Crowdsourcing for business strategy and sustainability: a partial least square structural equation model
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- Category: Content №3 2023
- Last Updated on 27 June 2023
- Published on 30 November -0001
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Authors:
M.M.Mia, orcid.org/0000-0001-9032-3302, Daffodil International University, Dhaka, the People’s Republic of Bangladesh, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
M.F.Shamsudin, orcid.org/0000-0002-6005-6423, Unikl Business School, Universiti Kuala Lumpur, Kuala Lumpur, Malaysia, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
N.M.Zayed*, orcid.org/0000-0001-7519-6552, Daffodil International University, Dhaka, the People’s Republic of Bangladesh, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
T.V.Mirzoieva, orcid.org/0000-0002-0034-6138, National University of Life and Environmental Sciences of Ukraine, Kyiv, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
I.Yu.Shtuler, orcid.org/0000-0002-0852-8526, National Academy of Management, Kyiv, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
O.S.Bogma, orcid.org/0000-0002-5637-6010, State University of Trade and Economics, Kyiv, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
* Corresponding author e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2023, (3): 184 - 193
https://doi.org/10.33271/nvngu/2023-3/184
Abstract:
Purpose. The goal of this research was to scrutinize how business strategy helps to increase business sustainability by considering the roles of quadratic effects and students’ Innovation in the formation of business. It is worthwhile to investigate the role of partial least square structural equation modeling (PLS-SEM) in crowdsourcing business strategy approaches toward sustainability.
Methodology. To attain these goals, we conducted quantitative research, which included first-order by three dimensions of business strategy for the analyzed reflective model. In order to gather quantitative data and identify the predictor factors that affect the sustainability associated with the quadratic effects, a thorough exploratory PLS-SEM strategy was applied.
Findings. The participants (N = 218) studying at Daffodil International University (DIU) in Bangladesh took part in the online survey. The findings indicate that DIU students’ intention for businesses strategy is conscious of the potential changes, and that they have begun to build internal processes geared toward sustainability. Also, the first-order constructs are the selection of environment, long-term behavior, and strategical involvements management resources into business strategies which have a positive correlation with the significant impact on business sustainability. While business strategy contributed to the formation of an innovative sustainability model, the presence of a linear effect and a positive parabolic effect was statistically significant. Finally, business strategy has a favorable impact on sustainability with both linear and parabolic effects.
Originality. Business strategy is proved to have contributed to forming an innovative model of sustainability, having a linear effect and a positive parabola effect as statistically significant. As a result, business strategy has a beneficial impact on sustainability, with both linear and parabolic effects. These findings have ramifications for how potential entrepreneurs handle their businesses in order to improve sustainability.
Practical value. The results show that business strategy is essential for aspiring entrepreneurs to increase creativity and efficiency in the direction of sustainability.
Keywords: crowdsourcing, business strategy, sustainability, structural equation modeling
References.
1. Hisrich, R. D., & Ramadani, V. (2017). Effective Entrepreneurial Management: Strategy, Planning, Risk Management, and Organization. Springer. https://doi.org/10.1007/978-3-319-50467-4.
2. Cappa, F., Rosso, F., & Hayes, D. (2019). Monetary and social rewards for crowdsourcing. Sustain., 11(10). https://doi.org/10.3390/su11102834.
3. Garrigos-Simon, F. J., Alizadeh Moghadam, S. S., Abdi, L., Pourmirali, Z., & Abdi, B. (2021). Digital Entrepreneurship Dimensions and Strategies: Crowdsourcing and Digital Financing. European Journal of Studies in Management and Business, 18, 1-15. https://doi.org/10.32038/mbrq.2021.18.01.
4. Franzoni, C., & Sauermann, H. (2014). Crowd science: The organization of scientific research in open collaborative projects. Research Policy, 43(1), 1-20. https://doi.org/10.1016/j.respol.2013.07.005.
5. Natalicchio, A., Messeni Petruzzelli, A., & Garavelli, A. C. (2017). Innovation problems and search for solutions in crowdsourcing platforms – A simulation approach. Technovation, 64-65, 28-42. https://doi.org/10.1016/j.technovation.2017.05.002.
6. Gans, J. S., Stern, S., & Wu, J. (2019). Foundations of entrepreneurial strategy. Strategic Management Journal, 40(5), 736-756. https://doi.org/10.1002/smj.3010.
7. Lechner, C., & Gudmundsson, S. V. (2014). Entrepreneurial orientation, firm strategy and small firm performance. International Small Business Journal, 32(1), 36-60. https://doi.org/10.1177/0266242612455034.
8. Piazza, M., Mazzola, E., Acur, N., & Perrone, G. (2019). Governance Considerations for Seeker–Solver Relationships: A Knowledge-Based Perspective in Crowdsourcing for Innovation Contests. British Journal of Management, 30(4), 810-828. https://doi.org/10.1111/1467-8551.12327.
9. Hair, J. F., Sarstedt, M., Ringle, C. M., & Gudergan, S. P. (2021). Advanced issues in partial least squares structural equation modeling (PLS-SEM). Sage: Thousand Oaks. Retrieved from https://www.researchgate.net/publication/317400451_Advanced_Issues_in_Partial_Least_Squares_Structural_Equation_Modeling#fullTextFileContent.
10. Wegner, D., Thomas, E., Teixeira, E. K., & Maehler, A. E. (2020). University entrepreneurial push strategy and students’ entrepreneurial intention. International Journal of Entrepreneurial Behavior & Research, 26(2), 307-325. https://doi.org/10.1108/IJEBR-10-2018-0648.
11. Sakas, D. P., & Giannakopoulos, N. T. (2020). Harvesting crowdsourcing platforms’ traffic in favour of air forwarders’ brand name and sustainability. Sustainability, 13(15). https://doi.org/10.3390/su13158222.
12. Thuan, N. H., Antunes, P., & Johnstone, D. (2017). A process model for establishing business process crowdsourcing. Australian Journal of Information Systems, 21. https://doi.org/10.3127/ajis.v21i0.1392.
13. Kohler, T. (2018). How to Scale Crowdsourcing Platforms. California Management Review, 60(2), 98-121. https://doi.org/10.1177/0008125617738261.
14. Aydiner, A. S., Tatoglu, E., Bayraktar, E., Zaim, S., & Delen, D. (2019). Business analytics and firm performance: The mediating role of business process performance. Journal of Business Research, 96, 228-237. https://doi.org/10.1016/j.jbusres.2018.11.028.
15. Lopes, C. M., Scavarda, A., Hofmeister, L. F., Thomé, A. M. T., & Vaccaro, G. L. R. (2017). An analysis of the interplay between organizational sustainability, knowledge management, and open innovation. Journal of Cleaner Production, 142, 476-488. https://doi.org/10.1016/j.jclepro.2016.10.083.
16. Mia, M. M., Rizwan, S., Zayed, N. M., Nitsenko, V., Miroshnyk, O., Kryshtal, H., & Ostapenko, R. (2022). The Impact of Green Entrepreneurship on Social Change and Factors Influencing AMO Theory. Systems, 10(5), 132. https://doi.org/10.3390/systems10050132.
17. Mia, M. M., Zayed, N. M., Islam, K. M. A., Nitsenko, V., Matusevych, T., & Mordous, I. (2022). The Strategy of Factors Influencing Learning Satisfaction Explored by First and Second-Order Structural Equation Modeling (SEM). Inventions, 7(3), 59. https://doi.org/10.3390/inventions7030059.
18. Gelman, A., Goodrich, B., Gabry, J., & Vehtari, A. (2019). R-squared for Bayesian Regression Models. The American Statistician, 73(3), 307-309. https://doi.org/10.1080/00031305.2018.1549100.
19. Barrett, G. B. (2020). The Coefficient of Determination: Understanding r squared and R squared. The Mathematics Teacher, 93(3), 230-234. https://doi.org/10.5951/mt.93.3.0230.
20. Dijkstra, T. K., & Henseler, J. (2015). Consistent partial least squares path modeling. MIS Quarterly, 39(2), 297-316.
21. Cho, E., & Kim, S. (2015). Cronbach’s Coefficient Alpha. Organizational Research Methods, 18(2), 207-230. https://doi.org/10.1177/1094428114555994.
22. Hair Jr., J. F., Matthews, L. M., Matthews, R. L., & Sarstedt, M. (2017). PLS-SEM or CB-SEM: updated guidelines on which method to use. International Journal of Multivariate Data Analysis, 1(2), 107. https://doi.org/10.1504/ijmda.2017.10008574.
23. Rifai, A., & Hasan, B. (2016). Exploring user expectancy with regard to the use of institutional repositories among university academics in Indonesia: A case study at Syarif Hidayatullah State Islamic University. Library Philosophy and Practice, 1, 1-16.
24. 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.
25. Evermann, J., & Tate, M. (2016). Assessing the predictive performance of structural equation model estimators. Journal of Business Research, 69(10), 4565-4582. https://doi.org/10.1016/j.jbusres.2016.03.050.
26. Joseph, M. S., Hair, Jr. H., Hult, T. M., & Ringle, C. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Thousand Oaks (3 rd ed.). Retrieved from https://library.oapen.org/bitstream/handle/20.500.12657/51463/1/9783030805197.pdf.