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Radio frequency identification (RFID) adoption: A cross-sectional comparison of voluntary and mandatory contexts

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Abstract

Understanding the adoption factors of a technological innovation is crucial. However, it is a wild assumption that these factors are of similar importance for mandatory and voluntary adoption. Hence, understanding the distinction is critical because, more than often an innovation is adopted with different organizational objectives—though operate in a same industry for a same application. The purpose of this study is to compare the organizational adoption factors of a technological innovation in mandatory and voluntary setting, taking Radio Frequency Identification (RFID) technology as the case innovation. The results indicate that perceptions of the adopters differ significantly on technological, organizational, and environmental characteristics and expectation when the contexts are different. Multi-group analysis confirms that, among the technological factors, compatibility is the major concern in a mandatory setting whereas cost and expected-benefits are the main for voluntary adoption; organizations attitude is more important than organizational resources—in both contexts; and, external pressure is important both in mandatory as well as voluntary environment.

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References

  • Adamson, I., & Shine, J. (2003). Extending the new Technology Acceptance Model to measure the end user information systems satisfaction in a mandatory environment: A bank’s treasury. Technology Analysis and Strategic Management, 15(4), 441–455.

    Article  Google Scholar 

  • Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211.

  • Ajzen, I., & Fishbein, M. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Reading: Addision-Wesley.

    Google Scholar 

  • Bandura, A. (2001). Social Cognitive Theory of Mass Communication. Media Psychology, 3(3), 265–299.

    Article  Google Scholar 

  • Barclay, D., Higgins, C., & Thomson, R. (1995). The partial least squares (PLS) approach to causal modeling: Personal computer adoption and use as an illustration. Technology Studies, 2(2), 285–309.

    Google Scholar 

  • Bennett, D., & Eustis, B. (1999). External Relationship Management: Health Care Implications and Future Digital Desirability. Information Systems Frontiers, 1(2), 155–162.

    Article  Google Scholar 

  • Brown, I., & Russell, J. (2007). Radio frequency identification technology: An exploratory study on adoption in the South African retail sector. International Journal of Information Management, 27(4), 250–265.

    Article  Google Scholar 

  • Brown, S. A., Massey, A. P., Montoya-Weiss, M. M., & Burkman, J. R. (2002). Do I really have to? User acceptance of mandated technology. European Journal of Information Systems, 4, 283–295.

    Article  Google Scholar 

  • Chau, P. Y. K., & Tam, K. Y. (1997). Factors Affecting the Adoption of Open Systems: An Exploratory Study. MIS Quarterly, 21(1), 1–24.

    Article  Google Scholar 

  • Chin, W. W. (2000). “Frequently Asked Questions - Partial Least Squares & PLS-Graph”.

  • Chin, W. W. (2001). “PLS-Graph User’s Guide”, Soft Modeling Inc.

  • Chin, W. W. (2010). How to write up and report PLS analyses. In V. E. Vinzi, W. W. Chin, J.Henseler, H. Wang (Eds.), Handbook of Partial Least Squares (pp. 655–690). Germany: Springer.

  • Chin, W. W., & Gopal, A. (1995). Adoption Intention in GSS: Relative Importance of Beliefs. Data Base, 26(2), 42–63.

    Article  Google Scholar 

  • Coffey, P., Tate, M., & Toland, J. (2013). Small business in a small country: Attitudes to “Green” IT. Information Systems Frontiers, 15(5), 761–778.

    Article  Google Scholar 

  • Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319–340.

    Article  Google Scholar 

  • Davis, F. D., Bagozzi, R., & Warshaw, P. R. (1989). User Acceptance of Computer Technology: A Comparison of Two Theoritical Models. Management Science, 35(8), 982–1003.

    Article  Google Scholar 

  • Diamantopoulos, A., & Siguaw, J. A. (2006). Formative Versus Reflective Indicators in Organizational Measure Development: A Comparison and Empirical Illustration. British Journal of Management, 17(4), 263–282.

    Article  Google Scholar 

  • Ghadim, A. K., Pannell, D. J., & Burton, M. P. (2005). Risk, uncertainty, and learning in adoption of a crop innovation. Agricultural Economics, 33, 1–9.

    Article  Google Scholar 

  • Gibbs, J. L., & Kraemer, K. L. (2004). A Cross-Country Investigation of the Determinants of Scope of E-commerce Use: An Institutional Approach. Electronic Markets, 14(2), 124–137.

    Article  Google Scholar 

  • Green, B. (2009). “Implementation of the National Livestock Identification System (Cattle) Business Plan in Western Australia (2005-2008)”, Department of Agriculture and Food, Western Australia.

  • Hooper, S. (2010)."Australian Beef: Financial performance of beef cattle producing farms, 2007–08 to 2009–10," ABARE (ed.), Canberra.

  • Hoske, M. T. (2004). RFID: Adoption increases despite costs. Control Engineering, 51(7), 46–47.

    Google Scholar 

  • Hossain, M. A., & Quaddus, M. (2011). The adoption and continued usage intention of RFID: An integrated framework. Information Technology & People, 24(3), 236–256.

    Article  Google Scholar 

  • Hossain, M. A., & Quaddus, M. (2013). "Does mandatory pressure increases RFID adoption?: A case study of Western Australian livestock industry,". In Y. Dwivedi, H. Z. Henriksen, D. Wastell, & R. De (Eds.), Grand Successes and Failures in IT: Private and Public Sectors (pp. 184–202). Boston: Springer.

    Chapter  Google Scholar 

  • Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: A review of four recent studies. Strategic Management Journal, 20, 195–204.

    Article  Google Scholar 

  • Huyskens, C., & Loebbecke, C. (2007). "Theoretical Concepts and Their Practical Application in Fashion," in: Organizational Dynamics of Technology-Based Innovation: Diversifying the Research Agenda (pp. 345–361). Boston: Springer.

    Google Scholar 

  • Iacovou, C., Benbasat, I., & Dexter, A. (1995). Electronic Data Interchange and Small Organizations: Adoption and Impact of Technology. MIS Quarterly, 19(4), 465–485.

    Article  Google Scholar 

  • Igbaria, M., Guimaraes, T., & Davis, G. B. (1995). Testing the Determinants of Microcomputer Usage via a Structural Equation Model. Journal of Management Information Systems, 11(4), 87–114.

    Google Scholar 

  • Jarvis, C. B., MacKenzie, S. B., & Podsakoff, P. M. (2003). A critical review of construct indicators and measurement model misspecification in marketing and consumer research. Journal of Consumer Research, 30(2), 199–218.

    Article  Google Scholar 

  • Jeyaraj, A., Rottman, J., & Lacity, W. (2006). A Review of the Predictors, Linkages, and Biases in IT Innovation Adoption Research. Journal of Information Technology, 21(1), 1–23.

    Article  Google Scholar 

  • Jiang, J. J., Klein, G., & Carr, C. L. (2002). Measuring Information System Service Quality: SERVQUAL from the Other Side. MIS Quarterly, 26(2), 145–166.

    Article  Google Scholar 

  • Kinsella, B. (2003). The Wal-mart factor. Industrial Engineer, 35(11), 32–36.

    Google Scholar 

  • Koh, C. E., Prybutok, V. R., Ryan, S. D., & Wu, Y. A. (2010). A Model for Mandatory Use of Software Technologies: An Integrative Approach by Applying Multiple Levels of Abstraction of Informing Science. Informing Science: The International Journal of an Emerging Transdiscipline, 13, 177–203.

    Google Scholar 

  • Kwon, T. H., & Zmud, R. W. (1987). Unifying the fragmented models of information systems implementation. In R. J. Boland & R. A. Hirschheim (Eds.), Critical Issues in Information Systems Research. New York: John Wiley.

    Google Scholar 

  • Lee, C., & Shim, J. (2007). An exploratory study of radio frequency identification (RFID) adoption in the healthcare industry. European Journal of Information Systems, 16, 712–724.

    Article  Google Scholar 

  • Leimeister, J. M., Knebel, U., & Krcmar, H. (2007). RFID as enabler for the boundless real-time organisation: Empirical insights from Germany. International Journal of Networking and Virtual Organisations, 4(1), 45–64.

    Article  Google Scholar 

  • Lin, C.-Y., & Ho, Y.-H. (2009). RFID technology adoption and supply chain performance: An empirical study in China’s logistics industry. Supply Chain Management: An International Journal, 14(5), 369–378.

    Article  Google Scholar 

  • Linda, C., & Samuel, F. W. (2007). An inside look at RFID technology. Journal of Technology Management & Innovation, 2, 128–141.

    Google Scholar 

  • Mather, D., Caputi, P., & Jayasuriya, T. (2002). " Is the Technology Acceptance Model a Valid Model of User Satisfaction of Information Technology in Environments where Usage is Mandatory?," (pp. 1241–1250). Vicpria: Proceedings of Australasia Conference on Information Systems.

    Google Scholar 

  • Mehrtens, J., Cragg, P. B., & Mills, A. M. (2001). A model of Internet adoption by SMEs. Information & Management, 39(3), 165–176.

    Article  Google Scholar 

  • Meng, S., Chiu, D. K., Kafeza, E., Wenyin, L., & Li, Q. (2010). Automated management of assets based on RFID triggered alarm messages. Information Systems Frontiers, 12(5), 563–578.

    Article  Google Scholar 

  • Mills, A. M. (2005). "Managing the IS Function: An Examination of the Determinants of IS-customer Expectations," University of Canterbury.

  • Moon, K. L., & Ngai, E. (2008). The Adoption of RFID in Fashion Retailing: A Business Value-added Framework. Industrial Management + Data Systems, 108(5), 596–612.

    Article  Google Scholar 

  • Nah, F. F. H., Tan, X., & Teh, S. H. (2004). An empirical investigation on end-users’ acceptance of enterprise systems. Information Resources Management Journal, 17(3), 32–53.

    Article  Google Scholar 

  • Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric Theory (3rd ed.). New York: McGraw-Hill.

    Google Scholar 

  • Oliver, R. L. (1980). A Cognitive Model for the Antecedents and Consequences of Satisfaction Decisions. Journal of Marketing Research, 17, 460–469.

    Article  Google Scholar 

  • Oni, O., and Papazafeiropoulou, A. (2012). "Diverse views on IT innovation diffusion among SMEs: Influencing factors of broadband adoption," Information Systems Frontiers), 1–19.

  • Petter, S., Straub, D., & Rai, A. (2007). Specifying formative constructs in information systems research. MIS Quarterly, 31(4), 623–656.

    Google Scholar 

  • Poirier, C. C., and McCollum, D. (2006). RFID Strategic Implementation and ROI: A practical roadmap to success J. ROSS Publishing.

  • Premkumar, G., & Roberts, M. (1999). Adoption of new information technologies in rural small businesses. Omega International Journal of Management Science, 27, 467–484.

    Article  Google Scholar 

  • Quaddus, M., and Hofmeyer, G. (2007) "An investigation into the factors influencing the adoption of B2B trading exchanges in small businesses," European Journal of Information Systems, 16 (3), 202–215.

    Google Scholar 

  • Rai, A., Patnayakuni, R., & Patnayakuni, N. (2006). Firm performance impacts of digitally enabled supply chain integration capabilities. Management Information Systems Quarterly, 30(2), 225–246.

    Google Scholar 

  • Rawstorne, P., Jayasuriya, R., and Caputi, P. (2000)."Issues in predicting and explaining usage behaviors with the technology acceptance model and the theory of planned behavior when usage is mandatory," Proceedings of the twenty first international Conference on Information Systems, 35-44.

  • Robertson, T. S., & Gatignon, H. (1986). Competitive Effects on Technology Diffusion. The Journal of Marketing, 50(3), 1–12.

    Article  Google Scholar 

  • Rogers, E. M. (1995). Diffusion of Innovation. New York: Free Press.

    Google Scholar 

  • Roh, J. J., Kunnathur, A., & Tarafdar, M. (2009). Classification of RFID adoption: An expected benefits approach. Information & Management, 46(6), 357–363.

    Article  Google Scholar 

  • Santosa, P. I., Wei, K. K., & Chan, H. C. (2005). User involvement and user satisfaction with information-seeking activity. European Journal of Information Systems, 14, 361–370.

    Article  Google Scholar 

  • Schmitt, P., & Michahelles, F. (2009). "Status of RFID/EPC Adoption," in: Auto-ID Labs White Paper, Auto-ID Labs, pp. 1-41.

  • Scupola, A. (2003). The adoption of Internet commerce by SMEs in the south of Italy: An environmental, technological, and organizational perspective. Journal of Global Information Technology Management, 6(1), 52–71.

    Article  Google Scholar 

  • Sheng, Q. Z., Zeadally, S., Luo, Z., Chung, J.-Y., & Maamar, Z. (2010). Ubiquitous RFID: Where are we? Information Systems Frontiers, 12(5), 485–490.

    Article  Google Scholar 

  • Shih, D.-H., Chiu, Y.-W., Chang, S.-I., & Yen, D. C. (2008). An Empirical Study of Factors Affecting RFID's Adoption in Taiwan. Journal of Global Information Management, 16(2), 58–80.

    Article  Google Scholar 

  • Swanson, E. B. (1994). Information Systems Innovation among Organizations. Management Science, 40(9), 1069–1092.

    Article  Google Scholar 

  • Swedberg, C. (2007)."Wisconsis ups RFID-adoption incentives for cattle growers," in: RFID Journal.

  • Tellkamp, C., Wiechert, T., Thiesse, F., & Fleisch, E. (2006). "The Adoption of RFID-based Self-Check-Out-Systems at the Point-of-Sale," in: Project E-Society: Building Bricks (pp. 153–165). Boston: Springer.

    Google Scholar 

  • Teo, H. H., Wei, K. K., & Benbasat, I. (2003). Predicting Intention to Adopt Interorganizational Linkages: An Institutional Perspective. MIS Quarterly, 27(1), 19–49.

    Google Scholar 

  • Thong, J. Y. L., & Yap, C. S. (1995). CEO characteristics, organizational characteristics and information technology adoption in small businesses. Omega, 23(4), 429–442.

    Article  Google Scholar 

  • Tornatzky, L. G., & Fleischer, M. (1990). The Process of Technological Innovation. Lexington Mass: Lexington Books.

    Google Scholar 

  • Tsai, M.-C., Lee, W., & Wu, H.-C. (2010). Determinants of RFID adoption intention: Evidence from Taiwanese retail chains. Information and Management, 47, 255–261.

    Article  Google Scholar 

  • Venkatesh, V., & Davis, F. D. (1996). A Model of the Antecedents of Perceived Ease of Use: Development and Test. Decision Sciences, 27(3), 451–481.

    Article  Google Scholar 

  • Venkatesh, V., & Davis, F. D. (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, 46(2), 186–204.

    Article  Google Scholar 

  • Venkatesh, V., Morris, M. G., Gordon, B. D., & Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425–478.

    Google Scholar 

  • Wang, Y.-M., Wang, Y.-S., & Yang, Y.-F. (2010). Understanding the determinants of RFID adoption in the manufacturing industry. Technological Forecasting and Social Change, 77(5), 803–815.

    Article  Google Scholar 

  • Wen, L., Zailani, S., & Fernando, Y. (2009). Determinants of RFID adoption in supply chain among manufacturing companies in China: A discriminant analysis. Journal of Technology Management & Innovation, 4(1), 22–32.

    Article  Google Scholar 

  • Whitaker, J., Mithas, S., & Krishnan, M. (2007). A field study of RFID deployment and return expectations. Production and Operations Management, 16(5), 599–612.

    Article  Google Scholar 

  • Wu, N., Nystrom, M., Lin, T., & Yu, H. (2006). Challenges to global RFID adoption. Technovation, 26(12), 1317–1323.

    Article  Google Scholar 

  • Zhang, N., Guo, X., & Chen, G. (2011). Why adoption and use behavior of IT/IS cannot last?—two studies in China. Information Systems Frontiers, 13(3), 381–395.

    Article  Google Scholar 

  • Zhu, K., Kraemer, K., & Xu, S. (2003). Electronic Business Adoption by European Firms: A Cross-Country Assessment of the Facilitators and Inhibitors. European Journal of Information Systems, 12(4), 251–268.

    Article  Google Scholar 

  • Zhu, K., Dong, S., Xu, S. X., & Kraemer, K. L. (2006). Innovation diffusion in global contexts: Determinants of post-adoption digital transformation of European companies. European Journal of Information Systems, 15, 601–616.

    Article  Google Scholar 

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Correspondence to Mohammad Alamgir Hossain.

Appendices

Appendix A

Table 9 List of measures and relevant references

Appendix B1

Table 10 Cross-loading matrix of the voluntary adoption model

Appendix B2

Table 11 Cross-loading matrix of the mandatory adoption model

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Hossain, M.A., Quaddus, M. Radio frequency identification (RFID) adoption: A cross-sectional comparison of voluntary and mandatory contexts. Inf Syst Front 17, 1057–1076 (2015). https://doi.org/10.1007/s10796-013-9482-1

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