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Applying TAM in B2C E-Commerce Research: An Extended Model
TSINGHUA SCIENCE AND TECHNOLOGY ISSN 1007-0214 02/26 pp265-272 Volume 13, Number 3, June 2008
Applying TAM in B2C E-Commerce Research: An Extended Model QIU Lingyun (邱凌云)**, LI Dong (李 东) Guanghua School of Management, Peking University, Beijing 100871, China Abstract: As one of the most widely accepted adoption models in information systems research, the technology acceptance model (TAM) focuses exclusively on cognition-oriented constructs such as perceived usefulness and perceived ease of use. This perspective may have limited the explanatory power of TAM when it is utilized in studying consumers’ adoption intentions of online shopping. Based on the contrasts between e-commerce systems and traditional workplace information systems as well as empirical findings from a variety of recent e-commerce research works, this paper analyzes an extended model which integrates three additional constructs: trust, social presence, and perceived enjoyment. The interrelationship between these constructs is also explained. Empirical validations of this extended model are expected in future research. Key words: technology acceptance model (TAM); B2C electronic commerce; online shopping; social presence; trust; perceived enjoyment
Introduction B2C (business-to-consumer) electronic commerce has not only shifted many aspects of our daily life, but also attracted many researchers’ interests in studying various facets associated with the adoption and use of online shopping[1]. Early research in e-commerce adopted a transactional perspective to focus on customer-company exchanges by investigating ways to improve the efficiency of an e-commerce website[2] with much of the research work using the technology acceptance model (TAM)[3] to explain online shoppers’ intentions to adopt a specific website or use a particular feature provided by online retailers. In recent studies, researchers have argued that online shopping websites should be designed with the goal of enhancing the customer’s overall experience[4,5]. Due Received: 2007-06-06; revised: 2007-12-15
﹡ ﹡To whom correspondence should be addressed. E-mail: [email protected]; Tel: 86-10-62757557
to the high cost of attracting and retaining customers, online retailers should not narrowly focus on the utilitarian value that their websites offer. Instead, they should realize the importance of building ongoing steady relationships with their customers, as well as providing them with a gratifying shopping experience. This paper describes a theoretical extension to the classical TAM model which integrates the factors of relationship building and hedonic experience. These addition constructs could provide a better understanding of many factors that affect the relationships between customers and online stores, especially those concerning the design of the website features and interface.
1
Technology Acceptance Model (TAM)
The TAM has become one of the most widely used theories in information systems research since proposed by Davis et al. in 1989[3]. The origins of TAM
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can be traced to the theory of reasoned action (TRA)[6]. The TRA requires that salient beliefs about one’s attitude towards a particular behavior (e.g., buying on the web) be elicited every time the behavior occurs in order to be relevant to the specific behavior being studied. As a simplification to TRA, the TAM suggests that the users’ decisions to accept a new information technology are based on two rational assessments of its expected outcomes: (1) perceived usefulness (PU), defined as the users’ expectation that using a new information technology could result in improved job performance, and (2) perceived ease of use (PEOU), defined as “the degree to which a person believes that using a particular system would be free of effort”[3]. Thanks to its straightforwardness and conciseness, the TAM makes information technology (IT) adoption research more efficient and facilitates the aggregation of results across settings. Its effectiveness has been established by numerous empirical studies[7]. Most empirical studies provide strong evidences that PU does directly influence users’ intentions of adopting a new technology. In contrast, the effects of PEOU are more controversial. In the original TAM, Davis argued that PEOU affects intended use primarily through PU, while other researchers have found that PEOU may sometimes directly influence IT adoption when the task is intrinsic to the IT[8].
2
Extended Model for Online Shopping
Most earlier TAM research focused on corporate information systems as well as professional users or employees who rely on these workplace systems to complete their jobs; therefore, it has paid exclusive attention to the cognitive beliefs, such as perceived usefulness and ease of use, and focused on the more extrinsic and utilitarian determinants of users’ intentions to accept and adopt the system. However, users’ decisions to adopt an online shopping website have a number of major differences: (1) most users of e-commerce systems are not professional IT workers and some are not even familiar with mainstream information technologies; (2) the IT systems (i.e., the shopping websites) used by the user usually do not belong to the company where the user is working; and (3) on most occasions, the tasks a user attempts to complete through
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interacting with an e-commerce system, either buying a product or browsing for information, are not mandatory, or at least the users have alternative means to perform the work. For example, shoppers can always go to a physical store to complete the transaction. With these major concerns in mind, e-commerce websites nowadays provide a range of features to address users’ various psychological needs rather than facilitating the purchasing procedure alone. For example, an online store could promote more social interactions between shoppers and service representatives by offering “live help” services or enhance users’ communications with each other through product reviews or discussion forums. In addition, with the help of Macromedia Flash and other multimedia software, many websites offer visitors a more enjoyable experience with functionalities such as animated product demos or humanoid recommendation agents. All these phenomena call for additional factors to be integrated into the original transaction-oriented TAM variables in the study of online shopping adoption behavior. This paper presents an extended TAM model based on recent studies on e-commerce adoptions, which includes three supplementary constructs, trust, social presence, and perceived enjoyment. This extended model is shown in Fig. 1. The following section gives an overview of these three constructs, followed by analyses of the roles they play in users’ perceptions of their interactions with e-commerce websites. 2.1
Trust
Establishing and maintaining a long-term relationship with customers are critical for any retail store[9-12]. An e-commerce relationship represents a social system in which a customer is interacting with a company embodied by a website. In marketing studies, the concept of relationship quality, which to a great extent determines future sales opportunities[10], is composed of trust in a salesperson[13] and satisfaction with a salesperson[9]. This paper focuses on the construct of trust. Trust is an important indicator reflecting the quality of interpersonal social relationships[14-16]. As a social construct that originates from interpersonal relationships[17], trust is one of the most desired qualities in any close relationship[18], as well as one that significantly
QIU Lingyun (邱凌云) et al.：Applying TAM in B2C E-Commerce Research: An Extended Model
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Fig. 1 Extended TAM model for online shopping
influences users’ intentions to adopt technological artifacts when they are perceived as social actors[19,20]. Recent research has analyzed trust from four major perspectives: (1) viewing trust as a belief or a collection of beliefs that the trustee has attributes that are beneficial to the trustor[21]; (2) viewing trust as an emotional feeling of security, comfort, and lack of fear[22]; (3) viewing trust as an intention or the willingness of a party to be vulnerable to the actions of another party[23]; and (4) viewing trust as a combination of these elements[24]. In traditional commerce, trust usually refers to the interpersonal trust between consumers and salespeople. In contrast, prior research on online consumer trust has focused on consumers’ trust towards either a website or a company[19,24,25]. There has been a debate about whether belief constructs such as trust can be applied to technological artifacts, especially in terms of beliefs about benevolence and integrity[26,27]. However, recent studies in social psychology have revealed that, due to years of continuous interactions with other people, consumers generally possess mental models that they apply to computers or other technological artifacts, ascribing social behavior and social attribute to the technology, especially when the technology possesses a set of characteristics normally associated with human behavior[28]. Recent studies on product recommendation agents have also indicated that although the formation processes of customer trust/distrust belief in “virtual salespersons” (software agents) and human salespersons are slightly different, trust in a software agent also contains belief in competence, benevolence, and integrity[29], similar to trust in a human salesperson[30]. The connections between trust and the TAM constructs have been widely discussed in previous studies[20,31-33]. Gefen et al.[31] integrated consumer trust
into the traditional TAM model in the context of online shopping, arguing that trust, conceptualized as a set of trusting beliefs towards an online vendor, directly affects intentions to use a B2C website, along with perceived usefulness (PU) and perceived ease of use (PEOU). Trust in a merchant can also affect PU in both the short term and the long term. In addition, PEOU has been hypothesized to exert a positive influence on trust, as PEOU can help promote consumers’ favorable impressions of e-vendors in the initial adoption and can enhance consumers’ willingness to make an investment and a commitment in buyer-seller relationships. Wang and Benbasat[20] have extended this integrated trust-TAM model to the context of online recommendation agents. Similarly, they have found that initial trust in online recommendation agents can positively affect intentions to adopt agents as well as the consumers’ perceived usefulness of the agent. Therefore, in our extended TAM model, we propose that: Proposition 1 Users’ trust in an e-commerce website will positively affect their intentions to adopt the website. Proposition 2 Users’ trust in an e-commerce website will positively affect perceived usefulness of the website. Proposition 3 Perceived ease of use of an ecommerce website will positively affect trust in the website. 2.2
Social presence
Shopping activities, on one hand, are analytical tasks during which a shopper tries to identify her needs and makes decisions on purchasing the products that best satisfy her. On the other hand, shopping activities are social experiences consisting of interacting with other people, such as friends, salespeople, and other
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shoppers. Nevertheless, when consumers shop online, the lack of social interactions and the absence of a “human touch” are significant disadvantages or even inhibitors[34]. In the communication literature, this feeling of “being together with others” is defined as social presence. The term social presence was first used in studies of interpersonal communications within organizations, to compare the effects of various types of telecommunication technologies for remote business meetings. It was originally developed to measure people’s subjective perceptions of other people when the communication is mediated by a communication medium. Defined as the subjective evaluation of a communication medium on “the degree of salience of the other person in the interaction and consequent salience of the interpersonal relationships”[35], it also describes the extent to which a medium is perceived as sociable, warm, sensitive, personal, or intimate when it is used to interact with other people[36]. In traditional social presence theory, social presence is defined as the characteristic that describes the capacity of each medium to give immediate feedback as well as a variety of communication cues. It is conceptualized as a subjective measure of a communication medium, which is exclusively determined by the characteristics of the medium.[35] However, recent viewpoints[37] have tended to conceptualize social presence “as a transient phenomenological state that varies with medium, knowledge of the other, content of the communication, environment, and social context.” We concur with Biocca et al.[37] that users’ feelings of social presence are formed through communication processes; therefore, the users are influenced not only by the medium, but also by the communication content and their possible courses of action as well. In other words, social presence is a subjective measure developed over the entire course of the interactions, rather than arising from a static inventory of various features of a communication medium. As mentioned above, social presence is particularly relevant in online shopping environment. For example, to offer online shoppers perceptions similar to what they could experience in the physical world, some ecommerce websites have attempted to reproduce consumer-to-serviceperson interactions through real-time online service features, such as “live help,” or to
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simulate interpersonal communications between shopping buddies by offering collaborative browsing and instant messaging tools. Emerging Web 2.0 technologies, such as Blog, Tag, and Wiki, are also being examined by online retailers with the goal of enhancing social communications among users. Social presence has been related to the TAM variables as well. Gefen et al.[31] have examined the effects of social presence on consumer trust in e-services, finding that social presence affects consumer trust, with the increased trust subsequently having a stronger effect on purchase intentions than TAM beliefs. Lee and Nass[38] also identified a significant mediating effect of social presence on website content credibility in their study of the effects of multiple synthetic voices in e-commerce context. In their study of IT-enabled support for personalization systems and virtual communities in online shopping websites, Kumar and Benbasat[39] found that social presence and perceived usefulness both significantly affect customer loyalty. In our extended model, we agree with Gefen and Straub[19] that the social presence an e-commerce website affords can positively contribute to consumer trust. In face-to-face human interactions, trustworthiness is usually manifested by a plethora of trivial but important social cues. As inexperienced users interact with a website for the first time, they have very few cues to judge an online store’s trustworthiness. As Fogg and Tseng[40] have pointed out, the impressions formed through simple inspection of “surface attributes” can directly influence users’ attitudes and behavior. When the interaction with a store is perceived as socially warm, the general social convention that “a nice person is usually trustworthy” is automatically applied. In addition, social presence, especially when supported by social network functionalities (e.g., consumer reviews, product discussion forums, or tagging) could to some extent address users’ social needs during shopping, which may consequently enhance their intentions of making purchases online. Proposition 4 Users’ perceptions of social presence will positively affect their trusting beliefs in an ecommerce website. Proposition 5 Users’ perceptions of social presence will positively affect their intentions to adopt an e-commerce website.
QIU Lingyun (邱凌云) et al.：Applying TAM in B2C E-Commerce Research: An Extended Model
2.3
Perceived enjoyment
Perceived enjoyment refers to the extent to which the activity of interacting with the e-commerce website is perceived to be enjoyable in its own right aside from the utilitarian value of the site[41]. It is closely related to the concept of intrinsic motivation, which refers to “the performance of an activity for no apparent reinforcement other than the process of performing the activity per se”[41]. The importance of intrinsic motivation as a lever to create favorable user perceptions has been empirically demonstrated[42-44]. In the human-computer interaction (HCI) and information systems literature, perceived enjoyment has been considered as a sub-dimension of various constructs measuring users’ intrinsic motivation towards or enjoyable experience from using a technology. For example, Moon and Kim[45] presented perceived enjoyment as a dimension of perceived playfulness, an intrinsic belief or motive formed from an individual’s subjective experiences using a technology such as the Internet. Perceived enjoyment is also included as a component of flow, which was initially presented as an optimal and enjoyable experience in which people are completely absorbed in their activities[46]. The flow construct was later adapted to the context of information technology and computer-mediated environments as a subjective psychological experience, in which the human-computer experience is characterized as playful and exploratory[47]. Enjoyment is also recognized as one of the five dimensions of cognitive absorption, a similar construct which describes a state of deep involvement with software[48]. In recent years, perceived enjoyment has received increasing interest in IS research, as researchers start to acknowledge that how enjoyable an information system is may be as important as how usable and useful it is[49]. Fun and enjoyment in the home and leisure context are as important as productivity and efficiency in the work context. The influence of enjoyment perceptions on users’ technology adoption intentions has been empirically examined in applications such as general computer usage[50], Internet usage[45,51,52], instant messaging tools[53], Internet-based learning medium[54,55], and online shopping[56,57]. Perceived enjoyment is considered to be an important addendum to the original TAM[41]. The IS
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literature includes studies that have demonstrated that enjoyment influences usefulness through the mediation of ease of use[43]. Others have found that, while intrinsic motivation has no direct influence on intention to use technology, it can serve as an important predictor for both perceived usefulness and perceived ease of use[44,54]. Recent research on non-workplace information systems, such as the Internet, online shopping, and video games, has suggested a more important role for perceived enjoyment. It is not only an immediate antecedent to perceived usefulness, but it is also more important to adoption of information systems[42,45,51,53,57,58]. Van der Heijden[57] argued that these systems share common characteristics with hedonic systems, which aim to provide self-fulfilling value to users, in contrast to utilitarian systems that aim to provide instrumental value to users. The encouragement of “prolonged use”, rather than “productive use”, should be the dominant design objective of hedonic systems. Although Van der Heijden[57] dichotomized information systems into either utilitarian or hedonic, we contend that many information systems possess the characteristics of both at the same time, especially for systems developed for home use, such as computer-aided tutoring systems and online shopping websites. Correspondingly, most marketing research suggests that individuals’ shopping behavior is driven by both instrumental and hedonic motivations[59]. Consumers’ shopping values are subjective, characterized by their interactions with an environment and indicated by both the event’s usefulness and an appreciation of its activities. Hedonic shopping motives are similar to the task orientation of utilitarian shopping motives, only the task is concerned with hedonic fulfillment, such as experiencing fun, amusement, fantasy, and sensory stimulation[59]. Past studies[60] have indicated that the hedonic and immersive aspects of an online shopping website are as important predictors of shopper’s attitude as the instrumental aspects. As a result, shopping enjoyment can be an important determinant of online customer loyalty[56,61]. Research has shown that when customers experience positive emotions, they tend to be more satisfied with their buyer-seller relationships[62] and they are more likely to complete a purchase[63]. In our extended model, we propose that for users of an online shopping website, perceived enjoyment can
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exert both direct and indirect influences on their adoption intentions and the task a user is trying to perform will very likely moderate the potential influence of this construct. As argued by Van der Heijden[57], the unmediated impacts of perceived enjoyment on adoption intentions are manifest only among hedonicoriented systems, in which the instrumental values of the system are less important than the pleasurable experience a user acquires from the usage. When the primary task of an online shopper is to complete a purchase through the website, the extrinsic motivations— find the right product and pay for it—are still the primary incentives for a user to interact with the site. When the website is fun to use, users will perceive the task as being less tiring and the users are likely to be more engaged in the task and, therefore, more likely to complete the task. Therefore, the impacts of perceived enjoyment on behavioral intentions will be fully mediated by perceived usefulness and perceived ease of use. On the other hand, when the major goal of an online shopper is limited to non-transaction related activities such as to browse the product information (“Windowshopping” in the virtual world) or interacting with other users on the discussion forum, the enjoyment perception will make the website more attractive and, thus, directly influence the users’ adoption intentions. Proposition 6 Users’ perceptions of enjoyment will positively affect perceived usefulness of an ecommerce website. Proposition 7 Users’ perceptions of enjoyment will positively affect perceived ease of use of an ecommerce website. Proposition 8 Users’ perceptions of enjoyment will positively affect their intentions to adopt an ecommerce website. In summary, despite its well-established applicability in workplace systems, the original TAM fails to offer an adequate explanation for users’ attitudes and adoption behaviors towards online shopping. The three constructs proposed in the extended model can exert equally, if not more, significant effects. In addition, these constructs may affect users’ attitudes indirectly by interactions with the traditional TAM constructs.
3
Conclusions and Future Research
An extended TAM model was developed to explain users’ adoption behavior when shopping online based
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on comparisons between online shopping websites and traditional workplace information systems and their respective users. In addition to the traditional utilitybased TAM variables, three additional factors and the interrelationship between these variables are viewed as important constructs for explaining users’ online shopping behavior. The value of this model should be examined by empirical investigations in future research. Other factors, such as product category or individual user differences, might moderate or mediate the impacts of these constructs. Therefore, more theoretical and emprical studies are needed to extend the TAM, one of the most established theories in IS research, to various new scenarios introduced by emerging information technologies. References [1]
Ngai E W T, Wat F K T. A literature review and classification of electronic commerce research. Information & Management, 2002, 39(5): 415-429.
[2]
Lohse G, Spiller P. Electronic shopping. Communication of the ACM, 2001, 41(7): 81-87.
[3]
Davis F D. Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Quarterly, 1989, 13(3): 319-339.
[4]
Keen P. Relationships—The electronic commerce imperative. In: Dickson G, Desanctis G, eds. Information Technology and the Future Enterprise: New Models for Managers. Upper Saddle River, New Jersey, USA: Prentice Hall, 2000: 163-185.
[5]
Kumar N, Benbasat I. Para-social presence and communication capabilities of a web site: A theoretical perspective. e-Service Journal, 2002, 1(3): 5-24.
[6]
Fishbein M, Ajzen I. Beliefs, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Reading, MA, USA: Addison-Wesley, 1975.
[7]
Lee Y, Kozar K A, Larsen K R T. The technology acceptance model: Past, present, and future. Communication of the Association for Information Systems, 2003, 12: 752780.
[8]
Gefen D. The relative importance of perceived ease of use in IS adoption: A study of e-commerce adoption. Journal of Association for Information Systems, 2000, 1: article 8. http://jais.aisnet.org/articles/default.asp?vol=1&art=8.
[9]
Crosby L A, Stephens S. Effects of relationship marketing on satisfaction, retention, and prices in the life insurance industry. Journal of Marketing Research, 1987, 24(4):
QIU Lingyun (邱凌云) et al.：Applying TAM in B2C E-Commerce Research: An Extended Model 404-411. [10] Crosby L A, Evans K, Cowles D. Relationship quality in services selling: An interpersonal influence perspective. Journal of Marketing, 1990, 54(3): 68-81. [11] Berry L L. Relationship marketing of services: Growing interest, emerging perspectives. Journal of the Academy of Marketing Science, 1995, 23(Fall): 236-245. [12] Morgan R M, Hunt S D. The commitment-trust theory of relationship marketing. Journal of Marketing, 1994, 58(July): 20-38. [13] Swan J E, Trawick F I. Measuring dimensions of purchaser trust of industrial salespeople. Journal of Personal Selling and Sales Management, 1988, 8(1): 1-9. [14] Blau P. Exchange and Power in Social Life. New York, USA: Wiley, 1964. [15] Fukuyama F. Trust: The Social Virtues and the Creation of Prosperity. New York, USA: The Free Press, 1995. [16] Luhmann N. Trust and Power. London: John Wiley and Sons, 1979. [17] Sztompka P. Trust: A Sociological Theory. Cambridge, UK: Cambridge University Press, 1999. [18] Rempel J K, Holmes J G, Zanna M P. Trust in close relationship. Journal of Personality and Social Psychology, 1985, 49(1): 95-112. [19] Gefen D, Straub D. Managing user trust in B2C e-services. e-Service Journal, 2003, 2(2): 7-24. [20] Wang W, Benbasat I. Trust in and adoption of online recommendation agents. Journal of the Association for Information Systems, 2005, 6(3): 72-101. [21] Bhattacherjee A. Individual trust in online firms: Scale development and initial test. Journal of Management Information Systems, 2002, 19(1): 211-241. [22] Komiak S X, Benbasat I. Understanding customer trust in
271
Concepts, evolving themes, a model. International Journal of Human-Computer Studies, 2003, 58(6): 737-758. [27] Chopra K, Wallace W A. Trust in electronic environment. In: Proceedings of 36th Hawaii International Conference on System Sciences. Big Island, Hawaii, 2003. [28] Reeves B, Nass C. The Media Equation: How People Treat Computers, Television, and New Media like Real People and Places. New York, USA: Cambridge University Press, 1996. [29] Cassell J, Bickmore T. External manifestations of trustworthiness in the interface. Communications of the ACM, 2000, 43(12): 50-56. [30] Komiak S X, Wang W, Benbasat I. Comparing customer trust in virtual salespersons with customer trust in human salesperson. In: Proceedings of 38th Hawaii International Conference on System Sciences. Big Island, Hawaii, 2005. [31] Gefen D, Karahanna E, Straub D W. Trust and TAM in online shopping: An integrated model. MIS Quarterly, 2003, 27(1): 51-90. [32] Pavlou P A. Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model. International Journal of Electronic Commerce, 2003, 7(3): 101-134. [33] Wu I L, Chen J L. An extension of trust and TAM model with TPB in the initial adoption of on-line tax: An empirical study. International Journal of Human-Computer Studies, 2005, 62(6): 784-808. [34] Qiu L, Jiang Z, Benbasat I. Real experience in your virtual store: Designing presence in online shopping. In: Proceedings of the 10th Pacific-Asia Conference on Information Systems (PACIS 2006). Kuala Lumpur, Malaysia, 2006. [35] Short J, Williams E, Christie B. The Social Psychology of Telecommunication. London: John Wiley & Sons, 1976.
agent-mediated electronic commerce, web-mediated elec-
[36] Lombard M, Ditton T. At the heart of it all: The concept of
tronic commerce, and traditional commerce. Information
presence. Journal of Computer-Mediated Communication,
Technology and Management, 2004, 5(1&2): 181-207.
1997, 3(2). http://jcmc.indiana.edu/vol3/issue2/lombard.
[23] Mayer R C, Davis J H. An integrative model of organizational trust. Academy of Management Review, 1995, 20(3): 709-734. [24] McKnight D H, Choudhury V, Kacmar C. Developing and validating trust measures for e-commerce: An integrative typology. Information Systems Research, 2002, 13(3): 334359. [25] Hoffman D L, Novak T P, Peralta M. Building consumer trust online. Communications of the ACM, 1999, 42(4): 80-85. [26] Corritore C L, Kracher B, Wiedenback S. On-line trust:
html. [37] Biocca F, Harms C, Burgoon J K. Towards a more robust theory and measure of social presence: Review and suggested criteria. Presence: Teleoperators and Virtual Environments, 2003, 12(5): 456-480. [38] Lee K M, Nass C. The multiple source effect and synthesized speech: Doubly-disembodied language as a conceptual framework. Human Communication Research, 2004, 30(2): 182-207. [39] Kumar N, Benbasat I. The influence of recommendations and consumer reviews on evaluations of websites.
272 Information Systems Research, 2006, 17(4): 425-439. [40] Fogg B J, Tseng H. The elements of computer credibility. In: Proceedings of ACM SIGCHI Conference on Human Factors in Computing Systems (CHI’99). Pittsburgh, Pennsylvania, USA, 1999: 80-87. [41] Davis F D, Bagozzi R P, Warshaw P R. Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 1992, 22(14): 11111132.
Tsinghua Science and Technology, June 2008, 13(3): 265-272 [52] Van der Heijden H. Factors influencing the usage of websites: The case of a generic portal in the Netherlands. Information & Management, 2003, 40(6): 541-549. [53] Li D, Chau P Y K, Lou H. Understanding individual adoption of instant messaging: An empirical investigation. Journal of the Association for Information Systems, 2005, 6(4): 102-129. [54] Yi M Y, Hwang Y. Predicting the use of web-based information systems: Self-efficacy, enjoyment, learning goal
[42] Venkatesh V. Creation of favorable user perceptions: Ex-
orientation, and the technology acceptance model. Interna-
ploring the role of intrinsic motivation. MIS Quarterly,
tional Journal of Human-Computer Studies, 2003, 59(4):
1999, 23(2): 239-260.
431-449.
[43] Venkatesh V. Determinants of perceived ease of use: Inte-
[55] Lee M K O, Cheung C M K, Chen Z. Acceptance of Inter-
grating control, intrinsic motivation, and emotion into the
net-based learning medium: The role of extrinsic and in-
technology acceptance model. Information Systems Re-
trinsic motivation. Information & Management, 2005,
search, 2000, 11(4): 342-365.
42(8): 1095-1104.
[44] Venkatesh V, Speier C, Morris M G. User acceptance en-
[56] Koufaris M. Applying the technology acceptance model
ablers in individual decision making about technology:
and flow theory to online consumer behavior. Information
Toward an integrated model. Decision Sciences, 2002, 33(2): 297-316. [45] Moon J-W, Kim Y-G. Extending the TAM for a worldwide-web context. Information & Management, 2001, 38(4): 217-230. [46] Csikszentmihalyi M. Beyond Boredom and Anxiety. San Francisco, CA, USA: Jossey-Bass, 1975. [47] Webster J, Trevino L K, Ryan L. The dimensionality and correlates of flow in human-computer interactions. Computers in Human Behavior, 1993, 9(4): 411-426. [48] Agarwal R, Karahanna E. Time flies when you’re having fun: Cognitive absorption and beliefs about information technology usage. MIS Quarterly, 2000, 24(4): 665-694. [49] Blythe M, Hassenzahl M, Wright P. More funology. Interactions, 2004, 11(5): 37. [50] Igbaria M, Iivari J, Maragahh H. Why do individuals use computer technology? A Finnish case study. Information & Management, 1995, 29(5): 227-238. [51] Teo T S H, Lim V K G, Lai R Y C. Intrinsic and extrinsic motivation in Internet usage. Omega: International Journal of Management Science, 1999, 27(1): 127-145.
Systems Research, 2002, 13(2): 205-233. [57] Van der Heijden H. User acceptance of hedonic information systems. MIS Quarterly, 2004, 28(4): 695-704. [58] Shang R-A, Chen Y-C, Shen L. Extrinsic versus intrinsic motivations for consumers to shop on-line. Information & Management, 2005, 42(3): 401-413. [59] Babin B J, Darden W R, Griffen M. Work and/or fun: Measuring hedonic and utilitarian shopping value. Journal of Consumer Research, 1994, 20(4): 644-656. [60] Childers T L, Carr C L, Peck J, Carson S. Hedonic and utilitarian motivations for online retail shopping behavior. Journal of Retailing, 2001, 77(4): 511-535. [61] Jarvenpaa S L, Todd P A. Consumer reactions to electronic shopping on the world wide web. International Journal of Electronic Commerce, 1997, 1(2): 59-88. [62] Reynolds K E, Beatty S E. A relationship customer typology. Journal of Retailing, 1999, 75(4): 509-523. [63] Reynolds K E, Beatty S E. Customer benefits and company consequences of customer-salesperson relationships in retailing. Journal of Retailing, 1999, 75(1): 11-32.
Applying TAM in B2C E-Commerce Research: An Extended Model QIU Lingyun (邱凌云)**, LI Dong (李 东) Guanghua School of Management, Peking University, Beijing 100871, China Abstract: As one of the most widely accepted adoption models in information systems research, the technology acceptance model (TAM) focuses exclusively on cognition-oriented constructs such as perceived usefulness and perceived ease of use. This perspective may have limited the explanatory power of TAM when it is utilized in studying consumers’ adoption intentions of online shopping. Based on the contrasts between e-commerce systems and traditional workplace information systems as well as empirical findings from a variety of recent e-commerce research works, this paper analyzes an extended model which integrates three additional constructs: trust, social presence, and perceived enjoyment. The interrelationship between these constructs is also explained. Empirical validations of this extended model are expected in future research. Key words: technology acceptance model (TAM); B2C electronic commerce; online shopping; social presence; trust; perceived enjoyment
Introduction B2C (business-to-consumer) electronic commerce has not only shifted many aspects of our daily life, but also attracted many researchers’ interests in studying various facets associated with the adoption and use of online shopping[1]. Early research in e-commerce adopted a transactional perspective to focus on customer-company exchanges by investigating ways to improve the efficiency of an e-commerce website[2] with much of the research work using the technology acceptance model (TAM)[3] to explain online shoppers’ intentions to adopt a specific website or use a particular feature provided by online retailers. In recent studies, researchers have argued that online shopping websites should be designed with the goal of enhancing the customer’s overall experience[4,5]. Due Received: 2007-06-06; revised: 2007-12-15
﹡ ﹡To whom correspondence should be addressed. E-mail: [email protected]; Tel: 86-10-62757557
to the high cost of attracting and retaining customers, online retailers should not narrowly focus on the utilitarian value that their websites offer. Instead, they should realize the importance of building ongoing steady relationships with their customers, as well as providing them with a gratifying shopping experience. This paper describes a theoretical extension to the classical TAM model which integrates the factors of relationship building and hedonic experience. These addition constructs could provide a better understanding of many factors that affect the relationships between customers and online stores, especially those concerning the design of the website features and interface.
1
Technology Acceptance Model (TAM)
The TAM has become one of the most widely used theories in information systems research since proposed by Davis et al. in 1989[3]. The origins of TAM
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can be traced to the theory of reasoned action (TRA)[6]. The TRA requires that salient beliefs about one’s attitude towards a particular behavior (e.g., buying on the web) be elicited every time the behavior occurs in order to be relevant to the specific behavior being studied. As a simplification to TRA, the TAM suggests that the users’ decisions to accept a new information technology are based on two rational assessments of its expected outcomes: (1) perceived usefulness (PU), defined as the users’ expectation that using a new information technology could result in improved job performance, and (2) perceived ease of use (PEOU), defined as “the degree to which a person believes that using a particular system would be free of effort”[3]. Thanks to its straightforwardness and conciseness, the TAM makes information technology (IT) adoption research more efficient and facilitates the aggregation of results across settings. Its effectiveness has been established by numerous empirical studies[7]. Most empirical studies provide strong evidences that PU does directly influence users’ intentions of adopting a new technology. In contrast, the effects of PEOU are more controversial. In the original TAM, Davis argued that PEOU affects intended use primarily through PU, while other researchers have found that PEOU may sometimes directly influence IT adoption when the task is intrinsic to the IT[8].
2
Extended Model for Online Shopping
Most earlier TAM research focused on corporate information systems as well as professional users or employees who rely on these workplace systems to complete their jobs; therefore, it has paid exclusive attention to the cognitive beliefs, such as perceived usefulness and ease of use, and focused on the more extrinsic and utilitarian determinants of users’ intentions to accept and adopt the system. However, users’ decisions to adopt an online shopping website have a number of major differences: (1) most users of e-commerce systems are not professional IT workers and some are not even familiar with mainstream information technologies; (2) the IT systems (i.e., the shopping websites) used by the user usually do not belong to the company where the user is working; and (3) on most occasions, the tasks a user attempts to complete through
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interacting with an e-commerce system, either buying a product or browsing for information, are not mandatory, or at least the users have alternative means to perform the work. For example, shoppers can always go to a physical store to complete the transaction. With these major concerns in mind, e-commerce websites nowadays provide a range of features to address users’ various psychological needs rather than facilitating the purchasing procedure alone. For example, an online store could promote more social interactions between shoppers and service representatives by offering “live help” services or enhance users’ communications with each other through product reviews or discussion forums. In addition, with the help of Macromedia Flash and other multimedia software, many websites offer visitors a more enjoyable experience with functionalities such as animated product demos or humanoid recommendation agents. All these phenomena call for additional factors to be integrated into the original transaction-oriented TAM variables in the study of online shopping adoption behavior. This paper presents an extended TAM model based on recent studies on e-commerce adoptions, which includes three supplementary constructs, trust, social presence, and perceived enjoyment. This extended model is shown in Fig. 1. The following section gives an overview of these three constructs, followed by analyses of the roles they play in users’ perceptions of their interactions with e-commerce websites. 2.1
Trust
Establishing and maintaining a long-term relationship with customers are critical for any retail store[9-12]. An e-commerce relationship represents a social system in which a customer is interacting with a company embodied by a website. In marketing studies, the concept of relationship quality, which to a great extent determines future sales opportunities[10], is composed of trust in a salesperson[13] and satisfaction with a salesperson[9]. This paper focuses on the construct of trust. Trust is an important indicator reflecting the quality of interpersonal social relationships[14-16]. As a social construct that originates from interpersonal relationships[17], trust is one of the most desired qualities in any close relationship[18], as well as one that significantly
QIU Lingyun (邱凌云) et al.：Applying TAM in B2C E-Commerce Research: An Extended Model
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Fig. 1 Extended TAM model for online shopping
influences users’ intentions to adopt technological artifacts when they are perceived as social actors[19,20]. Recent research has analyzed trust from four major perspectives: (1) viewing trust as a belief or a collection of beliefs that the trustee has attributes that are beneficial to the trustor[21]; (2) viewing trust as an emotional feeling of security, comfort, and lack of fear[22]; (3) viewing trust as an intention or the willingness of a party to be vulnerable to the actions of another party[23]; and (4) viewing trust as a combination of these elements[24]. In traditional commerce, trust usually refers to the interpersonal trust between consumers and salespeople. In contrast, prior research on online consumer trust has focused on consumers’ trust towards either a website or a company[19,24,25]. There has been a debate about whether belief constructs such as trust can be applied to technological artifacts, especially in terms of beliefs about benevolence and integrity[26,27]. However, recent studies in social psychology have revealed that, due to years of continuous interactions with other people, consumers generally possess mental models that they apply to computers or other technological artifacts, ascribing social behavior and social attribute to the technology, especially when the technology possesses a set of characteristics normally associated with human behavior[28]. Recent studies on product recommendation agents have also indicated that although the formation processes of customer trust/distrust belief in “virtual salespersons” (software agents) and human salespersons are slightly different, trust in a software agent also contains belief in competence, benevolence, and integrity[29], similar to trust in a human salesperson[30]. The connections between trust and the TAM constructs have been widely discussed in previous studies[20,31-33]. Gefen et al.[31] integrated consumer trust
into the traditional TAM model in the context of online shopping, arguing that trust, conceptualized as a set of trusting beliefs towards an online vendor, directly affects intentions to use a B2C website, along with perceived usefulness (PU) and perceived ease of use (PEOU). Trust in a merchant can also affect PU in both the short term and the long term. In addition, PEOU has been hypothesized to exert a positive influence on trust, as PEOU can help promote consumers’ favorable impressions of e-vendors in the initial adoption and can enhance consumers’ willingness to make an investment and a commitment in buyer-seller relationships. Wang and Benbasat[20] have extended this integrated trust-TAM model to the context of online recommendation agents. Similarly, they have found that initial trust in online recommendation agents can positively affect intentions to adopt agents as well as the consumers’ perceived usefulness of the agent. Therefore, in our extended TAM model, we propose that: Proposition 1 Users’ trust in an e-commerce website will positively affect their intentions to adopt the website. Proposition 2 Users’ trust in an e-commerce website will positively affect perceived usefulness of the website. Proposition 3 Perceived ease of use of an ecommerce website will positively affect trust in the website. 2.2
Social presence
Shopping activities, on one hand, are analytical tasks during which a shopper tries to identify her needs and makes decisions on purchasing the products that best satisfy her. On the other hand, shopping activities are social experiences consisting of interacting with other people, such as friends, salespeople, and other
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shoppers. Nevertheless, when consumers shop online, the lack of social interactions and the absence of a “human touch” are significant disadvantages or even inhibitors[34]. In the communication literature, this feeling of “being together with others” is defined as social presence. The term social presence was first used in studies of interpersonal communications within organizations, to compare the effects of various types of telecommunication technologies for remote business meetings. It was originally developed to measure people’s subjective perceptions of other people when the communication is mediated by a communication medium. Defined as the subjective evaluation of a communication medium on “the degree of salience of the other person in the interaction and consequent salience of the interpersonal relationships”[35], it also describes the extent to which a medium is perceived as sociable, warm, sensitive, personal, or intimate when it is used to interact with other people[36]. In traditional social presence theory, social presence is defined as the characteristic that describes the capacity of each medium to give immediate feedback as well as a variety of communication cues. It is conceptualized as a subjective measure of a communication medium, which is exclusively determined by the characteristics of the medium.[35] However, recent viewpoints[37] have tended to conceptualize social presence “as a transient phenomenological state that varies with medium, knowledge of the other, content of the communication, environment, and social context.” We concur with Biocca et al.[37] that users’ feelings of social presence are formed through communication processes; therefore, the users are influenced not only by the medium, but also by the communication content and their possible courses of action as well. In other words, social presence is a subjective measure developed over the entire course of the interactions, rather than arising from a static inventory of various features of a communication medium. As mentioned above, social presence is particularly relevant in online shopping environment. For example, to offer online shoppers perceptions similar to what they could experience in the physical world, some ecommerce websites have attempted to reproduce consumer-to-serviceperson interactions through real-time online service features, such as “live help,” or to
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simulate interpersonal communications between shopping buddies by offering collaborative browsing and instant messaging tools. Emerging Web 2.0 technologies, such as Blog, Tag, and Wiki, are also being examined by online retailers with the goal of enhancing social communications among users. Social presence has been related to the TAM variables as well. Gefen et al.[31] have examined the effects of social presence on consumer trust in e-services, finding that social presence affects consumer trust, with the increased trust subsequently having a stronger effect on purchase intentions than TAM beliefs. Lee and Nass[38] also identified a significant mediating effect of social presence on website content credibility in their study of the effects of multiple synthetic voices in e-commerce context. In their study of IT-enabled support for personalization systems and virtual communities in online shopping websites, Kumar and Benbasat[39] found that social presence and perceived usefulness both significantly affect customer loyalty. In our extended model, we agree with Gefen and Straub[19] that the social presence an e-commerce website affords can positively contribute to consumer trust. In face-to-face human interactions, trustworthiness is usually manifested by a plethora of trivial but important social cues. As inexperienced users interact with a website for the first time, they have very few cues to judge an online store’s trustworthiness. As Fogg and Tseng[40] have pointed out, the impressions formed through simple inspection of “surface attributes” can directly influence users’ attitudes and behavior. When the interaction with a store is perceived as socially warm, the general social convention that “a nice person is usually trustworthy” is automatically applied. In addition, social presence, especially when supported by social network functionalities (e.g., consumer reviews, product discussion forums, or tagging) could to some extent address users’ social needs during shopping, which may consequently enhance their intentions of making purchases online. Proposition 4 Users’ perceptions of social presence will positively affect their trusting beliefs in an ecommerce website. Proposition 5 Users’ perceptions of social presence will positively affect their intentions to adopt an e-commerce website.
QIU Lingyun (邱凌云) et al.：Applying TAM in B2C E-Commerce Research: An Extended Model
2.3
Perceived enjoyment
Perceived enjoyment refers to the extent to which the activity of interacting with the e-commerce website is perceived to be enjoyable in its own right aside from the utilitarian value of the site[41]. It is closely related to the concept of intrinsic motivation, which refers to “the performance of an activity for no apparent reinforcement other than the process of performing the activity per se”[41]. The importance of intrinsic motivation as a lever to create favorable user perceptions has been empirically demonstrated[42-44]. In the human-computer interaction (HCI) and information systems literature, perceived enjoyment has been considered as a sub-dimension of various constructs measuring users’ intrinsic motivation towards or enjoyable experience from using a technology. For example, Moon and Kim[45] presented perceived enjoyment as a dimension of perceived playfulness, an intrinsic belief or motive formed from an individual’s subjective experiences using a technology such as the Internet. Perceived enjoyment is also included as a component of flow, which was initially presented as an optimal and enjoyable experience in which people are completely absorbed in their activities[46]. The flow construct was later adapted to the context of information technology and computer-mediated environments as a subjective psychological experience, in which the human-computer experience is characterized as playful and exploratory[47]. Enjoyment is also recognized as one of the five dimensions of cognitive absorption, a similar construct which describes a state of deep involvement with software[48]. In recent years, perceived enjoyment has received increasing interest in IS research, as researchers start to acknowledge that how enjoyable an information system is may be as important as how usable and useful it is[49]. Fun and enjoyment in the home and leisure context are as important as productivity and efficiency in the work context. The influence of enjoyment perceptions on users’ technology adoption intentions has been empirically examined in applications such as general computer usage[50], Internet usage[45,51,52], instant messaging tools[53], Internet-based learning medium[54,55], and online shopping[56,57]. Perceived enjoyment is considered to be an important addendum to the original TAM[41]. The IS
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literature includes studies that have demonstrated that enjoyment influences usefulness through the mediation of ease of use[43]. Others have found that, while intrinsic motivation has no direct influence on intention to use technology, it can serve as an important predictor for both perceived usefulness and perceived ease of use[44,54]. Recent research on non-workplace information systems, such as the Internet, online shopping, and video games, has suggested a more important role for perceived enjoyment. It is not only an immediate antecedent to perceived usefulness, but it is also more important to adoption of information systems[42,45,51,53,57,58]. Van der Heijden[57] argued that these systems share common characteristics with hedonic systems, which aim to provide self-fulfilling value to users, in contrast to utilitarian systems that aim to provide instrumental value to users. The encouragement of “prolonged use”, rather than “productive use”, should be the dominant design objective of hedonic systems. Although Van der Heijden[57] dichotomized information systems into either utilitarian or hedonic, we contend that many information systems possess the characteristics of both at the same time, especially for systems developed for home use, such as computer-aided tutoring systems and online shopping websites. Correspondingly, most marketing research suggests that individuals’ shopping behavior is driven by both instrumental and hedonic motivations[59]. Consumers’ shopping values are subjective, characterized by their interactions with an environment and indicated by both the event’s usefulness and an appreciation of its activities. Hedonic shopping motives are similar to the task orientation of utilitarian shopping motives, only the task is concerned with hedonic fulfillment, such as experiencing fun, amusement, fantasy, and sensory stimulation[59]. Past studies[60] have indicated that the hedonic and immersive aspects of an online shopping website are as important predictors of shopper’s attitude as the instrumental aspects. As a result, shopping enjoyment can be an important determinant of online customer loyalty[56,61]. Research has shown that when customers experience positive emotions, they tend to be more satisfied with their buyer-seller relationships[62] and they are more likely to complete a purchase[63]. In our extended model, we propose that for users of an online shopping website, perceived enjoyment can
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exert both direct and indirect influences on their adoption intentions and the task a user is trying to perform will very likely moderate the potential influence of this construct. As argued by Van der Heijden[57], the unmediated impacts of perceived enjoyment on adoption intentions are manifest only among hedonicoriented systems, in which the instrumental values of the system are less important than the pleasurable experience a user acquires from the usage. When the primary task of an online shopper is to complete a purchase through the website, the extrinsic motivations— find the right product and pay for it—are still the primary incentives for a user to interact with the site. When the website is fun to use, users will perceive the task as being less tiring and the users are likely to be more engaged in the task and, therefore, more likely to complete the task. Therefore, the impacts of perceived enjoyment on behavioral intentions will be fully mediated by perceived usefulness and perceived ease of use. On the other hand, when the major goal of an online shopper is limited to non-transaction related activities such as to browse the product information (“Windowshopping” in the virtual world) or interacting with other users on the discussion forum, the enjoyment perception will make the website more attractive and, thus, directly influence the users’ adoption intentions. Proposition 6 Users’ perceptions of enjoyment will positively affect perceived usefulness of an ecommerce website. Proposition 7 Users’ perceptions of enjoyment will positively affect perceived ease of use of an ecommerce website. Proposition 8 Users’ perceptions of enjoyment will positively affect their intentions to adopt an ecommerce website. In summary, despite its well-established applicability in workplace systems, the original TAM fails to offer an adequate explanation for users’ attitudes and adoption behaviors towards online shopping. The three constructs proposed in the extended model can exert equally, if not more, significant effects. In addition, these constructs may affect users’ attitudes indirectly by interactions with the traditional TAM constructs.
3
Conclusions and Future Research
An extended TAM model was developed to explain users’ adoption behavior when shopping online based
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on comparisons between online shopping websites and traditional workplace information systems and their respective users. In addition to the traditional utilitybased TAM variables, three additional factors and the interrelationship between these variables are viewed as important constructs for explaining users’ online shopping behavior. The value of this model should be examined by empirical investigations in future research. Other factors, such as product category or individual user differences, might moderate or mediate the impacts of these constructs. Therefore, more theoretical and emprical studies are needed to extend the TAM, one of the most established theories in IS research, to various new scenarios introduced by emerging information technologies. References [1]
Ngai E W T, Wat F K T. A literature review and classification of electronic commerce research. Information & Management, 2002, 39(5): 415-429.
[2]
Lohse G, Spiller P. Electronic shopping. Communication of the ACM, 2001, 41(7): 81-87.
[3]
Davis F D. Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Quarterly, 1989, 13(3): 319-339.
[4]
Keen P. Relationships—The electronic commerce imperative. In: Dickson G, Desanctis G, eds. Information Technology and the Future Enterprise: New Models for Managers. Upper Saddle River, New Jersey, USA: Prentice Hall, 2000: 163-185.
[5]
Kumar N, Benbasat I. Para-social presence and communication capabilities of a web site: A theoretical perspective. e-Service Journal, 2002, 1(3): 5-24.
[6]
Fishbein M, Ajzen I. Beliefs, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Reading, MA, USA: Addison-Wesley, 1975.
[7]
Lee Y, Kozar K A, Larsen K R T. The technology acceptance model: Past, present, and future. Communication of the Association for Information Systems, 2003, 12: 752780.
[8]
Gefen D. The relative importance of perceived ease of use in IS adoption: A study of e-commerce adoption. Journal of Association for Information Systems, 2000, 1: article 8. http://jais.aisnet.org/articles/default.asp?vol=1&art=8.
[9]
Crosby L A, Stephens S. Effects of relationship marketing on satisfaction, retention, and prices in the life insurance industry. Journal of Marketing Research, 1987, 24(4):
QIU Lingyun (邱凌云) et al.：Applying TAM in B2C E-Commerce Research: An Extended Model 404-411. [10] Crosby L A, Evans K, Cowles D. Relationship quality in services selling: An interpersonal influence perspective. Journal of Marketing, 1990, 54(3): 68-81. [11] Berry L L. Relationship marketing of services: Growing interest, emerging perspectives. Journal of the Academy of Marketing Science, 1995, 23(Fall): 236-245. [12] Morgan R M, Hunt S D. The commitment-trust theory of relationship marketing. Journal of Marketing, 1994, 58(July): 20-38. [13] Swan J E, Trawick F I. Measuring dimensions of purchaser trust of industrial salespeople. Journal of Personal Selling and Sales Management, 1988, 8(1): 1-9. [14] Blau P. Exchange and Power in Social Life. New York, USA: Wiley, 1964. [15] Fukuyama F. Trust: The Social Virtues and the Creation of Prosperity. New York, USA: The Free Press, 1995. [16] Luhmann N. Trust and Power. London: John Wiley and Sons, 1979. [17] Sztompka P. Trust: A Sociological Theory. Cambridge, UK: Cambridge University Press, 1999. [18] Rempel J K, Holmes J G, Zanna M P. Trust in close relationship. Journal of Personality and Social Psychology, 1985, 49(1): 95-112. [19] Gefen D, Straub D. Managing user trust in B2C e-services. e-Service Journal, 2003, 2(2): 7-24. [20] Wang W, Benbasat I. Trust in and adoption of online recommendation agents. Journal of the Association for Information Systems, 2005, 6(3): 72-101. [21] Bhattacherjee A. Individual trust in online firms: Scale development and initial test. Journal of Management Information Systems, 2002, 19(1): 211-241. [22] Komiak S X, Benbasat I. Understanding customer trust in
271
Concepts, evolving themes, a model. International Journal of Human-Computer Studies, 2003, 58(6): 737-758. [27] Chopra K, Wallace W A. Trust in electronic environment. In: Proceedings of 36th Hawaii International Conference on System Sciences. Big Island, Hawaii, 2003. [28] Reeves B, Nass C. The Media Equation: How People Treat Computers, Television, and New Media like Real People and Places. New York, USA: Cambridge University Press, 1996. [29] Cassell J, Bickmore T. External manifestations of trustworthiness in the interface. Communications of the ACM, 2000, 43(12): 50-56. [30] Komiak S X, Wang W, Benbasat I. Comparing customer trust in virtual salespersons with customer trust in human salesperson. In: Proceedings of 38th Hawaii International Conference on System Sciences. Big Island, Hawaii, 2005. [31] Gefen D, Karahanna E, Straub D W. Trust and TAM in online shopping: An integrated model. MIS Quarterly, 2003, 27(1): 51-90. [32] Pavlou P A. Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model. International Journal of Electronic Commerce, 2003, 7(3): 101-134. [33] Wu I L, Chen J L. An extension of trust and TAM model with TPB in the initial adoption of on-line tax: An empirical study. International Journal of Human-Computer Studies, 2005, 62(6): 784-808. [34] Qiu L, Jiang Z, Benbasat I. Real experience in your virtual store: Designing presence in online shopping. In: Proceedings of the 10th Pacific-Asia Conference on Information Systems (PACIS 2006). Kuala Lumpur, Malaysia, 2006. [35] Short J, Williams E, Christie B. The Social Psychology of Telecommunication. London: John Wiley & Sons, 1976.
agent-mediated electronic commerce, web-mediated elec-
[36] Lombard M, Ditton T. At the heart of it all: The concept of
tronic commerce, and traditional commerce. Information
presence. Journal of Computer-Mediated Communication,
Technology and Management, 2004, 5(1&2): 181-207.
1997, 3(2). http://jcmc.indiana.edu/vol3/issue2/lombard.
[23] Mayer R C, Davis J H. An integrative model of organizational trust. Academy of Management Review, 1995, 20(3): 709-734. [24] McKnight D H, Choudhury V, Kacmar C. Developing and validating trust measures for e-commerce: An integrative typology. Information Systems Research, 2002, 13(3): 334359. [25] Hoffman D L, Novak T P, Peralta M. Building consumer trust online. Communications of the ACM, 1999, 42(4): 80-85. [26] Corritore C L, Kracher B, Wiedenback S. On-line trust:
html. [37] Biocca F, Harms C, Burgoon J K. Towards a more robust theory and measure of social presence: Review and suggested criteria. Presence: Teleoperators and Virtual Environments, 2003, 12(5): 456-480. [38] Lee K M, Nass C. The multiple source effect and synthesized speech: Doubly-disembodied language as a conceptual framework. Human Communication Research, 2004, 30(2): 182-207. [39] Kumar N, Benbasat I. The influence of recommendations and consumer reviews on evaluations of websites.
272 Information Systems Research, 2006, 17(4): 425-439. [40] Fogg B J, Tseng H. The elements of computer credibility. In: Proceedings of ACM SIGCHI Conference on Human Factors in Computing Systems (CHI’99). Pittsburgh, Pennsylvania, USA, 1999: 80-87. [41] Davis F D, Bagozzi R P, Warshaw P R. Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 1992, 22(14): 11111132.
Tsinghua Science and Technology, June 2008, 13(3): 265-272 [52] Van der Heijden H. Factors influencing the usage of websites: The case of a generic portal in the Netherlands. Information & Management, 2003, 40(6): 541-549. [53] Li D, Chau P Y K, Lou H. Understanding individual adoption of instant messaging: An empirical investigation. Journal of the Association for Information Systems, 2005, 6(4): 102-129. [54] Yi M Y, Hwang Y. Predicting the use of web-based information systems: Self-efficacy, enjoyment, learning goal
[42] Venkatesh V. Creation of favorable user perceptions: Ex-
orientation, and the technology acceptance model. Interna-
ploring the role of intrinsic motivation. MIS Quarterly,
tional Journal of Human-Computer Studies, 2003, 59(4):
1999, 23(2): 239-260.
431-449.
[43] Venkatesh V. Determinants of perceived ease of use: Inte-
[55] Lee M K O, Cheung C M K, Chen Z. Acceptance of Inter-
grating control, intrinsic motivation, and emotion into the
net-based learning medium: The role of extrinsic and in-
technology acceptance model. Information Systems Re-
trinsic motivation. Information & Management, 2005,
search, 2000, 11(4): 342-365.
42(8): 1095-1104.
[44] Venkatesh V, Speier C, Morris M G. User acceptance en-
[56] Koufaris M. Applying the technology acceptance model
ablers in individual decision making about technology:
and flow theory to online consumer behavior. Information
Toward an integrated model. Decision Sciences, 2002, 33(2): 297-316. [45] Moon J-W, Kim Y-G. Extending the TAM for a worldwide-web context. Information & Management, 2001, 38(4): 217-230. [46] Csikszentmihalyi M. Beyond Boredom and Anxiety. San Francisco, CA, USA: Jossey-Bass, 1975. [47] Webster J, Trevino L K, Ryan L. The dimensionality and correlates of flow in human-computer interactions. Computers in Human Behavior, 1993, 9(4): 411-426. [48] Agarwal R, Karahanna E. Time flies when you’re having fun: Cognitive absorption and beliefs about information technology usage. MIS Quarterly, 2000, 24(4): 665-694. [49] Blythe M, Hassenzahl M, Wright P. More funology. Interactions, 2004, 11(5): 37. [50] Igbaria M, Iivari J, Maragahh H. Why do individuals use computer technology? A Finnish case study. Information & Management, 1995, 29(5): 227-238. [51] Teo T S H, Lim V K G, Lai R Y C. Intrinsic and extrinsic motivation in Internet usage. Omega: International Journal of Management Science, 1999, 27(1): 127-145.
Systems Research, 2002, 13(2): 205-233. [57] Van der Heijden H. User acceptance of hedonic information systems. MIS Quarterly, 2004, 28(4): 695-704. [58] Shang R-A, Chen Y-C, Shen L. Extrinsic versus intrinsic motivations for consumers to shop on-line. Information & Management, 2005, 42(3): 401-413. [59] Babin B J, Darden W R, Griffen M. Work and/or fun: Measuring hedonic and utilitarian shopping value. Journal of Consumer Research, 1994, 20(4): 644-656. [60] Childers T L, Carr C L, Peck J, Carson S. Hedonic and utilitarian motivations for online retail shopping behavior. Journal of Retailing, 2001, 77(4): 511-535. [61] Jarvenpaa S L, Todd P A. Consumer reactions to electronic shopping on the world wide web. International Journal of Electronic Commerce, 1997, 1(2): 59-88. [62] Reynolds K E, Beatty S E. A relationship customer typology. Journal of Retailing, 1999, 75(4): 509-523. [63] Reynolds K E, Beatty S E. Customer benefits and company consequences of customer-salesperson relationships in retailing. Journal of Retailing, 1999, 75(1): 11-32.