Abstract
In recent years, open innovation communities (OICs), in which users are allowed to post ideas, have become a momentous source of product innovation and development for enterprises. Continuous generation of ideas is critical to the success of an OIC. When users post an idea more than once, they are considered to be conducting re-innovation behavior (RIB). Many enterprises have implemented management response systems in their OICs to motivate users’ RIB and promote the prosperity of the OIC. However, researchers have not yet examined whether management response is an effective management tool for motivating users’ RIB in OICs. This research shows that receiving management response has a positive effect on the volume, quality and novelty of user’s RIB. Furthermore, we found that the enterprise’s official adoption willingness expressed through management response may reduce the volume, quality, and novelty of ideas in user’s RIB, which may have an impact on the enterprise’s insights. Additionally, we conducted heterogeneity analyses to explore the effects of different lengths and sentiments of management response in this mechanism. This research has implications for managers and enterprises and contributes to the literature on management response, idea generation behavior, OICs, and, more broadly, co-innovation between enterprises and consumers.
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References
Liu Q, Du Q, Hong Y, Fan W, Wu S (2020) User idea implementation in open innovation communities: evidence from a new product development crowdsourcing community. Inf Syst J 30(5):899–927. https://doi.org/10.1111/isj.12286
Di Gangi PM, Wasko M (2009) Steal my idea! Organizational adoption of user innovations from a user innovation community: a case study of Dell IdeaStorm. Decis Support Syst 48(1):303–312. https://doi.org/10.1016/j.dss.2009.04.004
Kumar N, Qiu L, Kumar S (2018) Exit, voice, and response on digital platforms: an empirical investigation of online management response strategies. Inf Syst Res 29(4):849–870. https://doi.org/10.1287/isre.2017.0749
Boudreau KJ (2012) Let a thousand flowers bloom? An early look at large numbers of software app developers and patterns of innovation. Organ Sci 23(5):1409–1427. https://doi.org/10.1287/orsc.1110.0678
Chen W, Gu B, Ye Q, Zhu KX (2019) Measuring and managing the externality of managerial responses to online customer reviews. Inf Syst Res 30(1):81–96. https://doi.org/10.1287/isre.2018.0781
Wang Y, Chaudhry A (2018) When and how managers’ responses to online reviews affect subsequent reviews. J Mark Res 55(2):163–177. https://doi.org/10.1509/jmr.15.0511
Gu B, Ye Q (2014) First step in social media: measuring the influence of online management responses on customer satisfaction. Prod Oper Manag 23(4):570–582. https://doi.org/10.1111/poms.12043
Zhu F, Zhang X (2010) Impact of online consumer reviews on sales: the moderating role of product and consumer characteristics. J Mark 74(2):133–148. https://doi.org/10.1509/jmkg.74.2.133
Ye Q, Law R, Gu B (2009) The impact of online user reviews on hotel room sales. Int J Hosp Manag 28(1):180–182. https://doi.org/10.1016/j.ijhm.2008.06.011
Bayus BL (2013) Crowdsourcing new product ideas over time: an analysis of the Dell IdeaStorm community. Manag Sci 59(1):226–244. https://doi.org/10.1287/mnsc.1120.1599
Jeppesen LB, Frederiksen L (2006) Why do users contribute to firm-hosted user communities? The case of computer-controlled music instruments. Organ Sci 17(1):45–63. https://doi.org/10.1287/orsc.1050.0156
Xie KL, So KKF, Wang W (2017) Joint effects of management responses and online reviews on hotel financial performance: a data-analytics approach. Int J Hosp Manag 62:101–110. https://doi.org/10.1016/j.ijhm.2016.12.004
Hertel G, Niedner S, Herrmann S (2003) Motivation of software developers in Open Source projects: an Internet-based survey of contributors to the Linux kernel. Res Policy 32(7):1159–1177. https://doi.org/10.1016/s0048-7333(03)00047-7
Schlagwein VW, Bjorn-Andersen N (2018) Organizational learning with crowdsourcing: the revelatory case of LEGO. J Assoc Inf Syst 15(11):754–778. https://doi.org/10.17705/1jais.00380
Tang VW (2018) Wisdom of crowds: cross-sectional variation in the informativeness of third-party-generated product information on Twitter. J Account Res 56(3):989–1034. https://doi.org/10.1111/1475-679X.12183
Shah SK (2005) Open beyond software. Open Sources 2(339):360. https://doi.org/10.2139/ssrn.789805
Zhang Z, Li H, Yang Y, Xu Y (2021) Not all words are beneficial: the impact of management response contents on customer engagement behavior. Int J Hosp Manag. https://doi.org/10.1016/j.ijhm.2020.102805
Mayzlin D (2006) Promotional chat on the Internet. Mark Sci 25(2):155–163. https://doi.org/10.1287/mksc.1050.0137
Mueller JS, Melwani S, Goncalo JA (2012) The bias against creativity: why people desire but reject creative ideas. Psychol Sci 23(1):13–17. https://doi.org/10.1177/0956797611421018
Liu X, Wang GA, Fan W, Zhang Z (2020) Finding useful solutions in online knowledge communities: a theory-driven design and multilevel analysis. Inf Syst Res 3(31):731–752. https://doi.org/10.1287/isre.2019.0911
Goh K-Y, Heng C-S, Lin Z (2013) Social media brand community and consumer behavior: quantifying the relative impact of user- and marketer-generated content. Inf Syst Res 24(1):88–107. https://doi.org/10.1287/isre.1120.0469
Luca M, Zervas G (2016) Fake it till you make it: reputation, competition, and yelp review fraud. Manag Sci 62(12):3412–3427. https://doi.org/10.1287/mnsc.2015.2304
Smith PG (2004) Open innovation: the new imperative for creating and profiting from technology. J Prod Innov Manag 21(3):223–224. https://doi.org/10.1111/j.0737-6782.2004.072_2.x
Chang D, Chen C-H, Lee KM (2014) A crowdsourcing development approach based on a neuro-fuzzy network for creating innovative product concepts. Neurocomputing 142:60–72. https://doi.org/10.1016/j.neucom.2014.03.044
Yang M, Han C (2021) Stimulating innovation: managing peer interaction for idea generation on digital innovation platforms. J Bus Res 125:456–465. https://doi.org/10.1016/j.jbusres.2019.08.005
Ma J, Lu Y, Gupta S (2019) User innovation evaluation: empirical evidence from an online game community. Decis Support Syst 117:113–123. https://doi.org/10.1016/j.dss.2018.11.003
Li M, Kankanhalli A, Kim SH (2016) Which ideas are more likely to be implemented in online user innovation communities? An empirical analysis. Decis Support Syst 84:28–40. https://doi.org/10.1016/j.dss.2016.01.004
Hoornaert S, Ballings M, Malthouse EC, Van den Poel D (2017) Identifying new product ideas: waiting for the wisdom of the crowd or screening ideas in real time. J Prod Innov Manag 34(5):580–597. https://doi.org/10.1111/jpim.12396
Heimbach I, Hinz O (2018) The impact of sharing mechanism design on content sharing in online social networks. Inf Syst Res 29(3):592–611. https://doi.org/10.1287/isre.2017.0738
Chevalier JA, Mayzlin D (2006) The effect of word of mouth on sales: online book reviews. J Mark Res 43(3):345–354. https://doi.org/10.1509/jmkr.43.3.345
Park J, Ramaprasad A (2018) Toward ontology of designer-user interaction in the design process: a knowledge management foundation. J Knowl Manag 22(1):201–218. https://doi.org/10.1108/jkm-06-2017-0220
Duan W, Gu B, Whinston AB (2008) Do online reviews matter? An empirical investigation of panel data. Decis Support Syst 45(4):1007–1016. https://doi.org/10.1016/j.dss.2008.04.001
Forman C, Ghose A, Wiesenfeld B (2008) Examining the relationship between reviews and sales: the role of reviewer identity disclosure in electronic markets. Inf Syst Res 19(3):291–313. https://doi.org/10.1287/isre.1080.0193
Belen del Rio-Lanza A, Vazquez-Casielles R, Ma Diaz-Martin A (2009) Satisfaction with service recovery: perceived justice and emotional responses. J Bus Res 62(8):775–781. https://doi.org/10.1016/j.jbusres.2008.09.015
Martinez-Torres MR (2013) Application of evolutionary computation techniques for the identification of innovators in open innovation communities. Expert Syst Appl 40(7):2503–2510. https://doi.org/10.1016/j.eswa.2012.10.070
Schmidt-Keilich M, Schrader U (2019) Sustainability innovation by integrating employees: the potential of sustainable embedded lead users. Int J Innov Sustain Dev 13(1):98–115. https://doi.org/10.1504/ijisd.2019.10017257
Tsai WC, Huang YM (2002) Mechanisms linking employee affective delivery and customer behavioral intentions. J Appl Psychol 87(5):1001–1008. https://doi.org/10.1037//0021-9010.87.5.1001
Kamboj S, Sarmah B, Gupta S, Dwivedi Y (2018) Examining branding co-creation in brand communities on social media: applying the paradigm of Stimulus–Organism–Response. Int J Inf Manag 39:169–185. https://doi.org/10.1016/j.ijinfomgt.2017.12.001
Zhang C, Hahn J, De P (2013) Continued participation in online innovation communities: does community response matter equally for Everyone? Inf Syst Res 24(4):1112–1130. https://doi.org/10.1287/isre.2013.0485
Dahlander L, Wallin MW (2006) A man on the inside: unlocking communities as complementary assets. Res Policy 35(8):1243–1259. https://doi.org/10.1016/j.respol.2006.09.011
Xie KL, Zhang Z, Zhang Z (2014) The business value of online consumer reviews and management response to hotel performance. Int J Hosp Manag 43:1–12. https://doi.org/10.1016/j.ijhm.2014.07.007
Zhang, S., Pan, S. L., & Ouyang, T. H (2020) Building social translucence in a crowdsourcing process: a case study of Miui.com. Inf Manag 57(2). https://doi.org/10.1016/j.im.2019.103172
Goes PB, Guo C, Lin M (2016) Do incentive hierarchies induce user effort? Evidence from an onlineknowledge exchange. Inf Syst Res 27(3):497–516. https://doi.org/10.1287/isre.2016.0635
Hau YS, Kim Y-G (2011) Why would online garners share their innovation-conducive knowledge in the online game user community? Integrating individual motivations and social capital perspectives. Comput Hum Behav 27(2):956–970. https://doi.org/10.1016/j.chb.2010.11.022
Rodebaugh TL (2006) Self-efficacy and social behavior. Behav Res Ther 44(12):1831–1838. https://doi.org/10.1016/j.brat.2005.11.014
Park S-Y, Allen JP (2013) Responding to online reviews: Problem solving and engagement in hotels. Cornell Hospital Q 54(1):64–73. https://doi.org/10.1177/1938965512463118
Purvis R, Sambamurthy V (1997) An examination of designer and user perceptions of JAD and the traditional IS design methodology. Inf Manag 32(3):123–135. https://doi.org/10.1016/s0378-7206(96)01087-7
Diedrich J, Benedek M, Jauk E, Neubauer AC (2015) Are creative ideas novel and useful? Psychol Aesthet Creat Arts 9(1):35–40. https://doi.org/10.1037/a0038688
Bock GW, Zmud RW, Kim YG, Lee JN (2005) Behavioral intention formation in knowledge sharing: examining the roles of extrinsic motivators, social-psychological forces, and organizational climate. MIS Q 29(1):87–111. https://doi.org/10.2307/25148669
Fresneda JE, Gefen D (2019) A semantic measure of online review helpfulness and the importance of message entropy. Decis Support Syst. https://doi.org/10.1016/j.dss.2019.113117
Haas MR, Criscuolo P, George G (2015) Which problems to solve? Online knowledge sharing and attention allocation in organizations. Acad Manag J 58(3):680–711. https://doi.org/10.5465/amj.2013.0263
Heckman JJ (1979) Sample selection bias as a specification error. Econometrica 47:153–161. https://doi.org/10.2307/1912352
Bénabou R, Tirole J (2006) Incentives and prosocial behavior. Am Econ Rev 96(5):1652–1678. https://doi.org/10.1257/aer.96.5.1652
Bapna S, Benner MJ, Qiu L (2019) Nurturing online communities: an empirical investigation. MIS Q 43(2):425–452. https://doi.org/10.25300/MISQ/2019/14530
Sun Y, Dong X, McIntyre S (2017) Motivation of user-generated content: social connectedness moderates the effects of monetary rewards. Mark Sci 36(3):329–337. https://doi.org/10.1287/mksc.2016.1022
Hendrickx J (2002) Review of regression models for categorical dependent variables using Stata by long and Freese. Stand Genomic Sci 1(2):103–105. https://doi.org/10.1177/1536867X0600600208
Yang M, Ren Y, Adomavicius G (2019) Understanding user-generated content and customer engagement on Facebook business pages. Inf Syst Res 3(30):839–855. https://doi.org/10.1287/isre.2019.0834
Faraj S, Kudaravalli S, Wasko M (2015) Leading collaboration in online communities. MIS Q 2(39):393–412. https://doi.org/10.25300/MISQ/2015/39.2.06
Acknowledgements
This work was supported by Program for Innovative Research Team of Shanghai University of Finance and Economics (IRTSHUFE).
Funding
Funding was provided by the National Social Science Foundation of Shanghai (Grant No. 2018BGL026) and Natural Science Foundation of China (Grant No. 71911156).
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Han, D., Pang, Z., He, L. et al. Management response and user idea generation: evidence from an online open innovation community. Inf Technol Manag 24, 381–400 (2023). https://doi.org/10.1007/s10799-022-00381-9
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DOI: https://doi.org/10.1007/s10799-022-00381-9