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Published in: BMC Medical Informatics and Decision Making 1/2023

Open Access 01-12-2023 | Research

Research on the doctors’ win in crowdsourcing competitions: perspectives on service content and competitive environment

Authors: Xiuxiu Zhou, Shanshan Guo, Hong Wu

Published in: BMC Medical Informatics and Decision Making | Issue 1/2023

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Abstract

Medical crowdsourcing competitions can help patients get more efficient and comprehensive treatment advice than “one-to-one” service, and doctors should be encouraged to actively participate. In the crowdsourcing competitions, winning the crowdsourcing competition is the driving force for doctors to continue to participate in the service. Therefore, how to improve the winning probability needs to be revealed. From the service content and competitive environment perspectives, this study introduces doctor competence indicators to investigate the key influence factors of doctors’ wins on the online platform. The results show that the emotional interaction in doctors’ service content positively influences doctors’ wins. However, the influence of information interaction presents heterogeneity. Conclusive information helps doctors win, while suggestive information negatively affects them. For the competitive environment, the competitive environment negatively moderates the relationship between doctors’ service content and doctors’ wins. The results of this study provide important contributions to the research on crowdsourcing competitions and online healthcare services and guide the participants of the competition, including patients, doctors, and platforms.
Literature
1.
go back to reference Li Y, Du N, Liu C, Xie Y, Fan W, Li Q et al. Reliable Medical Diagnosis from Crowdsourcing: Discover Trustworthy Answers from Non-Experts. In: Proceedings of the Tenth ACM International Conference on Web Search and Data Mining. Cambridge United Kingdom: ACM; 2017. p. 253–61. Li Y, Du N, Liu C, Xie Y, Fan W, Li Q et al. Reliable Medical Diagnosis from Crowdsourcing: Discover Trustworthy Answers from Non-Experts. In: Proceedings of the Tenth ACM International Conference on Web Search and Data Mining. Cambridge United Kingdom: ACM; 2017. p. 253–61.
2.
go back to reference Yan L, LUCY, Tan Y. The Consensus Effect in Online Health-Care Communities. J Manage Inform Syst. 2017;34:11–39. Yan L, LUCY, Tan Y. The Consensus Effect in Online Health-Care Communities. J Manage Inform Syst. 2017;34:11–39.
3.
go back to reference Wang L, Yan L (Lucy), Zhou T, Guo X, Heim GR, editors. Understanding Physicians’ Online-Offline Behavior Dynamics: An Empirical Study. Information Systems Research. 2020;31:537–55. Wang L, Yan L (Lucy), Zhou T, Guo X, Heim GR, editors. Understanding Physicians’ Online-Offline Behavior Dynamics: An Empirical Study. Information Systems Research. 2020;31:537–55.
4.
go back to reference McComb S, Bond RR, CoDiagnose. Interactive software to harness collaborative diagnoses and to increase diagnostic accuracy amongst junior physicians. Technol Health Care. 2015;23:243–56.PubMed McComb S, Bond RR, CoDiagnose. Interactive software to harness collaborative diagnoses and to increase diagnostic accuracy amongst junior physicians. Technol Health Care. 2015;23:243–56.PubMed
6.
go back to reference Guo S, Guo X, Fang Y, Vogel D. How doctors Gain Social and economic returns in Online Health-Care Communities: a Professional Capital Perspective. J Manage Inform Syst. 2017;34:487–519. Guo S, Guo X, Fang Y, Vogel D. How doctors Gain Social and economic returns in Online Health-Care Communities: a Professional Capital Perspective. J Manage Inform Syst. 2017;34:487–519.
7.
go back to reference Zhang X, Guo F, Xu T, Li Y. What motivates physicians to share free health information on online health platforms? Inf Process Manag. 2020;57:102166. Zhang X, Guo F, Xu T, Li Y. What motivates physicians to share free health information on online health platforms? Inf Process Manag. 2020;57:102166.
8.
go back to reference Yan L, Tan Y. Feeling blue? Go online: an empirical study of Social Support among Patients. Inform Syst Res. 2014;25:690–709. Yan L, Tan Y. Feeling blue? Go online: an empirical study of Social Support among Patients. Inform Syst Res. 2014;25:690–709.
9.
go back to reference Wu H, Deng Z, Wang B, Wang H. How online health community participation affects physicians’ performance in hospitals: empirical evidence from China. Inf Manag. 2021;58:103443. Wu H, Deng Z, Wang B, Wang H. How online health community participation affects physicians’ performance in hospitals: empirical evidence from China. Inf Manag. 2021;58:103443.
10.
go back to reference Jiang S, Liu X, Chi X. Effect of writing style on social support in online health communities: a theoretical linguistic analysis framework. Inf Manage. 2022;59:103683. Jiang S, Liu X, Chi X. Effect of writing style on social support in online health communities: a theoretical linguistic analysis framework. Inf Manage. 2022;59:103683.
12.
go back to reference Mein Goh J, Gao G (Gordon), Agarwal R, editors. The creation of social value: Can an online health community reduce rural–urban health disparities? MIS Quarterly. 2016;40:247–63. Mein Goh J, Gao G (Gordon), Agarwal R, editors. The creation of social value: Can an online health community reduce rural–urban health disparities? MIS Quarterly. 2016;40:247–63.
13.
go back to reference Swan M. Health 2050: the realization of Personalized Medicine through Crowdsourcing, the quantified self, and the participatory Biocitizen. J Pers Med. 2012;2:93–118.PubMedPubMedCentral Swan M. Health 2050: the realization of Personalized Medicine through Crowdsourcing, the quantified self, and the participatory Biocitizen. J Pers Med. 2012;2:93–118.PubMedPubMedCentral
14.
go back to reference Brabham DC, Ribisl KM, Kirchner TR, Bernhardt JM. Crowdsourcing applications for Public Health. Am J Prev Med. 2014;46:179–87.PubMed Brabham DC, Ribisl KM, Kirchner TR, Bernhardt JM. Crowdsourcing applications for Public Health. Am J Prev Med. 2014;46:179–87.PubMed
15.
go back to reference Conrad EJ, Becker M, Powell B, Hall KC. Improving Health Promotion through the integration of Technology, Crowdsourcing, and Social Media. Health Promot Pract. 2020;21:228–37.PubMed Conrad EJ, Becker M, Powell B, Hall KC. Improving Health Promotion through the integration of Technology, Crowdsourcing, and Social Media. Health Promot Pract. 2020;21:228–37.PubMed
16.
go back to reference Wang X, Mudie L, Brady CJ. Crowdsourcing: an overview and applications to ophthalmology. Curr Opin Ophthalmol. 2016;27:256–61.PubMedPubMedCentral Wang X, Mudie L, Brady CJ. Crowdsourcing: an overview and applications to ophthalmology. Curr Opin Ophthalmol. 2016;27:256–61.PubMedPubMedCentral
17.
go back to reference Khare R, Good BM, Leaman R, Su AI, Lu Z. Crowdsourcing in biomedicine: challenges and opportunities. Brief Bioinform. 2016;17:23–32.PubMed Khare R, Good BM, Leaman R, Su AI, Lu Z. Crowdsourcing in biomedicine: challenges and opportunities. Brief Bioinform. 2016;17:23–32.PubMed
18.
go back to reference Afshinnekoo E, Ahsanuddin S, Mason CE. Globalizing and crowdsourcing biomedical research. Br Med Bull. 2016;120:27–33.PubMed Afshinnekoo E, Ahsanuddin S, Mason CE. Globalizing and crowdsourcing biomedical research. Br Med Bull. 2016;120:27–33.PubMed
19.
go back to reference Chia-An Tsai J, Kang T-C. Reciprocal intention in knowledge seeking: examining social exchange theory in an online professional community. Int J Inf Manag. 2019;48:161–74. Chia-An Tsai J, Kang T-C. Reciprocal intention in knowledge seeking: examining social exchange theory in an online professional community. Int J Inf Manag. 2019;48:161–74.
20.
go back to reference Milgrom PR, Weber RJ. A theory of Auctions and Competitive Bidding. Econometrica. 1982;50:1089–122. Milgrom PR, Weber RJ. A theory of Auctions and Competitive Bidding. Econometrica. 1982;50:1089–122.
21.
go back to reference Huang Y, Vir Singh P, Srinivasan K. Crowdsourcing New Product Ideas under Consumer Learning. Manage Sci. 2014;60:2138–59. Huang Y, Vir Singh P, Srinivasan K. Crowdsourcing New Product Ideas under Consumer Learning. Manage Sci. 2014;60:2138–59.
22.
go back to reference Brabham DC. Crowdsourcing as a model for Problem solving: an introduction and cases. Convergence. 2008;14:75–90. Brabham DC. Crowdsourcing as a model for Problem solving: an introduction and cases. Convergence. 2008;14:75–90.
23.
go back to reference Majchrzak A, Malhotra A. Towards an information systems perspective and research agenda on crowdsourcing for innovation. J Strateg Inf Syst. 2013;22:257–68. Majchrzak A, Malhotra A. Towards an information systems perspective and research agenda on crowdsourcing for innovation. J Strateg Inf Syst. 2013;22:257–68.
24.
go back to reference Boudreau KJ, Lacetera N, Lakhani KR. Incentives and problem uncertainty in Innovation Contests: an empirical analysis. Manage Sci. 2011;57:843–63. Boudreau KJ, Lacetera N, Lakhani KR. Incentives and problem uncertainty in Innovation Contests: an empirical analysis. Manage Sci. 2011;57:843–63.
25.
go back to reference Afuah A, Tucci C, Crowdsourcing As A. Solution to distant search. Acad Manage Rev. 2012;37:355–75. Afuah A, Tucci C, Crowdsourcing As A. Solution to distant search. Acad Manage Rev. 2012;37:355–75.
27.
go back to reference Ebner W, Leimeister JM, Krcmar H. Community engineering for innovations: the ideas competition as a method to nurture a virtual community for innovations. R&D Manage. 2009;39:342–56. Ebner W, Leimeister JM, Krcmar H. Community engineering for innovations: the ideas competition as a method to nurture a virtual community for innovations. R&D Manage. 2009;39:342–56.
28.
go back to reference Bullinger AC, Neyer A-K, Rass M, Moeslein KM. Community-based Innovation Contests: where Competition meets Cooperation. Creativity and Innovation Management. 2010;19:290–303. Bullinger AC, Neyer A-K, Rass M, Moeslein KM. Community-based Innovation Contests: where Competition meets Cooperation. Creativity and Innovation Management. 2010;19:290–303.
29.
go back to reference Archak N. Money, glory and cheap talk: analyzing strategic behavior of contestants in simultaneous crowdsourcing contests on TopCoder.com. In: Proceedings of the 19th international conference on World wide web. Raleigh North Carolina USA: ACM; 2010. p. 21–30. Archak N. Money, glory and cheap talk: analyzing strategic behavior of contestants in simultaneous crowdsourcing contests on TopCoder.com. In: Proceedings of the 19th international conference on World wide web. Raleigh North Carolina USA: ACM; 2010. p. 21–30.
30.
go back to reference Brabham DC. Moving the crowd at Threadless. Inform Communication Soc. 2010;13:1122–45. Brabham DC. Moving the crowd at Threadless. Inform Communication Soc. 2010;13:1122–45.
31.
go back to reference Yang Y, Banker C. Impact of Past Performance and Strategic Bidding on Winner Determination of Open Innovation Contest. 2010. Yang Y, Banker C. Impact of Past Performance and Strategic Bidding on Winner Determination of Open Innovation Contest. 2010.
32.
go back to reference Yang Y, Chen P, Pavlou P. Open innovation: strategic design of online contests. In: Open Innovation. 2009. p. 1–16. Yang Y, Chen P, Pavlou P. Open innovation: strategic design of online contests. In: Open Innovation. 2009. p. 1–16.
33.
go back to reference Yang J, Adamic LA, Ackerman MS. Crowdsourcing and knowledge sharing: strategic user behavior on taskcn. In: Proceedings of the 9th ACM conference on Electronic commerce. New York, NY, USA: Association for Computing Machinery; 2008. p. 246–55. Yang J, Adamic LA, Ackerman MS. Crowdsourcing and knowledge sharing: strategic user behavior on taskcn. In: Proceedings of the 9th ACM conference on Electronic commerce. New York, NY, USA: Association for Computing Machinery; 2008. p. 246–55.
34.
go back to reference Chen L, Baird A, Straub D. A linguistic signaling model of social support exchange in online health communities. Decis Support Syst. 2020;130:113233. Chen L, Baird A, Straub D. A linguistic signaling model of social support exchange in online health communities. Decis Support Syst. 2020;130:113233.
35.
go back to reference Feldman J, Lynch J. Self-generated validity and other Effects of Measurement on Belief, attitude, intention, and Behavior. J Appl Psychol. 1988;73:421–35. Feldman J, Lynch J. Self-generated validity and other Effects of Measurement on Belief, attitude, intention, and Behavior. J Appl Psychol. 1988;73:421–35.
36.
go back to reference Xiao N, Sharman R, Rao HR, Upadhyaya S. Factors influencing online health information search: an empirical analysis of a national cancer-related survey. Decis Support Syst. 2014;57:417–27. Xiao N, Sharman R, Rao HR, Upadhyaya S. Factors influencing online health information search: an empirical analysis of a national cancer-related survey. Decis Support Syst. 2014;57:417–27.
37.
go back to reference Terry C, Cain J. The emerging issue of Digital Empathy. AJPE. 2016;80. Terry C, Cain J. The emerging issue of Digital Empathy. AJPE. 2016;80.
38.
go back to reference Ouyang P, Wang J-J, Jasmine Chang A-C. Patients need emotional support: managing physician disclosure information to attract more patients. Int J Med Informatics. 2022;158:104674. Ouyang P, Wang J-J, Jasmine Chang A-C. Patients need emotional support: managing physician disclosure information to attract more patients. Int J Med Informatics. 2022;158:104674.
39.
go back to reference Friedman B, Khan PH, Howe DC. Trust online. Commun ACM. 2000;43:34–40. Friedman B, Khan PH, Howe DC. Trust online. Commun ACM. 2000;43:34–40.
40.
go back to reference Wilkinson S, Kitzinger C. Thinking differently about thinking positive: a discursive approach to cancer patients’ talk. Soc Sci Med. 2000;50:797–811.PubMed Wilkinson S, Kitzinger C. Thinking differently about thinking positive: a discursive approach to cancer patients’ talk. Soc Sci Med. 2000;50:797–811.PubMed
41.
go back to reference Chau C. Professional Capital: An Informational Approach to nursing. Knowledge Management. WORLD SCIENTIFIC; 2005. 671–3. Chau C. Professional Capital: An Informational Approach to nursing. Knowledge Management. WORLD SCIENTIFIC; 2005. 671–3.
42.
go back to reference Noordegraaf M, Schinkel W. Professional capital contested: a bourdieusian analysis of conflicts between professionals and managers. Comp Sociol. 2011;10:97–125. Noordegraaf M, Schinkel W. Professional capital contested: a bourdieusian analysis of conflicts between professionals and managers. Comp Sociol. 2011;10:97–125.
43.
go back to reference Molm LD. Structure, Action, and outcomes: the Dynamics of Power in Social Exchange. Am Sociol Rev. 1990;55:427–47. Molm LD. Structure, Action, and outcomes: the Dynamics of Power in Social Exchange. Am Sociol Rev. 1990;55:427–47.
44.
go back to reference Beddoe L. Building Professional Capital: New Zealand Social Workers and Continuing Education. Deakin University; 2010. Beddoe L. Building Professional Capital: New Zealand Social Workers and Continuing Education. Deakin University; 2010.
45.
go back to reference Liu S, Zhang M, Gao B, Jiang G. Physician voice characteristics and patient satisfaction in online health consultation. Inf Manag. 2020;57:103233. Liu S, Zhang M, Gao B, Jiang G. Physician voice characteristics and patient satisfaction in online health consultation. Inf Manag. 2020;57:103233.
46.
go back to reference Huang Z, Duan C, Yang Y, Khanal R. Online selection of a physician by patients: the impression formation perspective. BMC Med Inform Decis Mak. 2022;22:193.PubMedPubMedCentral Huang Z, Duan C, Yang Y, Khanal R. Online selection of a physician by patients: the impression formation perspective. BMC Med Inform Decis Mak. 2022;22:193.PubMedPubMedCentral
47.
go back to reference Piezunka H, Dahlander L. Distant search, narrow attention: how crowding Alters Organizations’ Filtering of Suggestions in Crowdsourcing. AMJ. 2015;58:856–80. Piezunka H, Dahlander L. Distant search, narrow attention: how crowding Alters Organizations’ Filtering of Suggestions in Crowdsourcing. AMJ. 2015;58:856–80.
48.
go back to reference Acar OA. Motivations and solution appropriateness in crowdsourcing challenges for innovation. Res Policy. 2019;48:103716. Acar OA. Motivations and solution appropriateness in crowdsourcing challenges for innovation. Res Policy. 2019;48:103716.
49.
go back to reference Lysyakov M, Viswanathan S. Recombinant Innovations: What Differentiates Experienced Designers in Open Crowdsourcing Contests? Academy of Management Proceedings. 2022;2022. Lysyakov M, Viswanathan S. Recombinant Innovations: What Differentiates Experienced Designers in Open Crowdsourcing Contests? Academy of Management Proceedings. 2022;2022.
50.
go back to reference Shao B, Shi L, Xu B, Liu L. Factors affecting participation of solvers in crowdsourcing: an empirical study from China. Electron Markets. 2012;22:73–82. Shao B, Shi L, Xu B, Liu L. Factors affecting participation of solvers in crowdsourcing: an empirical study from China. Electron Markets. 2012;22:73–82.
51.
go back to reference Connelly BL, Certo S, Ireland RD, Reutzel CR. Signaling theory: a review and assessment. J Manag. 2011;37:39–67. Connelly BL, Certo S, Ireland RD, Reutzel CR. Signaling theory: a review and assessment. J Manag. 2011;37:39–67.
52.
go back to reference Fang J, Wen L, Ren H, Wen C. The effect of technical and functional quality on online physician selection: moderation effect of competition intensity. Inf Process Manag. 2022;59:102969. Fang J, Wen L, Ren H, Wen C. The effect of technical and functional quality on online physician selection: moderation effect of competition intensity. Inf Process Manag. 2022;59:102969.
53.
go back to reference Li J, Tang J, Yen DC, Liu X. Disease risk and its moderating effect on the e-consultation market offline and online signals. Inform Technol People. 2019;32:1065–84. Li J, Tang J, Yen DC, Liu X. Disease risk and its moderating effect on the e-consultation market offline and online signals. Inform Technol People. 2019;32:1065–84.
54.
go back to reference Yang H, Du HS, Shang W. Understanding the influence of professional status and service feedback on patients’ doctor choice in online healthcare markets. Internet Res. 2020;31:1236–61. Yang H, Du HS, Shang W. Understanding the influence of professional status and service feedback on patients’ doctor choice in online healthcare markets. Internet Res. 2020;31:1236–61.
55.
go back to reference Huang Z, Duan C, Yang Y, Khanal R. Online selection of a physician by patients: the impression formation perspective. BMC Med Inf Decis Mak. 2022;22:193. Huang Z, Duan C, Yang Y, Khanal R. Online selection of a physician by patients: the impression formation perspective. BMC Med Inf Decis Mak. 2022;22:193.
56.
go back to reference Cao X, Liu Y, Zhu Z, Hu J, Chen X. Online selection of a physician by patients: empirical study from elaboration likelihood perspective. Comput Hum Behav. 2017;73:403–12. Cao X, Liu Y, Zhu Z, Hu J, Chen X. Online selection of a physician by patients: empirical study from elaboration likelihood perspective. Comput Hum Behav. 2017;73:403–12.
57.
go back to reference Sun Y, Feng Y, Shen X-L, Guo X. Fear appeal, coping appeal and mobile health technology persuasion: a two-stage scenario-based survey of the elderly. Inform Technol People. 2022;36:362–86. Sun Y, Feng Y, Shen X-L, Guo X. Fear appeal, coping appeal and mobile health technology persuasion: a two-stage scenario-based survey of the elderly. Inform Technol People. 2022;36:362–86.
58.
go back to reference Chen L, Baird A, Straub D. Fostering Participant Health Knowledge and Attitudes: an Econometric Study of a chronic disease-focused Online Health Community. J Manage Inform Syst. 2019;36:194–229. Chen L, Baird A, Straub D. Fostering Participant Health Knowledge and Attitudes: an Econometric Study of a chronic disease-focused Online Health Community. J Manage Inform Syst. 2019;36:194–229.
Metadata
Title
Research on the doctors’ win in crowdsourcing competitions: perspectives on service content and competitive environment
Authors
Xiuxiu Zhou
Shanshan Guo
Hong Wu
Publication date
01-12-2023
Publisher
BioMed Central
Published in
BMC Medical Informatics and Decision Making / Issue 1/2023
Electronic ISSN: 1472-6947
DOI
https://doi.org/10.1186/s12911-023-02309-x

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