Abstract
To attract more patients and improve the quality of health services, online health communities (OHCs) have launched a bundling feature that provides patients with a package of two or more existing health services for a discounted price. Existing bundling research has mostly focused on traditional industries, whereas bundled services in the field of professional health and their effects are usually neglected. Therefore, this study investigates the effects of bundling strategy on doctors’ online returns in OHCs. We focus on the effects of the launch of bundled services on separate components (doctors’ economic return) and online reputation (social return) and study the moderating effects of doctors’ characteristics on these returns. Based on analyses using a difference-in-difference model, we find that the launch of bundled services can positively affect doctors’ online reputation and part of separate components. A doctor’s tenure also moderates the effects of bundled services on doctors’ returns. Our study provides several theoretical implications for researchers and practical contributions for OHCs administrators.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data Availability
The datasets generated and analyzed during the current study are not publicly available due to the fact that they constitute and excerpt of research in progress but are available from the authors on reasonable request.
References
Abadie, A. (2010). Semiparametric difference-in-differences estimators. Review of Economic Studies, 72(1), 1–19. https://doi.org/10.2307/3700681
Afridi, S. A., Haider, M., & Shahjehan, A. (2020). Customers’ loyalty through healthcare quality; mediating role of customers’ commitment: A comparative study of public and private hospitals. City University Research Journal (CURJ), 10(1), 27–46. https://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=143018331&lang=zh-cn&site=ehost-live.
Aguiar, L., & Waldfogel, J. (2018). As streaming reaches flood stage, does it stimulate or depress music sales? International Journal of Industrial Organization, 57(2), 278–307. https://doi.org/10.1016/j.ijindorg.2017.06.004
Ahuja, M. K., & Galvin, J. E. (2003). Socialization in virtual groups. Journal of Management, 29(2), 161–185.
Algesheimer, R., Dholakia, U. M., & Herrmann, A. (2005). The social influence of brand community: Evidence from european car clubs. Journal of Marketing, 69(3), 19–34. https://doi.org/10.1509/jmkg.69.3.19.66363
Angrist, J. D., & Pischke, J.-S. (2008). Mostly harmless econometrics: An empiricist’s companion. Princeton University Press.
Baker, A. M., Donthu, N., & Kumar, V. (2016). Investigating how word-of-mouth conversations about brands influence purchase and retransmission intentions. Journal of Marketing Research, 53(2), 225–239. https://doi.org/10.1509/jmr.14.0099
Basdeo, D. K., Smith, K. G., Grimm, C. M., Rindova, V. P., & Derfus, P. J. (2006). The impact of market actions on firm reputation. Strategic Management Journal, 27(12), 1205–1219. https://doi.org/10.1002/smj.556
Bavafa, H., Hitt, L. M., & Terwiesch, C. (2018). The impact of e-visits on visit frequencies and patient health: Evidence from primary care. Management Science, 64(12), 5461–5480. https://doi.org/10.1287/mnsc.2017.2900
Bergquist, M., & Ljungberg, J. (2001). The power of gifts: Organizing social relationships in open source communities. Information Systems Journal, 11(4), 305–320. https://doi.org/10.1046/j.1365-2575.2001.00111.x
Bhargava, H. K. (2012). Retailer-driven product bundling in a distribution channel. Marketing Science, 31(6), 1014–1021. https://doi.org/10.1287/mksc.1120.0725
Burn, S. M., & Oskamp, S. (2010). Increasing community recycling with persuasive communication and public commitment. Journal of Applied Social Psychology, 16(1), 29–41.
Butler, B. S. (2001). Membership size, communication activity, and sustainability: A resource-based model of online social structures. Information Systems Research, 12(4), 346–362. https://doi.org/10.1287/isre.12.4.346.9703
Caffery, L. J., Farjian, M., & Smith, A. C. (2016). Telehealth interventions for reducing waiting lists and waiting times for specialist outpatient services: A scoping review. Journal of Telemedicine and Telecare, 22(8), 504–512. https://doi.org/10.1177/1357633x16670495
Cao, Q., Geng, X., & Zhang, J. (2015a). Strategic role of retailer bundling in a distribution channel. Journal of Retailing, 91(1), 50–67. https://doi.org/10.1016/j.jretai.2014.10.005
Cao, Q., Stecke, K. E., & Zhang, J. (2015b). The impact of limited supply on a firm’s bundling strategy. Production and Operations Management, 24(12), 1931–1944. https://doi.org/10.1111/poms.12388
Chatterjee, S., & Hadi, A. S. (2012). Regression analysis by example (5th ed.). Wiley.
Clark, B. H., & Montgomery, D. B. (1998). Deterrence, reputations, and competitive cognition. Management Science, 44(1), 62–82. https://doi.org/10.1287/mnsc.44.1.62
Correia, S., Guimares, P., & Zylkin, T. Z. (2020). Fast Poisson estimation with high-dimensional fixed effects. Stata Journal, 20(1), 95–115. https://doi.org/10.1177/1536867X20909691
Cranwell, J., & Seymour-Smith, S. (2012). Monitoring and normalising a lack of appetite and weight loss. A discursive analysis of an online support group for bariatric surgery. Appetite, 58(3), 873–881. https://doi.org/10.1016/j.appet.2012.01.029
Cropanzano, R., & Mitchell, M. S. (2005). Social exchange theory: An interdisciplinary review. Journal of Management, 31(6), 874–900. https://doi.org/10.1177/0149206305279602
Dadgar, M., & Joshi, K. D. (2018). The role of information and communication technology in self-management of chronic diseases: An empirical investigation through value sensitive design. Journal of the Association for Information Systems, 19(2), 86–112.
Dana, J. D. (2020). Bundling can signal high quality. International Journal of Industrial Organization, 69, 102579. https://doi.org/10.1016/j.ijindorg.2020.102579
Dana, J. D., Jr., & Spier, K. E. (2018). Bundling and quality assurance. RAND Journal of Economics, 49(1), 128–154. https://doi.org/10.1111/1756-2171.12222
Derdenger, T., & Kumar, V. (2013). The dynamic effects of bundling as a product strategy. Marketing Science, 32(6), 827–859. https://doi.org/10.1287/mksc.2013.0810
Donabedian, A. (1981). Explorations in quality assessment and monitoring. Volume 1: definition and measurement of quality. Medical Care, 19(10), 1066–1067. https://doi.org/10.1097/00005650-198110000-00010
Dugdale, D. C., Epstein, R., & Pantilat, S. Z. (1999). Time and the patient-physician relationship. Journal of General Internal Medicine, 14(1), S34–S40. https://doi.org/10.1046/j.1525-1497.1999.00263.x
Elberse, A. (2010). Bye-bye bundles: The unbundling of music in digital channels. Journal of Marketing, 74(3), 107–123.
Fang, H., Lin, J., Liang, L., Long, X., Zhu, X., & Cai, W. (2020). A nonsurgical and nonpharmacological care bundle for preventing upper urinary tract damage in patients with spinal cord injury and neurogenic bladder. International Journal of Nursing Practice, 26(2), 1–11. https://doi.org/10.1111/ijn.12761
Gaeth, G. J., Levin, I. P., & Levin, C. A. M. (1991). Consumer evaluation of multi-product bundles: An information integration analysis. Marketing Letters, 2(1), 47–57.
Gao, A., & Wang, G. H. K. (2007). Multiple transactions model: A panel data approach to estimate housing market indices. Journal of Real Estate Research, 29(3), 241–266. https://doi.org/10.1007/s11146-007-9031-0
Gao, G. G., Greenwood, B. N., Agarwal, R., & McCullough, J. S. (2015). Vocal minority and silent majority: How do online ratings reflect population perceptions of quality. MIS Quarterly, 39(3), 565–589. https://doi.org/10.2139/ssrn.2629837
Greenwood, B. N., & Wattal, S. (2017). Show me the way to go home: An empirical investigation of ride-sharing and alcohol related motor vehicle fatalities. MIS Quarterly, 41(1), 163–187. https://doi.org/10.25300/MISQ/2017b/41.1.08
Grégoire, Y., Tripp, T. M., & Legoux, R. (2009). When customer love turns into lasting hate: The effects of relationship strength and time on customer revenge and avoidance. Journal of Marketing, 73(6), 18–32. https://doi.org/10.1509/jmkg.73.6.18
Gummerus, J., Liljander, V., Weman, E., & Pihlstrm, M. (2012). Customer engagement in a Facebook brand community. Management Research Review, 35(9), 857–877.
Guo, S., Guo, X., Fang, Y., & Vogel, D. (2017). How doctors gain social and economic returns in online health-care communities: A professional capital perspective. Journal of Management Information Systems, 34(2), 487–519. https://doi.org/10.1080/07421222.2017.1334480
Heeler, R. M., Nguyen, A., & Buff, C. (2007). Bundles = discount? Revisiting complex theories of bundle effects. Journal of Product & Brand Management, 16(7), 492–500.
Hong, Y., & Pavlou, P. A. (2017). On buyer selection of service providers in online outsourcing platforms for IT services. Information Systems Research, 28(3), 547–562. https://doi.org/10.1287/isre.2017.0709
Honhon, D., & Pan, X. A. (2017). Improving profits by bundling vertically differentiated products. Production and Operations Management, 26(8), 1481–1497. https://doi.org/10.1111/poms.12686
Huang, N., Hong, Y., & Burtch, G. (2017). Social network integration and user content generation: Evidence from natural experiments. MIS Quarterly, 41(4), 1035–1058. https://doi.org/10.25300/MISQ/2017/41.4.02
Huang, N., Yan, Z., & Yin, H. (2021). Effects of online-offline service integration on e-healthcare providers: A quasi-natural experiment. Production & Operations Management, 30(8), 2359–2378. https://doi.org/10.1111/poms.13381
Jia, L., Zhang, Y., Ling, M., & Xuan, L. (2016). The impact of the internet on health consultation market concentration: An econometric analysis of secondary data. Journal of Medical Internet Research, 18(10), e276. https://doi.org/10.2196/jmir.6423
Jianran, L., & Wen, J. (2022). Evolution of Agents in the Case of a Balanced Diet. International Journal of Crowd Science, 6(1), 1–6. https://doi.org/10.26599/IJCS.2022.9100005
Keiningham, T. L., Cooil, B., Andreassen, T. W., & Aksoy, L. (2007). A longitudinal examination of net promoter and firm revenue growth. Journal of Marketing, 71(3), 39–51. https://doi.org/10.1509/jmkg.71.3.039
Khurana, S., Qiu, L., & Kumar, S. (2019). When a Doctor Knows, It Shows: An Empirical Analysis of Doctors’ Responses in a Q&A Forum of an Online Healthcare Portal. Information Systems Research, 30(3), 872–891. https://doi.org/10.1287/isre.2019.0836
Kordzadeh, N., Zhechao Liu, C., Au, Y. A., & Guynes Clark, J. (2014). A multilevel investigation of participation within virtual health communities. Communications of the Association for Information Systems, 34, 493–512. https://doi.org/10.17705/1CAIS.03426
Kuang, L., Huang, N., Hong, Y., & Yan, Z. (2019). Spillover effects of financial incentives on non-incentivized user engagement: Evidence from an online knowledge exchange platform. Journal of Management Information Systems, 36(1), 289–320. https://doi.org/10.1080/07421222.2018.1550564
Lavallée, J. F., Gray, T. A., Dumville, J., & Cullum, N. (2019). Preventing pressure ulcers in nursing homes using a care bundle: A feasibility study. Health & Social Care in the Community, 27(4), e417–e427. https://doi.org/10.1111/hsc.12742
Li, B., Li, X., & Liu, H. (2018). Consumer preferences, cannibalization, and competition: evidence from the personal computer industry. MIS Quarterly, 42(2), 661–678. https://doi.org/10.25300/MISQ/2018/13803
Li, J., Tang, J., Jiang, L., Yen, D. C., & Liu, X. (2019). Economic success of physicians in the online consultation market: A signaling theory perspective. International Journal of Electronic Commerce, 23(2), 244–271. https://doi.org/10.1080/10864415.2018.1564552
Liang, Q., Luo, J., & Wu, Z. (2017). The impact of doctor’s efforts and reputation on the number of new patients in online health community. Chinese Journal of Health Policy, 10(10), 63–71.
Lichterman, P. (1995). Beyond the seesaw model: Public commitment in a culture of self-fulfillment. Sociological Theory, 13(3), 275–300. https://doi.org/10.2307/223299
Liu, J., Bian, Y., Ye, Q., & Jing, D. (2019). Free for caring? The effect of offering free online medical-consulting services on physician performance in e-health care. Telemedicine & e-Health, 25(10), 979–986. https://doi.org/10.1089/tmj.2018.0216
Liu, J., Zhang, X., Meng, F., & Lai, K.-H. (2020a). Deploying gamification to engage physicians in an online health community: An operational paradox. International Journal of Production Economics, 228, 107847. https://doi.org/10.1016/j.ijpe.2020.107847
Liu, Q. B., Liu, X., & Guo, X. (2020b). The effects of participating in a physician-driven online health community in managing chronic disease: evidence from two natural experiments. MIS Quarterly, 44(1), 391–419. https://doi.org/10.25300/MISQ/2020b/15102
Liu, X., Guo, X., Wu, H., & Wu, T. (2016). The impact of individual and organizational reputation on physicians’ appointments online. International Journal of Electronic Commerce, 20(4), 551–577. https://doi.org/10.1080/10864415.2016.1171977
Lupton, D. (2013). The digitally engaged patient: Self-monitoring and self-care in the digital health era. Social Theory & Health, 11(3), 256–270. https://doi.org/10.1057/sth.2013.10
Mainous, A. G. I., Baker, R., Love, M. M., Gray, D. P., & Gill, J. M. (2001). Continuity of care and trust in one’s physician: Evidence from primary care in the United States and the United Kingdom. Family Medicine, 33(1), 22.
Mathwick, C., Wiertz, C., & De Ruyter, K. (2008). Social capital production in a virtual P3 community. Journal of Consumer Research, 34(6), 832–849. https://doi.org/10.1086/523291
McLure Wasko, M., & Faraj, S. (2005). Why should I share? Examining social capital and knowledge contribution in electronic networks of practice. MIS Quarterly, 29(1), 35–57. https://doi.org/10.2307/25148667
Mcquilken, L., Robertson, N., Polonsky, M., & Harrison, P. (2015). Consumer perceptions of bundles and time-limited promotion deals: Do contracts matter? Journal of Consumer Behaviour, 14(3), 145–157. https://doi.org/10.1002/cb.1513
Moon, J., & Shugan, S. M. (2018). Explaining bundle-framing effects with signaling theory. Marketing Science, 37(4), 668–681. https://doi.org/10.1287/mksc.2018.1097
Moqbel, M., Hewitt, B., Nah, F.F.-H., & McLean, R. M. (2021). Sustaining patient portal continuous use intention and enhancing deep structure usage: Cognitive dissonance effects of health professional encouragement and security concerns. Information Systems Frontiers. https://doi.org/10.1007/s10796-021-10161-5
Moreno, A., & Terwiesch, C. (2014). Doing business with strangers: Reputation in online service marketplaces. Information Systems Research, 25(4), 865–886. https://doi.org/10.1287/isre.2014.0549
Naiji, L., & Hong, W. (2016). Exploring the impact of word-of-mouth about Physicians’ service quality on patient choice based on online health communities. BMC Medical Informatics & Decision Making, 16, 1–10. https://doi.org/10.1186/s12911-016-0386-0
Nisar, T. M., Prabhakar, G., Ilavarasan, P. V., & Baabdullah, A. M. (2020). Up the ante: Electronic word of mouth and its effects on firm reputation and performance. Journal of Retailing & Consumer Services, 53, 101726. https://doi.org/10.1016/j.jretconser.2018.12.010
Niyato, D., Dinh Thai, H., Nguyen Cong, L., Wang, P., Kim, D. I., & Han, Z. (2016). Smart data pricing models for the Internet of things: A bundling strategy approach. IEEE Network, 30(2), 18–25. https://doi.org/10.1109/mnet.2016.7437020
Nov, O., Naaman, M., & Chen, Y. (2010). Analysis of participation in an online photo-sharing community: A multidimensional perspective. Journal of the American Society for Information Science & Technology, 61(3), 555–566. https://doi.org/10.1002/asi.21278
Nyer, P. U., & Dellande, S. (2010). Public commitment as a motivator for weight loss. Psychology and Marketing, 27(1), 1–12.
Pallak, M. S., & Cummings, W. (1976). Commitment and voluntary energy conservation. Personality and Social Psychology Bulletin, 2(1), 27–30. https://doi.org/10.1177/014616727600200105
Parrott, R., Monahan, J., Ainsworth, S., & Steiner, C. (1998). Communicating to farmers about skin cancer: The behavior adaptation model. Human Communication Research, 24(3), 386–409. https://doi.org/10.1111/j.1468-2958.1998.tb00422.x
Raie, M., Khadivi, A., & Khdaie, R. (2014). The effect of employees' customer orientation, customer's satisfaction and commitment on customer's sustainability. Oman Chapter of Arabian Journal of Business and Management Review, 4, 109–121. https://doi.org/10.12816/0016577.
Ranaweera, C., & Karjaluoto, H. (2017). The impact of service bundles on the mechanism through which functional value and price value affect WOM intent. Journal of Service Management, 28(4), 707–723. https://doi.org/10.1108/JOSM-03-2016-0065
Ridings, C., & Gefen, D. (2004). Virtual community attraction: Why people hang out online. Journal of Computer-Mediated Communication, 10(1), 00–00. https://doi.org/10.1111/j.1083-6101.2004.tb00229.x
Ronay, R., Oostrom, J. K., Lehmann-Willenbrock, N., & Van Vugt, M. (2017). Pride before the fall: (Over)confidence predicts escalation of public commitment. Journal of Experimental Social Psychology, 69, 13–22. https://doi.org/10.1016/j.jesp.2016.10.005
Rosenbaum, P. (2002). Observational studies (2nd ed.). Journal of the American Statistical Association, 97, 1207. https://doi.org/10.1007/978-1-4757-3692-2
Sarin, S., Sego, T., & Chanvarasuth, N. (2003). Strategic use of bundling for reducing consumers’ perceived risk associated with the purchase of new high-tech products. Journal of Marketing Theory & Practice, 11(3), 71–83. https://doi.org/10.1080/10696679.2003.11658502
Shaarani, I., Taleb, R., & Antoun, J. (2017). Effect of computer use on physician-patient communication using a validated instrument: Patient perspective. International Journal of Medical Informatics, 108, 152–157. https://doi.org/10.1016/j.ijmedinf.2017.10.007
Sheng, S., Parker, A. M., & Nakamoto, K. (2007). The effects of price discount and product complementarity on consumer evaluations of bundle components. Journal of Marketing Theory and Practice, 15(1), 53–64. https://doi.org/10.2753/MTP1069-6679150104
Silva, J. M. C. S., & Tenreyro, S. (2015). PPML: Stata module to perform Poisson pseudo-maximum likelihood estimation. Statistical Software Components S458102. Department of Economics, Boston College. https://ideas.repec.org/c/boc/bocode/s458102.html. Accessed 27 Oct 2018.
Singh, R., Mathiassen, L., Stachura, M. E., & Astapova, E. V. (2011). Dynamic capabilities in home health: IT- enabled transformation of post- acute care. Journal of the Association for Information Systems, 12(2), 163–188. https://doi.org/10.1002/asi.21417
Spence, M. (1973). Job market signaling. The Quarterly Journal of Economics, 87(3), 355–374. https://doi.org/10.2307/1882010
Sun, H., Fan, M., & Tan, Y. (2020). An empirical analysis of seller advertising strategies in an online marketplace. Information Systems Research, 31(1), 37–56. https://doi.org/10.1287/isre.2019.0874
Tate, D. F., Finkelstein, E. A., Khavjou, O., & Gustafson, A. (2009). Cost effectiveness of internet interventions: Review and recommendations. Annals of Behavioral Medicine, 38(1), 40. https://doi.org/10.1007/s12160-009-9131-6
Tversky, K. A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–291. https://doi.org/10.2307/1914185
Vamosiu, A. (2018). Optimal bundling under imperfect competition. International Journal of Production Economics, 195(1), 45–53. https://doi.org/10.1016/j.ijpe.2017.09.016
Wang, L., Yan, L., Zhou, T., Guo, X., & Heim, G. R. (2020). Understanding physicians’ online-offline behavior dynamics: An empirical study. Information Systems Research, 31(2), 297–652. https://doi.org/10.1287/isre.2019.0901
Wray, J., & Oldham, G. (2020). Using parent-reported experience measures as quality improvement tools in paediatric cardiothoracic services: Making it happen. International Journal for Quality in Health Care, 32(2), 140–148. https://doi.org/10.1093/intqhc/mzaa001
Wu, H., Deng, Z., Wang, B., & Wang, H. (2021). How online health community participation affects physicians’ performance in hospitals: Empirical evidence from China. Information & Management, 103443. https://doi.org/10.1016/j.im.2021.103443
Wu, H., & Lu, N. (2017). Online written consultation, telephone consultation and offline appointment: An examination of the channel effect in online health communities. International Journal of Medical Informatics, 107, 107–119. https://doi.org/10.1016/j.ijmedinf.2017.08.009
Xing, B., Yin, H., Yan, Z., & Wang, J. (2021). A study of similar question retrieval method in online health communities. International Journal of Crowd Science, 5(2), 154–165.
Xu, K., Chan, J., Ghose, A., & Han, S. P. (2017). Battle of the channels: The impact of tablets on digital commerce. Management Science, 63(5), 1469–1492. https://doi.org/10.1287/mnsc.2015.2406
Yan, L., & Tan, Y. (2014). Feeling blue? Go online: An empirical study of social support among patients. Information Systems Research, 25(4), 690–709. https://doi.org/10.1287/isre.2014.0538
Yan, L., & Tan, Y. (2017). The consensus effect in online health-care communities. Journal of Management Information Systems, 34(1), 11–39.
Yan, Z., Wang, T., Chen, Y., & Zhang, H. (2016). Knowledge sharing in online health communities: A social exchange theory perspective. Information & Management, 53(5), 643–653. https://doi.org/10.1016/j.im.2016.02.001
Acknowledgements
This work was supported by National Natural Science Foundation of China (Grant No: 72072011, 71872013, 72110107003) and Beijing Municipal Social Science Foundation (Grant No: 18JDGLB040).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of Interest
We have no conflict of interest to disclose.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendices
Appendix A
We expand the study from hypertension to a broader range of diseases, including 1,259 diseases (e.g., coronary heart disease, cerebral infarction, and depression). As the observation period of our study is from April 2016 to April 2017, we chose doctors who have registered in the OHCs before April 2016 as our samples. Then, we eliminated doctors with less than four-period activities in the data set, until we finally have 630 doctors in the treatment group (Sun et al., 2020). We re-estimated our DID model using the new data sample. The results are presented in Table 13 and are consistent with those obtained for hypertension.
Appendix B
Table 14
Appendix C
Table 15
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Yin, Q., Guo, C., He, C. et al. Effect of New Bundled Services on Doctors’ Online Social and Economic Returns: Evidence from an Online Health Community. Inf Syst Front 25, 2393–2416 (2023). https://doi.org/10.1007/s10796-022-10362-6
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10796-022-10362-6