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Young Women's Continuance Intentions to use Communication and Social Media Apps
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The rapid adoption of smartphones in the last few years indicates the changing scenario of communication patterns. The mobile app market is taking prime space in the digital world with high adoption and year-on-year growth rate. Out of all the categories, social media and communication (instant messaging apps) consume more than half of the digital time in most of the countries across the world. Generally, men and women have different patterns for preferences and usage of any particular thing. Similarly, preferences for mobile applications and usage styles also differ amongst them. Literature supports the fact that the usage of mobile apps among women is high compared with men. Thus, this study focused on the impact of satisfaction and attitude on the continuance intention of usage for communication and social media apps among young women. A hypothesized model was developed by the authors to find out the impact of perceived usefulness, enjoyment, and confirmation of expectations on satisfaction and attitude for the continuance usage of communication and social media apps. The data were collected by circulating the questionnaire on online and offline platforms. A total of 263 respondents from four different regions of Gujarat were considered for the analysis, and model validation was done by adopting the structural equation modelling method. The results confirmed that satisfaction was the strongest predictor for the continuance usage of communication and social media apps led by perceived usefulness and confirmation of expectations, while attitude significantly affected continuance usage led by perceived enjoyment.
Keywords
Women, Mobile Applications, TAM, ECM, Communication and Social Media Apps.
Paper Submission Date : January 6, 2020; Paper Sent Back for Revision : July 21, 2020; Paper Acceptance Date : October 18, 2020; Paper Published Online : March 10, 2021.
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- Amoroso, D., & Lim, R. (2017). The mediating effects of habit on continuance intention. International Journal of Information Management, 37(6), 693–702. https://doi.org/10.1016/j.ijinfomgt.2017.05.003
- App Annie. (2018). 2017 retrospective : A monumental year for the app economy. https://www.appannie.com/en/insights/market-data/app-annie-2017-retrospective/
- App Annie. (2019). The state of mobile. https://www.appannie.com/en/go/state-of-mobile-2019/
- Bhattacherjee, A. (2001). Understanding information systems continuance : An expectation - confirmation model. MIS Quarterly, 25(3), 351–370. https://doi.org/10.2307/3250921
- Brown, S.A., & Venkatesh V. (2005). Model of adoption of technology in the household : A baseline model test and extension incorporating household life cycle. MIS Quarterly, 29(3), 399–426. https://doi.org/10.2307/25148690
- Browne, M. W., & Cudeck, R. (1992). Alternative ways of assessing model fit. Sociological Methods & Research, 21(2), 230–258. https://doi.org/10.1177/0049124192021002005
- Chea, S., & Luo, M. M. (2008). Post-adoption behaviours of e-service customers : The interplay of cognition and emotion. International Journal of Electronic Commerce, 12(3), 29–56. https://doi.org/10.2753/jec1086-4415120303
- Cheng, S. - I. (2011). Comparisons of competing models between attitudinal loyalty and behavioural loyalty. International Journal of Business and Information, 2(10), 149–166.
- Chin, W. W., & Gopal, A. (1995). Adoption intention in GSS : Relative importance of beliefs. ACM SIGMIS Database : The Database for Advances in Information Systems, 26(2–3), 42–64. https://doi.org/10.1145/217278.217285
- Choi, G., & Chung, H. (2013). Applying the technology acceptance model to social networking sites (SNS) : Impact of subjective norm and social capital on the acceptance of SNS. International Journal of Human–Computer Interaction, 29(10), 619–628. https://doi.org/10.1080/10447318.2012.756333
- Chou, C. - H., Chiu, C. - H., Ho, C. - Y., & Lee, J. - C. (2013). Understanding mobile apps continuance usage behavior and habit : An expectance–confirmation theory. PACIS 2013 Proceedings, 132. https://aisel.aisnet.org/pacis2013/132
- Comscore. (2018). Global digital future in focus 2018. https://www.comscore.com/Insights/Presentations-and Whitepapers/2018/Global-Digital-Future-in-Focus-2018
- Coursaris, C.K., & Sung J. (2012). Antecedents and consequents of a mobile website’s interactivity. New Media & Society, 14(7), 1128–1146. https://doi.org/10.1177/1461444812439552
- 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. https://doi.org/10.1111/j.1559 1816.1992.tb00945.x
- Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13 (3), 319–340. https://doi.org/10.2307/249008
- Dickinger, A., & Kleijnen, M. (2008) Coupons going wireless : Determinants of consumer intentions to redeem mobile coupons. Journal of Interactive Marketing, 22(3), 24–39. https://doi.org/10.1002/dir.20115
- Ghani, J. A., Supnick, R., & Rooney, P. (1991). The experience of flow in computer-mediated and in face-to-face groups. ICIS 1991 Proceedings, 9. https://aisel.aisnet.org/icis1991/9
- Gupta, R., & Mathad, K. (2017). A study of factors affecting consumer behavioural intentions towards adoption of gamification. Indian Journal of Marketing, 47(7), 7–19. https://doi.org/10.17010/ijom/2017/v47/i7/116471
- Hair, J. F., W. C. Black, B. J. Babin, R. E. Anderson, & R. L. Tatham. (2006). Multivariate data analysis (6th ed.). Prentice-Hall.
- Islam, M.Z., Low, P.K., & Hasan, I. (2013). Intention to use advanced mobile phone services (AMPS). Management Decision, 51(4), 824–838. https://doi.org/10.1108/00251741311326590
- Kang, S. (2014). Factors influencing intention of mobile application use. International Journal of Mobile Communications, 12(4), 360–379. https://doi.org/10.1504/ijmc.2014.063653
- Kim, B. (2011). Understanding antecedents of continuance intention in social - networking services. Cyberpsychology, Behavior, and Social Networking, 14(4), 199–205. https://doi.org/10.1089/cyber.2010.0009
- Kim, B., & Han, I. (2009). The role of trust belief and its antecedents in a community-driven knowledge environment. Journal of the American Society for Information Science and Technology, 60(5), 1012–1026. https://doi.org/10.1002/asi.21041
- Kim, B., Kang, M., & Jo, H. (2014). Determinants of post-adoption behaviours of mobile communications applications : A dual-model perspective. International Journal of Human-Computer Interaction, 30(7), 547–559. https://doi.org/10.1080/10447318.2014.888501
- 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. https://doi.org/10.1016/j.im.2011.05.004
- Kumar, A., Gupta, S. L., & Kishor, N. (2016). The antecedents of customer loyalty: Attitudinal and behavioral perspectives based on Oliver's loyalty model. Indian Journal of Marketing, 46(3), 31–53. https://doi.org/10.17010/ijom/2016/v46/i3/88996
- Lai, P. C. (2017). The literature review of technology adoption models and theories for the novelty technology. https://ssrn.com/abstract=3005897
- Lee, H. - M., & Chen, T. (2014). Perceived quality as a key antecedent in continuance intention on mobile commerce. International Journal of Electronic Commerce Studies, 5(2), 123–142. https://doi.org/10.7903/ijecs.1150
- Lee, S., & Quan, C.F. (2013). Factors affecting Chinese ubiquitous game service usage intention. International Journal of Mobile Communications, 11(2), 194–212. https://doi.org/10.1504/ijmc.2013.052641
- Lin, C.S., Wu, S., & Tsai, R.J. (2005). Integrating perceived playfulness into expectation - confirmation model for web portal context. Information & Management, 42(5), 683–693. https://doi.org/10.1016/j.im.2004.04.003
- Lin, K. - Y., & Lu, H. - P. (2011). Why people use social networking sites: An empirical study integrating network externalities and motivation theory. Computers in Human Behavior, 27(3), 1152–1161. https://doi.org/10.1016/j.chb.2010.12.009
- Lin, T. - C., Huang, S.- L., & Hsu, C. - J. (2015). A dual-factor model of loyalty to IT product — The case of smartphones. International Journal of Information Management, 35(2), 215–228. https://doi.org/10.1016/j.ijinfomgt.2015.01.001
- Momani, A. M., & Jamous, M. (2017). The evolution of technology acceptance theories. SSRN. https://ssrn.com/abstract=2971454
- Moon, J. - W., & Kim, Y. - G. (2001). Extending the TAM for a World-Wide-Web context. Information & Management, 38(4), 217–230. https://doi.org/10.1016/S0378-7206(00)00061-6
- Nagdev, K., & Rajesh, A. (2018). Consumers' intention to adopt internet banking : An Indian perspective. Indian Journal of Marketing, 48(6), 42–56. https://doi.org/10.17010/ijom/2018/v48/i6/127835
- Noh, M. J., & Lee, K. T. (2016). An analysis of the relationship between quality and user acceptance in smartphone apps. Information Systems and e-Business Management, 14(2), 273–291. https://doi.org/10.1007/s10257-015-0283-6
- Nunnally, J. (1978). Psychometric theory (2nd ed.). McGraw-Hill.
- Oliver, R. L. (1993). Cognitive, affective, and attribute bases of the satisfaction response. Journal of Consumer Research, 20(3), 418–430. https://doi.org/10.1086/209358
- Oliver, R.L., & Swan, J.E. (1989). Consumer perceptions of interpersonal equity and satisfaction in transactions : A field survey approach. Journal of Marketing, 53(2), 21–35. https://doi.org/10.1177/002224298905300202
- Park, E., Baek, S., Ohm, J., & Chang, H.J. (2014). Determinants of player acceptance of mobile social network games : An application of extended technology acceptance model. Telematics and Informatics, 31(3), 3–15. https://doi.org/10.1016/j.tele.2013.07.001
- Park, J., Snell, W., Ha, S., & Chung, T. - L. (2011). Consumers’ post-adoption of M-services: Interest in future Mservices based on consumer evaluations of current M-services. Journal of Electronic Commerce Research, 12(3), 165–175.
- Qin, L., Kim, Y., Hsu, J., & Tan, X. (2011). The effects of social influence on user acceptance of online social networks. International Journal of Human–Computer Interaction, 27(9), 885–899. https://doi.org/10.1080/10447318.2011.555311
- Reddy, T. T., & Rao, B. M. (2019). The moderating effect of gender on continuance intention toward mobile wallet services in India. Indian Journal of Marketing, 49(4), 48–62. https://doi.org/10.17010/ijom/2019/v49/i4/142976
- Rungta, S. (2015). WhatsApp usage differences amongst genders : An exploratory study. Indian Journal of Marketing, 45(5), 27–37. https://doi.org/10.17010/ijom/2015/v45/i5/79938
- Setyawan, N., Shihab, M. R., Hidayanto, A. N., & Pinem, A. A. (2017). Continuance usage intention and intention to recommend on information based mobile application : A technological and user experience perspective. In, 2017 International Conference on Advanced Computer Science and Information Systems (ICACSIS) (pp. 184 –189). IEEE. https://doi.org/10.1109/icacsis.2017.8355031
- Sharma, R., & Mishra, R. (2014). A review of evolution of theories and models of technology adoption. Indore Management Journal, 6(2), 17–29.
- Teo, A. - C., Tan, G.W. - H., Cheah, C. - M., Ooi, K. - B., & Yew, K. - T. (2012). Can the demographic and subjective norms influence the adoption of mobile banking ? International Journal of Mobile Communications, 10(6), 578–597. https://doi.org/10.1504/ijmc.2012.049757
- Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology : Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
- Verkasalo, H., Lopez - Nicolas, C., Molina - Castillo, F.J., & Bouwman, H. (2010). Analysis of users and non-users of smartphone applications. Telematics and Informatics, 27 (3), 242–255. https://doi.org/10.1016/j.tele.2009.11.001
- Verto Analytics. (2017). Who are the cross-device consumers ? https://vertoanalytics.com/who-is-cross-deviceconsumer
- Wang, Y.J., Hernandez, M.D., & Minor, M.S. (2010). Web aesthetics effects on perceived online service quality and satisfaction in an e-tail environment : The moderating role of purchase task. Journal of Business Research, 63(9–10), 935–942. https://doi.org/10.1016/j.jbusres.2009.01.016
- Wu, H. - Y., Liao, W. - H., Chen, P. - M., Hsu, C. - Y., & Li, T. - Y. (2014). Logging and analyzing long-term mobile user behavior. International Journal of Electronic Commerce Studies, 5(2), 161–180. https://doi.org/10.7903/ijecs.1349
- Xu, J., Forman, C., Kim, J. B., & Van Ittersum, K. (2014). News media channels : Complements or substitutes ? Evidence from mobile phone usage. Journal of Marketing, 78(4), 97–112. https://doi.org/10.1509/jm.13.0198
- Yang, H. C. (2013). Bon Appétit for apps : Young American consumers' acceptance of mobile applications. Journal of Computer Information Systems, 53(3), 85–96. https://doi.org/10.1080/08874417.2013.11645635
- Zhou, T. (2013). Understanding continuance usage of mobile sites. Industrial Management & Data Systems, 113(9), 1286 –1299. https://doi.org/10.1108/imds-01-2013-0001
- Zhou, T., & Lu, Y. (2011). Examining postadoption usage of mobile services from a dual perspective of enablers and inhibitors. International Journal of Human–Computer Interaction, 27(12), 1177–1191. https://doi.org/10.1080/10447318.2011.565717
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