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The nexus of big data analytics, knowledge sharing, and product innovation in manufacturing

    Bülent Yildiz Affiliation
    ; Şemsettin Çiğdem Affiliation
    ; Ieva Meidutė-Kavaliauskienė Affiliation
    ; Renata Činčikaitė Affiliation

Abstract

In today‘s highly competitive business environments, manufacturers face stiff competition. As digital technologies have become more pervasive, many businesses in the manufacturing sector have begun to tap into the potential of big data analytics to gain an edge in their markets. Companies in the manufacturing sector can gain a significant competitive advantage by strategically utilizing big data analytics to uncover profound insights that have the potential to significantly enhance their capabilities in product innovation.


This research delves into communication’s role as a go-between for big data analytics and product innovations’ success at manufacturing firms. The validity and reliability of the measurement scales were first thoroughly examined in this study. The research model was then tested using structural equation modeling and process macro analysis.


The analytical findings unveil those big data analytics exert a pronounced, positive, and statistically significant impact on product innovation performance and information-sharing dynamics. Furthermore, it is discerned that information-sharing exerts a substantial and affirmative influence on the capacity for product innovation. Additionally, it is established that the impact of big data analytics on product innovation performance undergoes moderation by the information-sharing mechanism.

Keyword : big data analytics, product innovation, information sharing, analytics-driven innovation, data analytics in manufacturing, innovation performance

How to Cite
Yildiz, B., Çiğdem, Şemsettin, Meidutė-Kavaliauskienė, I., & Činčikaitė, R. (2024). The nexus of big data analytics, knowledge sharing, and product innovation in manufacturing. Journal of Business Economics and Management, 25(1), 66–84. https://doi.org/10.3846/jbem.2024.20713
Published in Issue
Jan 26, 2024
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This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Akroush, M. N., & Awwad, A. S. (2018). Enablers of NPD financial performance: The roles of NPD capabilities improvement, NPD knowledge sharing, and NPD internal learning. International Journal of Quality & Reliability Management, 35(1), 163–186. https://doi.org/10.1108/IJQRM-08-2016-0122

Ali, Z. (2023). Investigating information processing paradigm to predict performance in emerging firms: The mediating role of technological innovation. Journal of Business & Industrial Marketing, 38(4), 724–735. https://doi.org/10.1108/JBIM-07-2020-0342

AL-Khatib, A. W. (2022). Intellectual capital and innovation performance: The moderating role of big data analytics: evidence from the banking sector in Jordan. EuroMed Journal of Business, 17(3), 391–423. https://doi.org/10.1108/EMJB-10-2021-0154

Bahrami, M., & Shokouhyar, S. (2021). The role of big data analytics capabilities in bolstering supply chain resilience and firm performance: A dynamic capability view. Information Technology & People, 35(5), 1621–1651. https://doi.org/10.1108/ITP-01-2021-0048

Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173–1182. https://doi.org/10.1037/0022-3514.51.6.1173

Bennett, J. A. (2000). Mediator and moderator variables in nursing research: Conceptual and statistical differences. Research in Nursing & Health, 23(5), 415–420. https://doi.org/10.1002/1098-240X(200010)23:5<415::AID-NUR8>3.0.CO;2-H

Borkovich, D. S., & Noah, P. (2014). Big data in the information age: Exploring the intellectual foundation of communication theory. Information Systems Education Journal, 12(1), 15–26.

Bstieler, L. (2006). Trust formation in collaborative new product development. Journal of Product Innovation Management, 23(1), 56–72. https://doi.org/10.1111/j.1540-5885.2005.00181.x

Calic, G., & Ghasemaghaei, M. (2021). Big data for social benefits: Innovation as a mediator of the relationship between bi g data and corporate social performance. Journal of Business Research, 131, 391–401. https://doi.org/10.1016/j.jbusres.2020.11.003

Capurro, R., Fiorentino, R., Garzella, S., & Giudici, A. (2021). Big data analytics in innovation processes: Which forms of dynamic capabilities should be developed and how to embrace digitization? European Journal of Innovation Management, 25(6), 273–294. https://doi.org/10.1108/EJIM-05-2021-0256

Chen, M., Mao, S., Zhang, Y., & Leung, V. C. M. (2014). Big Data. Springer International Publishing. https://doi.org/10.1007/978-3-319-06245-7

Chen, X., Li, B., Chen, W., & Wu, S. (2021). Influences of information sharing and online recommendations in a supply chain: Reselling versus agency selling. Annals of Operations Research. https://doi.org/10.1007/s10479-021-03968-7

Cherian, E. J. (2007). The impact of organizational structure on interorganizational information sharing during crisis response. In B. VandeWalle, X. Li, & S. Zhang (Eds.), ISCRAM China 2007: Proceedings of the 2nd International Workshop on Information Systems for Crisis Response and Management (pp. 451–454). Harbin Engineering University. China. https://www.webofscience.com/wos/woscc/full-record/WOS:000250334100085

Chierici, R., Mazzucchelli, A., Garcia-Perez, A., & Vrontis, D. (2019). Transforming big data into knowledge: The role of knowledge management practice. Management Decision, 57(8), 1902–1922. https://doi.org/10.1108/MD-07-2018-0834

Contreras Pinochet, L. H., Amorim, G. de C. B., Lucas Júnior, D., & Souza, C. A. de. (2021). Consequential factors of Big Data’s Analytics Capability: How firms use data in the competitive scenario. Journal of Enterprise Information Management, 34(5), 1406–1428. https://doi.org/10.1108/JEIM-11-2020-0445

Elgendy, N., & Elragal, A. (2014). Big data analytics: A literature review paper. In P. Perner (Ed.), Lecture notes in computer science: Vol. 8557. Advances in data mining. Applications and theoretical aspects (pp. 214–227). Springer International Publishing. https://doi.org/10.1007/978-3-319-08976-8_16

Fayyaz, A., Chaudhry, B. N., & Fiaz, M. (2021). Upholding knowledge sharing for organization innovation efficiency in Pakistan. Journal of Open Innovation: Technology, Market, and Complexity, 7(1), Article 4. https://doi.org/10.3390/joitmc7010004

Fernando, Y., Chidambaram, R. R. M., & Wahyuni-TD, I. S. (2018). The impact of Big Data analytics and data security practices on service supply chain performance. Benchmarking: An International Journal, 25(9), 4009–4034. https://doi.org/10.1108/BIJ-07-2017-0194

Field, A. (2017). Discovering statistics using IBM SPSS statistics (5th ed.). SAGE Publications.

Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3), 382–388. https://doi.org/10.1177/002224378101800313

Fritz, M. S., & MacKinnon, D. P. (2007). Required sample size to detect the mediated effect. Psychological Science, 18(3), 233–239. https://doi.org/10.1111/j.1467-9280.2007.01882.x

Gandomi, A., & Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management, 35(2), 137–144. https://doi.org/10.1016/j.ijinfomgt.2014.10.007

Gonzalez-Zapatero, C., Gonzalez-Benito, J., & Lannelongue, G. (2016). Antecedents of functional integration during new product development: The purchasing–marketing link. Industrial Marketing Management, 52, 47–59. https://doi.org/10.1016/j.indmarman.2015.07.015

Gürsakal, N. (2017). Büyük Veri. Dora Yayincilik.

Hader, M., Tchoffa, D., Mhamedi, A. E., Ghodous, P., Dolgui, A., & Abouabdellah, A. (2022). Applying integrated Blockchain and Big Data technologies to improve supply chain traceability and information sharing in the textile sector. Journal of Industrial Information Integration, 28, Article 100345. https://doi.org/10.1016/j.jii.2022.100345

Hair, J., Anderson, R., Black, B., & Babin, B. (2016). Multivariate data analysis (7th ed.). Pearson Education.

Hayes, A. F. (2017). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach (2 ed.). Guilford Publications.

Hoch, J. E. (2014). Shared leadership, diversity, and information sharing in teams. Journal of Managerial Psychology, 29(5), 541–564. https://doi.org/10.1108/JMP-02-2012-0053

Hsu, C., Kannan, V. R., Tan, K., & Keong Leong, G. (2008). Information sharing, buyer‐supplier relationships, and firm performance: A multi‐region analysis. International Journal of Physical Distribution & Logistics Management, 38(4), 296–310. https://doi.org/10.1108/09600030810875391

Hu, D., Li, Y., Pan, L., Li, M., & Zheng, S. (2021). A blockchain-based trading system for big data. Computer Networks, 191, Article 107994. https://doi.org/10.1016/j.comnet.2021.107994

Huo, B., Ul Haq, M. Z., & Gu, M. (2021). The impact of information sharing on supply chain learning and flexibility performance. International Journal of Production Research, 59(5), 1411–1434. https://doi.org/10.1080/00207543.2020.1824082

Intezari, A., & Gressel, S. (2017). Information and reformation in KM systems: Big data and strategic decision-making. Journal of Knowledge Management, 21(1), 71–91. https://doi.org/10.1108/JKM-07-2015-0293

Janssen, M., van der Voort, H., & Wahyudi, A. (2017). Factors influencing big data decision-making quality. Journal of Business Research, 70, 338–345. https://doi.org/10.1016/j.jbusres.2016.08.007

Jiaxi, W. (2009, November). The impact of inter-organizational relationship on new product development performance with the intermediate role of information sharing. In 2009 Fourth International Conference on Cooperation and Promotion of Information Resources in Science and Technology (pp. 285–289). Beijing, China. IEEE. https://doi.org/10.1109/COINFO.2009.47

Kache, F., & Seuring, S. (2017). Challenges and opportunities of digital information at the intersection of Big Data Analytics and supply chain management. International Journal of Operations & Production Management, 37(1), 10–36. https://doi.org/10.1108/IJOPM-02-2015-0078

Kalyvas, J. R., & Albertson, D. R. (2015). A big data primer for executives. In J. R. Kalyvas & M. R. Overly, Big data: A business and legal guide (pp. 1–10). CRC Press.

Keszey, T. (2018). Boundary spanners’ knowledge sharing for innovation success in turbulent times. Journal of Knowledge Management, 22(5), 1061–1081. https://doi.org/10.1108/JKM-01-2017-0033

Kulangara, N. P., Jackson, S. A., & Prater, E. (2016). Examining the impact of socialization and information sharing and the mediating effect of trust on innovation capability. International Journal of Operations & Production Management, 36(11), 1601–1624. https://doi.org/10.1108/IJOPM-09-2015-0558

Le, C. T. D., Pakurár, M., Kun, I. A., & Oláh, J. (2021). The impact of factors on information sharing: An application of meta-analysis. PLoS ONE, 16(12), Article e0260653. https://doi.org/10.1371/journal.pone.0260653

Liao, Y., & Li, Y. (2019), Complementarity effect of supply chain competencies on innovation capability. Business Process Management Journal, 25(6), 1251–1272. https://doi.org/10.1108/BPMJ-04-2018-0115

Liedong, T. A., Rajwani, T., & Lawton, T. C. (2020). Information and nonmarket strategy: Conceptualizing the interrelationship between big data and corporate political activity. Technological Forecasting and Social Change, 157, Article 120039. https://doi.org/10.1016/j.techfore.2020.120039

Lin, C., Kunnathur, A., & Forrest, J. (2022). Supply chain dynamics, big data capability and product performance. American Journal of Business, 37(2), 53–75. https://doi.org/10.1108/AJB-08-2020-0136

Lin, M. J., & Chen, C. (2008). Integration and knowledge sharing: Transforming to long‐term competitive advantage. International Journal of Organizational Analysis, 16(1/2), 83–108. https://doi.org/10.1108/19348830810915514

Lin, R., Che, R., & Ting, C. (2012). Turning knowledge management into innovation in the high‐tech industry. Industrial Management & Data Systems, 112(1), 42–63. https://doi.org/10.1108/02635571211193635

Liu, S., & Wang, H. (2018). Analysis of supply chain collaboration with big data suppliers participating in competition. In J. Xu, M. Gen, A. Hajiyev, & F. L. Cooke (Eds.), Proceedings of the Eleventh International Conference on Management Science and Engineering Management (pp. 998–1006). Springer International Publishing. https://doi.org/10.1007/978-3-319-59280-0_82

MacKinnon, D. P., Krull, J. L., & Lockwood, C. (2000). Equivalence of the mediation, confounding and suppression effect. Prevention Science, 1(4), 173–181. https://doi.org/10.1023/A:1026595011371

Makkonen, H., Pohjola, M., Olkkonen, R., & Koponen, A. (2014). Dynamic capabilities and firm performance in a financial crisis. Journal of Business Research, 67(1), 2707–2719. https://doi.org/10.1016/j.jbusres.2013.03.020

Maras, M.-H. (2017). Overcoming the intelligence-sharing paradox: Improving information sharing through change in organizational culture. Comparative Strategy, 36(3), 187–197. https://doi.org/10.1080/01495933.2017.1338477

Markovic, S., & Bagherzadeh, M. (2018). How does breadth of external stakeholder co-creation influence innovation performance? Analyzing the mediating roles of knowledge sharing and product innovation. Journal of Business Research, 88, 173–186. https://doi.org/10.1016/j.jbusres.2018.03.028

McAfee, A., Brynjolfsson, E., Davenport, T. H., Patil, D. J., & Barton, D. (2012). Big data: The management revolution. Harvard Business Review, 90(10), 60–68.

Mikalef, P., Boura, M., Lekakos, G., & Krogstie, J. (2020). The role of information governance in big data analytics driven innovation. Information & Management, 57(7), Article 103361. https://doi.org/10.1016/j.im.2020.103361

Morimura, F., & Sakagawa, Y. (2023). The intermediating role of big data analytics capability between responsive and proactive market orientations and firm performance in the retail industry. Journal of Retailing and Consumer Services, 71, Article 103193. https://doi.org/10.1016/j.jretconser.2022.103193

Munir, S., Abdul Rasid, S. Z., Aamir, M., Jamil, F., & Ahmed, I. (2023). Big data analytics capabilities and innovation effect of dynamic capabilities, organizational culture and role of management accountants. Foresight, 25(1), 41–66. https://doi.org/10.1108/FS-08-2021-0161

Najafi Tavani, S., Sharifi, H., Soleimanof, S., & Najmi, M. (2013). An empirical study of firm’s absorptive capacity dimensions, supplier involvement and new product development performance. International Journal of Production Research, 51(11), 3385–3403. https://doi.org/10.1080/00207543.2013.774480

Najafi-Tavani, S., Najafi-Tavani, Z., Naudé, P., Oghazi, P., & Zeynaloo, E. (2018). How collaborative innovation networks affect new product performance: Product innovation capability, process innovation capability, and absorptive capacity. Industrial Marketing Management, 73, 193–205. https://doi.org/10.1016/j.indmarman.2018.02.009

Perks, H. (2000). Marketing information exchange mechanisms in collaborative new product development: The influence of resource balance and competitiveness. Industrial Marketing Management, 29(2), 179–189. https://doi.org/10.1016/S0019-8501(99)00074-7

Ragatz, G. L., Handfield, R. B., & Petersen, K. J. (2002). Benefits associated with supplier integration into new product development under conditions of technology uncertainty. Journal of Business Research, 55(5), 389–400. https://doi.org/10.1016/S0148-2963(00)00158-2

Raman, S., Patwa, N., Niranjan, I., Ranjan, U., Moorthy, K., & Mehta, A. (2018). Impact of big data on supply chain management. International Journal of Logistics Research and Applications, 21(6), 579–596. https://doi.org/10.1080/13675567.2018.1459523

Sagiroglu, S., & Sinanc, D. (2013, May). Big data: A review. In 2013 International Conference on Collaboration Technologies and Systems (CTS) (pp. 42–47). San Diego. IEEE. https://doi.org/10.1109/CTS.2013.6567202

Şahin, H., & Topal, B. (2019). Examination of effect of information sharing on businesses performance in the supply chain process. International Journal of Production Research, 57(3), 815–828. https://doi.org/10.1080/00207543.2018.1484954

Saleem, H., Li, Y., Ali, Z., Ayyoub, M., Wang, Y., & Mehreen, A. (2021). Big data use and its outcomes in supply chain context: The roles of information sharing and technological innovation. Journal of Enterprise Information Management, 34(4), 1121–1143. https://doi.org/10.1108/JEIM-03-2020-0119

Slater, S. F., Mohr, J. J., & Sengupta, S. (2014). Radical product innovation capability: Literature review, synthesis, and illustrative research propositions. Journal of Product Innovation Management, 31(3), 552–566. https://doi.org/10.1111/jpim.12113

Su, X., Zeng, W., Zheng, M., Jiang, X., Lin, W., & Xu, A. (2022). Big data analytics capabilities and organizational performance: The mediating effect of dual innovations. European Journal of Innovation Management, 25(4), 1142–1160. https://doi.org/10.1108/EJIM-10-2020-0431

Sun, B., & Liu, Y. (2021). Business model designs, big data analytics capabilities and new product development performance: Evidence from China. European Journal of Innovation Management, 24(4), 1162–1183. https://doi.org/10.1108/EJIM-01-2020-0004

Swink, M., & Song, M. (2007). Effects of marketing-manufacturing integration on new product development time and competitive advantage. Journal of Operations Management, 25(1), 203–217. https://doi.org/10.1016/j.jom.2006.03.001

Szczepańska-Woszczyna, K. (2015). Leadership and organizational culture as the normative influence of top management on employee’s behaviour in the innovation process. Procedia Economics and Finance, 34, 396–402. https://doi.org/10.1016/S2212-5671(15)01646-9

Thomas, E. (2013). Supplier integration in new product development: Computer mediated communication, knowledge exchange and buyer performance. Industrial Marketing Management, 42(6), 890–899. https://doi.org/10.1016/j.indmarman.2013.05.018

Tian, X. (2017). Big data and knowledge management: A case of déjà vu or back to the future? Journal of Knowledge Management, 21(1), 113–131. https://doi.org/10.1108/JKM-07-2015-0277

Tsang, Y. P., Wu, C. H., Lin, K.-Y., Tse, Y. K., Ho, G. T. S., & Lee, C. K. M. (2022). Unlocking the power of big data analytics in new product development: An intelligent product design framework in the furniture industry. Journal of Manufacturing Systems, 62, 777–791. https://doi.org/10.1016/j.jmsy.2021.02.003

Tunc-Abubakar, T., Kalkan, A., & Abubakar, A. M. (2023). Impact of big data usage on product and process innovation: The role of data diagnosticity. Kybernetes, 52(9), 3178–3196. https://doi.org/10.1108/K-11-2021-1138

Vázquez-Casielles, R., Iglesias, V., & Varela-Neira, C. (2013). Collaborative manufacturer-distributor relationships: The role of governance, information sharing and creativity. Journal of Business & Industrial Marketing, 28(8), 620–637. https://doi.org/10.1108/JBIM-05-2011-0070

Wamba, S. F., Dubey, R., Gunasekaran, A., & Akter, S. (2020). The performance effects of big data analytics and supply chain ambidexterity: The moderating effect of environmental dynamism. International Journal of Production Economics, 222, Article 107498. https://doi.org/10.1016/j.ijpe.2019.09.019

Wan, W., & Liu, L. (2021). Intrapreneurship in the digital era: Driven by big data and human resource management? Chinese Management Studies, 15(4), 843–875. https://doi.org/10.1108/CMS-07-2020-0282

Wang, Z., Wang, T., Hu, H., Gong, J., Ren, X., & Xiao, Q. (2020). Blockchain-based framework for improving supply chain traceability and information sharing in precast construction. Automation in Construction, 111, Article 103063. https://doi.org/10.1016/j.autcon.2019.103063

Ye, L., Pan, S. L., Wang, J., Wu, J., & Dong, X. (2021). Big data analytics for sustainable cities: An information triangulation study of hazardous materials transportation. Journal of Business Research, 128, 381–390. https://doi.org/10.1016/j.jbusres.2021.01.057

Yin, S., & Kaynak, O. (2015). Big data for modern industry: Challenges and trends [Point of View]. Proceedings of the IEEE, 103(2), 143–146. https://doi.org/10.1109/JPROC.2015.2388958

Zhan, Y., Tan, K. H., Ji, G., Chung, L., & Tseng, M. (2017). A big data framework for facilitating product innovation processes. Business Process Management Journal, 23(3), 518–536. https://doi.org/10.1108/BPMJ-11-2015-0157

Zhou, H., & Benton, W. C. (2007). Supply chain practice and information sharing. Journal of Operations Management, 25(6), 1348–1365. https://doi.org/10.1016/j.jom.2007.01.009