Electronic Markets

, Volume 23, Issue 1, pp 29–47 | Cite as

Continuance of mHealth services at the bottom of the pyramid: the roles of service quality and trust

Special Theme

Abstract

Continued usage of information systems (or, IS continuance) has proven to be a critical success parameter for ICT implementation at the top of the global economic pyramid. However, there are few studies which have explored continued IS usage at the bottom of the economic pyramid (BOP) though it represents the majority of the world’s population. To fill this knowledge gap, this study develops an mHealth continuance model at the BOP framing the impact of two post adoption expectation beliefs (i.e., perceived service quality and perceived trust). This study extends ECM (expectation confirmation model) perspective synthesizing the extant literature on continued IS usage, service quality and consumer trust. The proposed model was empirically tested within the context of mHealth (mobile health) services at the BOP, applying PLS (partial least squares) under a cross sectional study. The findings confirm that both perceived service quality and perceived trust have significant explanatory power under an integrated ECM providing superior prediction of continuance intentions. The study concludes by discussing conceptual contributions, practical implications, limitations and future research directions.

Keywords

ECM (expectation confirmation model) BOP (bottom of the pyramid) Service quality Consumer trust PLS path analysis 

JEL classification

M15 M31 L15 L86 

References

  1. Ahluwalia, P., & Varshney, U. (2009). Composite quality of service and decision making perspectives in wireless networks. Decision Support Systems, 46(2009), 542–551.CrossRefGoogle Scholar
  2. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179–211.CrossRefGoogle Scholar
  3. Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs: Prentice-Hall.Google Scholar
  4. Akter, S., & Ray, P. (2010). mHealth- an ultimate platform to serve the unserved. IMIA Yearbook of Medical Informatics, 94–100.Google Scholar
  5. Akter, S., D’Ambra, J., & Ray, P. (2010). Service quality of mHealth: development and validation of a hierarchical model using PLS. Electronic Markets, 20(3), 209–227.CrossRefGoogle Scholar
  6. Akter, S., D’Ambra, J., & Ray, P. (2011). Trustworthiness in mHealth information services: an assessment of a hierarchical model with mediating and moderating effects using partial least squares (PLS). Journal of the American Society for Information Science and Technology, 62(1), 100–116.CrossRefGoogle Scholar
  7. Alter, S. (2010). Viewing systems as services: a fresh approach in the IS field. Communications of the AIS, 26(11), 195–224.Google Scholar
  8. Andaleeb, S. S. (2001). Service quality perceptions and patient satisfaction: a study of hospitals in a developing country. Social Science & Medicine, 52(9), 1359–1370.CrossRefGoogle Scholar
  9. Anderson, E. W., & Sullivan, M. W. (1993). The antecedents and consequences of customer satisfaction for firms. Marketing Science, 12(2), 125–143.CrossRefGoogle Scholar
  10. Au, N., Ngai, E. W. T., & Cheng, T. C. E. (2002). A critical review of end-user information system satisfaction research and a new research framework. Omega, 30, 451–478.CrossRefGoogle Scholar
  11. Baroudi, J. J., & Orlikowski, W. J. (1988). A short-form measure of user information satisfaction: a psychometric evaluation and notes on use. Journal of MIS, 4(4), 44–59.Google Scholar
  12. Barrett, C. R. (2008). Perspectives on inclusive ICT business by intel. Electronic Markets, 18(4), 300–301.CrossRefGoogle Scholar
  13. Bauer, H., Grether, M., & Leach, M. (2002). Building customer relations over the internet. Industrial Marketing Management, 31, 155–163.CrossRefGoogle Scholar
  14. Bejou, D., Ennew, C. T., & Palmer, A. (1998). Trust, ethics and relationship satisfaction. International Journal of Bank Marketing, 16(4), 170–175.CrossRefGoogle Scholar
  15. Bhattacherjee, A. (2001a). An empirical analysis of the antecedents of electronic commerce service continuance. Decision Support Systems, 32, 201–214.CrossRefGoogle Scholar
  16. Bhattacherjee, A. (2001b). Understanding information systems continuance. An expectation–confirmation model. MIS Quarterly, 25(3), 351–370.CrossRefGoogle Scholar
  17. Bhattacherjee, A. (2002). Individual trust in online firms: scale development and initial test. Journal of Management Information Systems, 19(1), 211–241.Google Scholar
  18. Bhattacherjee, A., & Premkumar, G. (2004). Understanding changes in belief and attitude toward information technology usage: a theoretical model and an empirical test. MIS Quarterly, 28, 229–255.Google Scholar
  19. Blau, P. M. (1964). Exchange and power in social life. New York: Wiley.Google Scholar
  20. Brady, M. K., & Cronin, J. J. (2001). Some new thoughts on conceptualizing perceived service quality: a hierarchical approach. Journal of Marketing, 65(July), 34–49.CrossRefGoogle Scholar
  21. Brady, M. K., & Robertson, C. J. (2001). Searching for a consensus on the antecedent role of service quality and satisfaction: an exploratory cross-national study. Journal of Business Research, 51(1), 53–60.CrossRefGoogle Scholar
  22. Brommey, M. (2003). Challenges in e-health service delivery. 2nd annual online summit. Available at: http://www.health.gov.au/healthonline/docs/summit2/brommeyer.pdf [accessed 2010 September 24].
  23. Chatterjee, S., Chakraborty, S., Sarker, S., Sarker, S., & Lau, Y. F. (2009). Examining the success factors for mobile work in healthcare: a deductive study. Decision Support Systems, 46, 620–633.CrossRefGoogle Scholar
  24. Chin, W. W. (1998). The partial least squares approach to structural equation modeling. In G. A. Marcoulides (Ed.), Modern business research methods (pp. 295–336). Mahwah: Lawrence Erlbaum Associates.Google Scholar
  25. Chin, W. W. (2001). PLS – graph user’s guide version 3.0. Houston: Soft Modeling Inc.Google Scholar
  26. Chin, W. W. (2010). How to write up and report PLS analyses. In V. Esposito Vinzi, W. W. Chin, J. Henseler, & H. Wang (Eds.), Handbook of partial least squares: Concepts, methods and application (pp. 645–689). Germany: Springer.Google Scholar
  27. Chin, W. W., & Newsted, P. R. (1999). Structural equation modeling analysis with small samples using partial least squares. In R. Hoyle (Ed.), Statistical strategies for small sample research (pp. 307–341). Thousand Oaks: Sage Publications.Google Scholar
  28. Chiou, J., & Droge, C. (2006). Service quality, trust, specific asset investment, and expertise: direct and indirect effects in a satisfaction-loyalty framework. Journal of the Academy of Marketing Science, 34(4), 613–627.CrossRefGoogle Scholar
  29. Chou, S. W., & Chen, P. Y. (2009). The influence of individual differences on continuance intentions of enterprise resource planning (ERP). International Journal of Human Computer Studies, 67, 484–496.CrossRefGoogle Scholar
  30. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale: L. Erlbaum Associates.Google Scholar
  31. Cronin, J., & Taylor, S. A. (1992). Measuring service quality: a reexamination and extension. Journal of Marketing, 56(July), 55–68.CrossRefGoogle Scholar
  32. Cronin, J. J., Brady, M. K., & Hult, G. T. (2000). Assessing the effects of quality, value and customer satisfaction on consumer behavioral intentions in service environments. Journal of Retailing, 76(2), 193–218.CrossRefGoogle Scholar
  33. Dabholkar, P. A., Shepard, C. D., & Thorpe, D. I. (2000). A comprehensive framework for service quality: an investigation of critical conceptual and measurement issues through a longitudinal study. Journal of Retailing, 76(2), 139–173.CrossRefGoogle Scholar
  34. Dagger, T. S., Sweeney, J. C., & Johnson, L. W. (2007). A hierarchical model of health service quality: scale development and investigation of an integrated model. Journal of Service Research, 10(2), 123–142.CrossRefGoogle Scholar
  35. Dahlberg, O., Mallat, N., Ondrus, J., & Zmijewska, A. (2008). Past, present and future of mobile payments research: A literature review. Electronic Commerce Research & Applications, 7(2), 165–181.Google Scholar
  36. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.CrossRefGoogle Scholar
  37. Deluca, J. M., & Enmark, R. (2000). E-health: the changing model of healthcare. Front Health Service Management, 17(1), 3–15.Google Scholar
  38. Efron, B., & Tibshirani, R. J. (1993). An introduction to the bootstrap. New York: Chapman and Hall.Google Scholar
  39. Eisingerich, B. A., & Bell, J. S. (2008). Perceived service quality and customer trust: does enhancing customers’ service knowledge matter? Journal of Service Research, 10(3), 256–268.CrossRefGoogle Scholar
  40. Faul, F., Erdfelder, E., Buchner, A., & Lang, G. A. (2009). Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses. Behavior Research Methods, 41(4), 1149–1160.CrossRefGoogle Scholar
  41. Flavian, C., Guinaliu, M., & Gurrea, R. (2006). The role played by perceived usability, satisfaction and consumer trust on website loyalty. Information Management, 43, 1–14.CrossRefGoogle Scholar
  42. Fornell, C., & Bookstein, F. L. (1982). Two structural equation models: LISREL and PLS applied to consumer exit-voice theory. Journal of Marketing Research (19), November 1982, pp. 440–452.Google Scholar
  43. Fornell, C., & Cha, J. (1994). Partial least squares. In R. Bagozzi (Ed.), Advanced methods of marketing (pp. 52–78). Cambridge: Blackwell.Google Scholar
  44. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.CrossRefGoogle Scholar
  45. Gefen, D., & Straub, D. W. (2004). Consumer trust in B2C e-ecommerce and the importance of social presence: experiments in e products and e services. Omega, 32, 407–424.CrossRefGoogle Scholar
  46. Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: an integrated model. MIS Quarterly, 27(1), 51–90.Google Scholar
  47. Geisser, S. (1975). The predictive sample reuse method with applications. Journal of the American Statistical Association, 70(350), 320–328.CrossRefGoogle Scholar
  48. Gotlieb, J. B., Dhruv, G., & Stephen, W. B. (1994). Consumer satisfaction and perceived quality: complementary or divergent constructs. Journal of Applied Psychology, 79(6), 875–885.CrossRefGoogle Scholar
  49. Gregor, S. (2006). The nature of theory in information systems. MISQ, 30(3), 611–642.Google Scholar
  50. Gronroos, C. (1984). A service quality model and its marketing implications. European Journal of Marketing, 18(4), 36–44.CrossRefGoogle Scholar
  51. Gwinner, K. P., Gremler, D. D., & Bitner, M. J. (1998). Relational benefits in services industries: the customer’s perspective. Journal of the Academy of Marketing Science, 26(2), 101–114.CrossRefGoogle Scholar
  52. Hammond, A. L., Kramer, W. J., Katz, R. S., Tran, J. T., & Walker, C. (2007). The next four billion: Market size and business strategy at the base of the pyramid. Washington: World Resources Institute and International Finance Corporation.Google Scholar
  53. Hart, S. L., & Milstein, M. B. (2003). Creating sustainable value. The Academy of Management Executive, 17(2), 56–67.CrossRefGoogle Scholar
  54. Hong, S.-J., & Tam, K. Y. (2006). Understanding the adoption of multipurpose information appliances: the case of mobile data services. Information Systems Research, 17(2), 162–179.CrossRefGoogle Scholar
  55. Ivatury, G., Moore, J., & Bloch, A. (2009). A doctor in your pocket: health hotlines in developing countries. Innovations: Technology, Governance, Globalization, 4(1), 119–153.CrossRefGoogle Scholar
  56. Jarvenpaa, S. L., Tractinsky, N., & Vitale, M. (2000). Consumer trust in an internet store. Information Technology and Management, 1(1–2), 45–71.CrossRefGoogle Scholar
  57. Jasperson, J., Carter, P. E., & Zmud, R. W. (2005). A comprehensive conceptualization of post-adoptive behaviors associated with information technology enabled work systems. MIS Quarterly, 29(3), 525–557.Google Scholar
  58. Johnson, D., & Grayson, K. (2005). Cognitive and affective trust in service relationships. Journal of Business Research, 58, 500–507.CrossRefGoogle Scholar
  59. Kalil, T. (2009). Harnessing the mobile revolution. Innovations: Technology, Governance, Globalization, 4(1), 11–26.CrossRefGoogle Scholar
  60. Kandachar, P., & Halme, M. (2008). Sustainability challenges and solutions at the base of the pyramid. Sheffield: Greenleaf Publishing.Google Scholar
  61. Kang, S. Y., Hong, S., & Lee, H. (2009). Exploring continued online service usage behavior, the roles of self image congruity and regret. Computers in Human Behavior, 25, 111–122.CrossRefGoogle Scholar
  62. Kaplan, W. A. (2006). Can the ubiquitous power of mobile phones be used to improve health outcomes in developing countries? Global Health, 2–9.Google Scholar
  63. Kaplan, B., & Litwka, S. (2008). Ethical challenges of telemedicine and telehealth. Cambridge Quarterly of Healthcare Ethics, 17, 401–416.CrossRefGoogle Scholar
  64. Karahanna, E., Straub, D. W., & Chervany, N. L. (1999). Information technology adoption across time: a cross-sectional comparison of pre-adoption and postadoption beliefs. MIS Quarterly, 23(2), 183–213.CrossRefGoogle Scholar
  65. Kassim, N. M., & Abdullah, N. A. (2008). Customer loyalty in e-commerce settings: an empirical study. Electronic Markets, 18(3), 275–290.CrossRefGoogle Scholar
  66. Kim, D. J., Ferrin, D. L., & Rao, H. R. (2008). A trust-based consumer decision-making model in electronic commerce: the role of trust, perceived risk, and their antecedents. Decision Support Systems, 44, 544–564.CrossRefGoogle Scholar
  67. Liao, C., Chen, J.-L., & Yen, D. C. (2007). Theory of planning behavior (TPB) and customer satisfaction in the continued use of e-service. An integrated model. Computers in Human Behavior, 23(6), 2804–2822.CrossRefGoogle Scholar
  68. Limayem, M., Hirt, S. G., & Cheung, C. M. K. (2007). How habit limits the predictive power of intention: the case of information systems continuance. MIS Quarterly, 31(4), 705–737.Google Scholar
  69. Lin, C. P., & Bhattacherjee, A. (2007). Extending technology usage models to interactive hedonic technologies: A theoretical model and empirical test. Information Systems Journal, 1–19.Google Scholar
  70. Lin, C. P., & Bhattacherjee, A. (2009). Understanding online social support and its antecedents: a socio-cognitive model. The Social Science Journal, 46, 724–737.CrossRefGoogle Scholar
  71. 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.CrossRefGoogle Scholar
  72. London, T. (2008). The base-of-the-pyramid perspective: A new approach to poverty alleviation. In G. T. Solomon (Ed.), Academy of Management Best Paper Proceedings (CD). Google Scholar
  73. London, T. (2009). Making better investments at the base of the pyramid. Harvard Business Review, 87(5), 106–113.Google Scholar
  74. London, T., & Hart, S. L. (2004). Reinventing strategies for emerging markets: beyond the transnational model. Journal of International Business Studies, 35(5), 350–370.CrossRefGoogle Scholar
  75. Mallat, N. (2007). Exploring consumer adoption of mobile payments – a qualitative study. The Journal of Strategic Information Systems, 16(4), 413–432.CrossRefGoogle Scholar
  76. Mechael, P. (2009). The case for mHealth in developing countries. Innovations: Technology, Governance, Globalization, 4(1), 103–118.CrossRefGoogle Scholar
  77. Morgan, R. M., & Hunt, S. D. (1994). The commitment-trust theory of relationship marketing. Journal of Marketing, July, 20–38.Google Scholar
  78. Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 17(4), 460–469.CrossRefGoogle Scholar
  79. Oliver, R. L. (1993). Cognitive, affective, and attribute bases of the satisfaction response. Journal of Consumer Research, 20(3), 418–430.CrossRefGoogle Scholar
  80. Orlikowski, W., & Iacono, C. S. (2001). Research commentary: desperately seeking the “IT” in IT research—a call to theorizing the IT artifact. Information Systems Research, 12(2), 121–134.CrossRefGoogle Scholar
  81. Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1988). SERVQUAL: a multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing, 64(1), 5–6.Google Scholar
  82. Parthasarathy, M., & Bhattacherjee, A. (1998). Understanding post-adoption behavior in the context of online services. Information Systems Research, 9(4), 362–379.CrossRefGoogle Scholar
  83. Patterson, P. G., Johnson, L. W., & Spreng, R. A. (1997). Modeling the determinants of customer satisfaction for business-to-business professional services. Journal of the Academy of Marketing Science, 25(1), 4–17.CrossRefGoogle Scholar
  84. Prahalad, C. K. (2004). The fortune at the bottom of the pyramid: Eradicating poverty through profits. Upper Saddle River: Wharton School Publishing.Google Scholar
  85. Prahalad, C. K., & Hammond, A. (2002). Serving the world’s poor, profitably. Harvard Business Review, 80(9), 48–57.Google Scholar
  86. Prahalad, C. K., & Hart, S. L. (2002). The fortune at the bottom of the pyramid. Strategy + Business, 26, 2–14.Google Scholar
  87. Premkumar, G., & Bhattacherjee, A. (2008). Explaining information technology usage: a test of competing models. Omega, 36, 64–75.CrossRefGoogle Scholar
  88. Quelch, J., & Klein, L. (1996). The internet and international marketing. Sloan Management Review, 1996, 60–75.Google Scholar
  89. Rangan, V. K., Quelch, J. A., Herrero, G., & Barton, B. (2007). Business solutions for the global poor: Creating social and economic value. San Francisco: Jossey-Bass.Google Scholar
  90. Rosa, J. A., & Viswanathan, M. (2007). Product and market development for subsistence marketplaces. Oxford: Elsevier Ltd.Google Scholar
  91. Rust, R. T., & Zahorik, A. J. (1993). Customer satisfaction, customer retention, and market share. Journal of Retailing, 69(2), 193–215.CrossRefGoogle Scholar
  92. Saga, V. L., & Zmud, R. W. (1994). The nature and determinants of IT acceptance, routinization, and infusion. In L. Levine (Ed.), Diffusion, transfer and implementation of information technology (pp. 67–86). Amsterdam: Elsevier Science.Google Scholar
  93. Sen, A. (1999). Development as freedom. Oxford: Oxford University Press.Google Scholar
  94. Spreng, R. A., MacKenzie, S. B., & Olshavsky, R. W. (1996). A reexamination of the determinants of customer satisfaction. Journal of Marketing, 60(3), 15–32.CrossRefGoogle Scholar
  95. Srideshmukh, D., Singh, J., & Sabol, B. (2002). Consumer trust, value and loyalty in relational exchanges. Journal of Marketing, 66, 15–37.CrossRefGoogle Scholar
  96. Stone, M. (1974). Cross validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society, 36(2), 111–147.Google Scholar
  97. Tenenhaus, M., Vinzi, V. E., Chatelin, Y.-M., & Lauro, C. (2005). PLS path modeling. Computational Statistics and Data Analysis, 48(1), 159–205.CrossRefGoogle Scholar
  98. Teo, T. S. H., & Liu, J. (2007). Consumer trust in e-commerce in the United States, Singapore and China. Omega, 35(1), 22–38.CrossRefGoogle Scholar
  99. Teo, T. S. H., Srivastava, S. C., & Jiang, L. (2008). Trust and electronic government success: an empirical study. Journal of Management Information Systems, 25(3), 99–131.CrossRefGoogle Scholar
  100. Thong, J. Y. L., Hong, S.-J., & Tam, K. Y. (2006). The effects of post-adoption beliefs on the expectation–confirmation model for information technology continuance. International Journal of Human Computer Studies, 64(9), 799–810.CrossRefGoogle Scholar
  101. United Nations. (2008). The millennium development goals report. New York: United Nations.Google Scholar
  102. United Nations Foundation and Vodafone Foundation. (2009). mHealth for development: The opportunity of mobile technology for healthcare in developing world. Available at: http://www.vitalwaveconsulting.com/insights/mHealth.htm [Accessed May 23, 2011].
  103. Van der Heijden, H. (2004). User acceptance of hedonic information systems. MIS Quarterly, 28(4), 695–704.Google Scholar
  104. Varshney, U. (2005). Pervasive healthcare: applications, challenges and wireless solutions. Communications of the Association for Information Systems, 16(3), 57–72.Google Scholar
  105. 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.Google Scholar
  106. Viswanathan, M., Gajendiran, S., & Venkatesan, R. (2008). Understanding and enabling marketplace literacy in subsistence contexts: the development of a consumer and entrepreneurial literacy educational programs in south India. International Journal of Educational Development, 23(3), 300–319.CrossRefGoogle Scholar
  107. Vital Wave Consulting. (2008). mHealth in the global south: Landscape analysis. Available at: http://www.vitalwaveconsulting.com/pdf/mHealth_in_the_Global_South_Landscape_Analysis.pdf [Accessed May 23, 2011].
  108. Walsham, G., Robey, D., & Sahay, S. (2007). Foreword: special issue on information systems in developing countries. MIS Quarterly, 31(2), 317–326.Google Scholar
  109. Wetzels, M., Schroder, G. O., & Oppen, V. C. (2009). Using PLS path modeling for assessing hierarchical construct models: guidelines and empirical illustration. MIS Quarterly, 33(1), 177–195.Google Scholar
  110. Whetten, D. A. (1989). What constitutes a theoretical contributions. Academy of Management Review, 14(4), 490–495.Google Scholar
  111. World Bank. (2004). World development report: Making services work for poor people. New York: Oxford University Press.Google Scholar
  112. World Health Organization. (2006). The world health report 2006—Working together for health. Geneva: WHO.Google Scholar
  113. Zeithaml, V. (1987). Defining and relating price, perceived quality, and perceived value (pp. 87–101). Cambridge: Marketing Science Institute. Report No. 87–101.Google Scholar
  114. Zeithaml, V. A. (2000). Service quality, profitability, and the economic worth of customers: what we know and what we need to learn. Journal of the Academy of Marketing Science, 28(1), 67–85.CrossRefGoogle Scholar

Copyright information

© Institute of Information Management, University of St. Gallen 2012

Authors and Affiliations

  1. 1.School of Management and Marketing, University of WollongongNew South WalesAustralia
  2. 2.Australian School of Business, University of New South WalesNew South WalesAustralia

Personalised recommendations