The Impact of Cross-Sector Collaboration on F&B Micro Business Revenue through Ecosystem Orchestration and Innovation

Pristanto Ria Irawan

doi:10.55927/ijis.v4i9.567

Authors

Pristanto Ria Irawan Philippine Womens’ University

DOI:

https://doi.org/10.55927/ijis.v4i9.567

Keywords:

Cross-Sector Collaboration, Micro-Business Revenue, Ecosystem Orchestration, Innovation Capability

Abstract

This study seeks to examine the impact of cross-sector collaboration on the revenue of micro-food and beverage (F&B) enterprises, utilizing ecosystem orchestration and innovation skills as mediating variables. Micro-food and beverage (F&B) firms are important to the Indonesian economy, but they have a lot of competition, few resources, and limited access to markets. People think that working together across sectors is a good way to get support, networks, and new ideas.The research employed an explanatory design alongside a quantitative methodology. A pu rposive sample questionnaire survey was utilized to gather data from 300 proprietors of food and beverage microbusinesses in the Koja Subdistrict of North Jakarta. We used Structural Equation Modeling-Partial Least Squares (SEM-PLS) to look at the data more closely. Cross-sector collaboration has a big effect on microbusiness income, innovation capacity, and ecosystem orchestration, according to this study. Ecosystem orchestration has little effect on revenue, while innovation capability has no direct consequence. Ecosystem orchestration does not significantly mediate the impact of cross-sector collaboration on revenue, whereas innovation capabilities does. These results show how important it is for enterprises in different sectors to work together to help microbusinesses make more money by improving innovation and ecosystem coordination

References

Alfarobi, M. N., & Hartono, A. (2022). The effect of open innovation on innovation performance in SMEs in Indonesia. EKOMBIS Review: Journal of Economics and Business, 10(2), 1149–1158. https://doi.org/10.37676/ekombis.v10i2.2231

Ansell, C., & Gash, A. (2018). Collaborative platforms as a governance strategy. Journal of Public Administration Research and Theory, 28(1), 16-32. https://doi.org/10.1016/j.respol.2017.10.016

Audretsch, D. B., Belitski, M., Caiazza, R., & Phan, P. (2023). Collaboration strategies and SME innovation performance. Journal of Business Research, 164, 114018. DOI: 10.1016/j.jbusres.2023.114018

Battistella, C., & Attanasio, G. (2025). Circular innovation ecosystem orchestrators: A capabilities-as-routines-bundles framework. Technological Forecasting and Social Change, 182, 2524517. https://doi.org/10.1080/13662716.2025.2524517

Chin, W. W. (1998). The partial least squares approach for structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295–336). Mahwah, NJ: Lawrence Erlbaum Associates

Dzhengiz, T., & Patala, S. (2024). The role of cross‐sector partnerships in the dynamics between places and innovation ecosystems. R&D Management, 54(2), 370–397. https://doi.org/10.1111/radm.12589

Dzhengiz, T., & Patala, S. (2025). The role of cross-sector partnerships in the dynamics between places and innovation ecosystems. R&D Management, 55(1), 145–162. https://doi.org/10.1111/radm.12758

Florek-Paszkowska, A., & Ujwary-Gil, A. (2025). The digital-sustainability ecosystem: A conceptual framework for digital transformation and sustainable innovation. Journal of Entrepreneurship, Management and Innovation, 21(2), 27–49. https://doi.org/10.7341/20252127

Gupta, S., Joshi, D., Jagtap, S. et al.(2025) Unveiling the role of stakeholder involvement for digital transformation of Indian food SMEs. Discover Food, Vol. 5, Article 210. DOI: 10.1007/s44187-025-00510-7

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2021). A primer on partial least squares structural equation modeling (PLS-SEM) (3rd ed.). Thousand Oaks, CA: Sage Publications

Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8

Kusumaningrum, A., et al. (2024). The Role of Maritime Intelligence Agency in Fostering the Basics of National Maritime Resilience in Indonesia. Indonesian Journal of Social Science Research, 5(1), 50-60. https://doi.org/10.11594/ijssr.05.01.06

Klein, M., & Spychalska-Wojtkiewicz, M. (2020). Cross-sector partnerships for innovation and growth: Can creative industries support traditional sector innovations? Sustainability, 12(23), 10122. https://doi.org/10.3390/su122310122

Kuan, J., & West, J. (2023). How DARPA modularized the semiconductor ecosystem. Research Policy, 52(8), 104789. https://doi.org/10.1016/j.respol.2023.104789

Lachowicz, M. J., Preacher, K. J., & Kelley, K. (2018). A novel measure of effect size for mediation analysis. Psychological Methods, 23(2), 244–261. https://doi.org/10.1037/met0000165

Lingens, B., & Huber, F. (2023). Heading the orchestra of innovation: How firms align partners in ecosystems. Innovation, 25(3), 257–281. https://doi.org/10.1080/14479338.2021.2016418

Liu, X., Wang, J., & Luo, Y. (2025). Acceptance and Use of Technology on Digital Learning Resource Utilization and Digital Literacy Among Chinese Engineering Students: A Longitudinal Study Based on the UTAUT2 Model. Behavioral Sciences, 15(6), 728. https://doi.org/10.3390/bs15060728

Long, T. B., Blok, V., & Coninx, A. (2023). Collaborative innovation in times of crisis: A case study of the Dutch hospitality sector. Technological Forecasting and Social Change, 194, 122713. https://doi.org/10.1016/j.techfore.2023.122713.

Mayr, P. (2022). Editorial to the special issue on JCDL 2022. International Journal on Digital Libraries, 25(3), 237–240. https://doi.org/10.1007/s00799-024-00407-3

Merín-Rodrigáñez, J., Alegre, J., & Dasí, À. (2025). International entrepreneurship in innovative SMEs: Examining the connection between CEOs’ dynamic managerial capabilities, business model innovation and export performance. International Business Review, 34(2). https://doi.org/10.1016/j.ibusrev.2024.10232 1

Rahman, A., Syamsun, M., & Maulana, A. (2021). Agrifood value chain assessment in developing countries: A case of Indonesia’s cashew sector. E3S Web of Conferences, 306, 02045. https://doi.org/10.1051/e3sconf/202130602045

Robbiano, S. (2022). The innovative impact of public research institutes: Evidence from Italy. Research Policy, 51(10), 104567. https://doi.org/10.1016/j.respol.2022.104567

Sarstedt, M., Ringle, C. M., & Hair, J. F. (2019). Treating unobserved heterogeneity in PLS-SEM: A multigroup analysis approach. MIS Quarterly, 43(3), 801–826. https://doi.org/10.25300/MISQ/2019/15198

Scuotto, A., Magni, A., Del Giudice, M., & Papa, F. (2023). Open innovation and SME performance: The mediating role of innovation capability. Journal of Business Research, 168, 4236. https://doi.org/10.1016/j.jbusres.2023.114236

Saunila, M. (2020). Innovation capability in SMEs: a systematic review of the literature. Journal of Innovation & Knowledge, 5(4), 260-265. DOI: 10.1016/j.jik.2019.11.002

Semanjski, I., & Gautama, S. (2019). Smart city mobility application — Gradient boosting trees for mobility prediction and analysis based on crowdsourced data. Sensors, 19(2), 1189. https://doi.org/10.3390/s19051189

Shen, L., Shi, Q., Parida, V., & Jovanovic, M. (2024). Ecosystem orchestration practices for industrial firms: A qualitative meta-analysis, framework development, and research agenda. Journal of Business Research, 173, 113–126. https://doi.org/10.1016/j.jbusres.2023.12.016

Singh, S., Kaur, R., & Dana, L.-P. (2024). Partial least squares structural equation modeling: An application to women entrepreneurship research. In Building Sustainable Business Models in Digital Spaces, Case Studies, and Experiences (pp. 109-123). CRC Press

Shen, L., Shi, Q., Parida, V., & Jovanovic, M. (2024). Ecosystem orchestration practices for industrial firms. Journal of Business Research, 182, 101122. https://doi.org/10.1016/j.jbrese.2023.101122

Sipos, G. L., & Ionescu, A. (2024). Sustainable development through eco-innovation. Empirical evidence from the EU-27 member states. Journal of Business Economics and Management, 25(4), 809-827. https://doi.org/10.3846/jbem.2024.22037

Sultana, N., & Turkina, E. (2023). Collaboration for sustainable innovation ecosystem: The role of intermediaries. Sustainability, 15(10), 7754. https://doi.org/10.3390/su15107754

Tambunan, T. T. H. (2019). UMKM di Indonesia: Perkembangan, kendala, dan tantangan. Jakarta: LP3ES.

Yamin, S. (2022). Partial Least Squares Path Modeling (PLS-PM) dengan SmartPLS. Jakarta: Salemba Empat.

Wetzels, M., Odekerken-Schröder, G., & van Oppen, C. (2009). Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration. MIS Quarterly, 33(1), 177–195. https://doi.org/10.2307/20650284

Zastempowski, M. (2022). What Shapes Innovation Capability in Micro-Enterprises? New-to-the-Market Product and Process Perspective. Journal of Open Innovation: Technology, Market, and Complexity, 8(1), 59. DOI: 10.3390/joitmc8010059

Zhang, Y., & Li, X. (2022). A study on financial risk early warning and factor hierarchy of middle-aged and elderly households in China—Identification and reconstruction based on the Chinese context. Northwest Population, 43(1), 15–27