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Service quality of mHealth platforms: development and validation of a hierarchical model using PLS

Abstract

Advancing research on service quality requires clarifying the theoretical conceptualizations and validating an integrated service quality model. The purpose of this study is to facilitate and elucidate practical issues and decisions related to the development of a hierarchical service quality model in mobile health (mHealth) services research. Conceptually, it extends theory by reframing service quality as a reflective, hierarchical construct and modeling its impact on satisfaction, intention to continue using and quality of life. Empirically, it confirms that PLS path modeling can be used to estimate the parameters of a higher order construct and its association with subsequent consequential latent variables in a nomological network. The findings of the study show that service quality is the third-order, reflective construct model with strong positive effects on satisfaction, continuance intentions and quality of life in the context of mHealth services. Finally, the study discusses the implications of hierarchical service quality modeling in electronic markets and highlights future research directions.

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References

  1. Aharony, L., & Strasser, S. (1993). Patient satisfaction: what we know about and what we still need to explore. Medical Care Review, 50(1), 49–79.

    Article  Google Scholar 

  2. Ahluwalia, P., & Varshney, U. (2009). Composite quality of service and decision making perspectives in wireless networks. Decision Support Systems, 46(2), 542–551.

    Article  Google Scholar 

  3. Akter, S., & Ray, P. (2010). mHealth-an ultimate platform to serve the unserved. IMIA Yearbook of Medical Informatics, 2010, 75–81.

    Google Scholar 

  4. Akter, S., D’Ambra, J., Ray, P. (2010). User perceived services quality of mHealth services in developing countries. In the Proceedings of the Eighteen European Conference on conference on Information Systems, Pretoria, South Africa.

  5. 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.

    Article  Google Scholar 

  6. Andrade, R., Wangenheim, A. V., & Bortoluzzi, M. K. (2003). Wireless and PDA: a novel strategy to access DICOMcompliant medical data on mobile devices. International Journal of Medical Informatics, 71(23), 157–163.

    Article  Google Scholar 

  7. Angst, M. C., & Agarwal, R. (2009). Adoption of electronic health records in the presence of privacy concerns: the elaborate likelihood model and individual persuasion. MIS Quarterly, 33(2), 339–370.

    Google Scholar 

  8. Bailey, J. E., & Pearson, S. W. (1983). Development of a tool for measuring and analyzing computer user satisfaction. Management Science, 29(5), 530–545.

    Article  Google Scholar 

  9. Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: conceptual, strategic and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173–1182.

    Article  Google Scholar 

  10. 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 

  11. Baroudi, J. J., & Orlikowski, W. J. (1989). The problem of statistical power in MIS research. MIS Quarterly, 13(1), 87–106.

    Article  Google Scholar 

  12. Bhattacherjee, A. (2001). Understanding information systems continuance. An expectation–confirmation model. MIS Quarterly, 25(3), 351–370.

    Article  Google Scholar 

  13. Bitner, M. J. (1990). Evaluating Service Encounters: The Effects of Physical Surrounding and Employee Responses. Journal of Marketing, 54(2), 69-81.

    Google Scholar 

  14. Bollen, K. A., & Lennox, R. (1991). Conventional wisdom on measurement: a structural equation perspective. Psychological Bulletin, 110(2), 305–314.

    Article  Google Scholar 

  15. Brady, M. K., & Cronin, J. J. (2001). Some new thoughts on conceptualizing perceived service quality: a hierarchical approach. Journal of Marketing, 65, 34–49.

    Article  Google Scholar 

  16. Campbell, A., Converse, P. E., & Rodgers, W. L. (1976). The quality of American life. New York: Russel Sage Foundation.

    Google Scholar 

  17. Chae, M., Kim, J., Kim, H., & Ryu, H. (2002). Information quality for mobile internet services: a theoretical model with empirical validation. Electronic Markets, 12, 38–46.

    Article  Google Scholar 

  18. Chatterjee, S., Chakraborty, S., Sarker, S., Sarker, S., & Lau, F. Y. (2009). Examining the success factors for mobile work in healthcare: a deductive study. Decision Support Systems, 46(3), 620–633.

    Article  Google Scholar 

  19. Chin, W. W. (1998). Issues and opinion on structural equation modeling. MIS Quarterly, 22(1), vii–xvi.

    Google Scholar 

  20. Chin, W. W. (2001). PLS – Graph User’s Guide Version 3.0., Houston, TX: Soft Modeling Inc.

  21. 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 

  22. Chin, W. W., & Gopal, A. (1995). Adoption intention in GSS: importance of beliefs. Data Base Advance, 26, 42–64.

    Google Scholar 

  23. 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 

  24. Choi, H., Lee, M., Lm, K. S., & Kim, J. (2007). Contribution to quality of life: a new outcome variable for mobile data service. Journal of the Association for Information Systems, 8(12), 598–618.

    Google Scholar 

  25. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale: L. Erlbaum Associates.

    Google Scholar 

  26. Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155–159.

    Article  Google Scholar 

  27. Cronin, J. J., & Taylor, S. A. (1992). Measuring service quality: a reexamination and extension. Journal of Marketing, 56, 55–68.

    Article  Google Scholar 

  28. Dabholkar, P. A., Thorpe, D. I., & Rentz, J. O. (1996). A measure of service quality for retail stores: scale development and validation. Journal of the Academy of Marketing Science, 24(1), 3–16.

    Article  Google Scholar 

  29. Dabholkar, P. A., David, C. S., & Dayle, I. T. (2000). A comprehensive framework for service quality: an investigation of critical conceptual and measurement issues through a longitudinal study. Journal of Retailing, 72(2), 139–173.

    Article  Google Scholar 

  30. Dagger, T. S., & Sweeney, C. J. (2006). The effect of service evaluations on behavioral intentions and quality of life. Journal of Service Research, 9(1), 3–18.

    Article  Google Scholar 

  31. 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.

    Article  Google Scholar 

  32. Davis, F. D. (1989). Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Quarterly, 13(3), 318–339.

    Article  Google Scholar 

  33. De Ruyter, K., & Wetzels, M. (1998). On the complex nature of patient evaluations of general practice service. Journal of Economic Psychology, 19, 565–590.

    Article  Google Scholar 

  34. DeLone, W. H., & McLean, E. R. (1992). Information systems success: the quest for the dependent variable. Information Systems Research, 3(1), 60–95.

    Article  Google Scholar 

  35. DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: a ten-year update. Journal of Management Information Systems, 19(4), 9–30.

    Google Scholar 

  36. Diener, E. (1984). Subjective well-being. Psychological Bulletin, 95, 542–575.

    Article  Google Scholar 

  37. Edwards, J. R. (2001). Multidimensional constructs in organizational behavior research: an integrative analytical framework. Organizational Research Methods, 4(2), 144–192.

    Article  Google Scholar 

  38. Edwards, J. R., & Bagozzi, R. P. (2000). On the nature and direction of relationships between constructs. Psychological Methods, 5(2), 155–174.

    Article  Google Scholar 

  39. Efron, B., & Tibshirani, R. J. (1993). An introduction to the bootstrap. New York: Chapman and Hall.

    Google Scholar 

  40. Fassnacht, M. A., & Koese, I. (2006). Quality of electronic services: conceptualizing and testing a hierarchical model. Journal of Service Research, 9(19), 19–37.

    Article  Google Scholar 

  41. 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.

    Article  Google 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, 440–452.

    Article  Google Scholar 

  43. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.

    Article  Google Scholar 

  44. Gotlieb, J. B., Dhruv, G., & Stephen, W. B. (1994). Consumer satisfaction and perceived quality: complementary or divergent constructs. The Journal of Applied Psychology, 79(6), 875–885.

    Article  Google Scholar 

  45. Gregor, S. (2006). The nature of theory in information systems. MIS Quarterly, 30(3), 611–642.

    Google Scholar 

  46. Gronroos, C. (1984). A service quality model and its marketing implications. European Journal of Marketing, 18(4), 36–44.

    Article  Google Scholar 

  47. Holmbeck, G. N. (1997). Toward terminological, conceptual, and statistical clarity in the study of mediators and moderators: examples from the child-clinical and pediatric psychology literatures. Journal of Counseling and Clinical Psychology, 65(4), 599–610.

    Article  Google Scholar 

  48. Istepanian, R., & Lacal, J. (2003). Emerging mobile communication technologies for health: Some imperative notes on m-Health. Paper presented at the 25th International Conference of the IEEE Engineering in Medicine and Biology Society, Cancun, Mexico.

  49. 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.

    Article  Google Scholar 

  50. 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, 199–218.

    Article  Google Scholar 

  51. 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 

  52. Jen, W. Y., Chao, C. C., Hung, M. C., Li, Y. C., & Chi, Y. P. (2007). Mobile information and communication in the hospital outpatient service. International Journal of Medical Informatics, 76, 565–574.

    Article  Google Scholar 

  53. Jiang, J. J., & Klein, G. (1999). User Evaluation of Information Systems: By System Typology. IEEE Transactions on System, Man, and Cybernetics, 29(1), 111-116.

    Google Scholar 

  54. Jiang, J. J., Klein, G., & Crampton, S. (2000). A note on SERVQUAL reliability and validity in information system service quality measurement. Decision Sciences, 31(3), 725–745.

    Article  Google Scholar 

  55. Jiang, J. J., Klein, G., Roan, J., & Lin, T. M. (2001). IS service performance: self-perceptions and user perceptions. Information Management, 38(8), 499–506.

    Article  Google Scholar 

  56. Jiang, J. J., Klein, G., & Carr, C. (2002). Measuring information systems quality: SERVQUAL from the other side. MIS Quarterly, 26(2), 145–166.

    Article  Google Scholar 

  57. Kaplan, B., & Litewka, S. (2008). Ethical challenges of telemedicine and telehealth. Cambridge Quarterly of Healthcare Ethics, 17, 401–416.

    Article  Google Scholar 

  58. Kettinger, W. J., & Lee, C. C. (1994). Perceived service quality and user satisfaction with the information services function. Decision Sciences, 25(5/6), 737–766.

    Article  Google Scholar 

  59. Kettinger, W. J., & Lee, C. C. (1995). Exploring a ‘gap’ model of information services quality. Information Resources Management Journal, 8(3), 5–16.

    Google Scholar 

  60. Kettinger, W. J., & Lee, C. C. (1999). Replication of measures in information systems research: the case of IS SERVQUAL. Decision Sciences, 30(3), 893–899.

    Article  Google Scholar 

  61. Kettinger, W. J., & Lee, C. C. (2005). Zones of tolerance: alternative scales for measuring information systems service quality. MIS Quarterly, 29(4), 607-623.

    Google Scholar 

  62. Koivisto, M. (2007). Development of quality expectations in mobile information systems, Proceedings of the International Joint Conferences on Computer, Information, and Systems Sciences, and Engineering, University of Bridgeport, CT, USA.

  63. Krause, A., Hartl, D., Theis, F., Stangl, M., Gerauer, K. E., & Mehlhorn, A. T. (2004). Mobile decision support for transplantation patient data. International Journal of Medical Informatics, 73(5), 461–464.

    Article  Google Scholar 

  64. Law, K., & Wong, C.-S. (1998). Multidimensional constructs in structural equation analysis: an illustration using the job perception and job satisfaction constructs. Journal of Management, 25(2), 143–160.

    Article  Google Scholar 

  65. Limayem, M., Hirt, S. G., & Cheung, M. K. C. (2007). How habit limits the predictive power of intention: the case of information systems continuance. MIS Quarterly, 31(4), 705–737.

    Google Scholar 

  66. Lohmöller, J.-B. (1989). Latent variable path modeling with partial least squares. Heidelberg: Physica-Verlag.

    Google Scholar 

  67. MacKenzie, S. B., Podsakoff, P. M., & Jarvis, C. B. (2005). The problem of measurement model misspecification in behavioral and organizational research and some recommended solutions. The Journal of Applied Psychology, 90(4), 710–730.

    Article  Google Scholar 

  68. Malhotra, N. (2004). Marketing research: an applied orientation, 4th ed., Upper Saddle River, NJ: Pearson Education.

    Google Scholar 

  69. Mechael, P. (2009). The case for mHealth in developing countries. Innovations: Technology, Governance, Globalization, 4(1), 103–118.

    Article  Google Scholar 

  70. Michalowski, W., Rubin, S., Slowinski, R., & Wilk, S. (2003). Mobile clinical support system for pediatric emergencies. Decision Support Systems, 36, 161–176.

    Article  Google Scholar 

  71. Myers, B. L., Kappelman, L. A., & Prybutok, V. R. (1998). A comprehensive model for assessing the quality and productivity of the information systems function: Toward a theory for information systems assessment. In E.J. Garrity and G.L. Sanders (eds.). Information Systems Success Measurement. Hershey. PA: Idea Group, pp. 94–121.

  72. Nelson, R. R., Todd, P. A., & Wixom, B. H. (2005). Antecedents of information and systems quality: an empirical examination within the context of data warehousing. Journal of Management Information Systems, 21(4), 199–235.

    Google Scholar 

  73. Noonan, R., & Wold, H. (1993). Evaluating school systems using partial least squares. Evaluation in Education, 7, 219–364.

    Article  Google Scholar 

  74. Norris, T., Stockdale, R., & Sharma, S. (2008). Mobile health: strategy and sustainability. The Journal of Information Technology in Healthcare, 6(5), 326–333.

    Google Scholar 

  75. Orlikowski, W. J., & Iacono, C. S. (2001). Research commentary: desperately seeking the “IT” in IT researches—a call to theorizing the IT artifact. Information Systems Research, 2(12), 121–134.

    Article  Google Scholar 

  76. Parasuraman, A., Valarie A. Z., & Berry L.L. (1985). A conceptual model of service quality and its implications for future research, Journal of Marketing, 49(Fall), 41–50.

    Google Scholar 

  77. 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 

  78. Parasuraman, A., Zeithaml, V. A., & Malhotra, A. (2005). E-S-QUAL: a multiple-item scale for assessing electronic service quality. Journal of Service Research, 7(3), 213–233.

    Article  Google Scholar 

  79. Petter, S., & McLean, R. E. (2009). A meta analytic assessment of the DeLone and McLean IS success model: an examination of IS success at the individual level. Information Management, 46, 159–166.

    Article  Google Scholar 

  80. Petter, S., Straub, D., & Rai, A. (2007). Specifying formative constructs in information systems research. MIS Quarterly, 31(1), 623–656.

    Google Scholar 

  81. Pitt, L. F., Watson, R. T., & Kavan, C. B. (1995). Service quality: a measure of information systems effectiveness. MIS Quarterly, 19(2), 173–187.

    Article  Google Scholar 

  82. Pitt, L. F., Watson, R. T., & Kavan, C. B. (1997). Measuring information systems service quality: concerns for a complete canvas. MIS Quarterly, 21(2), 209–221.

    Article  Google Scholar 

  83. RACE (1994) UMTS System Structure Document, Issue 1.0. RACE 2066 Mobile Networks (MONET), CEC Deliverable No:R2066/LMF/GA1/DS/P/052/b1

  84. Reeves, C., & Bednar, D. A. (1994). Defining quality: alternatives and implications. Academy of Management Review, 19(3), 419–445.

    Article  Google Scholar 

  85. 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 

  86. Seddon, P. B. (1997). A respecification and extension of the DeLone and McLean model of IS success. Information Systems Research, 240–253.

  87. Shaw, C., & Ivens, J. (2002). Building great customer experiences. New York: Macmillan.

    Book  Google Scholar 

  88. Sheth, J., Bruce, N., Newman, I., & Barbara, L. G. (1991). Consumption values and market choices: theory and applications. Cincinnati: South-Western.

    Google Scholar 

  89. Sirgy, M. J., Hansen, D. E., & Littlefield, J. E. (1994). Does hospital satisfaction affect life satisfaction? Journal of Macromarketing, 14(2), 36–46.

    Article  Google Scholar 

  90. Sousa, R., & Voss, C. (2006). Service quality in multichannel services employing virtual channels. Journal of Service Research, 8(4), 356–371.

    Article  Google Scholar 

  91. 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.

    Article  Google Scholar 

  92. Straub, D. W., & Watson, R. T. (2001). Research commentary: transformational issues in researching IS and net-enabled organizations. Information Systems Research, 12(4), 337–345.

    Article  Google Scholar 

  93. Straub, D. W., Boudreau, M.-C., & Gefen, D. (2004). Validation guidelines for IS positivist research. Communications of AIS, 13(24), 380–427.

    Google Scholar 

  94. Sweeney, J. C., & Soutar, G. N. (2001). Consumer perceived value: the development of a multiple item scale. Journal of Retailing, 77(2), 203–220.

    Article  Google Scholar 

  95. Taylor, S. A., & Baker, T. L. (1994). An assessment of the relationship between service quality and customer satisfaction in the formation of consumers’ purchase intentions. Journal of Retailing, 70(2), 163–178.

    Article  Google Scholar 

  96. Tenenhaus, M., Vinzi, V. E., Chatelin, Y.-M., & Lauro, C. (2005). PLS path modeling. Computational Statistics and Data Analysis, 48(1), 159–205.

    Article  Google Scholar 

  97. United Nations foundation & 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 September 03, 2010]

  98. Varshney, U. (2005). Pervasive healthcare: applications, challenges and wireless solutions. Communications of the Association for Information Systems, 16(3), 57–72.

    Google Scholar 

  99. Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: four longitudinal field studies. Management Science, 46, 186–204.

    Article  Google Scholar 

  100. Watson, R. T., Pitt, L. F., & Kavan, C. B. (1998). Measuring information systems service quality: lessons from two longitudinal case studies. MIS Quarterly, 22(1), 61–79.

    Article  Google Scholar 

  101. 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 

  102. Whetten, D.A. (1989). What constitutes a theoretical contributions. Academy of Management Review, 14(4), 490–495.

    Google Scholar 

  103. Wixom, H. B., & Todd, P. A. (2005). A theoretical integration of user satisfaction and technology acceptance. Information Systems Research, 16(1), 85–102.

    Article  Google Scholar 

  104. Wold, H. (1985). Partial least squares. In S. Kotz & N. L. Johnson (Eds.), Encyclopedia of statistical sciences. New York: Wiley.

    Google Scholar 

  105. 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 

  106. Zviran, M., & Erlich, Z. (2003). Measuring IS user satisfaction: review & implications. Communications of the AIS, 12, 81–103.

    Google Scholar 

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Acknowledgement

This research was funded by the Asia Pacific Ubiquitous Healthcare Research Centre (APuHC), University of New South Wales, Australia. The authors appreciate and gratefully acknowledge constructive comments of Prof. Richard Vidgen (University of New South Wales) and Prof. Wynne W. Chin (University of Houston).

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Correspondence to Shahriar Akter.

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Responsible editor: Rainer Alt

Appendix

Appendix

A1. Path coefficients, standard error and t-values of the research model

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Akter, S., D’Ambra, J. & Ray, P. Service quality of mHealth platforms: development and validation of a hierarchical model using PLS. Electron Markets 20, 209–227 (2010). https://doi.org/10.1007/s12525-010-0043-x

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Keywords

  • Service quality
  • Satisfaction
  • Intention to continue using
  • Quality of life
  • PLS path modeling

JEL

  • I11
  • L80
  • M15
  • M31