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How top leaders’ support affects open government data (OGD)-driven innovation capacity of firms: Based on the TOE framework perspective

Published online by Cambridge University Press:  14 March 2024

Yu Wang
Affiliation:
Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center (National Supercomputer Center in Jinan), Qilu University of Technology (Shandong Academy of Sciences), Jinan, China Shandong Provincial Key Laboratory of Computer Networks, Shandong Fundamental Research Center for Computer Science, Jinan, China SHANDONG SCICOM Information and Economy Research Institute Co.,Ltd., Jinan, China
Hui Jiang
Affiliation:
School of Information Management and Artificial Intelligence, Zhejiang University of Finance and Economics, Hangzhou, China
Delong Han
Affiliation:
Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center (National Supercomputer Center in Jinan), Qilu University of Technology (Shandong Academy of Sciences), Jinan, China Shandong Provincial Key Laboratory of Computer Networks, Shandong Fundamental Research Center for Computer Science, Jinan, China
Mingle Zhou
Affiliation:
Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center (National Supercomputer Center in Jinan), Qilu University of Technology (Shandong Academy of Sciences), Jinan, China Shandong Provincial Key Laboratory of Computer Networks, Shandong Fundamental Research Center for Computer Science, Jinan, China SHANDONG SCICOM Information and Economy Research Institute Co.,Ltd., Jinan, China
Gang Li*
Affiliation:
Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center (National Supercomputer Center in Jinan), Qilu University of Technology (Shandong Academy of Sciences), Jinan, China Shandong Provincial Key Laboratory of Computer Networks, Shandong Fundamental Research Center for Computer Science, Jinan, China
*
Corresponding author: Gang Li; Email: lig@qlu.edu.cn

Abstract

The innovation value of open government data (OGD) drives firms to the participation in OGD-driven innovation. However, to fully excavate the innovation value of OGD for firms, it is essential to explore the factors and mechanisms that affect OGD-driven innovation capacity. On the basis of the technology–organization–environment (TOE) framework, a theoretical model affecting OGD-driven innovation capacity is proposed for analysis by partial least squares structural equation modeling with 236 sample data from China. The results indicate that top leaders’ support positively impacts on OGD-driven innovation capacity in firms. And we also prove that technical competence, organizational arrangement, and innovation support partially mediate the relationship between top leaders’ support and OGD-driven innovation capacity on the basis of the TOE framework. Consequently, the findings provide new research perspectives and practical guidance for promoting OGD-driven innovation capacity in firms.

Type
Research Article
Copyright
© The Author(s), 2024. Published by Cambridge University Press in association with Australian and New Zealand Academy of Management.

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References

Ahmadi Zeleti, F., Ojo, A., & Curry, E. (2016). Exploring the economic value of open government data. Government Information Quarterly, 33(3), 535551.CrossRefGoogle Scholar
Amabile, T. M., & Conti, R. (1999). Changes in the work environment for creativity during downsizing. Academy of Management Journal, 42(6), 630640.CrossRefGoogle Scholar
Amabile, T. M., Schatzel, E. A., Moneta, G. B., & Kramer, S. J. (2004). Leader behaviors and the work environment for creativity: Perceived leader support. The Leadership Quarterly, 15(1), 532.Google Scholar
Andrews, R., Beynon, M. J., & McDermott, A. M. (2016). Organizational capability in the public sector: A configurational approach. Journal of Public Administration Research and Theory, 26(2), 239258.CrossRefGoogle Scholar
Arpaci, I., Kesici, Ş., & Baloğlu, M. (2018). Individualism and internet addiction: The mediating role of psychological needs. Internet Research, 28(2), 293314.Google Scholar
Balasubramanian, N., & Lee, J. (2008). Firm age and innovation. Industrial and Corporate Change, 17(5), 10191047.CrossRefGoogle Scholar
Bates, J. (2014). The strategic importance of information policy for the contemporary neoliberal state: The case of Open Government Data in the United Kingdom. Government Information Quarterly, 31(3), 388395.CrossRefGoogle Scholar
Benitez, J., Henseler, J., Castillo, A., & Schuberth, F. (2020). How to perform and report an impactful analysis using partial least squares: Guidelines for confirmatory and explanatory IS research. Information & Management, 57(2), .CrossRefGoogle Scholar
Chan, S. C., & Mak, W. (2014). Transformational leadership, pride in being a follower of the leader and organizational commitment. Leadership & Organization Development Journal, 35(8), 674690.CrossRefGoogle Scholar
Chatfield, A. T., & Reddick, C. G. (2018). The role of policy entrepreneurs in open government data policy innovation diffusion: An analysis of Australian Federal and State Governments. Government Information Quarterly, 35(1), 123134.CrossRefGoogle Scholar
Daft, R. L., & Weick, K. E. (1984). Toward a model of organizations as interpretation systems. Academy of Management Review, 9(2), 284295.CrossRefGoogle Scholar
Dukeov, I., Bergman, J.-P., Heilmann, P., Platonov, V. V., & Jaschenko, V. V. (2018). A firm’s age and size as determinants for its organizational innovativeness. Journal of Innovation Management, 6(3), 98133.Google Scholar
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 3950.CrossRefGoogle Scholar
Garcia-Ortega, B., Lopez-Navarro, M. A., & Galan-Cubillo, J. (2021). Top management support in the implementation of industry 4.0 and business digitization: The case of companies in the main European stock indices. IEEE Access, 9, 139994140007.CrossRefGoogle Scholar
Ghasemaghaei, M., & Calic, G. (2019). Does big data enhance firm innovation competency? The mediating role of data-driven insights. Journal of Business Research, 104, 6984.CrossRefGoogle Scholar
GOV.UK. (2012). Open Data User Group. Retrieved August 24 , 2022, from https://www.gov.uk/government/groups/open-data-user-group.Google Scholar
Guo, G., Pang, X. Q., & Li, W. (2018). The role of top management team diversity in shaping the performance of business model innovation: A threshold effect. Technology Analysis & Strategic Management, 30(2), 241253.CrossRefGoogle Scholar
Hair, J. F. Jr, Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM). New York: SAGE.Google Scholar
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139152.CrossRefGoogle Scholar
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 224.CrossRefGoogle Scholar
Hair, J. F. Jr, Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. (2014). Partial least squares structural equation modeling (PLS-SEM). European Business Review, 26(2), 106121.CrossRefGoogle Scholar
Hansen, J. A. (1992). Innovation, firm size, and firm age. Small Business Economics, 4(1), 3744.CrossRefGoogle Scholar
Henseler, J. (2010). On the convergence of the partial least squares path modeling algorithm. Computational Statistics, 25(1), 107120.CrossRefGoogle Scholar
Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. In Sinkovics, R. R. & Ghauri, P. N. (Eds.), New challenges to international marketing (pp. 279319). Bingley: Emerald Group Publishing Limited.Google Scholar
Hsu, H. Y., Liu, F. H., Tsou, H. T., & Chen, L. J. (2019). Openness of technology adoption, top management support and service innovation: A social innovation perspective. Journal of Business and Industrial Marketing, 34(3), 575590.CrossRefGoogle Scholar
Iryna, S., Åke, G., & Marijn, J. (2015). Organizational measures to stimulate user engagement with open data. Transforming Government: People, Process and Policy, 9(2), 181206.Google Scholar
Janssen, M., Charalabidis, Y., & Zuiderwijk, A. (2012). Benefits, adoption barriers and myths of open data and open government. Information Systems Management, 29(4), 258268.CrossRefGoogle Scholar
Jaw, C., Lo, J.-Y., & Lin, Y.-H. (2010). The determinants of new service development: Service characteristics, market orientation, and actualizing innovation effort. Technovation, 30(4), 265277.Google Scholar
Jetzek, T., Avital, M., & Bjorn-Andersen, N. (2014). Data-driven innovation through open government data. Journal of Theoretical and Applied Electronic Commerce Research, 9(2), 100120.CrossRefGoogle Scholar
Kaasenbrood, M., Zuiderwijk, A., Janssen, M., de Jong, M., & Bharosa, N. (2015). Exploring the factors influencing the adoption of open government data by private organisations. International Journal of Public Administration in the Digital Age, 2(2), 7592.Google Scholar
Kalampokis, E., Tambouris, E., & Tarabanis, K. A. (2011). A classification scheme for open government data: Towards linking decentralised data. International Journal of Web Engineering and Technology, 6(3), 266285.CrossRefGoogle Scholar
Kaplan, S. N., Klebanov, M. M., & Sorensen, M. (2012). Which CEO characteristics and abilities matter? The Journal of Finance, 67(3), 9731007.CrossRefGoogle Scholar
Kassen, M. (2013). A promising phenomenon of open data: A case study of the Chicago open data project. Government Information Quarterly, 30(4), 508513.CrossRefGoogle Scholar
Khayer, A., Bao, Y., & Nguyen, B. (2020). Understanding cloud computing success and its impact on firm performance: An integrated approach. Industrial Management and Data Systems, 120(5), 963985.CrossRefGoogle Scholar
Koziol-Nadolna, K. (2020). The role of a leader in stimulating innovation in an organization. Administrative Sciences, 10(3), .CrossRefGoogle Scholar
Lee, G., & Kwak, Y. H. (2012). An open government maturity model for social media-based public engagement. Government Information Quarterly, 29(4), 492503.CrossRefGoogle Scholar
Leviäkangas, P., & Molarius, R. (2020). Open government data policy and value added – Evidence on transport safety agency case. Technology in Society, 63, .CrossRefGoogle Scholar
Liang, Y. K., Wang, W. J., Dong, K. X., Zhang, G. J., & Qi, G. J. (2021). Adoption of mobile government cloud from the perspective of public sector. Mobile Information Systems, 2021, 120.Google Scholar
Liao, S. H., Chen, C. C., Hu, D. C., Chung, Y. C., & Liu, C. L. (2017). Assessing the influence of leadership style, organizational learning and organizational innovation. Leadership & Organization Development Journal, 38(5), 590609.CrossRefGoogle Scholar
Li, H., & Atuahene‐Gima, K. (2002). The adoption of agency business activity, product innovation, and performance in Chinese technology ventures. Strategic Management Journal, 23(6), 469490.CrossRefGoogle Scholar
Magalhaes, G., & Roseira, C. (2020). Open government data and the private sector: An empirical view on business models and value creation. Government Information Quarterly, 37(3), .CrossRefGoogle Scholar
Mei, C. (2018). A study on the value of open government data: Connotation, evaluation and practice. Library, 288(9), 2732.Google Scholar
Mikalef, P., Krogstie, J., Pappas, I. O., & Pavlou, P. (2020). Exploring the relationship between big data analytics capability and competitive performance: The mediating roles of dynamic and operational capabilities. Information & Management, 57(2), .CrossRefGoogle Scholar
Nitzl, C., Roldan, J. L., & Cepeda, G. (2016). Mediation analysis in partial least squares path modeling: Helping researchers discuss more sophisticated models. Industrial Management and Data Systems, 116(9), 18491864.CrossRefGoogle Scholar
The People’s Government of Zhejiang Province. (2020). Zhejiang Open Data Innovation and Application Competition. Retrieved August 24 , 2022, from https://odic.zjzwfw.gov.cn/.Google Scholar
Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40(3), 879891.CrossRefGoogle ScholarPubMed
Ragu-Nathan, B. S., Apigian, C. H., Ragu-Nathan, T., & Tu, Q. (2004). A path analytic study of the effect of top management support for information systems performance. Omega, 32(6), 459471.Google Scholar
Reb, J., Narayanan, J., & Chaturvedi, S. (2014). Leading mindfully: Two studies on the influence of supervisor trait mindfulness on employee well-being and performance. Mindfulness, 5(1), 3645.CrossRefGoogle Scholar
Rodríguez, N. G., Pérez, M. J. S., & Gutiérrez, J. A. T. (2008). Can a good organizational climate compensate for a lack of top management commitment to new product development? Journal of Business Research, 61(2), 118131.CrossRefGoogle Scholar
Rosenbloom, R. S. (2000). Leadership, capabilities, and technological change: The transformation of NCR in the electronic era. Strategic Management Journal, 21(10‐11), 10831103.3.0.CO;2-4>CrossRefGoogle Scholar
Seifert, J. W. (2004). Data mining and the search for security: Challenges for connecting the dots and databases. Government Information Quarterly, 21(4), 461480.CrossRefGoogle Scholar
Shao, Z., Feng, Y. Q., & Hu, Q. (2017). Impact of top management leadership styles on ERP assimilation and the role of organizational learning. Information & Management, 54(7), 902919.CrossRefGoogle Scholar
Shin, S. J., & Zhou, J. (2003). Transformational leadership, conservation, and creativity: Evidence from Korea. Academy of Management Journal, 46(6), 703714.Google Scholar
Slevin, D. P., & Covin, J. G. (1997). Strategy formation patterns, performance, and the significance of context. Journal of Management, 23(2), 189209.CrossRefGoogle Scholar
Sobel, M. E. (1982). Asymptotic confidence intervals for indirect effects in structural equation models. Sociological Methodology, 13, 290312.CrossRefGoogle Scholar
Sohal, S., Moss, A., & Ng, L. (2001). Comparing IT success in manufacturing and service industries. International Journal of Operations and Production Management, 21(1/2), 3045.Google Scholar
Susha, I., Grönlund, Å., & Janssen, M. (2015). Driving factors of service innovation using open government data: An exploratory study of entrepreneurs in two countries. Information Polity, 20(1), 1934.CrossRefGoogle Scholar
Talke, K., Salomo, S., & Rost, K. (2010). How top management team diversity affects innovativeness and performance via the strategic choice to focus on innovation fields. Research Policy, 39(7), 907918.CrossRefGoogle Scholar
Teece, D. J. (2007). Explicating dynamic capabilities: The nature and microfoundations of (sustainable) enterprise performance. Strategic Management Journal, 28(13), 13191350.CrossRefGoogle Scholar
Tornatzky, L. G., Fleischer, M., & Chakrabarti, A. K. (1990). Processes of technological innovation. UK: Lexington Books.Google Scholar
Vaccaro, I. G., Jansen, J. J. P., Van Den Bosch, F. A. J., & Volberda, H. W. (2012). Management innovation and leadership: The moderating role of organizational size. Journal of Management Studies, 49(1), 2851.CrossRefGoogle Scholar
Wamba, S. F., Gunasekaran, A., Akter, S., Ren, S. J.-F., Dubey, R., & Childe, S. J. (2017). Big data analytics and firm performance: Effects of dynamic capabilities. Journal of Business Research, 70, 356365.CrossRefGoogle Scholar
Wang, H.-J., & Lo, J. (2016). Adoption of open government data among government agencies. Government Information Quarterly, 33(1), 8088.CrossRefGoogle Scholar
Wang, H.-J., & Lo, J. (2020). Factors influencing the adoption of open government data at the firm level. IEEE Transactions on Engineering Management, 67(3), 670682.CrossRefGoogle Scholar
Weiner, B. J., Shortell, S. M., & Alexander, J. (1997). Promoting clinical involvement in hospital quality improvement efforts: The effects of top management, board, and physician leadership. Health Services Research, 32(4), 491510.Google ScholarPubMed
Yang, J. (2008). Unravelling the link between knowledge integration and new product timeliness. Technology Analysis & Strategic Management, 20(2), 231243.CrossRefGoogle Scholar
Yukl, G., Gordon, A., & Taber, T. (2002). A hierarchical taxonomy of leadership behavior: Integrating a half century of behavior research. Journal of Leadership & Organizational Studies, 9(1), 1532.CrossRefGoogle Scholar
Yu, C. P., Wang, Y., Li, T. C., & Lin, C. P. (2022). Do top management teams’ expectations and support drive management innovation in small and medium-sized enterprises? Journal of Business Research, 142, 8899.CrossRefGoogle Scholar
Zhang, N., Zhao, X., Zhang, Z., Meng, Q., & Tan, H. (2017). What factors drive open innovation in China’s public sector? A case study of official document exchange via microblogging (ODEM) in Haining. Government Information Quarterly, 34(1), 126133.CrossRefGoogle Scholar
Zhao, Y., & Fan, B. (2018). Exploring open government data capacity of government agency: Based on the resource-based theory. Government Information Quarterly, 35(1), 112.CrossRefGoogle Scholar
Zhao, Y., & Fan, B. (2021). Effect of an agency’s resources on the implementation of open government data. Information & Management, 58(4), .CrossRefGoogle Scholar
Zhou, M., Wang, Y., Jiang, H., Li, M., & Li, G. (2023). How leadership influences open government data (OGD)-driven innovation: The mediating role of organizational commitment. Sustainability, 15(2), .Google Scholar
Zuiderwijk, A., Helbig, N., Gil-García, J. R., & Janssen, M. (2014). Special issue on innovation through open data – A review of the state-of-the-art and an emerging research agenda: Guest editors’ introduction. Journal of Theoretical and Applied Electronic Commerce Research, 9(2), 113.CrossRefGoogle Scholar
Zuiderwijk, A., & Janssen, M. (2014). Open data policies, their implementation and impact: A framework for comparison. Government Information Quarterly, 31(1), 1729.CrossRefGoogle Scholar
Zuiderwijk, A., Janssen, M., Poulis, K., & Kaa, G. V. D. (2015). Open data for competitive advantage: Insights from open data use by companies. Proceedings of the 16th Annual International Conference on Digital Government Research, 7988CrossRefGoogle Scholar
Zurada, J., & Karwowski, W. (2011). Knowledge discovery through experiential learning from business and other contemporary data sources: A review and reappraisal. Information Systems Management, 28(3), 258274.CrossRefGoogle Scholar