E-governance using mobile applications: A case study of India during the COVID-19 pandemic
Healthcare initiatives backed by electronic-governance (e-governance) principles have contributed well to the extant literature and practice. Governments and healthcare systems across the world were taken aback by the swamping impact of the COVID-19 pandemic. However, they reacted quickly by developing contact-tracing mobile applications (apps) for creating awareness, providing information about various healthcare initiatives, and helping citizens to use the required information in case of emergency. The major challenge was to develop such e-governance interventions in a short time and ensure their quick adoption among the masses. Hence, it is worthwhile to investigate the factors leading to the adoption of such e-governance initiatives, especially in the context of a widespread pandemic situation. The present study is an attempt to analyze the factors driving the intention to use contact tracing mobile apps launched by governments globally during the COVID-19 pandemic. We have conducted the study in the context of India, where the government launched a community-driven contact tracing mobile app for its citizens during the COVID-19 pandemic in April 2020. The study adopted an empirical approach to test how epistemic value, convenience value, conditional value, functional value, and privacy concerns influenced the intention to use this approach. The study found that intention to use such an app was positively influenced by functional value, which in turn was positively influenced by convenience and conditional values. It suggests that the convenience of using the app, perceived seriousness of the pandemic (i.e., conditional value), and utilitarian benefits (i.e., functional value) of the contact-tracing mobile app enhanced its acceptance. However, its novelty (i.e., epistemic value) and privacy concerns are not significant predictors of intention to use. The study recommends that the government should place more emphasis on improving the functional value which is driven by convenience and context-specific features to push the use of an e-governance initiative during the crisis.
Aarogya Setu Website (2021). Retrieved January 9, 2021, from https://aarogyasetu.gov.in/
Agarwal, S., & Sharma, Y. S. (2020). Aarogya Setu coming on feature phones; to cover the entire country. Retrieved September 21, 2020, from
Agrebi, S., & Jallais, J. (2015). Explain the intention to use smartphones for mobile shopping. Journal of Retailing and Consumer Services, 22, 16-23.
Alhassan, A., Li, L., Reddy, K., & Duppati, G. (2020). Consumer acceptance and continuance of mobile money. Australasian Journal of Information Systems, 24. https://doi.org/10.3127/ajis.v24i0.2579
Altman, I. (1976). Privacy: A conceptual analysis. Environment and Behavior, 8(1),7-28.
Anckar, B., & D'incau, D. (2002). Value creation in mobile commerce: Findings from a consumer survey. Journal of Information Technology Theory and Application, 4(1), 43-64.
Anderson, J. C., & Gerbing, D. W. (1991). Predicting the performance of measures in a confirmatory factor analysis with a pretest assessment of their substantive validities. Journal of Applied Psychology, 76(5), 732-740.
Anderson, R.E., & Srinivasan, S.S. (2003). E‐satisfaction and e‐loyalty: A contingency framework. Psychology & marketing, 20(2), 123-138.
Angst, C. M., & Agarwal, R. (2009). Adoption of electronic health records in the presence of privacy concerns: The elaboration likelihood model and individual persuasion. MIS Quarterly, 33(2), 339-370.
Banerjea, A. (2020). India's Aarogya Setu becomes world's highest downloaded app in just 13 days. Retrieved September 21, 2020, from https://www.livemint.com/technology/tech-news/india-s-aarogya-setu-becomes-world-s-highest-downloaded-app-in-just-13-days-11586954392024.html
Boon-Itt, S., & Wong, C. Y. (2016). Empirical investigation of alternate cumulative capability models: a multi-method approach. Production Planning & Control, 27(4), 299-311.
Cengiz, E., & Kirkbir, F. (2007). Customer perceived value: the development of a multiple item scale in hospitals. Problems and perspectives in management, 5(3), 252-268.
Chauhan, S., & Kaushik, A. (2016). Evaluating citizen acceptance of unique identification number in India: an empirical study. Electronic Government, an International Journal, 12(3), 223-242.
Chen, G., & Kotz, D. (2000). A survey of context-aware mobile computing research. Dartmouth Computer Science Technical Report TR2000-381. Retrieved September 21, 2020, from https://digitalcommons.dartmouth.edu/cgi/viewcontent.cgi?article=4201&context=facoa
Chib, A., van Velthoven, M. H., & Car, J. (2015). mHealth adoption in low-resource environments: a review of the use of mobile healthcare in developing countries. Journal of Health Communication, 20(1), 4-34.
Chin, W.W., & Newsted, P.R. (1999). Structural equation modeling analysis with small samples using partial least squares. Statistical Strategies for Small Sample Research, 1(1), 307-341.
Chow, W. S., & Shi, S. (2014). Investigating students’ satisfaction and continuance intention toward e-learning: An Extension of the expectation–confirmation model. Procedia-Social and Behavioral Sciences, 141, 1145-1149.
Churchill Jr, G. A. (1979). A paradigm for developing better measures of marketing constructs. Journal of Marketing Research, 16(1), 64-73.
Clarance, A. (2020). Aarogya Setu: Why India's Covid-19 contact tracing app is controversial. Retrieved September 21, 2020, from https://www.bbc.com/news/world-asia-india-52659520
Colwell, S. R., Aung, M., Kanetkar, V., & Holden, A. L. (2008). Toward a measure of service convenience: multiple‐item scale development and empirical test. Journal of Services Marketing, 22(2), 160-169.
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), 982-1003.
Dhaggara, D., Goswami, M., & Kumar, G. (2020). Impact of Trust and Privacy Concerns on Technology Acceptance in Healthcare: An Indian Perspective. International Journal of Medical Informatics, 141, 104164.
Dinev, T., & Hart, P. (2006). An extended privacy calculus model for e-commerce transactions. Information Systems Research, 17(1), 61-80.
Falbo, T., Kim, S., & Chen, K. Y. (2009). Alternate models of sibling status effects on health in later life. Developmental Psychology, 45(3), 677-687.
Farronato, C., Iansiti, M., Bartosiak, M., Denicolai, S., Ferretti, L., & Fontana, R. (2020). How to Get People to Actually Use Contact-Tracing Apps. Harvard Business Review Digital Articles. Retrieved September 18, 2020, from https://hbr.org/2020/07/how-to-get-people-to-actually-use-contact-tracing-apps
Fishbein, M., & Ajzen, I. (1975). Belief, attitudes, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
Firstpost (2020). Aarogya Setu: Lack of Data Privacy Laws, Transparent Policies Make App Worrisome, Say MIT Researchers. Retrieved September 21, 2020, from https://www.firstpost.com/tech/news-analysis/aarogya-setu-the-mandatory-contact-tracing-app-of-india-gets-reviewed-by-mit-university-here-is-what-they-think-8354661.html
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
Garg, S., Bhatnagar, N., & Gangadharan, N. (2020). A case for participatory disease surveillance of the COVID-19 pandemic in India. JMIR Public Health and Surveillance, 6(2), e18795.
Ghosh, A., Nundy, S., & Mallick, T. K. (2020). How India is dealing with COVID-19 pandemic. Sensors International, 1, 100021.
Gonçalves, H. M., Lourenço, T. F., & Silva, G. M. (2016). Green buying behavior and the theory of consumption values: A fuzzy-set approach. Journal of Business Research, 69(4), 1484-1491.
Gu, J., Xu, Y. C., Xu, H., Zhang, C., & Ling, H. (2017). Privacy concerns for mobile app download: An elaboration likelihood model perspective. Decision Support Systems, 94, 19-28.
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2010). Multivariate data analysis (7th ed.). NJ: Pearson Prentice Hall, Uppersaddle River.
Hasan, H., & Linger, H. (2020). Letting the public in: Dialectic tensions when governments use ICT to engage citizens. Australasian Journal of Information Systems, 24. https://doi.org/10.3127/ajis.v24i0.1897
Hew, T. S., & Kadir, S. L. S. A. (2017). Applying Channel Expansion and Self-Determination Theory in predicting use behaviour of cloud-based VLE. Behaviour & Information Technology, 36(9), 875-896.
Hill, T., Smith, N. D., & Mann, M. F. (1987). Role of efficacy expectations in predicting the decision to use advanced technologies: The case of computers. Journal of Applied Psychology, 72(2), 307-313.
Hoehle, H., & Venkatesh, V. (2015). Mobile application usability: conceptualization and instrument development. MIS Quarterly, 39(2), 435-472.
Holbrook, M. B. (1994). The nature of customer value: an axiology of services in the consumption experience. Service quality: New directions in theory and practice, 21(1), 21-71.
Immuni Website (2021). Retrieved February 7, 2021, from https://www.immuni.italia.it/
Iqbal, N., & Dar, K. A. (2020). Coronavirus disease (COVID-19) pandemic: Furnishing experiences from India. Psychological Trauma: Theory, Research, Practice, and Policy, 12(S1), S33-S34.
Khanra, S., & Joseph, R. P. (2019). Adoption of e-Governance: the mediating role of language proficiency and digital divide in an emerging market context. Transforming Government: People, Process and Policy, 13(2), 122-142.
Kijsanayotin, B., Pannarunothai, S., & Speedie, S. M. (2009). Factors influencing health information technology adoption in Thailand's community health centers: Applying the UTAUT model. International Journal of Medical Informatics, 78(6), 404-416.
Kilbourne, W., & Pickett, G. (2008). How materialism affects environmental beliefs, concern, and environmentally responsible behavior. Journal of Business Research, 61(9), 885–893.
Kumar, R., Sachan, A., & Kumar, R. (2020). The impact of service delivery system process and moderating effect of perceived value in internet banking adoption. Australasian Journal of Information Systems, 24. https://doi.org/10.3127/ajis.v24i0.1923
Lah, F. (2008). Are IP addresses “personal identifiable information”? I/S: A Journal of Law and Policy for the Information Society, 4(3), 681-706.
Lee, E., & Han, S. (2015). Determinants of adoption of mobile health services. Online Information Review, 39(4), 556-573.
Lee, E., Han, S., & Jo, S. H. (2017). Consumer choice of on-demand mHealth app services: Context and contents values using structural equation modeling. International Journal of Medical Informatics, 97, 229-238.
Lee, M. C. (2010). Explaining and predicting users’ continuance intention toward e-learning: An extension of the expectation–confirmation model. Computers & Education, 54(2).506-516.
Lee-Geiller, S., & Lee, T. D. (2019). Using government websites to enhance democratic E-governance: A conceptual model for evaluation. Government Information Quarterly, 36(2), 208-225.
Leitner, C. (2003). eGovernment in Europe: The State of Affairs. European Institute of Public Administration, Maastricht.
Lim, W. M. (2018a). Dialectic antidotes to critics of the technology acceptance model: Conceptual, methodological, and replication treatments for behavioural modelling in technology-mediated environments. Australasian Journal of Information Systems, 22. https://doi.org/10.3127/ajis.v22i0.1651
Lim, W. M. (2018b). Revisiting concepts and theories in information systems and technology. Australasian Journal of Information Systems, 22. https://doi.org/10.3127/ajis.v22i0.1733
Lim, W. M., Lim, A. L., & Phang, C. S. C. (2019). Toward a conceptual framework for social media adoption by non-urban communities for non-profit activities: Insights from an integration of grand theories of technology acceptance. Australasian Journal of Information Systems, 23. https://doi.org/10.3127/ajis.v23i0.1835
Livemint (2020). More than 50% of India’s population 25 yrs or older: Survey. Retrieved September 15, 2020, from https://www.livemint.com/news/india/more-than-50-of-india-s-population-25-yrs-or-older-survey-11593793054491.html
Lohchab, H. (2019). Overall, India handset market growth to fall in 2020. Retrieved September 21, 2020, from https://economictimes.indiatimes.com/tech/hardware/overall-india-handset-market-growth-to-fall-in-2020/articleshow/72950192.cms?from=mdr
Long, M.M., & Schiffman, L.G. (2000). Consumption values and relationships: Segmenting the market for frequency programs. Journal of Consumer Marketing, 17(3), 214-232.
Lu, H. K., Lin, P. C., & Chen, A. N. (2017). An empirical study of behavioral intention model: Using learning and teaching styles as individual differences. Journal of Discrete Mathematical Sciences and Cryptography, 20(1), 19-41.
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.
MacKenzie, S. B., Podsakoff, P. M., & Podsakoff, N. P. (2011). Construct measurement and validation procedures in MIS and behavioral research: Integrating new and existing techniques. MIS Quarterly, 35(2), 293-334.
O’Neill, P.H., Ryan-Mosley, T., & Johnson, R. (2020). A flood of coronavirus apps are tracking us. Now it’s time to keep track of them. Retrieved September 21, 2020, from https://www.technologyreview.com/2020/05/07/1000961/launching-mittr-covid-tracing-tracker/
O’Neill, P. H. (2020). India is forcing people to use its covid app, unlike any other democracy. Retrieved September 18, 2020, from https://www.technologyreview.com/2020/05/07/
Okazaki, S. (2008). Exploring experiential value in online mobile gaming adoption. Cyberpsychology & Behavior, 11(5), 619-622.
Pagani, M. (2004). Determinants of adoption of third generation mobile multimedia services. Journal of Interactive Marketing, 18(3), 46-59.
Pan, S. L., & Zhang, S. (2020). From fighting COVID-19 pandemic to tackling sustainable development goals: An opportunity for responsible information systems research. International Journal of Information Management, 55, 102196.
Pihlström, M., & Brush, G. J. (2008). Comparing the perceived value of information and entertainment mobile services. Psychology & Marketing, 25(8), 732-755.
Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: a critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879-903.
Pura, M. (2005). Linking perceived value and loyalty in location-based mobile services. Managing Service Quality, 15(6), 509-538.
Reuters (2020). Italy launches COVID-19 contact-tracing app amid privacy concerns. Retrieved February 7, 2021, from https://www.reuters.com/article/us-health-coronavirus-italy-app-idINKBN2383EW
Rintamäki, T., Kanto, A., Kuusela, H., & Spence, M. T. (2006). Decomposing the value of department store shopping into utilitarian, hedonic and social dimensions. International Journal of Retail & Distribution Management, 34(1), 6-24.
Rokeach, M. (1968). A Theory of Organization and Change Within Value‐Attitude Systems. Journal of Social Issues, 24(1), 13-33.
Sarkar, S., Chauhan, S., & Khare, A. (2020). A meta-analysis of antecedents and consequences of trust in mobile commerce. International Journal of Information Management, 50, 286-301.
Saxena, K. B. C. (2005). Towards excellence in e‐governance. International Journal of Public Sector Management, 18(6), 498-513.
Sheth, J. N., Newman, B. I., & Gross, B. L. (1991). Why we buy what we buy: A theory of consumption values. Journal of Business Research, 22(2), 159-170.
Shroff, R. H., & Keyes, C. J. (2017). A proposed framework to understand the intrinsic motivation factors on university students’ behavioral intention to use a mobile application for learning. Journal of Information Technology Education: Research, 16(1), 143-168.
Singh, M., & Sahu, G. P. (2018). Study of e-governance implementation: a literature review using classification approach. International Journal of Electronic Governance, 10(3), 237-260.
Singh, S. (2020). An integrated model combining ECM and UTAUT to explain users’ post-adoption behavior towards mobile payment systems. Australasian Journal of Information Systems, 24. https://doi.org/10.3127/ajis.v24i0.2695
Smith, H. J., Dinev, T., & Xu, H. (2011). Information privacy research: An interdisciplinary review. MIS Quarterly, 35(4), 989-1016.
Soma, K., Termeer, C. J., & Opdam, P. (2016). Informational governance–A systematic literature review of governance for sustainability in the Information Age. Environmental Science & Policy, 56, 89-99.
Statistics Times (2020). Population of India. Retrieved September 15, 2020, from http://statisticstimes.com/demographics/country/india-population.php
Steenkamp, J. B. E., & Baumgartner, H. (1992). The role of optimum stimulation level in exploratory consumer behavior. Journal of Consumer Research, 19(3), 434-448.
Stemberger, M. I., & Jaklic, J. (2007). Towards E-government by business process change—A methodology for public sector. International Journal of Information Management, 27(4), 221-232.
The Economic Times (2020). Rahul Gandhi raises security, privacy concerns over Aarogya Setu app. Retrieved September 21, 2020, from https://economictimes.indiatimes.com/news/politics-and-nation/rahul-gandhi-raises-security-privacy-concerns-over-arogya-setu-app/articleshow/75508771.cms
The Hindu (2020). Data | How safe is Aarogya Setu compared to COVID-19 contact tracing apps of other countries? Retrieved September 21, 2020, from https://www.thehindu.com/data/how-safe-is-aarogya-setu-compared-to-contact-tracing-apps-of-other-countries/article31618852.ece
The Quint (2020). MIT Researchers Downgrade Aarogya Setu App to One Star in Review. Retrieved September 21, 2020, from https://www.thequint.com/tech-and-auto/tech-news/aarogya-setu-app-gets-one-star-out-of-five-in-mit-review
The Times of India (2020). Government launches Covid-19 tracking app Aarogya Setu. Retrieved September 21, 2020, from http://timesofindia.indiatimes.com/articleshow/
Toots, M. (2019). Why E-participation systems fail: The case of Estonia's Osale.ee. Government Information Quarterly, 36(3), 546-559.
Tzeng, J. Y. (2011). Perceived values and prospective users’ acceptance of prospective technology: The case of a career eportfolio system. Computers & Education, 56(1), 157-165.
Vinson, D. E., Scott, J. E., & Lamont, L. M. (1977). The role of personal values in marketing and consumer behavior. Journal of Marketing, 41(2), 44-50.
Wang, H. Y., Liao, C., & Yang, L. H. (2013). What affects mobile application use? The roles of consumption values. International Journal of Marketing Studies, 5(2), 11-22.
Westin, A. F. (2003). Social and political dimensions of privacy. Journal of Social Issues, 59(2), 431-453.
Worldometer (2021). Countries in the world by population (2021). Retrieved February 20, 2021, from https://www.worldometers.info/world-population/population-by-country/
Xu, H., Teo, H. H., Tan, B. C., & Agarwal, R. (2012). Research note—effects of individual self-protection, industry self-regulation, and government regulation on privacy concerns: a study of location-based services. Information Systems Research, 23(4), 1342-1363.
Yang, H.-L., & Lin, R.-X. (2017). Determinants of the intention to continue use of SoLoMo services: Consumption values and the moderating effects of overloads. Computers in Human Behavior, 73, 583-595.
Zainuddin, N., Russell-Bennett, R. & Previte, J. (2013). The value of health and wellbeing: an empirical model of value creation in social marketing. European Journal of Marketing, 47(9), 1504-1524.
Zandifar, A., & Badrfam, R. (2020). Iranian mental health during the COVID-19 epidemic. Asian Journal of Psychiatry, 51, 101990.
Zhang, Y., Yu, P., & Shen, J. (2012). The benefits of introducing electronic health records in residential aged care facilities: a multiple case study. International Journal of Medical Informatics, 81(10), 690-704.
AJIS publishes open-access articles distributed under the terms of a Creative Commons Non-Commercial and Attribution License which permits non-commercial use, distribution, and reproduction in any medium, provided the original author and AJIS are credited. All other rights including granting permissions beyond those in the above license remain the property of the author(s).