Factors Influencing User-Idea Selection in Open Innovation Communities

ABSTRACT

It is becoming an important innovation strategy for firms to gather the user-idea extensively through open innovation communities (OICs). However, screening out valuable ideas from massive user ideas in an OIC is a huge challenge for the firm. It is very important to identify the relevant factors that influence user-idea selection. Drawing upon persuasion theory, we develop a conceptual model integrating idea quality characteristics, idea contributor characteristics, and idea emotion characteristics to explain the likelihood of idea selection, using 23,165 user ideas in the MIUI Community hosted by Xiaomi, a Chinese mobile phone manufacturer ranked among the Fortune Global 500. The empirical results show that these characteristics variables have significant impacts on user-idea selection. Specifically, the length of the idea and title has an inverted U-shaped relationship with idea selection. The emotions contained in user ideas have a significant positive impact on idea selection, and user attention negatively moderates the relationship between emotion and idea selection. This study contributes to the user co-creation literature by offering a persuasion perspective to explain user-idea selection in OICs. It also offers novel insights for building reasonable rules in OICs to guide user behavior for managers.

KEY WORDS AND PHRASES:

• Open innovation
• user-idea selection
• idea selection
• idea characteristics
• sentiment analysis
• persuasion theory
• online innovation
• innovation communities

Acknowledgments

This work is supported by grants from the National Natural Science Foundation of China (71102138) and the National Social Science Foundation of China (20BGL287).

Disclosure Statement

No potential conflict of interest was reported by the authors.

Supplemental data

Supplemental data for this article can be accessed online at https://doi.org/10.1080/10864415.2022.2123644

Notes

¹ Some literature may use “idea adoption” instead of “idea selection.” These two phrases are slightly different in nature. Idea adoption emphasizes that idea is implemented and absorbed, including the meaning of choice, and idea selection emphasizes the screening process or conditions. Although there are some subtle differences, both are intended to identify and filter ideas.

2 In general, communities will classify users into different groups based on their participation in innovation, activity, contribution, professionalism, and other user information. In this study, users are divided into two groups. The user with a higher level group is 1, and the user with a general group is 0. See Appendix 3 for details of user levels and groups.

3 Chinese word segmentation software.

4 https://github.com/fannix/Chinese-Sentiment-Lexicon

Additional information

Notes on contributors

Qingfeng Zeng

Qingfeng Zeng ([email protected]) is an associate professor in the School of Information Management & Engineering at Shanghai University of Finance and Economics, China. He received his Ph.D. in management science and engineering from Fudan University, China. Dr. Zeng’s research interests are in the areas of open innovation, social media analytics, and online customer behavior research. His work has appeared in International Journal of Information Management, Information Systems Frontiers, Electronic Commerce Research and Applications, Information Technology & People, Electronic Markets, and other journals.

Lanlan Zhang

Lanlan Zhang ([email protected]; corresponding author) is a lecturer in the School of E-Commerce and Logistics Management at Henan University of Economics and Law, China. She holds a Ph.D in school of information management and engineering from Shanghai University of Finance and Economics, China. Dr. Zhang’s research interests are open innovation, product innovation, data mining, and text mining.

Qian Guo

Qian Guo ([email protected]) is a doctoral candidate in the School of Information Management & Engineering at Shanghai University of Finance and Economics, China. Her research interests are online customer behavior, social commerce, and business analytics.

Wei Zhuang

Wei Zhuang ([email protected]) is a doctoral candidate in the School of Information Management & Engineering at Shanghai University of Finance and Economics, China. Her research interests are knowledge management, social media analytics, and data mining.

Weiguo Fan

Weiguo Fan ([email protected]) is the Henry Tippie Endowed Chair in Business Analytics at the University of Iowa. He received his Ph.D. in business administration from the Ross School of Business, University of Michigan, Ann Arbor. His research interests focus on evolutionary computation, data mining, text mining, social media analytics, Big Data, social computing, and business analytics. Dr. Fan has published more than 200 refereed journal and conference papers. His research has appeared in many premier IT/IS/OM journals, such as Information Systems Research, Journal of Management Information Systems, MIS Quarterly, Productions and Operations Management, IEEE Transactions on Knowledge and Data Engineering, Information Systems, Communications of the ACM, Information and Management, and others.