Empirical Examination of the Role of Three Sets of Innovation Attributes for Determining Adoption of IRCTC Mobile Ticketing Service

REFERENCES

• Ajili, A., Salehi, S., Rezaei-Moghaddam, K., Hayati, D., & Karbalaee, F. (2012). Estimating the model of investigating attitude and intention in the usage of variable rate irrigation technology. American Journal of Experimental Agriculture,2(3), 542–556. doi:10.9734/AJEA/2012/1267
   Google Scholar
• Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes,50(2), 179–211. doi:10.1016/0749-5978(91)90020-T
   Web of Science ®Google Scholar
• Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting behavior. Englewood Cliffs, NJ: Prentice Hall.
   Google Scholar
• Arts, J. W. C., Frambach, R. T., & Bijmolt, T. H. A. (2011). Generalizations on consumer innovation adoption: A meta-analysis on drivers of intention and behavior. International Journal of Research in Marketing,28(2), 134–144. doi:10.1016/j.ijresmar.2010.11.002
   Web of Science ®Google Scholar
• Aubert, B. A., & Hamel, G. (2001). Adoption of smart cards in the medical sector: The Canadian experience. Social Science and Medicine,53(7), 879–894. doi:10.1016/S0277-9536(00)00388-9
   PubMed Web of Science ®Google Scholar
• Barnes, S. J. (2002). The mobile commerce value chain: Analysis and future developments. International Journal of Information Management,22(2), 91–108. doi:10.1016/S0268-4012(01)00047-0
   Web of Science ®Google Scholar
• Brace, N., Kemp, R., & Snelgar, R. (2003). SPSS for psychologists: A guide to data analysis using SPSS for windows. New York, NY: Palgrave Macmillan.
   Google Scholar
• Brumec, S. (2006). Predicting the intention to use Internet—A comparative study. Journal of Information and Organizational Sciences,30(1), 13–28.
   Google Scholar
• Carter, L., & Bélanger, F. (2005). The utilization of e-government services: Citizen trust, innovation and acceptance factors. Information Systems Journal,15(1), 5–25. doi:10.1111/j.1365-2575.2005.00183.x
   Web of Science ®Google Scholar
• Chen, L. D. (2008). A model of consumer acceptance of mobile payment. International Journal of Mobile Communications,6(1), 32–52. doi:10.1504/IJMC.2008.015997
   Web of Science ®Google Scholar
• Chen, L.-D., Gillenson, M. L., & Sherrell, D. L. (2002). Enticing online consumers: An extended technology acceptance perspective. Information and Management,39(8), 705–719. doi:10.1016/S0378-7206(01)00127-6
   Web of Science ®Google Scholar
• Claudy, M. C., Michelsen, C., & O’Driscoll, A. (2011). The diffusion of microgeneration technologies—Assessing the influence of perceived product characteristics on home owners’ willingness to pay. Energy Policy,39(3), 1459–1469. doi:10.1016/j.enpol.2010.12.018
   Web of Science ®Google Scholar
• Compeau, D. R., Meister, D. B., & Higgins, C. A. (2007). From prediction to explanation: Reconceptualizing and extending the perceived characteristics of innovating. Journal of the Association for Information Systems,8(8), 409–439.
   Web of Science ®Google Scholar
• Dahlberg, T., Mallat, N., Ondrus, J., & Zmijewska, A. (2008). Past, present and future of mobile payments research: A literature review. Electronic Commerce Research and Applications,7(2), 165–181. doi:10.1016/j.elerap.2007.02.001
   Web of Science ®Google Scholar
• Damanpour, F., & Schneider, M. (2009). Characteristics of innovation and innovation adoption in public organizations: Assessing the role of managers. Journal of Public Administration Research and Theory,19(3), 495–522. doi:10.1093/jopart/mun021
   Web of Science ®Google Scholar
• Dwivedi, Y. K., & Irani, Z. (2009). Understanding the adopters and non-adopters of broadband. Communications of the ACM,52(1), 122–125. doi:10.1145/1435417.1435445
   Web of Science ®Google Scholar
• Dwivedi, Y. K., Tamilmani, K., Williams, M. D., & Lal, B. (2014). Adoption of M-commerce: Examining factors affecting intention and behavior of Indian consumers. International Journal of Indian Culture and Business Management, 8(3), 345–360.
   Google Scholar
• Frambach, R. T., Barkema, H. G., Nooteboom, B., & Wedel, M. (1998). Adoption of a service innovation in the business market: An empirical test of supply-side variables. Journal of Business Research,41(2), 161–174. doi:10.1016/S0148-2963(97)00005-2
   Web of Science ®Google Scholar
• Gerpott, T. J. (2011). Attribute perceptions as factors explaining mobile internet acceptance of cellular customers in Germany—An empirical study comparing actual and potential adopters with distinct categories of access appliances. Expert Systems with Applications,38(3), 2148–2162. doi:10.1016/j.eswa.2010.08.001
   Web of Science ®Google Scholar
• Gounaris, S., & Koritos, C. (2008). Investigating the drivers of internet banking adoption decision: A comparison of three alternative frameworks. International Journal of Bank Marketing,26(5), 282–304. doi:10.1108/02652320810894370
   Google Scholar
• Greenhalgh, T., Robert, G., Macfarlane, F., Bate, P., & Kyriakidou, O. (2004). Diffusion of innovations in service organizations: Systematic review and recommendations. The Milbank Quarterly,82(4), 581–629. doi:10.1111/j.0887-378X.2004.00325.x
   PubMed Web of Science ®Google Scholar
• Gumussoy, C. A., & Calisir, F. (2009). Understanding factors affecting e-reverse auction use: An integrative approach. Computers in Human Behavior,25(4), 975–988. doi:10.1016/j.chb.2009.04.006
   Web of Science ®Google Scholar
• Gupta, S., & Xu, H. (2010). Examining the relative influence of risk and control on intention to adopt risky technologies. Journal of Technology Management and Innovation,5(4), 22–37. doi:10.4067/S0718-27242010000400003
   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. doi:10.1016/j.jbusres.2008.06.016
   Web of Science ®Google Scholar
• Hansen, T. (2006). Determinants of consumers’ repeat online buying of groceries. The International Review of Retail, Distribution and Consumer Research,16(1), 93–114. doi:10.1080/09593960500453617
   Google Scholar
• Hester, A. J., & Scott, J. E. (2008). A conceptual model of wiki technology diffusion. In Proceedings of the 41st Hawaii International Conference on System Sciences (pp. 32). Waikoloa, HI: IEEE.
   Google Scholar
• Hinton, P. R., Brownlow, C., McMurray, I., & Cozens, B. (2004). SPSS explained. East Sussex, England: Routledge.
   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(6), 715–726. doi:10.1016/j.omega.2006.03.005
   Web of Science ®Google Scholar
• Irani, Z., Dwivedi, Y. K., & Williams, M. D. (2009). Understanding consumer adoption of broadband: An extension of the technology acceptance model. Journal of the Operational Research Society,60(10), 1322–1334. doi:10.1057/jors.2008.100
   Web of Science ®Google Scholar
• Prabhudesai, A. (2012). Book Indian Railways Tickets through Mobile Using Paymate, Ngpay & Atom. Retrieved from http://trak.in/tags/business/2012/01/03/book-indian-railways-tickets-mobile-paymate-ngpay-atom/.
   Google Scholar
• IRCTC (2013). Pre-requisites to Book a Ticket Through SMS on 139. Retrieved from http://www.services.irctc.co.in/beta_images/sms_booking/SMS_BOOKING_139.htm.
   Google Scholar
• Jacoby, J., & Kaplan, L. B. (1972). The components of perceived risk cited by Rijsdijk, S. A, & Hultink, E. J. (2003). Honey, have you seen our hamster? Consumer evaluations of autonomous domestic products. Journal of Product Innovation Management,20(3), 204–216.
   Google Scholar
• Jamieson, S. (2004). Likert scales: How to (ab)use them. Medical Education,38(12), 1217–1218. doi:10.1111/j.1365-2929.2004.02012.x
   PubMed Web of Science ®Google Scholar
• Jung, J., Chan-Olmsted, S., Park, B., & Kim, Y. (2012). Factors affecting e-book reader awareness, interest, and intention to use. New Media and Society,14(2), 204–224. doi:10.1177/1461444811410407
   Web of Science ®Google Scholar
• Kapoor, K. K., Dwivedi, Y. K., & Williams, M. D. (2014). Rogers’ innovation adoption attributes: A systematic review and synthesis of existing research. Information Systems Management,31, 74–91. doi:10.1080/10580530.2014.854103
   Web of Science ®Google Scholar
• Kapoor, K. K., Williams, M. D., Dwivedi, Y. K., & Lal, B. (2011). An analysis of existing publications to explore the use of the diffusion of innovations theory and innovation attributes. In Information and Communication Technologies (WICT), 2011 World Congress (pp. 229–234). Mumbai, India: IEEE.
   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 beliefs. MIS Quarterly,23(2), 183–213. doi:10.2307/249751
   Web of Science ®Google Scholar
• Kishore, R., & McLean, E. R. (2007). Reconceptualizing innovation compatibility as organizational alignment in secondary IT adoption contexts: An investigation of software reuse infusion. IEEE Transactions on Engineering Management,54(4), 756–775. doi:10.1109/TEM.2007.906849
   Web of Science ®Google Scholar
• Koenig-Lewis, N., Palmer, A., & Moll, A. (2010). Predicting young consumers’ take up of mobile banking services. International Journal of Bank Marketing,28(5), 410–432. doi:10.1108/02652321011064917
   Google Scholar
• Kulviwat, S., Bruner, G. C., II, & Al-Shuridah, O. (2009). The role of social influence on adoption of high tech innovations: The moderating effect of public/private consumption. Journal of Business Research,62(7), 706–712. doi:10.1016/j.jbusres.2007.04.014
   Web of Science ®Google Scholar
• Lee, Y., & Kozar, K. (2008). An empirical investigation of anti-spyware software adoption: A multitheoretical perspective. Information and Management,45(2), 109–119. doi:10.1016/j.im.2008.01.002
   Web of Science ®Google Scholar
• Lee, Y. H., Hsieh, Y. C., & Hsu, C. N. (2011). Adding innovation diffusion theory to the technology acceptance model: Supporting employees’ intentions to use e-learning systems. Educational Technology & Society,14(4), 124–137.
   Web of Science ®Google Scholar
• Lee-Partridge, J. E., & Ho, P. S. (2003). A retail investor’s perspective on the acceptance of internet stock trading. In Proceedings of the 36th annual Hawaii international conference on system sciences. Hawaii: IEEE.
   Google Scholar
• Légaré, F., Ratté, S., Gravel, K., & Graham, I. D. (2008). Barriers and facilitators to implementing shared decision-making in clinical practice: Update of a systematic review of health professionals’ perceptions. Patient Education and Counseling,73(3), 526–535. doi:10.1016/j.pec.2008.07.018
   PubMed Web of Science ®Google Scholar
• Li, X., Troutt, M. D., Brandyberry, A., & Wang, T. (2011). Decision factors for the adoption and continued use of online direct sales channels among SMEs. Journal of the Association for Information Systems,12(1), 1–31.
   Web of Science ®Google Scholar
• Li, Y.-H. (2008). An empirical investigation on the determinants of e-procurement adoption in Chinese manufacturing enterprises. In International conference on management science and engineering (15th) (pp. 32–37). Long Beach, CA; Publisher: IEEE.
   Google Scholar
• Liang, T.-P., Huang, C.-W., Yeh, Y.-H., & Lin, B. (2007). Adoption of mobile technology in business: A fit-viability model. Industrial Management and Data Systems,107(8), 1154–1169. doi:10.1108/02635570710822796
   Web of Science ®Google Scholar
• Lu, J., Liu, C., Yu, C.-S., & Wang, K. (2008). Determinants of accepting wireless mobile data services in China. Information & Management,45(1), 52–64. doi:10.1016/j.im.2007.11.002
   Web of Science ®Google Scholar
• Mahmod, R., Dahlan, N., Ramayah, T., Karia, N., & Asaari, M. H. A. H. (2005). Attitudinal belief on adoption of e-MBA program in Malaysia. Higher Education Research Report, Malaysia. Retrieved from http://eric.ed.gov/?id=ED490366.
   Google Scholar
• Mallat, N. (2007). Exploring consumer adoption of mobile payments—A qualitative study. The Journal of Strategic Information Systems,16(4), 413–432. doi:10.1016/j.jsis.2007.08.001
   Web of Science ®Google Scholar
• Mallat, N., Rossi, M., Tuunainen, V. K., & Öörni, A. (2007). An empirical investigation of mobile ticketing service adoption in public transportation. Personal and Ubiquitous Computing,12(1), 57–65. doi:10.1007/s00779-006-0126-z
   Web of Science ®Google Scholar
• Mallat, N., Rossi, M., Tuunainen, V. K., & Öörni, A. (2009). The impact of use context on mobile services acceptance: The case of mobile ticketing. Information & Management,46(3), 190–195.
   Web of Science ®Google Scholar
• Maxwell, S. E. (2000). Sample size and multiple regression analysis. Psychological Methods,5(4), 434–458. doi:10.1037/1082-989X.5.4.434
   PubMed Web of Science ®Google Scholar
• Meuter, M. L., Bitner, M. J., Ostrom, A. L., & Brown, S. W. (2005). Choosing among alternative service delivery modes: An investigation of customer trial of self-service technologies. The Journal of Marketing,69(2), 61–83. doi:10.1509/jmkg.69.2.61.60759
   Web of Science ®Google Scholar
• Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research,2(3), 192–222. doi:10.1287/isre.2.3.192
   Web of Science ®Google Scholar
• Nunnally, J. C. (1978). Psychometric theory (2nd ed.). New York, NY: McGraw-Hill.
   Google Scholar
• Odumeru, J. A. (2012). Diffusion of online recruiting technology in Nigeria. Online Journal of Social Sciences Research,1(4), 104–114.
   Google Scholar
• Patel, A., & Grover, I. (2010). Map-based interaction for inputting in mobile phones. In Proceedings of the 2010 international conference on interaction design & international development, British Computer Society (pp. 60–64). Indian Institute of Technology, Mumbai, India: British Computer Society.
   Google Scholar
• Pikkarainen, T., Pikkarainen, K., Karjaluoto, H., & Pahnila, S. (2004). Consumer acceptance of online banking: An extension of the technology acceptance model. Internet Research,14(3), 224–235. doi:10.1108/10662240410542652
   Web of Science ®Google Scholar
• Premkumar, G., Ramamurthy, K., & Nilakanta, S. (1994). Implementation of electronic data interchange: An innovation diffusion perspective. Journal of Management Information Systems,1(2), 157–186.
   Google Scholar
• Rezaei-Moghaddam, K., & Salehi, S. (2010). Agricultural specialists’ intention toward precision agriculture technologies: Integrating innovation characteristics to technology acceptance model. African Journal of Agricultural Research,5(11), 1191–1199.
   Web of Science ®Google Scholar
• Richardson, J. W. (2011). Technology adoption in Cambodia: Measuring factors impacting adoption rates. Journal of International Development,23(5), 697–710. doi:10.1002/jid.1661
   Web of Science ®Google Scholar
• Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York, NY: The Free Press.
   Google Scholar
• Rogers, EM (1995). Diffusion of innovations (4th ed.). New York, Free Press.
   Google Scholar
• Schierz, P. G., Schilke, O., & Wirtz, B. W. (2010). Understanding consumer acceptance of mobile payment services: An empirical analysis. Electronic Commerce Research and Applications,9(3), 209–216. doi:10.1016/j.elerap.2009.07.005
   Web of Science ®Google Scholar
• Shih, H.-P. (2008). Continued use of a Chinese online portal: An empirical study. Behaviour & Information Technology,27(3), 201–209. doi:10.1080/01449290600802403
   Web of Science ®Google Scholar
• Shih, Y.-Y., & Fang, K. (2004). The use of a decomposed theory of planned behavior to study internet banking in Taiwan. Internet Research,14(3), 213–223. doi:10.1108/10662240410542643
   Web of Science ®Google Scholar
• Shin, D.-H. (2010). MVNO services: Policy implications for promoting MVNO diffusion. Telecommunications Policy,34(10), 616–632. doi:10.1016/j.telpol.2010.07.001
   Web of Science ®Google Scholar
• Shiu, E., Hassan, L. M., & Walsh, G. (2009). Demarketing tobacco through governmental policies—The 4Ps revisited. Journal of Business Research,62(2), 269–278. doi:10.1016/j.jbusres.2008.01.034
   Web of Science ®Google Scholar
• Sia, C.-L., Teo, H.-H., Tan, B. C. Y., & Wei, K.-K. (2004). Effects of environmental uncertainty on organizational intention to adopt distributed work arrangements. IEEE Transactions on Engineering Management,51(3), 253–267. doi:10.1109/TEM.2004.830859
   Web of Science ®Google Scholar
• Siau, K., & Shen, Z. (2003). Building customer trust in mobile commerce. Communications of the ACM,46(4), 91–94. doi:10.1145/641205.641211
   Web of Science ®Google Scholar
• Singh, K., & Yammiyar, P. (2008). Establishing a user centered approach to evaluate Indian market for m-commerce—Conference on Advances in Usability Engineering (CAUE) 2008. Pune, India: Vishwakarma Institute of Information Technology (VIIT).
   Google Scholar
• Slyke, C. V., Belanger, F., & Comunale, C. L. (2004). Factors influencing the adoption of web-based shopping: The impact of trust. Analysis,35(2), 32–49.
   Google Scholar
• Slyke, C. V., Belanger, F., & Hightower, R. (2005). Understanding gender-based differences in consumer e-commerce adoption. In SAIS proceedings. Paper 5. Savannah, GA: Association of Information Systems.
   Google Scholar
• Slyke, C. V., Lou, H., Belanger, F., & Sridhar, V. (2010). The influence of culture on consumer-oriented electronic commerce adoption. Journal of Electronic Commerce Research,11(1), 30–40.
   Web of Science ®Google Scholar
• Slyke, C. V., Lou, H., & Day, J. (2002). The impact of perceived innovation characteristics on intention to use groupware. Information Resource Management Journal,15(1), 5–12.
   Google Scholar
• Sreekumar, S. (2010). Biometric authentication in mobile payments (Masters thesis). University of Koblenz-Landau, Koblenz, Germany.
   Google Scholar
• Srivastava, S. C., Mathur, S. S., & Teo, T. S. (2007). Modernization of passenger reservation system: Indian railways’ dilemma. Journal of Information Technology,22(4), 432–439. doi:10.1057/palgrave.jit.2000112
   Web of Science ®Google Scholar
• Suki, N. M. (2010). An empirical study of factors affecting the internet banking adoption among Malaysian consumers. Journal of Internet Banking and Commerce,15(2), 1–11.
   Google Scholar
• Tan, M., & Teo, T. S. H. (2000). Factors influencing the adoption of internet banking. Journal of the Association for Information Systems,1(5), 1–42.
   Google Scholar
• Tanakinjal, G. H., Deans, K. R., & Gray, B. J. (2010). Third screen communication and the adoption of mobile marketing: A Malaysia perspective. International Journal of Marketing Studies,2(1), 36–47.
   Google Scholar
• Taylor, D. G., & Strutton, D. (2010). Has e-marketing come of age? Modeling historical influences on post-adoption era Internet consumer behaviors. Journal of Business Research,63(9), 950–956. doi:10.1016/j.jbusres.2009.01.018
   Web of Science ®Google Scholar
• Taylor, S., & Todd, P. (1995). Understanding information technology usage: A test of competing models. Information Systems Research,6(2), 144–176. doi:10.1287/isre.6.2.144
   Web of Science ®Google Scholar
• Teo, T. S. H., & Pok, S. H. (2003). Adoption of WAP-enabled mobile phones among internet users. Omega,31(6), 483–498. doi:10.1016/j.omega.2003.08.005
   Web of Science ®Google Scholar
• Tornatzky, L. G., & Klein, K. J. (1982). Innovation characteristics and innovation adoption-implementation: A meta-analysis of findings. IEEE Transactions on Engineering Management,EM-29(1), 28–45. doi:10.1109/TEM.1982.6447463
   Web of Science ®Google Scholar
• Vishwanath, A., & Goldhaber, G. M. (2003). An examination of the factors contributing to adoption decisions among late-diffused technology products. New Media & Society,5(4), 547–572. doi:10.1177/146144480354005
   Web of Science ®Google Scholar
• Wampold, B. E., & Freund, R. D. (1987). Use of multiple regression in counseling psychology research: A flexible data-analytic strategy. Journal of Counseling Psychology,34(4), 372–382. doi:10.1037/0022-0167.34.4.372
   Web of Science ®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. doi:10.1016/j.techfore.2010.03.006
   Web of Science ®Google Scholar
• Worster, A., Fan, J., & Ismaila, A. (2007). Understanding linear and logistic regression analyses, pedagogical tools and methods. Canadian Journal of Emergency Medicine,9(2), 111–113.
   Google Scholar
• Wu, J.-H., & Wang, S.-C. (2005). What drives mobile commerce? An empirical evaluation of the revised technology acceptance model. Information and Management,42(5), 719–729. doi:10.1016/j.im.2004.07.001
   Web of Science ®Google Scholar
• Yang, H., Lay, Y., & Tsai, C. (2006). An implementation and usability evaluation of automatic cash-payment system for hospital. Journal of Scientific and Industrial Research,65(6), 485–487.
   Web of Science ®Google Scholar