Factors Affecting Re-usage Intentions of Virtual Communities Supporting Cosmetic Products

INTRODUCTION The business world has assumed that virtual communities (VC) can be leveraged to provide access to consumers and consumer data (Spaulding, 2010). According to the summary report of the Taiwan Network Information Center (TWNIC) in July 2016, the Internet use rate in Taiwan was up to 84.8%, whereas the VC use rate was up to 64.4%, thereby implying that VC gained the attention of Internet users. By contrast, the growth rate of VC from 2015 to 2016 increased 30%, thus indicating a promising business opportunity. Participation in a VC is related to the delivery of a variety of services to users within all sectors, to computer-supported collaborative tasks within information services, and to both informal and formal activities for professional updating, learning, and development (Levy, 1997). Pai and Tsai (2011) found that VC participation significantly enhances consumer loyalty intentions. Accordingly, applying VC in communication with online customers can be a significant approach for strategy planning. A cosmetic-related VC is often provided on a cosmetic-related website, such as a customer forum. For example, UrCosme (https://wwwurcosme.com), the first cosmetic-related portal site in Taiwan, allows cosmetic users to share their experiences in cosmetic product use. Currently, 103,700 articles of usage experience and 74,465 cosmetic product data are accumulated in its database, and 442,257 members have registered. UrCosme provides rich information about cosmetics and beauty care, which members can browse through before shopping. When buying cosmetic products, most consumers search for related information on the Internet, such as blogs and cosmetic-related websites, before making a decision (Insightxplorer, 2013). Compared with TV and magazines, cosmetic websites affect consumer purchase intentions the most, and after searching for cosmetic information online, more than 40% people would like to purchase afterward (Insightxplorer, 2013). Therefore, we consider that understanding the determinants of re-usage intention related to this kind of VC is important for encouraging customers who continuously wander in a cosmetic-related VC. Industries that want to apply VC as a marketing tool to perform marketing activities can then have a specific guideline for strategic planning. Many theoretical models, such as the technology acceptance model (TAM), theory of reasoned action (TRA), and theory of planned behavior (TPB), have been applied to examine human behavioral intentions. Davis (1989) indicated that these models could successfully predict the acceptance of an innovation at about 40%. Superior to these models is the Unified Theory of Acceptance and Use of Technology model (UTAUT), a technology innovation acceptance model that can account for an impressive 70% of the variance in behavioral intention and 50% of actual usage (Venkatesh, Thong, & Xu, 2012). Thus, the authors of this study were motivated to use UTAUT as the theoretical framework to conduct an empirical study using cosmetic-related VC (an IT-based and self-supported business application) as the research context. The specific purposes of this study were: (1) to understand whether or not UTAUT can provide a solid theoretical basis for examining VC re-usage in cosmetics web business; (2) to investigate the factors affecting VC members' VC re-use intentions; and (3) to determine the potential moderating effects of demographic variables. Answers to these questions can assist industries to solve business promotion problems and to design a more effective online marketing strategy. The remainder of this paper presents first the relevant studies on VC, the UTAUT model, and an overview of cosmetic products sales in the Literature Review section. In the Methodology section, we present the research method including our research model, development of the hypotheses, questionnaire design, and data-collecting process. We discuss in detail the analysis results in the Analysis and Result section. …

[1]  E. Carvajal-Trujillo,et al.  Online purchasing tickets for low cost carriers: An application of the unified theory of acceptance and use of technology (UTAUT) model , 2014 .

[2]  Hsien-Tung Tsai,et al.  How virtual community participation influences consumer loyalty intentions in online shopping contexts: an investigation of mediating factors , 2011, Behav. Inf. Technol..

[3]  Héctor San Martín,et al.  Influence of the user's psychological factors on the online purchase intention in rural tourism: integrating innovativeness to the UTAUT framework. , 2012 .

[4]  J. Miller,et al.  Toward a new psychology of women , 1976 .

[5]  G. Hutton Net gain: Expanding markets through virtual communities , 1998 .

[6]  Wuu-Yee Chen,et al.  Factors Affecting Consumers' Motivation in Online Group Buyers , 2010, 2010 Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing.

[7]  Gi Mun Kim,et al.  Understanding dynamics between initial trust and usage intentions of mobile banking , 2009, Inf. Syst. J..

[8]  Hsiu-Yuan Wang,et al.  User acceptance of mobile internet based on the Unified Theory of Acceptance and Use of Technology: Investigating the determinants and gender differences , 2010 .

[9]  K. Williamson,et al.  Understanding Consumer Adoption of Internet Banking: An Interpretive Study in the Australian Banking Context , 2006 .

[10]  Judith Donath,et al.  Identity and deception in the virtual community , 1998 .

[11]  L. Hamre Exploring the use of social capital to support technology adoption and implementation , 2008 .

[12]  F. Rothaermel,et al.  Virtual internet communities and commercial success: individual and community-level theory grounded in the atypical case of TimeZone.com , 2001 .

[13]  Bin Wang,et al.  From virtual community members to C2C e-commerce buyers: Trust in virtual communities and its effect on consumers' purchase intention , 2010, Electron. Commer. Res. Appl..

[14]  Anna Grimán,et al.  Critical success factors for a customer relationship management strategy , 2007, Inf. Softw. Technol..

[15]  G. Hofstede,et al.  Culture′s Consequences: International Differences in Work-Related Values , 1980 .

[16]  Zoonky Lee,et al.  Social influence on technology acceptance behavior: self-identity theory perspective , 2006, DATB.

[17]  Sameer Kumar,et al.  Comparative innovative business strategies of major players in cosmetic industry , 2006, Ind. Manag. Data Syst..

[18]  Jerold L. Hale,et al.  The Theory of Reasoned Action , 2002 .

[19]  Sunanda Sangwan,et al.  Virtual Community Success: A Uses and Gratifications Perspective , 2005, Proceedings of the 38th Annual Hawaii International Conference on System Sciences.

[20]  A. Bandura Self-efficacy: toward a unifying theory of behavioral change. , 1977, Psychology Review.

[21]  Shirley Dyer,et al.  Adoption of business information systems in an automotive manufacturing environment: a case study , 2008 .

[22]  Fred D. Davis Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[23]  Guo-yin Jiang,et al.  User Transfer in Collaborative Commerce: Evident from Virtual Community to Social Commerce , 2013 .

[24]  Jiyoung Kim,et al.  Social Capital in the Chinese Virtual Community: Impacts on the Social Shopping Model for Social Media , 2014 .

[25]  John Marumbwa,et al.  Exploring the Moderating Effects of Socio-Demographic Variables on Consumer Acceptance and Use of Mobile Money Transfer Services (MMTs) in Southern Zimbabwe , 2014 .

[26]  Jijie Wang,et al.  Information technology (IT) in Saudi Arabia: Culture and the acceptance and use of IT , 2007, Inf. Manag..

[27]  Joan Meyers-Levy,et al.  The Influence of Sex Roles on Judgment , 1988 .

[28]  R. Bagozzi,et al.  A Social Influence Model of Consumer Participation in Network- and Small-Group-Based Virtual Communities , 2004 .

[29]  Agnetha Broos,et al.  Gender and Information and Communication Technologies (ICT) Anxiety: Male Self-Assurance and Female Hesitation , 2005, Cyberpsychology Behav. Soc. Netw..

[30]  J. H. Vineburgh A Study of Organizational Trust and Related Variables among Faculty Members at HBCUs. , 2010 .

[31]  Thomas B. Lawrence POWER AND RESOURCES IN AN ORGANIZATIONAL COMMUNITY. , 1995 .

[32]  Viswanath Venkatesh,et al.  Why Don't Men Ever Stop to Ask for Directions? Gender, Social Influence, and Their Role in Technology Acceptance and Usage Behavior , 2000, MIS Q..

[33]  Philippa Levy,et al.  Virtual communities and information services: an overview , 1997 .

[34]  E. Hargittai,et al.  Differences in Actual and Perceived Online Skills: The Role of Gender* , 2006 .

[35]  P. P. Lynott,et al.  The Impact of Age vs. Life Experience on the Gender Role Attitudes of Women in Different Cohorts , 2000, Journal of women & aging.

[36]  J. Michael Pearson,et al.  Internet banking in Jordan: The unified theory of acceptance and use of technology (UTAUT) perspective , 2007, J. Syst. Inf. Technol..

[37]  Jyh-Jeng Wu,et al.  Trust factors influencing virtual community members: A study of transaction communities , 2010 .

[38]  Mahdi Shadkam,et al.  Influence of Virtual Communities on Online Consumers ’ Trust , .

[39]  Tiago Oliveira,et al.  Understanding the Internet banking adoption: A unified theory of acceptance and use of technology and perceived risk application , 2014, Int. J. Inf. Manag..

[40]  Detmar W. Straub,et al.  Inexperience and experience with online stores: the importance of TAM and trust , 2003, IEEE Trans. Engineering Management.

[41]  Xiaoping Yang,et al.  The Influence of Discussions in Virtual Communities on Consumers' Purchasing Behaviors in E-commerce: Implications for Trust Sources, Trust Building, and Consumer Purchase Intention , 2009, 2009 Fourth International Conference on Computer Sciences and Convergence Information Technology.

[42]  Xinran Y. Lehto,et al.  Gender differences in online travel information search: Implications for marketing communications on the internet , 2007 .

[43]  Manuel J. Sánchez-Franco,et al.  The moderating effect of gender on relationship quality and loyalty toward Internet service providers , 2009, Inf. Manag..

[44]  Izak Benbasat,et al.  Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation , 1991, Inf. Syst. Res..

[45]  France Bélanger,et al.  Gender differences in perceptions of web-based shopping , 2002, CACM.

[46]  Gordon B. Davis,et al.  User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..

[47]  Jerry Wind,et al.  What kind of patients and physicians value direct-to-consumer advertising of prescription drugs , 2000, Health care management science.

[48]  P. Sztompka Trust: A Sociological Theory , 2000 .

[49]  Robert M. Schindler,et al.  Internet forums as influential sources of consumer information , 2001 .

[50]  C. Fornell,et al.  Evaluating structural equation models with unobservable variables and measurement error. , 1981 .

[51]  Almamy Touray,et al.  The Impact of Moderating Factors on Behavioral Intention Towards Internet: a Transnational Perspective , 2013 .

[52]  Berend Wierenga,et al.  Virtual communities: A marketing perspective , 2009, Decis. Support Syst..

[53]  Andrew B. Whinston,et al.  Electronic Communities in E-Business: Their Role and Issues , 2000, Inf. Syst. Frontiers.

[54]  James C. Anderson,et al.  STRUCTURAL EQUATION MODELING IN PRACTICE: A REVIEW AND RECOMMENDED TWO-STEP APPROACH , 1988 .

[55]  A. Athiyaman Internet users’ intention to purchase air travel online: an empirical investigation , 2002 .

[56]  T. Thomas,et al.  The utility of the UTAUT model in explaining mobile learning adoption in higher education in Guyana , 2013 .

[57]  R. Murugan BRAND LOYALTY’S INFLUENCE ON WOMEN’S BUYING BEHAVIOR WITH SPECIAL REFERENCE TO PERSONAL CARE PRODUCTS , 2011 .

[58]  Ming-Chi Lee,et al.  Understanding the behavioural intention to play online games: An extension of the theory of planned behaviour , 2009, Online Inf. Rev..

[59]  Trent J. Spaulding How can virtual communities create value for business? , 2010, Electron. Commer. Res. Appl..

[60]  Natasha Merat,et al.  Acceptance of Automated Road Transport Systems (ARTS): An adaptation of the UTAUT model , 2016 .

[61]  Tom Christensen,et al.  TRUST IN GOVERNMENT: The Relative Importance of Service Satisfaction, Political Factors, and Demography , 2005 .

[62]  Stuart J. Barnes,et al.  Why people buy virtual items in virtual worlds with real money , 2007, DATB.

[63]  Maged Ali,et al.  Extending the UTAUT model to understand the customers' acceptance and use of internet banking in Lebanon: A structural equation modeling approach , 2016, Inf. Technol. People.

[64]  Viswanath Venkatesh,et al.  Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology , 2012, MIS Q..

[65]  Detmar W. Straub,et al.  Gender Differences in the Perception and Use of E-Mail: An Extension to the Technology Acceptance Model , 1997, MIS Q..

[66]  John F. Kihlstrom,et al.  Gemeinschaft and Gesellschaft in Social Psychology. , 1984 .

[67]  Fred D. Davis,et al.  A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies , 2000, Management Science.

[68]  Russ Harris,et al.  The Confidence Gap , 2011 .