications provide correct content. C2 Enterprise applications provide consistent content. C3 Enterprise applications provide useful content.Dependability
D1 Enterprise applications are reliable. D2 Enterprise applications are predictable. D2 Enterprise applications satisfy what the user needs.Ease of use
E1 Enterprise applications are user friendly. E2 Enterprise applications are easy to use.Overall user satisfaction
O1 As a whole, enterprise applications are successful. O2 As a whole, I am satisfied with enterprise applications.References
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Jung-Yu Lai is an assistant professor in the Institute of Electronic
Commerce at National Chung Hsing University (NCHU) in Taiwan. He
received his Ph.D. from the Department of Information Management at
the National Taiwan University (NTU). He was previously a senior
software engineer at the United Microelectronics Corporation (UMC) in
Taiwan. His current research interests include enterprise resource
planning, e-business, e-learning, service quality management, and knowl-
edge management. He has publications in Information & Management and
Computers in Human behavior.
