Skip to main content

Examining the Underlying Attitudinal Components Driving Technology Adoption, Adaptation Behaviour and Outcome in Entirety

  • Chapter
  • First Online:

Part of the book series: Advances in Theory and Practice of Emerging Markets ((ATPEM))

Abstract

Technology use, adoption and adaptation have been discussed extensively in existing scholarly works but scant consideration is given to technology adoption, adaptation and appropriation. This chapter endeavours to address this gap in the literature by conducting a critical review of the scholarly works to examine the underlying antecedents and discrete adaptation behaviour (the entirety of technology adoption, adaptation and appropriation). The findings of this review reveal that such entirety has the following key underlying joint attitudinal cognitive (perceived opportunity, perceived relative advantage, perceived social influence, perceived control) and affective (enjoyment, self-enhancement, threat, fear and trust) components as antecedents to interaction and leading to discrete adaptation and appropriation behaviour of exploration to maximise and exploitation to satisfice technology benefits on the one hand and exploration to revert from technology to complete abandoning of technology on the other. The conceptual underpinning presented and analysed in this chapter advances the scholarship of technology adoption, adaptation and appropriation in entirety and provides useful direction for future empirical research for both academics and practitioners.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  • Agarwal, R., & Prasad, J. (1999). Are individual differences germane to the acceptance of new information technologies? Decision Sciences, 30(2), 361–391.

    Article  Google Scholar 

  • Agarwal, N., Chauhan, S., Kar, A. K., Goyal, S. (2017). Role of human behaviour attributes in mobile crowd sensing: a systematic literature review. Digital Policy, Regulation and Governance, 19(2):168–185.

    Article  Google Scholar 

  • Ajzen, I. (1991). The theory of planned behaviour. Organizational Behaviour & Human Decision Processes, 50(2), 179–211.

    Article  Google Scholar 

  • Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Upper Saddle River, NJ: Prentice Hall.

    Google Scholar 

  • Akar, E., & Topçu, B. (2011). An examination of the factors influencing consumers’ attitudes toward social media marketing. Journal of Internet Commerce, 10(1), 35–67.

    Article  Google Scholar 

  • Ali, H. (2011). Exchanging value within individuals’ networks: Social support implications for health marketers. Journal of Marketing Management, 27(3/4), 316–335.

    Article  Google Scholar 

  • Ali, M., & Lee, H. (2010, April 12–13). Culture or social interaction? A study of influential factors on weblog design. Paper presented at the European and Mediterranean Conference on Information Systems, Abu Dhabi. Retrieved April 7, 2016, from http://v-scheiner.brunel.ac.uk/bitstream/2438/4305/1/C90.pdf.

  • Al-Jabri, I. M., Sohail, M. S., & Ndubisi, N. O. (2015). Understanding the usage of global social networking sites by Arabs through the lens of uses and gratifications theory. Journal of Service Management, 26(4), 662–680.

    Article  Google Scholar 

  • Al-Gahtani, S. S., Hubona, G. S., Wang, J. (2007). Information technology (IT) in Saudi Arabia: Culture and the acceptance and use of IT. Information & Management, 44(8):681–691.

    Article  Google Scholar 

  • Alwi, S. F. S., & Kitchen, P. J. (2014). Projecting corporate brand image and behavioral response in business schools: Cognitive or affective brand attributes? Journal of Business Research, 67(11), 2324–2336.

    Article  Google Scholar 

  • Amichai-Hamburger, Y., Wainapel, G., & Fox, S. (2002). On the internet no one knows I’m an introvert: Extroversion, neuroticism, and internet interaction. CyberPsychology & Behaviour, 5, 125–128.

    Article  Google Scholar 

  • Armitage, C. J., & Conner, M. (2000). Attitudinal ambivalence: A test of three key hypotheses. Personality and Social Psychology Bulletin, 26(11), 1421–1433.

    Article  Google Scholar 

  • Bala, H., & Venkatesh, V. (2016). Adaptation to information technology: A holistic nomological network from implementation to job outcomes. Management Science, 62(1), 156–179.

    Article  Google Scholar 

  • Beaudry, A., & Pinsonneault, A. (2005). Understanding user responses to information technology: A coping model of user adaptation. MIS Quarterly, 29(3), 493–525.

    Article  Google Scholar 

  • Bharati, P., Zhang, C., & Chaudhury, A. (2014). Social media assimilation in firms: Investigating the roles of absorptive capacity and institutional pressures. Information Systems Frontiers, 16(2), 257–272.

    Article  Google Scholar 

  • Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. Management Information Systems Quarterly, 25(3), 351–370.

    Article  Google Scholar 

  • Blanchard, A., & Markus, M. (2004). The experience ‘sense’ of a virtual community: Characteristics and process. Database for Advances in Information Systems, 35, 65–79.

    Article  Google Scholar 

  • Boudreau, M. C., & Robey, D. (2005). Enacting integrated information technology: A human agency perspective. Organisation Science, 16(1), 3–18.

    Article  Google Scholar 

  • Boyd, D. (2008). Facebook’s privacy trainwreck: Exposure, invasion, and social convergence. Convergence, 14(1), 13–20.

    Article  Google Scholar 

  • Boyd, D. M., & Ellison, N. B. (2007). Social network sites: Definition, history, and scholarship. Journal of Computer-Mediated Communication, 13(1), 210–230.

    Article  Google Scholar 

  • Breckler, S. J. (1984). Empirical validation of affect, behavior, and cognition as distinct components of attitude. Journal of Personality and Social Psychology, 47, 1191–1205.

    Article  Google Scholar 

  • Carroll, J., Howard, S., Peck, J., & Murphy, J. (2003). From adoption to use the process of appropriating a mobile phone. Australian Journal of Information Systems, 10(2), 38–48.

    Google Scholar 

  • Champoux, J. E. (1996). Organizational behavior: Integrating individuals, groups, and process. St. Paul: West Publishing Company.

    Google Scholar 

  • Chang, H. H., & Chuang, S. S. (2011). Social capital and individual motivations on knowledge sharing: Participant involvement as a moderator. Information & Management, 48(1), 9–18.

    Article  Google Scholar 

  • Charlesworth, A. (2014). An introduction to social media marketing. Oxon: Routledge.

    Book  Google Scholar 

  • Cheek, J. M., & Buss, A. H. (1981). Shyness and sociability. Journal of Personality and Social Psychology, 41(2), 330–339.

    Article  Google Scholar 

  • Chen, J. V., Yen, D. C., & Chen, K. (2009). The acceptance and diffusion of the innovative smartphone use: A case study of a delivery service company in logistics. Information & Management, 46(4), 241–248.

    Article  Google Scholar 

  • Cheung, C. M., & Lee, M. K. (2006). Understanding consumer trust in Internet shopping: A multidisciplinary approach. Journal of the American Society for Information Science and Technology, 57(4), 479–492.

    Article  Google Scholar 

  • Cheung, C., Lee, Z. W., & Chan, T. K. (2015). Self-disclosure in social networking sites: The role of perceived cost, perceived benefits and social influence. Internet Research, 25(2), 279–299.

    Article  Google Scholar 

  • Chew, M., Balfanz, D., & Laurie, B. (2008). (Under) mining privacy in social networks. Paper presented at Web 2.0 Security and Privacy 2008, Oakland, CA.

    Google Scholar 

  • Chhonker, M. S., Verma, D., Kar, A. K. (2017). Review of Technology Adoption frameworks in Mobile Commerce. Procedia Computer Science, 122:888–895.

    Article  Google Scholar 

  • Chiang, H. S. (2013). Continuous usage of social networking sites: The effect of innovation and gratification attributes. Online Information Review, 37(6), 851–871.

    Article  Google Scholar 

  • Chiasson, M. W., & Lovato, C. Y. (2001). Factors influencing the formation of a user’s perception and use of a DSS software innovation. Database for Advances in Information Systems, 32(3), 16–35.

    Article  Google Scholar 

  • Chiu, H.-C. (2002). A study on the cognitive and affective components of service quality. Total Quality Management, 13(2), 265–274.

    Article  Google Scholar 

  • Chiu, C.-M., Hsu, M.-H., & Wang, E. T. G. (2006). Understanding knowledge sharing in virtual communities: An integration of social capital and social cognitive theories. Decision Support Systems, 42, 1872–1888.

    Article  Google Scholar 

  • Chow, W. S., & Chan, L. S. (2008). Social network, social trust and shared goals in organizational knowledge sharing. Information and Management, 45, 458–465.

    Article  Google Scholar 

  • Cobb, S. (1976). Social support as a moderator of life stress. Psychosomatic Medicine, 38(5), 300–314.

    Article  Google Scholar 

  • Cohen, D., & Prusak, L. (2001). In good company: How social capital makes organizations work. Boston: Harvard Business School Press.

    Google Scholar 

  • Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189–211.

    Article  Google Scholar 

  • Crocker, J., & Canevello, A. (2008). Creating and undermining social support in communal relationships: The role of compassionate and self-image goals. Journal of Personality and Social Psychology, 95(3), 555–575.

    Article  Google Scholar 

  • Csikszentmihalyi, M. (1977). Beyond boredom and anxiety. San Francisco, CA: Jossey-Bass.

    Google Scholar 

  • Culnan, M. J. (2000). Protecting privacy online: Is self-regulation working? Journal of Public Policy & Marketing, 19(1), 20–26.

    Article  Google Scholar 

  • Cyr, D., Bonanni, C., Bowes, J., & Ilsever, J. (2005). Beyond trust: Web site design preferences across cultures. Journal of Global Information Management, 13(4), 25–54.

    Article  Google Scholar 

  • Da Silva, R. V., & Syed Alwi, S. F. (2008). Online brand attributes and offline corporate brand images: Do they differ? Corporate Reputation Review, 10(4), 217–244.

    Google Scholar 

  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–339.

    Article  Google Scholar 

  • Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1002.

    Article  Google Scholar 

  • Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 22(14), 1111–1132.

    Article  Google Scholar 

  • De Valck, K., van Bruggen, G. H., & Wierenga, B. (2009). Virtual communities: A marketing perspective. Decision Support Systems, 47(3), 185–203.

    Article  Google Scholar 

  • Dey, B. L., Binsardi, B., Prendergast, R., & Saren, M. (2013). A qualitative enquiry into the appropriation of mobile telephony at the bottom of the pyramid. International Marketing Review, 30(4), 297–322.

    Article  Google Scholar 

  • Dholakia, U. M., Bagozzi, R. P., & Pearo, L. K. (2004). A social influence model of consumer participation in network- and small-group-based virtual communities. International Journal of Research in Marketing, 21, 241–263.

    Article  Google Scholar 

  • Diffley, S., Kearns, J., Bennett, W., & Kawalek, P. (2011). Consumer behaviour in social networking sites: Implications for marketers. Irish Journal of Management, 30, 47–66. Retrieved from http://iamireland.ie/wpcontent/uploads/2012/05/IJM_30_2_Final_crop.pdf#page=57.

    Google Scholar 

  • Dishaw, M. T., & Strong, D. M. (1999). Extending the technology acceptance model with task technology fit constructs. Information and Management, 36(1), 9–21.

    Article  Google Scholar 

  • Domina, T., Lee, S.-E., & MacGillivray, M. (2012). Understanding factors affecting consumer intention to shop in a virtual world. Journal of Retailing and Consumer Services, 19(6), 613–620.

    Article  Google Scholar 

  • Dutton, J. E., & Jackson, S. E. (1987). Categorizing strategic issues: Links to organizational actions. Academy of Management Review, 12(1), 76–90.

    Article  Google Scholar 

  • Dwivedi, Y. K., Rana, N. P., Jeyaraj, A., Clement, M., & Williams, M. D. (2017a). Re-examining the unified theory of acceptance and use of technology (UTAUT): Towards a revised theoretical model. Information Systems Frontiers, 1–16. https://doi.org/10.1007/s10796-017-9774-y.

    Article  Google Scholar 

  • Dwivedi, Y. K., Rana, N. P., Janssen, M., Lal, B., Williams, M. D., & Clement, R. M. (2017b). An empirical validation of a unified model of electronic government adoption (UMEGA). Government Information Quarterly, 34(2), 211–230.

    Article  Google Scholar 

  • Dyson, E. (1998). A design for living in the digital age. New York: Broadway Books.

    Google Scholar 

  • Dwork, C., and Mulligan, D. K. (2013). It’s not privacy, and it’s not fair. Stan. L. Rev. Online, 66, 35.

    Google Scholar 

  • Eagly, A. H., & Chaiken, S. (1993). The psychology of attitudes. Fort Worth, TX: Harcourt Brace Jovanovich College Publishers.

    Google Scholar 

  • Eastlick, M. A., Lotz, S. L., & Warrington, P. (2006). Understanding online B-to-C relationships: An integrated model of privacy concerns, trust, and commitment. Journal of Business Research, 59(8), 877–886.

    Article  Google Scholar 

  • Edwards, K. (1990). The interplay of affect and cognition in attitude formation and change. Journal of Personality and Social Psychology, 59, 202–216.

    Article  Google Scholar 

  • Ellison, N. B., Steinfield, C., & Lampe, C. (2007). The benefits of Facebook “friends:” Social capital and college students’ use of online social network sites. Journal of Computer-Mediated Communication, 12(4), 143–1168.

    Article  Google Scholar 

  • Fazio, R. H. (1986). How do attitudes guide behavior. In R. M. Sorrentino & E. T. Higgins (Eds.), Handbook of motivation and cognition: Foundations of social behavior (Vol. 1, pp. 204–243). New York: Guilford Press.

    Google Scholar 

  • Featherman, M. S., & Pavlou, P. A. (2003). Predicting e-services adoption: A perceived risk facets perspective. International Journal of Human-Computer Studies, 59(4), 451–474.

    Article  Google Scholar 

  • Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behaviour: An introduction to theory and research. Reading, MA: Addison-Wesley Publishing Company.

    Google Scholar 

  • Folkman, S. (1992). Making the case for coping. In B. N. Carpenter (Ed.), Personal coping: Theory, research, and application (pp. 31–46). Westport, CT: Praeger.

    Google Scholar 

  • Folkman, S., & Moskowitz, J. T. (2000). Positive affect and the other side of coping. American Psychologist, 55(6), 647–654.

    Article  Google Scholar 

  • Folkman, S., Lazarus, R. S., Gruen, R. J., & DeLongis, A. (1986). Appraisal, coping, health status and psychological symptoms. Journal of Personality and Social Psychology, 50(3), 571–579.

    Article  Google Scholar 

  • Ford, G. T., & Smith, R. A. (1987). Inferential beliefs in consumer evaluations: An assessment of alternative processing strategies. Journal of Consumer Research, 14(3), 363–371.

    Article  Google Scholar 

  • Franke, N., & Shah, S. (2003). How communities support innovative activities: An exploration of assistance and sharing among end-users. Research Policy, 32, 157–178.

    Article  Google Scholar 

  • Franzen, G., & Bouwman, M. (2001). The mental world of brands. Oxfordshire, UK: World Advertising Research (WARC).

    Google Scholar 

  • Fugate, M., Kinicki, A. J., & Prussia, G. E. (2008). Employee coping with organizational change: An examination of alternative theoretical perspectives and models. Personnel Psychology, 61(1), 1–36.

    Article  Google Scholar 

  • Füller, J., Jawecki, G., & Mühlbacher, H. (2007). Innovation creation by online basketball communities. Journal of Business Research, 60, 60–71.

    Article  Google Scholar 

  • Fish, T. (2009). My Digital Footprint A two-sided digital business model where your privacy will be someone else’s business!. Futuretext.

    Google Scholar 

  • Gamboa, A. M., & Gonçalves, H. M. (2014). Customer loyalty through social networks: Lessons from Zara on Facebook. Business Horizons, 57(6), 709–717.

    Article  Google Scholar 

  • Garcia, R., & Calantone, R. (2002). A critical look at technological innovation typology and innovativeness terminology. Journal of Product Innovation Management, 19(2), 110–132.

    Article  Google Scholar 

  • Gefen, D., Rao, V. S., & Tractinsky, N. (2003, January 6–9). The conceptualization of trust, risk, and their relationships in e-commerce. Proceeding of 36th Hawaii International Conference on System Sciences, Big Island, HI.

    Google Scholar 

  • Ghosh, A., Varshney, S., & Venugopal, P. (2014). Social media WOM: Definition, consequences and inter-relationships. Management and Labour Studies, 39(3), 293–308.

    Article  Google Scholar 

  • Gironda, J. T., & Korgaonkar, P. K. (2014). Understanding consumers’ social networking site usage. Journal of Marketing Management, 30(5–6), 571–605.

    Article  Google Scholar 

  • Grace, D., Ross, M., & Shao, W. (2015). Examining the relationship between social media characteristics and psychological dispositions. European Journal of Marketing, 49(9/10), 1366–1390.

    Article  Google Scholar 

  • Grieve, R., Indian, M., Witteveen, K., Anne Tolan, G., & Marrington, J. (2013). Face-to-face or Facebook: Can social connectedness be derived online? Computers in Human Behaviour, 29(3), 604–609.

    Article  Google Scholar 

  • Gross, R., & Acquisti, A. (2005). Information revelation and privacy in online social networks. In Proceedings of the 2005 ACM Workshop on Privacy in the Electronic Society, Alexandria (pp. 71–80).

    Google Scholar 

  • Gupta, S., & Pirsch, J. (2006). The company–cause–customer fit decision in cause-related marketing. Journal of Consumer Marketing, 23(6), 314–326.

    Article  Google Scholar 

  • Ha, S., & Stoel, L. (2009). Consumer e-shopping acceptance: Antecedents in a technology acceptance model. Journal of Business Research, 62(5), 565–571.

    Article  Google Scholar 

  • Hadjikhani, A., Lee, J. W., & Ghauri, P. N. (2008). Network view of MNCs’ socio-political behavior. Journal of Business Research, 61(9), 912–924.

    Article  Google Scholar 

  • Hajli, M. N. (2014). A study of the impact of social media on consumers. International Journal of Market Research, 56(3), 388–404.

    Article  Google Scholar 

  • Hau, Y. S., & Kim, Y. G. (2010). Why would online gamers share their innovation-conducive knowledge in the online game user community? Integrating individual motivations and social capital perspectives. Computers in Human Behavior, 27(2), 956–970.

    Article  Google Scholar 

  • Hennig-Thurau, T., Gwinner, K. P., Walsh, G., & Gremler, D. D. (2004). Electronic word-of-mouth via consumer-opinion platforms: What motivates consumers to articulate themselves on the Internet? Journal of Interactive Marketing, 18(1), 38–52.

    Article  Google Scholar 

  • Hepper, E. G., Hart, C. M., Gregg, A. P., & Sedikides, C. (2011). Motivated expectations of positive feedback in social interactions. Journal of Social Psychology, 151(4), 455–477.

    Article  Google Scholar 

  • Hoffman, D. L., Novak, T. P., & Peralta, M. (1999). Building consumer trust online. Communications of the ACM, 42(4), 80–85.

    Article  Google Scholar 

  • Hsu, C., & Wu, C. (2011). Understanding users’ continuance of Facebook: An integrated model with the unified theory of acceptance and use of technology, expectation disconfirmation model, and flow theory. International Journal of Virtual Communities and Social Networking, 3(2), 1–16.

    Article  Google Scholar 

  • Hsu, C. L., Lu, H. P., & Hsu, H. H. (2007). Adoption of the mobile internet: An empirical study of multimedia message service (MMS). Omega, 35(5), 715–726.

    Article  Google Scholar 

  • Huang, E. (2012). Online experiences and virtual goods purchase intention. Internet Research, 22(3), 252–274.

    Article  Google Scholar 

  • Hussain, I. (2012). A study to evaluate the social media trends among university students. Procedia – Social and Behavioral Sciences, 64, 639–645.

    Article  Google Scholar 

  • Im, I., Kim, Y., & Han, H. J. (2008). The effects of perceived risk and technology type on users’ acceptance of technologies. Information & Management, 45(1), 1–9.

    Article  Google Scholar 

  • Jackson, S. A., & Marsh, H. W. (1996). Development and validation of a scale to measure optimal experience: The flow state scale. Journal of Sport & Exercise Psychology, 18(1), 17–35.

    Article  Google Scholar 

  • Jan, A. U., & Contreras, V. (2011). Technology acceptance model for the use of information technology in universities. Computers in Human Behavior, 27(8), 845–851.

    Article  Google Scholar 

  • Jeppesen, L. B., & Molin, M. J. (2003). Consumer as co-developers: Learning and innovation outside the firm. Technology Analysis and Strategic Management, 15, 363–384.

    Article  Google Scholar 

  • Kabadayi, S., & Gupta, R. (2005). Website loyalty: An empirical investigation of its antecedents. International Journal of Internet Marketing and Advertising, 2(4), 321–345.

    Article  Google Scholar 

  • Karahanna, E., Straub, D. W., & Chervany, N. L. (1999). Information technology adoption across time: A cross-sectional comparison of pre-adoption and post-adoption belief. MIS Quarterly, 23(2), 183–213.

    Article  Google Scholar 

  • Karyda, M., Gritzalis, S., Hyuk Park, J., & Kokolakis, S. (2009). Privacy and fair information practices in ubiquitous environments: Research challenges and future directions. Internet Research, 19(2), 194–208.

    Article  Google Scholar 

  • Kessler, T. A. (1998). The cognitive appraisal of health scale: Development and psychometric evaluation. Research in Nursing & Health, 21, 73–82.

    Article  Google Scholar 

  • Kim, J., & Lee, R. J.-E. (2011). The Facebook paths to happiness: Effects of the number of Facebook friends and self-presentation on subjective well-being. Cyberpsychology, Behavior, and Social Networking, 14(6), 359–364.

    Article  Google Scholar 

  • Kim, H. W., Gupta, S., & Koh, J. (2011). Investigating the intention to purchase digital items in social networking communities: A customer value perspective. Information & Management, 48(6), 228–234.

    Article  Google Scholar 

  • Kitchen, P., & Panopoulos, A. (2010). Online PR: The adoption process and innovation challenge, a Greek example. Public Relations Review, 36(4), 222–229.

    Article  Google Scholar 

  • Ko, H., Cho, C. H., & Roberts, M. S. (2005). Internet uses and gratifications: A structural equation model of interactive advertising. Journal of Advertising, 34(2), 57–70.

    Article  Google Scholar 

  • Korgaonkar, P. K., & Wolin, L. D. (1999). A multivariate analysis of web uses. Journal of Advertising Research, 39(1), 53–68.

    Google Scholar 

  • Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research, 13(2), 205–223.

    Article  Google Scholar 

  • Krasnova, H., Spiekermann, S., Koroleva, K., & Hildebrand, T. (2010). Online social networks: Why we disclose. Journal of Information Technology, 25(2), 109–125.

    Article  Google Scholar 

  • Kwon, J., & Vogt, C. A. (2010). Identifying the role of cognitive, affective, and behavioral components in understanding residents’ attitudes toward place marketing. Journal of Travel Research, 49, 423–434.

    Article  Google Scholar 

  • Lanier, C. D., Jr., & Saini, A. (2008). Understanding consumer privacy: A review and future directions. Academy of Marketing Science Review, 12(2), 1.

    Google Scholar 

  • Lapointe, L., & Rivard, S. (2005). A multilevel model of resistance to information technology implementation. MIS Quarterly, 29(3), 461–491.

    Article  Google Scholar 

  • Laurenceau, J., Barrett, L. F., & Pietromonaco, P. R. (1998). Intimacy as an interpersonal process: The importance of self-disclosure, partner disclosure, and perceived partner responsiveness in interpersonal exchanges. Journal of Personality and Social Psychology, 74(5), 1238–1251.

    Article  Google Scholar 

  • Lazarus, R. S. (1982). Thoughts on the relation between emotion and cognition. American Psychology, 37(9), 1019–1024.

    Article  Google Scholar 

  • Lazarus, R. S., & Folkman, S. (1984). Stress, appraisal, and coping. New York: Springer Publishing Company.

    Google Scholar 

  • Lean, O. K., Zailani, S., Ramayah, T., & Fernando, Y. (2009). Factors influencing intention to use e-government services among citizens in Malaysia. International Journal of Information Management, 29(6), 458–475.

    Article  Google Scholar 

  • Lee, D., Park, J. Y., Kim, J., & Moon, J. (2011). Understanding music sharing behaviour on social network services. Online Information Review, 35(5), 716–733.

    Article  Google Scholar 

  • Lee, H., Park, H., & Kim, J. (2013). Why do people share their context information on Social Network Services? A qualitative study and an experimental study on users’ behavior of balancing perceived benefit and risk. International Journal of Human-Computer Studies, 71(9), 862–877.

    Article  Google Scholar 

  • Lerner, J., & Tirole, J. (2002). Some simple economics of open source. Journal of Industrial Economics, 50, 197–234.

    Article  Google Scholar 

  • Li, D., Browne, G. J., & Wetherbe, J. C. (2006). Why do internet users stick with a specific web site? A relationship perspective. International Journal of Electronic Commerce, 10(4), 105–141.

    Article  Google Scholar 

  • Liang, H., & Xue, Y. (2009). Avoidance of information technology threats: A theoretical perspective. MIS Quarterly, 33(1), 71–90.

    Article  Google Scholar 

  • Liang, T.-P., Ho, Y.-T., Li, Y.-W., & ScTurban, E. (2011). What drives social commerce: The role of social support and relationship quality. International Journal of Electronic Commerce, 16(2), 69–90.

    Article  Google Scholar 

  • Lin, H. F. (2011). An empirical investigation of mobile banking adoption: The effect of innovation attributes and knowledge-based trust. International Journal of Information Management, 31(3), 252–260.

    Article  Google Scholar 

  • Lin, C. P., & Anol, B. (2008). Learning online social support: An investigation of network information technology based on UTAUT. Cyberpsychology & Behavior, 11(3), 268–272.

    Article  Google Scholar 

  • Lin, C., Gregor, S., & Ewing, M. (2008). Developing a scale to measure the enjoyment of web experiences. Journal of Interactive Marketing, 22(4), 40–57.

    Article  Google Scholar 

  • Louis, M. R., & Sutton, R. I. (1991). Switching cognitive gears: From habits of mind to active thinking. Human Relations, 44, 55–76.

    Article  Google Scholar 

  • Lu, J., Yao, J. E., & Yu, C. S. (2005). Personal innovativeness, social influences and adoption of wireless Internet services via mobile technology. The Journal of Strategic Information Systems, 14(3), 245–268.

    Article  Google Scholar 

  • Lu, J., Yu, C. S., & Liu, C. (2009a). Mobile data service demographics in urban China. Journal of Computer Information Systems, 50(2), 117–126.

    Google Scholar 

  • Lu, Y., Zhou, T., & Wang, B. (2009b). Exploring Chinese users’ acceptance of instant messaging using the theory of planned behavior, the technology acceptance model, and the flow theory. Computers in Human Behavior, 25(1), 29–39.

    Article  Google Scholar 

  • Lwin, M. O., Williams, J. D., & Lan, L. L. (2002). Social marketing initiative: National Kidney Foundations’ Organ Donation Programs in Singapore. Journal of Public Policy and Marketing, 21(1), 66–77.

    Article  Google Scholar 

  • Lyytinen, K., & Rose, G. M. (2003). The disruptive nature of information technology innovations: The case of internet computing in systems development organizations. MIS Quarterly, 27(4), 557–596.

    Article  Google Scholar 

  • Majchrzak, A., Rice, R. E., Malhotra, A., King, N., & Ba, S. (2000). Technology adaptation: The case of a computer-supported inter-organizational virtual team. MIS Quarterly, 24(4), 569–600.

    Article  Google Scholar 

  • Major, B., Richards, M. C., Cooper, M. L., Cozzarelli, C., & Zubek, J. (1998). Personal resilience, cognitive appraisals, and coping: An integrative model of adjustment to abortion. Journal of Personality and Social Psychology, 74(3), 735–752.

    Article  Google Scholar 

  • Maslow, A. H. (1954). Motivation and personality. New York: Harper and Brothers.

    Google Scholar 

  • McKnight, D. H., Choudhury, V., & Kacmar, C. (2002). Developing and validating trust measures for e-commerce: An integrative typology. Information Systems Research, 13(3), 334–359.

    Article  Google Scholar 

  • Metzger, M. J. (2004). Privacy, trust, and disclosure: Exploring barriers to electronic commerce. Journal of Computer-Mediated Communication, 9(4). https://doi.org/10.1111/j.1083-6101.2004.tb00292.x.

    Article  Google Scholar 

  • Moon, J. W., & Kim, Y. G. (2001). Extending the TAM for World-Wide-Web context. Information & Management, 38(4), 217–230.

    Article  Google Scholar 

  • Moore, G. C., & Benbasat, I. (1991). Development of an instrument to ensure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192–222.

    Article  Google Scholar 

  • Moorman, C., Deshpande, R., & Zaltman, G. (1993). Factors affecting trust in market research relationships. The Journal of Marketing, 57, 81–101.

    Article  Google Scholar 

  • Morgan, R. M., & Hunt, S. D. (1994). The commitment-trust theory of relationship marketing. The Journal of Marketing, 58, 20–38.

    Article  Google Scholar 

  • Morris, M. G., & Venkatesh, V. (2010). Job characteristics and job satisfaction: Understanding the role of enterprise resource planning system implementation. MIS Quarterly, 34(1), 143–161.

    Article  Google Scholar 

  • Muhammad, S. S., Dey, B. L., & Weerakkody, V. (2018). Analysis of factors that influence customers’ willingness to leave big data digital footprints on social media: A systematic review of literature. Information Systems Frontiers, 20(3), 559–576.

    Article  Google Scholar 

  • Nan, N. (2011). Capturing bottom-up information technology use processes: A complex adaptive systems model. MIS Quarterly, 35(2), 505–532.

    Article  Google Scholar 

  • Nie, N. H. (2001). Sociability, interpersonal relations, and the internet: Reconciling conflicting findings. The American Behavioral Scientist, 45(3), 420–435.

    Article  Google Scholar 

  • Nov, O., Naaman, M., & Ye, C. (2010). Analysis of participation in an online photo sharing community: A multidimensional perspective. Journal of American Society for Information Science and Technology, 61(3), 555–566.

    Google Scholar 

  • Novak, T. P., Hoffman, D. L., & Yung, Y. F. (2000). Measuring the customer experience in online environments: A structural modeling approach. Marketing Science, 19(1), 22–42.

    Article  Google Scholar 

  • Obst, P., & Stafurik, J. (2010). Online we are all able bodied: Online psychological sense of community and social support found through membership of disability-specific Websites promotes well-being for people living with a physical disability. Journal of Community & Applied Social Psychology, 20(6), 525–531.

    Article  Google Scholar 

  • Oldmeadow, J. A., Quinn, S., & Kowert, R. (2013). Attachment style, social skills, and Facebook use amongst adults. Computers in Human Behaviour, 29(3), 1142–1149.

    Article  Google Scholar 

  • Palmgreen, P., & Rayburn, J. (1979). Uses and gratifications and exposure to public television. Communication Research, 6(2), 155–180.

    Article  Google Scholar 

  • Papacharissi, Z. (2009). The virtual geographies of social networks: A comparative analysis of Facebook, LinkedIn and ASmallWorld. New Media and Society, 11(1–2), 199–220.

    Article  Google Scholar 

  • Papacharissi, Z., & Rubin, A. M. (2000). Predictors of internet use. Journal of Broadcasting & Electronic Media, 44(2), 175–196.

    Article  Google Scholar 

  • Papies, D., & Clement, M. (2008). Adoption of new movie distribution services on the internet. Journal of Media Economics, 21(3), 131–157.

    Article  Google Scholar 

  • Park, H., & Kim, Y.-K. (2014). The role of social network websites in the consumer–brand relationship. Journal of Retailing and Consumer Services, 21(4), 460–467.

    Article  Google Scholar 

  • Park, N., Kee, K., & Valenzuela, S. (2009). Being immersed in social networking environment: Facebook groups, uses and gratifications, and social outcomes. Cyberpsychology & Behavior, 12(6), 729–733.

    Article  Google Scholar 

  • Patrickson, M. (1986). Adaptation by employees to new technology. Journal of Occupational Psychology, 59, 1–11.

    Article  Google Scholar 

  • Pavlou, P. A., Liang, H., & Xue, Y. (2007). Understanding and mitigating uncertainty in online exchange relationships: A principal-agent perspective. MIS Quarterly, 31(1), 105–136.

    Article  Google Scholar 

  • Pentina, I., Zhang, L., & Basmanova, O. (2013). Antecedents and consequences of trust in a social media brand: A cross-cultural study of Twitter. Computers in Human Behavior, 29(4), 1546–1555.

    Article  Google Scholar 

  • Phelps, J., Nowak, G., & Ferrell, E. (2000). Privacy concerns and consumer willingness to provide personal information. Journal of Public Policy & Marketing, 19(1), 27–41.

    Article  Google Scholar 

  • Pike, S., & Ryan, C. (2004). Destination positioning analysis through a comparison of cognitive, affective, and conative perception. Journal of Travel Research, 42(May), 333–342.

    Article  Google Scholar 

  • Plouffe, C. R., Hulland, J. S., & Vandenbosch, M. (2001). Research report: Richness versus parsimony in modeling technology adoption decisions-understanding merchant adoption of a smart card-based payment system. Information Systems Research, 12(2), 208–222.

    Article  Google Scholar 

  • Porter, L. W., Bigley Bigley, G. A., & Steers, R. M. (2003). Motivation and work behavior (7th ed.). New York: McGraw-Hill.

    Google Scholar 

  • Rana, N. P., Dwivedi, Y. K., Williams, M. D., & Weerakkody, V. (2016). Adoption of online public grievance redressal system in India: Toward developing a unified view. Computers in Human Behavior, 59, 265–282.

    Article  Google Scholar 

  • Rana, N. P., Dwivedi, Y. K., Lal, B., Williams, M. D., & Clement, M. (2017). Citizens’ adoption of an electronic government system: Towards a unified view. Information Systems Frontiers, 19(3), 549–568.

    Article  Google Scholar 

  • Rettie, R. (2001). An exploration of flow during Internet use. Internet Research, 11(2), 103–113.

    Article  Google Scholar 

  • Ridings, C., Gefen, D., & Arinze, B. (2002). Some antecedents and effects of trust in virtual communities. Journal of Strategic Information Systems, 11, 271–295.

    Article  Google Scholar 

  • Rogers, E. M. (2003). Diffusion of innovations. New York: The Free Press.

    Google Scholar 

  • Rosen, C. (2007). Virtual friendship and the new narcissism. The New Atlantis, 17(2), 3–15.

    Google Scholar 

  • Rosenberg, M. J., & Hovland, C. I. (1960). Cognitive, affective, and behavioral components of attitudes. In C. I. Hovland & M. J. Rosenberg (Eds.), Attitude organization and change: An analysis of consistency among attitude components (pp. 1–14). New Haven, CT: Yale University Press.

    Google Scholar 

  • Rosenblum, D. (2007). What anyone can know: The privacy risks of social networking sites. IEEE Security & Privacy, 5(3), 40–49.

    Article  Google Scholar 

  • Sas, C., Dix, J. A., Hart, J., & Su, R. (2009). Dramaturgical capitalization of positive emotions: The answer for Facebook success? Proceedings of the 23rd British HCI Group Annual Conference on People and Computers: Celebrating People and Technology, ACM Digital Library (pp. 120–129).

    Google Scholar 

  • Sedikides, C., & Gregg, A. P. (2008). Self-enhancement: Food for thought. Perspectives on Psychological Science, 3(2), 102–116.

    Article  Google Scholar 

  • Sharma, S. K. (2017). Integrating cognitive antecedents into TAM to explain mobile banking behavioral intention: A SEM-neural network modeling. Information Systems Frontiers, 2017, 1–13.

    Google Scholar 

  • Shaw, L. H., & Gant, L. M. (2002). In defense of the Internet: The relationship between Internet communication and depression, loneliness, self-esteem, and perceived social support. Cyberpsychology & Behavior, 5(2), 157–171.

    Article  Google Scholar 

  • Shumaker, S. A., & Brownell, A. (1984). Toward a theory of social support: Closing conceptual gaps. Journal of Social Issues, 40, 11–36.

    Article  Google Scholar 

  • Sledgianowski, D., & Kulviwat, S. (2009). Using social networks sites: The effects of playfulness, critical mass and trust in a hedonic context. Journal of Computer Information Systems, 49, 74–83.

    Article  Google Scholar 

  • Szmigin, I. (2018). Consumer behaviour. Oxford: Oxford University Press.

    Google Scholar 

  • Talukder, M., & Quazi, A. (2011). The impact of social influence on individuals’ adoption of innovation. Journal of Organizational Computing and Electronic Commerce, 21(2), 111–135.

    Article  Google Scholar 

  • Taylor, S. E., Sherman, D. K., Kim, H. S., Jarcho, J., Takagi, K., & Dunagan, M. S. (2004). Culture and social support: Who seeks it and why? Journal of Personality and Social Psychology, 87(3), 354–362.

    Article  Google Scholar 

  • Terry, M., Sweeny, K., & Shepperd, J. (2007). Self-presentation. In R. R. Baumeister & K. Vohs (Eds.), Encyclopedia of social psychology (pp. 836–839). Thousand Oaks, CA: SAGE Publications.

    Google Scholar 

  • Thatcher, J., McKnight, H., Arsal, R., Baker, E., & Roberts, N. (2011). The role of trust in post-adoption IT exploration: An empirical examination of knowledge management systems. IEEE Transactions on Engineering Management, 58(1), 56–70.

    Article  Google Scholar 

  • Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal computing: Toward a conceptual model of utilization. MIS Quarterly, 15(1), 124–143.

    Article  Google Scholar 

  • Thurstone, L. L., & Chave, E. J. (1929). The measurement of attitude. Chicago: University of Chicago Press.

    Google Scholar 

  • Trivedi, N., Asamoah, D. A., & Doran, D. (2016). Keep the conversations going: engagement-based customer segmentation on online social service platforms. Information Systems Frontiers, 20, 239–257.

    Article  Google Scholar 

  • Tucker, C. E. (2014). Social networks, personalized advertising, and privacy controls. Journal of Marketing Research, 51(5), 546–562.

    Article  Google Scholar 

  • Van der Heijden, H. (2004). User acceptance of hedonic information systems. MIS Quarterly, 28(4), 695–704.

    Article  Google Scholar 

  • Venkatesh, V., & Morris, M. G. (2000). Why don’t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. Management Information Systems Quarterly, 24(1), 115–139.

    Article  Google Scholar 

  • Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. Management Information Systems Quarterly, 27(3), 425–478.

    Article  Google Scholar 

  • Venkatesh, V., Brown, S. A., Maruping, L. M., & Bala, H. (2008). Predicting different conceptualizations of system use: The competing roles of behavioral intention, facilitating conditions, and behavioral expectation. MIS Quarterly, 32(3), 483–502.

    Article  Google Scholar 

  • Venkatesh, V., Bala, H., & Sykes, T. A. (2010). Impacts of information and communication technology implementations on employees’ jobs in India: A multi-method longitudinal field study. Production and Operations Management, 19(5), 591–613.

    Article  Google Scholar 

  • Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178.

    Article  Google Scholar 

  • Venkatesh, V., Thong, J. Y., & Xu, X. (2016). Unified theory of acceptance and use of technology: A synthesis and the road ahead. Journal of the Association for Management Information Systems, 17(5), 328–376.

    Article  Google Scholar 

  • Vijayasarathy, L. R. (2004). Predicting consumer intentions to use on-line shopping: The case for an augmented technology acceptance model. Information and Management, 41(6), 747–762.

    Article  Google Scholar 

  • Vroom, V. H. (1964). Work and motivation. New York: John Wiley and Sons.

    Google Scholar 

  • Wang, X., Yu, C., & Wei, Y. (2012). Social media peer communication and impacts on purchase intentions: A consumer socialization framework. Journal of Interactive Marketing, 26(4), 198–208.

    Article  Google Scholar 

  • Warren, S. D., & Brandeis, L. D. (1890). The right to privacy. Harvard Law Review, 4, 193–220.

    Article  Google Scholar 

  • Warrington, T. B., Abgrab, N. J., & Caldwell, H. M. (2000). Building trust to develop competitive advantage in e-business relationships. Competitiveness Review, 10(2), 160–168.

    Article  Google Scholar 

  • Wei, T. T., Marthandan, G., Chong, A. Y. L., & Ooi, K. B. (2009). What drives Malaysian m-commerce adoption? An empirical analysis. Industrial Management & Data Systems, 109(3), 370–388.

    Article  Google Scholar 

  • Whiting, A., & Williams, D. (2013). Why people use social media: A uses and gratifications approach. Qualitative Market Research, 16(4), 362–369.

    Article  Google Scholar 

  • Wu, J. J., & Chang, Y. S. (2005). Towards understanding members’ interactivity, trust, and flow in online travel community. Industrial Management & Data Systems, 105(7), 937–954.

    Article  Google Scholar 

  • Wu, J.-J., Chen, Y.-H., & Chung, Y.-S. (2010). Trust factors influencing virtual community members: A study of transaction communities. Journal of Business Research, 63(9–10), 1025–1032.

    Article  Google Scholar 

  • Zajonc, R. B. (1980). Feeling and thinking: Preferences need no inferences. American Psychologist, 35(2), 151–175.

    Article  Google Scholar 

  • Zajonc, R. B., & Markus, H. (1982). Affective and cognitive factors in preferences. Journal of Consumer Research, 9(2), 123–131.

    Article  Google Scholar 

  • Zhang, H., Lu, Y., Gupta, S., & Zhao, L. (2014). What motivates customers to participate in social commerce? The impact of technological environments and virtual customer experiences. Information & Management, 51(8), 1017–1030.

    Article  Google Scholar 

  • Zigurs, I., & Buckland, B. K. (1998). A theory of task/technology fit and group support systems effectiveness. MIS Quarterly, 22(2), 313–334.

    Article  Google Scholar 

  • Zolkepli, I. A., & Kamarulzaman, Y. (2015). Social media adoption: The role of media needs and innovation characteristics. Computers in Human Behavior, 43, 189–209.

    Article  Google Scholar 

  • Zuboff, S. (1988). In the age of the smart machine: The future of work and power. New York: Basic Books.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Syed S. Muhammad .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Muhammad, S.S., Dey, B., Alwi, S., Babu, M.M. (2020). Examining the Underlying Attitudinal Components Driving Technology Adoption, Adaptation Behaviour and Outcome in Entirety. In: Rana, N.P., et al. Digital and Social Media Marketing. Advances in Theory and Practice of Emerging Markets. Springer, Cham. https://doi.org/10.1007/978-3-030-24374-6_14

Download citation

Publish with us

Policies and ethics