Exploring the Different Roles of Service Quality, Satisfaction and Perceived Usefulness in Generating WOM in E-service Context

Transcription

1 Association for Information Systems AIS Electronic Library (AISeL) Eleventh Wuhan International Conference on e- Business Wuhan International Conference on e-business Exploring the Different Roles of Service Quality, Satisfaction and Perceived Usefulness in Generating WOM in E-service Context Hongxiu Li School of Engineering, Aalto University, Finland Yong Liu IAMSR, Abo Academy, Finland Reima Suomi Information Systems Science, Turku School of Economics, University of Turku, Finland Follow this and additional works at: Recommended Citation Li, Hongxiu; Liu, Yong; and Suomi, Reima, "Exploring the Different Roles of Service Quality, Satisfaction and Perceived Usefulness in Generating WOM in E-service Context" (2012). Eleventh Wuhan International Conference on e-business This material is brought to you by the Wuhan International Conference on e-business at AIS Electronic Library (AISeL). It has been accepted for inclusion in Eleventh Wuhan International Conference on e-business by an authorized administrator of AIS Electronic Library (AISeL). For more information, please contact

2 412 The Eleventh Wuhan International Conference on E-Business Human Behavior in IS Applications Track Exploring the Different Roles of Service Quality, Satisfaction and Perceived Usefulness in Generating WOM in E-service Context Hongxiu Li 1, Yong Liu 2, Reima Suomi 3 1 School of Engineering, Aalto University, Finland 2 IAMSR, Abo Academy, Finland 3 Information Systems Science, Turku School of Economics, University of Turku, Finland Abstract: Post adoption behaviours of e-service users are important for e-service providers to increase both their revenues and profits. WOM, as an important post adoption behavior, have not received the attention of IS researchers. The current paper develops a model to investigate the factors influencing individual e-service users Word of Mouth (WOM) behavior. Based on 543 useful questionnaires, the research model is empirically tested together with a number of hypotheses. The results show that satisfaction together with perceived usefulness and service quality positively impact users recommendations of e-service to others. The study finding implies that individuals would like to spread WOM more based on e-service attributes and service performance than on their own affect. Finally, the implications to theories and practice are discussed as well. Key words: WOM, E-service, service quality, satisfaction, perceived usefulness. 1. INTROCTION Post adoption behaviors of e-service users are important for e-service providers to increase both their revenues and profits. In the IS literature, numerous studies have been conducted to investigate the post adoption behaviors of individual e-service users, mainly focusing on continued intention or continued use of e-service. Word of Mouth ( WOM), as another form of post adoption behavior of e-service users, has received less attention among IS researchers though it has been argued to be critical in the online environment. As Reference [1] argued WOM is one of the most important sources of information and has a powerful impact on customers actions. The penetration of Internet into people life also makes WOM become widely available. Customers are able to post their thoughts, opinions, and feelings about products and services online via different social media channels [2], which might offer reliable information for others to support their decision on purchasing of products and services. Nowadays, more and more e-service users would like to post information online based on their e-service using experience. Their WOM might influence other individuals decision on e-service usage. The importance of WOM recently attract the attention of IS researchers. Some IS researchers have attempted to investigate WOM behaviors by explaining how WOM influences individual users decision process on IS use. However, fundamental and essential studies regarding what motivate individual IS users to disseminate WOM have not yet been undertaken. Therefore, this study intended to explore what are the motivators for individual e-service users to make WOM.

3 The Eleventh Wuhan International Conference on E-Business Human Behavior in IS Applications Track 413 The rest of the paper is structured as follows. In the next section we discuss the literature and develop our conceptual framework of WOM in the context of e-services. Then we describe the research methods employed in this research. Next, we discuss the research findings based on our empirical study. Finally, we conclude the paper by discussion the implications for both research and practice. 2. THEORETICAL BACKGROUND 2.1 WOM According to the literature in marketing, WOM is defined as a consumer-dominated channel for broadcasting product, service or company information in which senders are independent of the market [1], [3]. Reference [3] argued that customers often value WOM information more highly compared to firm-initiated information, and use WOM information to guide their behavior or decision process, such as information searching, assessment, subsequent decision making and purchasing behavior. WOM senders were argued to have neither an underlying motive nor an incentive for their referral. WOM information is perceived to be more reliable, credible and trustworthy for customers compared to information released by firms [3], [4]. Thus, when individuals are considering purchasing new products or services, they often rely heavily on WOM information and advice. A growing body of literature has attempted to investigate the influence of WOM on sales and customer purchase decisions in the retail industry. Prior research shows that WOM exert a significant influence on retailer sales on various products and services [5] [7]. In the information systems (IS) field, WOM are argued to be critical in IS usage, especially in the online environment. Reference [8] posited that the Internet has created a huge community of unconstrained consumer voices, and WOM has become more influential at the Internet ages due to its speed, convenience, one-to-many or many-to-many reach, and no face-to-face interaction. As Reference [1] stated that WOM includes communication between producers and consumers as well as those between consumers themselves. WOM consists of two dimensional activities. One is communication activities, such as from one to one by s, one to many via review sites, and many to many via virtual communities. The other is the level of interactivity, such as from asynchronous interactivity via s, review sites, and blogs to synchronous interactivity via chat rooms, newsgroups, and instant messaging. In the IS literature, it is argued that positive WOM may lead to the adoption of IS, and vice verse, negative WOM may reduce IS adoption [9], [10]. With the increasing application of e-service in business, people are employing e-service in their work and life. When considering using new e-services, individual users are keen to get the information and advices from other experienced users, which will guide their decision on e-service usage. WOM of experienced e-service users is becoming influential on the individuals decision on e-service use since WOM is normally made based on individuals prior experience of e-service usage. Thus, WOM of individual e-service users is worthy researching on due to its influence on the adoption behavior of other individual users [11], [12]. 2.2 Antecedents of WOM Prior literature has attempted to investigate the factors motivating WOM mainly from the marketing field, and suggests that a variety of product or service factors can affect individuals propensity to spread WOM, such

4 414 The Eleventh Wuhan International Conference on E-Business Human Behavior in IS Applications Track as perceived usefulness, perceived risks, product/service performance, product/service complexity [13]. Normally, individuals spread and seek more WOM for services than for goods due to the characteristic of being participatory in services [14]. Reference [15] posited that customers always recommend the most useful service options to others. In their study they also found that perceived value and perceived service quality are the two salient motivators for WOM behavior. Perceived usefulness has been found to be related to WOM in the study of [13]. As they stated that higher levels of usefulness leads to relatively more positively valenced WOM and, conversely, that lower levels of usefulness leads to relatively more negatively valenced WOM. In the IS literature, perceived usefulness refers to expectancy users have with regards to the IS performance. Perceived usefulness has been regarded a salient attribute of IS services. Drawing on these findings, we suggest that both perceived service quality and perceived usefulness will exert impacts on e-service users WOM, and the following hypotheses are proposed: H1: Service quality is positively associated with e-service users WOM behavior. H2: Perceived usefulness is positively associated with e-service users WOM behavior. In the prior research, user satisfaction has been argued to be the main motivating factor for the WOM behavior of online users [11], [12]. Reference [16] explored the role of user satisfaction in developing customer loyalty and positive WOM in the context of e-banking services and found that user satisfaction is positively related to WOM together customer loyalty. It suggests that a higher user satisfaction will lead to a more positive WOM. Thus, in the current study user satisfaction is suggested to be a driver of WOM behavior, and the following hypothesis is suggested: H3: User satisfaction is positively associated with e-service users WOM behavior. In general, prior research has suggested user satisfaction as the dominant and salient consequence of service quality [17] [19]. According to the Appraisal Response Theory [20], observations of external stimuli are processed cognitively and lead to an overall affective reaction. Service quality refers the extent to which an individual feels about service performance. Individuals cognitive appraisal of service quality performance will lead to their satisfaction with the service, an overall affection reaction to the service [21]. Prior IS research has validated the association between service quality and user satisfaction in various settings empirically [21] [23]. As Reference [21] suggested, if a user perceives that he or she has been well served by business-to-consumer websites, he or she will be more satisfied with websites in general. Drawing on the above reasoning, e-service quality is suggested to be positively related to user satisfaction with e-service, and the following hypothesis is put forward: H4: Service quality of e-services is positively associated with user satisfaction with e-services. Reference [24] suggests that perceived usefulness is a significant determinant of user satisfaction. According to Expectation Confirmation Theory [25], perceived performance has been assumed to be a significant antecedent of satisfaction. In IS literature, perceived usefulness can be regarded as perceived performance at the post-adoption stage in IS use. As Reference [24] stated, user perception on the usefulness of IS is expected to have an impact on their satisfaction with IS from the expectancy-confirmation paradigm. The positive relationship between perceived usefulness and satisfaction was empirically supported in others IS studies in different research contexts [26] [29]. Thus, perceived usefulness is expected to influence user satisfaction positively in the e-service context, and the following hypothesis is proposed:

5 The Eleventh Wuhan International Conference on E-Business Human Behavior in IS Applications Track 415 H5: Perceived usefulness of e-services is positively associated with user satisfaction with e-services. Figure 1. The proposed research model 3. RESEARCH METHOD 3.1 Data collection In this study the empirical data was collected via a survey of online travel service users. The respondents of the survey in the current study were the customers of an online travel service company in China. The sample of the survey includes 1500 randomly selected customers from the customer base of the online travel service company. The respondents were asked to indicate the motivators for them to make recommendation of the online travel services they have used to others. A mail was delivered to each customer from the online travel service company encouraging their participation in this survey together with the questionnaire. Totally 543 usable responses were obtained as the sample base of the current study. The respondents ages from 18 to 65. Among the respondents, 61.9% were male and 38.1% were female. All the respondents had used the Internet for more than 2 years, and had used online travel services before. The majority (90%) of the respondents ranges from 18 to 45 years old. Table 1 presents the demographic information profile of the respondents in this study. Table 1. Demographic profile of respondents Demographic profile Category Frequency Percentage (%) Male Gender Female Total Age Total College student Bachelor s level Education Master s level Ph.D level Total More than 2 years More than 3 years Duration of using Internet Online travel service booking experience Total times More than 5 times Total

6 416 The Eleventh Wuhan International Conference on E-Business Human Behavior in IS Applications Track 3.2 Measurement The measurements in this study were based on a five-point Likert-scale anchoring from strongly disagree (1) to strongly agree (5). In the research model three factors are suggested to determine individual e-service users WOM, namely satisfaction, perceived usefulness and service quality. The four constructs included in the resrach model were measured using multiple observed items adapted from existing IS literature. Some rewording has been conducted in the questionnaire in order to fit the online travel service context, In this study, the four measurements for WOM were taken from [29], [30]. The three items for satisfaction were adapted from [24], [31]. The construct service quality was assessed using the measures from [32]. The four items for perceived usefulness were modified from [33] in order to reflect the utility of online travel service. 3.3 Data analysis In this study, the data analysis was performed using Partial Least Squares (PLS) path modeling. PLS was used to make a simultaneous analysis of both measurement model and structural parameters in the proposed research model. In this study an algorithm procedure in PLS was employed to test the measurement model, and the bootstrap procedure was used to test the significance of all proposed path in the research model. Smart PLS version 2.0 was used in the current study. 3.4 Validity and reliability Convergent validity indicates the degrees to which the items of a scale that are assumed to be theoretically associated are also related in reality. In this study, most loadings of the measures in the research model are satisfactory with the cut-off value above 0.7, except for three whose values are acceptable with the cut-off value between 0.5 and 0.7 [34]. The values of composite reliability (CR) of all constructs were higher than 0.80, and the values of the average extracted variance (AVE) were higher than The values of CR and AVE satisfy the threshold values of 0.8 for CR and 0.5 for AVE recommended by [35]. The Cronbach s alpha values range from to 0.819, exceeding the 0.7 level. The test results indicated a good internal consistency and reliability of the research instrument, supporting the convergent validity of the research data. Table 2. The Measurement Model Construct Items CR AVE Cronbach s alpha Factor Loading t-value PU Perceived Usefulness PU PU PU SAT Satisfaction SAT SAT Service quality SQ SQ WOM Word of Mouth WOM WOM WOM

7 The Eleventh Wuhan International Conference on E-Business Human Behavior in IS Applications Track 417 Discriminant validity involves checking whether the items of a scale reflect the construct in question or reflect another related construct. Discriminant validity can be verified with the square root of the average variance extracted for each construct higher than any correlation between this construct and all other constructs [35]. Table 3 shows that each construct in the proposed research model shares a greater variance with its own reflective construct than with any other construct in the research model. Thus, the discriminant validity in this study was supported. Table 3. Correlation Matrix and Discriminant Assessment PU SAT SQ WOM PU SAT SQ WOM RESULTS Figure 3 presents a graphical description of the research results in the current study, including path coefficient, variances explained and associated t-value of paths. The test results indicated that all the proposed hypotheses are statistically significant. Thus, all the proposed hypotheses in the research model were supported. Service quality (β=0.335, p<0.001), satisfaction (β=0.192, p<0.001) and perceived us efulness (β=0.215, p<0.001) are found to have positive impacts on WOM. Satisfaction was found to be positively associated with service quality (β=0.351, p<0.001) and perceived usefulness (β=0.200, p<0.001) significantly. The proposed research model accounts for 33.4 per cent of the variance in WOM and 22 per cent of the variance in satisfaction. Figure 2. Structural analysis of the research model 5. DISCUSSION AND CONCLUSIONS This study is attempting to investigate the motivators of WOM behavior from the perspective of individual e-service users. The study results specify service quality, perceived usefulness and user satisfaction as the three motivators for individual online travel service users WOM behavior. Service quality was found to have the strongest influence in predicting WOM behavior of the online travel service users. In other words, the WOM

8 418 The Eleventh Wuhan International Conference on E-Business Human Behavior in IS Applications Track behavior of individual online travel service users is mainly driven by their perceptions of online travel service quality, their perceptions of the usefulness of online travel service and their satisfaction with their prior usage of online travel service. Though in this study satisfaction was found to be a significant determinant of WOM, its effect is weaker compared to the strong effects of service quality and perceived usefulness. This finding is in contrast to the argument in the prior literature that user satisfaction was the salient motivator for users WOM behavior [10] [12]. The findings in this study indicates that individual e-service users will make recommendations of e-service to other customers mainly based on their perceptions on the e-service quality and the usefulness of e-service, but not their own satisfaction with e-service. In this study, user satisfaction refers to individuals affect based on their prior use of online travel services. The research findings imply that though both affect and service attributes are important aspects influencing individual e-service users WOM behavior, individual e-service users would like to make WOM relying more on the e-service attributes and e-service performance rather than on their affect (such as satisfaction) after their use of e-service. This study has offered some valuable insight in the post adoption behavior of individual e-service users by investigating the motivators of individual e-service users WOM behavior. Understanding these motivations could also enhance the ability of the managers and corporate decision-makers to encourage WOM. We believe that WOM also influence others decision on e-service usage. Thus, future research should also try to investigate how WOM influence others decision on e-service use or purchasing online. REFERENCE [1] Litvin S W., Goldsmith R E., Pan B. (2008) Electronic word -of-mouth in the hospitality and tourism management. Tourism Management, 29(3): [2] Schinler R M., Bickart B. (2005) Published Word of Mouth: Referable, Consumer-Generated Information on the Internet. Online Consumer Psychology: Understanding and Influencing Consumer Behavior in the Virtual World. Lawrence Erlbaum Associates, Inc, NJ. [3] Brown J., Broderick A.J., Lee N. (2007) Word of mouth communication within online communities: Conceptualizing the online social network. Journal of Active Marketing, 21(3): [4] Grewal R., Cline T.W., Davies A. (2003) Early-Entrant Advantage, Word-of-Mouth Communication, Brand Similarity, and the Consumer Decision-Making Process. Journal of Consumer Psychology, 13(3): [5] Clemons E K., Gao G., Hitt L. M. (2006) When online reviews meet hyperdifferentiation: A study of craft beer industry. Journal of Management Information Systems, 23(2): [6] Duan W., Gu B., Whinston A B. (2008) Online reviews matter? An empirical investigation of panel data. Decision Support Systems, 45(4): [7] Zhu F., Zhang X. (2010) Impact of online consumer reviews on sales: The moderating role of product and consumer characteristics. Journal of Marketing, 74(2): [8] Ronner F., Hoog R. (2011) Vacationers and ewom: Who posts, and why, where and what? Journal of Travel Research, 50(1): [9] Bonfrer A. (2010). The effect of negative word-of-mouth in social networks. In: Wuyts S M. Dekimpe G., Gijsbrechts

9 The Eleventh Wuhan International Conference on E-Business Human Behavior in IS Applications Track 419 E., Pieters R. eds. The Connected Customer: The Changing Nature of Consumer and Business Markets. New York, Routledge, [10] East R., Hammond K., Wright M. (2007) The relative incidence of positive and negative word of mouth: A multicategory study. International Journal of Research in Marketing, 24(2): [11] Chea S., Luo M M. (2008) Post-adoption behaviours of e-service customers: The interplay of cognition and emotion. International Journal of Electronic Commerce, 12(3): [12] Kim S S., Son J-Y. (2009) Out of dedication or constraint? A dual model of post-adoption phenomena and its empirical test in the context of online services. MIS quarterly, 33(1): [13] Moldovan S., Goldenberg J., Chattopadhyay A. (2011) The different role of product originality and usefulness in generating Word-of-Mouth. International Journal of Research in Marketing. 28: [14] Buttle F A. (1998) Word of mouth: Understanding and managing referral marketing. Journal of Strategic Marketing, 6(3): [15] Mangold W G., Miller F., Brockway G R. (1999) Word-of-mouth communication in the service marketplace. The Journal of Services Marketing, 13(1): [16] Casalo LV., Flavian C., Guinaliu M. (2008) The role of satisfaction and website design usability in developing customer loyalty and positive word-of-mouth in the e-banking services. The International Journal of Bank Marketing, 26(6): [17] Cronin J J., Brady M K., Hult G T M. (2000) Assessing the effects of quality, value, and customer satisfaction on consumer behavioral intentions in service environments. Journal of Retailing, 76(2): [18] Cronin J J., Taylor, S A. (1992) Measuring serv ice quality A reexamination and extension. Journal of Marketing, 56(3): [19] Robinson S. (1999) Measuring service quality: Current thinking, future requirements. Marketing Intelligence and Planning, 17(1): [20] Bagozzi R P. (1992) The self-regulation of attitudes, intentions, and behavior. Soc. Psych. Quarterly, 55(2): [21] Cenfetelli R T., Benbasat I., Al-Natour S. (2008) Addressing the What and How of online services: Positioning supporting-services functionality and service quality for business-to-customer success. Information Systems Research, 19(2): [22] Anderson E W., Sullivan M W. (1993) The antecedents and consequences of customer satisfaction for firms. Marketing Science, 12(2): [23] Spreng R A., Mackoy R D. (1996) An empirical examination of a model of perceived service quality and satisfaction. Journal of Retailing, 72(2): [24] Oliver R L. (1980) A cognitive model for the antecedents and consequences of satisfaction. Jour nal of Marketing Research, 17(6): [25] Bhattacherjee A. ( 2001) Understanding information systems continuance: An expectation confirmation model. MIS Quarterly, 25(3): [26] Bhattacherjee A., Perols J. and Sanford C. (2008) Information technology continuance: A theoretic extension and empirical test. Journal of Computer Information Systems, Fall(2008):

10 420 The Eleventh Wuhan International Conference on E-Business Human Behavior in IS Applications Track [27] Lin C S., Wu S., Tsai R J. (2005) Integrating perceived playfulness into expectation confirmation model for web portal context. Information & Management, 42(5): [28] Rai A., Lang S S., Welker R B. (2002) Assessing the validity of IS success models: An empirical test and theoretical analysis. Information Systems Research, 13(1): [29] Dolen W. M., Dabholkar P.A., Ruyter K. (2007) Satisfaction with online commercial group chat: The influence of perceived technology attributes, chat group characteristics, and advisor communication style. Journal of Retailing, 83 (3), [30] Maxham J G. (2001). Service recovery s influence on consumer satisfaction, positive word -of-mouth, and purchase intentions. Journal of Business Research, 54(4): [31] Spreng R A., MacKenzie S B., Olshavsky R W. (1996) A re-examination of the determinants of consumer satisfaction. Journal of Marketing, 60(3): [32] Carlson J., O Cass J. Developing a framework for understanding e-service quality, its antecedents, consequences, and mediators. Managing Service Quality, 21(3): [33] Davis F D. (1989) Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Quarterly, 13(3): [34] Hair J F., Black W C., Babin B J., Anderson R E., Tatham R L. (2006) Multivariate data analysis (6th edition). Prentice Hall, New Jersey. [35] Fornell C., Larcker D F. (1981) Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18: