With the development of the Internet and the widespread use of Web 2.0, social Q&A communities have become important sources for users to acquire and share knowledge. The key to the success of social Q&A communities lies in the fact that they can motivate and sustain users' continuous knowledge contributions. However, most social Q&A communities still face the problem of users' low activity and low willingness to continue contributing knowledge, which makes the sustainable development of online communities difficult. As a result, it becomes a challenge for social Q&A communities to increase user stickiness and motivate users to continue participating in knowledge contribution.#br#This paper constructs a framework based on the socioecological model (SEM) for analyzing the influence factors of users' continuous knowledge contribution behavior. It uses a Python program to longitudinally track 2 419 users in the Zhihu community to obtain one-year data on users' continuous participation behavior from June 15, 2020 to June 15, 2021, and adopts the fsQCA model to analyze the interaction effects between the influencing factors of continuous knowledge contribution behavior, changing from a single-dimensional perspective to a multi-dimensional interactive overall perspective.#br#Research results show that users' continuous knowledge contribution behavior in social Q&A communities is the result of the interaction effect of multiple combination factors, and there is no single core condition that can directly influence users' continuous knowledge contribution behavior. There are three configurations to achieve a high quantity of users' continuous knowledge contribution: achievement-motivation-driven, interpersonal relationship-driven, and full-dimensional-driven. And there are two configuration ways to achieve a high quality of users' continuous knowledge contribution, namely, image-incentive-driven and participation-motivation-driven. Thus, achievement motivation, responsibility and identity in the individual motivation level are important core factors to trigger individuals enthusiasm for continuous knowledge contributions, while community image motivation and peer influence in the community environment exist as important supporting factors, and interpersonal factors exist more as potential causes of different configuration paths of the quantity and quality of users' continuous knowledge contributions.#br#The theoretical contributions of this study are presented below. Firstly, it constructs an integrative model to examine the joint influence of individual factors, interpersonal factors and community environment factors on users' continuous knowledge contribution behavior from an integrative perspective;then, it explores multiple motives that influence the continuous knowledge contribution behavior of social Q&A communities and reveals the influence mechanism of the factor groups of users' continuous knowledge contribution behavior. Secondly, with a focus on the influencing factors of continuous knowledge contribution behavior, it explains the persistence of users' knowledge contribution behavior and obtains users' extent data by continuously tracking users. Thirdly, the existing studies neglect the importance of the quality of knowledge contributions, for only effective and responsive knowledge contributions account for knowledge contributions. This paper not only expands the dimensional division of continuous knowledge contribution behavior by dividing it into continuous knowledge contribution quantity and continuous knowledge contribution quality, but also provides different path options to promote the users' continuous knowledge contribution in different dimensions, which provides a more comprehensive understanding of knowledge contribution behavior in online communities and promotes further development research on user knowledge contribution behavior.〖HJ*3〗#br#In order to encourage users to engage in continuous knowledge contribution in the community, community managers should pay attention to the interaction between community members and improve the social design of online community platforms to increase the frequency of interaction among users so that they can build trust with each other through in-depth communication. Furthermore, the community should establish a diverse incentive system to encourage users to share their ideas and creativity. Community managers can use a combination of material and spiritual incentives to encourage users to actively participate in community activities, thereby increasing their enthusiasm for continuous knowledge contributions. In addition, communities should place a high priority on the quality of users' knowledge contributions. Through the evaluation mechanism, the community can objectively evaluate user-generated content based on the number of approvals, likes and shares achieved by each user's post and then rank user-generated content according to certain evaluation weights to recommend high-quality contents to the corresponding users, and further build an effective push for high-quality content.#br#
[1] YAN Y, DAVISON R M. Exploring behavioral transfer from knowledge seeking to knowledge contributing: the mediating role of intrinsic motivation [J]. Journal of the Association for Information Science and Technology, 2013, 64:1144-1157.
[2] JIN J, LI Y, ZHONG X,et al. Why users contribute knowledge to online communities:an empirical study of an online social Q&A community [J].Information & Management, 2015, 52(7):840-849.
[3] XIONG Y, CHENG Z, LIANG E, et al. Accumulation mechanism of opinion leaders' social interaction ties in virtual communities:empirical evidence from China [J].Computers in Human Behavior, 2018, 82:81-93.
[4] CHEN L, AARON BAIRD, DETMAR STRAUB. Why do participants continue to contribute? comment of usefulness voting and commenting motivational affordances within an online knowledge community [J].Decision Support Systems, 2019, 118:21-32.
[5] JABR W, MOOKERJEE R,TAN Y, et al. Leveraging philanthropic behavior for customer support: the case of user support forums [J].MIS Quarterly, 2014, 38(1):187-208.
[6] DONG J Q, NETTEN J. Information technology and external search in the open innovation age:new findings from Germany [J].Technological Forecasting and Social Change, 2017, 120: 223-231.
[7] HUANG P, TAFTI A, MITHAS S. Platform sponsor investments and user contributions in knowledge communities: the role of knowledge seeking [J].MIS Quarterly, 2018, 42(1): 213-240.
[8] ZHANG X, LIU S, CHEN X, et al. Social capital, motivations, and knowledge sharing intention in health Q&A communities [J].Management Decision,2017,1(55): 1536-1557.
[9] GUAN T, WANG L, JIN J, et al. Knowledge contribution behavior in online Q&A communities:an empirical investigation [J].Computers in Human Behavior, 2018,81:137-147.
[10] 龚主杰, 赵文军. 虚拟社区知识共享持续行为的机理探讨——基于心理认知的视角 [J].情报理论与实践, 2013, 36(3): 27-31.
[11] OGINK T, DONG J Q. Stimulating innovation by user feedback on social media:the case of an online user innovation community [J].Technological Forecasting & Social Change, 2017(2):5-12.
[12] 李海峰, 王炜. 在线学习社区的知识共享质量影响因素:以学习者书评质量分析为例 [J].现代远距离教育, 2021,38(5):12-23.
[13] ZASTROW C, KIRST-ASHMAN K. Understand human behavior and social environment (Six edition) [M].Thomson Brooks/ Cole, 2004.
[14] 王楠,王莉雅,李瑶,等. 同侪影响对用户贡献行为的作用研究——基于网络客观大数据的分析 [J].科学学研究, 2021, 39(12): 2294-2304.
[15] LAW K K, CHAN A, OZER M, et al. Towards an integrated framework of intrinsic motivators, extrinsic motivators and knowledge sharing [J].Journal of Knowledge Management, 2017, 21(6): 1486-1502.
[16] ZHAO L,DETLOR B,CONNELLY C E.Sharing knowledge in social Q&A sites:the unintended consequences of extrinsic motivation[J].Journal of Management Information Systems,2016, 33(1):70-100.
[17] HAU Y S, KIM B, LEE H, et al. The effects of individual motivations and social capital on employees' tacit and explicit knowledge sharing intentions [J].International Journal of Information Management, 2013, 33(2): 356-366.
[18] BASAK E, CALISIR F. An empirical study on factors affecting continuance intention of using Facebook [J].Computers in Human Behavior, 2015, 48: 181-189.
[19] YANG X, LI G. Factors influencing the popularity of customer-generated content in a company-hosted online co-creation community: a social capital perspective [J].Computers in Human Behavior, 2016,64:760-768.
[20] BHATTACHERJEE A. Understanding information systems continuance: an expectation confirmation model [J].MIS Quarterly, 2001, 25(3):351-370.
[21] CHEUNG C M K, LEE M K O, LEE Z W Y. Understanding the continuance intention of knowledge sharing in online communities of practice through the post-knowledge-sharing evaluation processes [J].Journal of the American Society for Information Science and Technology, 2013, 64(7):1357-1374.
[22] CAI Y, YANG Y, SHI W. A predictive model of the knowledge-sharing intentions of social Q&A community members: a regression tree approach[J].International Journal of Human-Computer Interaction, 2021:1-15.
[23] CAI Y, SHI W. The influence of the community climate on users' knowledge-sharing intention: the social cognitive theory perspective [J].Behaviour & Information Technology,2020:1-17.
[24] LI Z, LIN Z, NIE J. How personality and social capital affect knowledge sharing intention in online health support groups:a person-situation perspective [J].International Journal of Human-Computer Interaction, 2021:1-12.
[25] 万莉, 程慧平. 基于自我决定理论的虚拟知识社区用户持续知识贡献行为动机研究 [J].情报科学, 2016, 34(10):15-19.
[26] LOU J, FANG Y, LIM K H. Contributing high quantity and quality knowledge to online Q&A communities [J].Journal of the American Society for Information Science and Technology, 2013, 64(2): 356-371.
[27] SEDIGHI M,HAMEDI M.Knowledge contribution in knowledge networks:effects of participants' central positions on contribution quality [D].Proceedings of the International Conference on Intellectual Capital,Knowledge Management and Organizational Learning,2016.
[28] BRONFENBRENNER U. Contexts of child rearing: problems and prospect [J].American Psychologist, 1979, 34(10):844-850.
[29] MELIUS J. Exploring social workers' use of the socio-ecological model as an intervention and research framework for treating overweight or obese clients [J].Social Work, 2015, 60(1): 55-63.
[30] 俞国良,李建良,王勍. 生态系统理论与青少年心理健康教育 [J].教育研究, 2018, 39(3):110-117.
[31] XIAO Y, HUANG W, LU M, et al. Social-ecological analysis of the factors influencing Shanghai adolescents' table tennis skills:a cross-sectional study [J].Frontiers in psychology, 2020, 11:1372.
[32] 赵欣,张之光,向希尧. 专业虚拟社区研究综述与PVC知识创造模型构建[J].科研管理,2018,39(11):132-145.
[33] 沈校亮,厉洋军. 虚拟品牌社区知识贡献意愿研究:基于动机和匹配的整合视角[J].管理评论, 2018, 30(10):82-94.
[34] 杨昕雅. 知识型微信社群用户参与动机对参与行为的影响 [J].重庆邮电大学学报(社会科学版), 2017, 29(5):20-28.
[35] LIU S, XIAO W, FANG C, et al. Social support, belongingness, and value co-creation behaviors in online health communities [J].Telematics and Informatics, 2020,50.
[36] CHANG H H, CHUANG S-S. Social capital and individual motivations on knowledge sharing:participant involvement as a moderator [J].Information & Management,2011,48(1):9-18.
[37] YAN J, LEIDNERB D E, BENBYAC H, et al. Social capital and knowledge contribution in online user communities: one-way or two-way relationship[J].Decision Support Systems,2019,127: 113131.
[38] LIANG Y, OW T T, WANG X. How do group performances affect users' contributions in online communities?a cross-level moderation model [J].Journal of Organizational Computing and Electronic Commerce, 2020, 30(2):129-149.
[39] DONG L, HUANG L, HOU J, et al. Continuous content contribution in virtual community:the role of status-standing on motivational mechanisms [J].Decision Support Systems, 2020, 132: 113283.
[40] CHIU C M, HSU M H, WANG E T G. Understanding knowledge sharing in virtual communities:an integration of social capital and social cognitive theories [J].Decision Support Systems,2006, 42(3):1872-1888.
[41] CHIA-AN TSAIA J,KANG T.Reciprocal intention in knowledge seeking:examining social exchange theory in an online professional community [J].International Journal of Information Management,2019,48:161-174.
[42] 易明,罗瑾琏,王圣慧,等. 时间压力会导致员工沉默吗——基于SEM与 fsQCA的研究 [J].南开管理评论, 2018, 21(1): 203-215.
[43] RAGIN C C. Redesigning social inquiry:fuzzy sets and beyond[D].University of Chicago Press, 2008.
[44] YE H, FENG Y. Why do you return the favor in online knowledge communities? a study of the motivations of reciprocity [J].Computers in Human Behavior,2016,63:342-349.
[45] YAN B, JIAN L. Beyond reciprocity: the bystander effect of knowledge response in online knowledge communities [J].Computers in Human Behavior, 2017,76:9-18.
[46] LIU Z, WANG X. How to regulate individuals' privacy boundaries on social network sites: a crosscultural comparison [J].Information & Management,2018,55(8):1005-1023.
[47] CRESS U, BARQUERO B, SCHWAN S, et al. Improving quality and quantity of contributions: two models for promoting knowledge exchange with shared databases [J].Computers and Education, 2017,49(2): 423-440.
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