Generational and Socio-Cultural Effects on Algorithmic Mastery in Denpasar Creative Industry Actors

Authors

  • Mahadhika Feryo Gotama Universitas Pendidikan Nasional, Indonesia
  • Nyoman Sri Subawa Universitas Pendidikan Nasional, Indonesia https://orcid.org/0000-0001-5837-4863

DOI:

https://doi.org/10.59653/jbmed.v4i02.2468

Keywords:

Algorithm mastery, creative industry, digital lifestyle, generational cohort, socio-cultural factors

Abstract

This study analyzes the influence of demographic and socio-cultural characteristics on social media algorithm understanding among creative industry actors in the Visual Communication Design (VCD) subsector in Denpasar City. Using a quantitative survey approach with 107 respondents selected via purposive sampling from a population of 342 individuals, the study employed Partial Least Squares–Structural Equation Modeling (PLS-SEM) for data analysis. Four independent variables were examined: Generational Cohort (X1), Social Lifestyle (X2), Digital Lifestyle (X3), and Socio-Cultural Environmental Factors (X4), with Social Media Algorithm Mastery (Y) as the dependent variable. Results indicate that the model explains 76.2% of the variance in algorithm mastery (Adjusted R² = 0.762). Hypothesis testing revealed that Digital Lifestyle (t = 2.780; p = 0.005) and Socio-Cultural Environmental Factors (t = 3.342; p = 0.001) have positive and significant effects on Social Media Algorithm Mastery, while Generational Cohort (t = 2.687; p = 0.007) shows a negative and significant effect. Social Lifestyle, however, did not show a significant effect (t = 1.445; p = 0.149). These findings suggest that generational differences, digital activity intensity, and a supportive socio-cultural environment are key determinants of algorithmic mastery among creative entrepreneurs, providing both theoretical contributions to the digital marketing literature and practical implications for enhancing digital capacity in the creative industry sector. This study contributes to the creative economy and digital business literature by demonstrating that socio-cultural environment and digital lifestyle are important determinants of algorithmic capability among creative entrepreneurs in emerging urban economies.

Downloads

Download data is not yet available.

References

Agárdi, I., & Alt, M. A. (2024). Do digital natives use mobile payment differently than digital immigrants? A comparative study between generation X and Z. Electronic Commerce Research, 24(3), 1463–1490. https://doi.org/10.1007/s10660-022-09537-9

Alam, S., Susbiyantoro, S., Yuwantiningrum, S. E., Suwastika, I. W. K., & Muhdaliha, E. (2024). The influence of social media algorithms on consumer behavior: A strategic analysis for brand positioning. The Journal of Academic Science, 1(7), 832–841. https://doi.org/10.59613/nwtd2a57

Alimin, I., & Tukiran, M. (2024). Exploring the efficacy of reward systems for Generation Z and Millennials: A systematic literature review. International Journal of Social and Management Studies, 5(4), 10–20. https://doi.org/10.5555/ijosmas.v5i4.424

Chang, C. W., & Chang, S. H. (2023). The Impact of Digital Disruption: Influences of Digital Media and Social Networks on Forming Digital Natives’ Attitude. SAGE Open, 13(3), 1–10. https://doi.org/10.1177/21582440231191741

Chatterjee, A., Prinz, A., Gerdes, M., & Martinez, S. (2021). Digital interventions on healthy lifestyle management: Systematic review. Journal of Medical Internet Research, 23(11), 1–20. https://doi.org/10.2196/26931

Chaudhary, M., & Biswas, A. (2024). From mindset to market: Unveiling the nexus of cognition, behavior and environment in igniting students’ e-entrepreneurial intentions. International Journal of Educational Management, 38(7), 1839–1861. https://doi.org/10.1108/IJEM-11-2023-0550

Chee, S. Y. (2024). Age-related digital disparities, functional limitations, and social isolation: Unraveling the grey digital divide between baby boomers and the silent generation in senior living facilities. Aging & Mental Health, 28(4), 621–632. https://doi.org/10.1080/13607863.2023.2233454

Choudhary, R., Shaik, Y. A., Yadav, P., & Rashid, A. (2024). Generational differences in technology behavior: A systematic literature review. Journal of Infrastructure, Policy and Development, 8(9), 6755. https://doi.org/10.24294/jipd.v8i9.6755

Conny, C., Zaid, S., Sinarwaty, S., Yusuf, Y., & Nur, N. (2026). Sensory, Behavioral, And Affective Effects on Engagement and Destination Brand Love: A Platform Study. Journal of Business Management and Economic Development, 4(01), 326–342. https://doi.org/10.59653/jbmed.v4i01.2369

Darwisman, S. (2025). From model to interpretation: A comprehensive and critical guide to PLS-SEM implementation in scientific research. Journal Internasional of Management and Business, 1(1), 1–28. https://doi.org/10.5281/zenodo.17387121

De Pelsmacker, P. (2025). Generational cohort theory research: The good, the bad and the ugly. International Journal of Advertising, 44(6), 1148–1170. https://doi.org/10.1080/02650487.2025.2522011

Devasthali, S., Sharma, M., Sharma, A., & Gupta, G. (2025). Technology use across age cohorts in older adults: Review and future directions. Communications of the Association for Information Systems, 57, 745–787. https://doi.org/10.17705/1CAIS.05734

Dharini, M. G. (2025). The algorithmic consumer: How AI shapes desire and decision in digital markets. Global Dimensions of Multidisciplinary Research, 237. https://doi.org/10.25215/9371837764.31

Firmansyah, D., & Saepuloh, D. (2022). Social learning theory: Cognitive and behavioral approaches. Jurnal Ilmiah Pendidikan Holistik (JIPH), 1(3), 297–324. https://doi.org/10.55927/jiph.v1i3.2317

Frishammar, J., Essen, A., Simms, C., Edblad, R., & Hardebro, V. (2022). Older individuals and digital healthcare platforms: Usage motivations and the impact of age on postadoption usage patterns. IEEE Transactions on Engineering Management, 70(8), 2903–2919. https://doi.org/10.1109/TEM.2022.3187792

Giuffrida, M., Jiang, H., & Mangiaracina, R. (2021). Investigating the relationships between uncertainty types and risk management strategies in cross-border e-commerce logistics. International Journal of Logistics Management, 32(4), 1406–1433. https://doi.org/10.1108/IJLM-04-2020-0158

Gran, A. B., Booth, P., & Bucher, T. (2021). To be or not to be algorithm aware: A question of a new digital divide? Information Communication and Society, 24(12), 1779–1796. https://doi.org/10.1080/1369118X.2020.1736124

Hokmabadi, H., Rezvani, S. M. H. S., & Matos, C. A. (2024). Business resilience for small and medium enterprises and startups by digital transformation and the role of marketing capabilities—A systematic review. Systems. https://doi.org/10.3390/systems12060220

Islam, K. F., Awal, A., Mazumder, H., Munni, U. R., Majumder, K., Afroz, K., Tabassum, M. N., & Hossain, M. M. (2023). Social cognitive theory-based health promotion in primary care practice: A scoping review. Heliyon, 9(4), e14889. https://doi.org/10.1016/j.heliyon.2023.e14889

Joseph F. Hair, Jr., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (Third Edit). SAGE Journal.

Judek, J. R. (2024). Willingness to Use Algorithms Varies with Social Information on Weak vs. Strong Adoption: An Experimental Study on Algorithm Aversion. FinTech, 3(1), 55–65. https://doi.org/10.3390/fintech3010004

Kshirsagar, K. P., & Ingle, A. (2025). Impacts of digital technologies across generations. In Bridging academia and industry through cloud integration in education (pp. 1–36). https://doi.org/10.4018/979-8-3693-6705-6.ch001

Kusumawardani, K. A., Widyanto, H. A., & Tambunan, J. E. G. (2023). The role of gamification, social, hedonic and utilitarian values on e-commerce adoption. Spanish Journal of Marketing - ESIC, 27(2), 158–177. https://doi.org/10.1108/SJME-09-2022-0188

Liang, M. (2026). How marketing mechanisms build trust in AI recommendation systems: A serial mediation model in live-streaming commerce. Cogent Business & Management, 13(1). https://doi.org/10.1080/23311975.2026.2658868

Maharani, D., & Wardhana, K. E. (2024). Digitalisasi Sistem Administrasi Sekolah Dengan Pembuatan Website di SD Negeri 001 Loa Kulu. Nusantara Education and Innovation Journal, 1(3), 133–141.

Mahmood, W., Nadeem, R. U., & Masood, I. (2024). Adoption and adaptation: Social media practices among young entrepreneurs. Journal of Development and Social Sciences, 5(2), 623–631. https://doi.org/10.47205/jdss.2024(5-II-S)60

Martín-Rojas, R., Garrido-Moreno, A., & García-Morales, V. J. (2026). Building organizational resilience in SMEs: The key role of digital technologies, transformational leadership, and innovation. Review of Managerial Science. https://doi.org/10.1007/s11846-025-00965-z

Mckercher, B. (2023). Annals of Tourism Research Age or generation? Understanding behaviour differences. Annals of Tourism Research, 103, 103656. https://doi.org/10.1016/j.annals.2023.103656

Metzler, H., & Garcia, D. (2024). Social Drivers and Algorithmic Mechanisms on Digital Media. Perspectives on Psychological Science, 19(5), 735–748. https://doi.org/10.1177/17456916231185057

Mujahidah, N., & Yusdiana, Y. (2023). Application of Albert Bandura’s social-cognitive theories in teaching and learning. Edukasi Islami: Jurnal Pendidikan Islam, 12(2), 2131–2146. https://doi.org/10.30868/ei.v12i02.4585

Nery-da-Silva, G., Henrique de Araujo, M., & de Souza Meirelles, F. (2024). Contributions to the segmentation of e-commerce nonusers: Clustering the reasons not to shop online. Revista de Gestao, 31(2), 201–214. https://doi.org/10.1108/REGE-06-2022-0087

Patiño-Galvan, I., Hernández-Aguilar, J. A., & Vallejo-Trujillo, S. (2021). Development of A Methodology Through Genetic Algorithmst Suggest the Probability of Success of a MSME in Mexico. Journal of Small Business and Entrepreneurship Development, 9(2). https://doi.org/10.15640/jsbed.v9n2a4

Patiro, S. P. S., Budiyanti, H., & Hendarto, K. A. H. (2022). Panic-buying behavior during the COVID-19 pandemic in Indonesia: A social cognitive theoretical model. Gadjah Mada International Journal of Business, 24(1), 25–55. https://doi.org/10.22146/gamaijb.64578

Pellandini-Simányi, L. (2023). Algorithmic classifications in credit marketing: How marketing shapes inequalities. Marketing Theory, 24(2), 211–232. https://doi.org/10.1177/14705931231160828

Prihatna, K. A., So, I. G., Saroso, H., & Abdinagoro, S. B. (2024). The role of creativity in mediating absorptive capacity and human capital to increase product innovation in creative industry MSMEs. WSEAS Transactions on Business and Economics, 21, 317–327. https://doi.org/10.37394/23207.2024.21.28

Rahmayanti, A. P., & Kencana, W. H. (2025). Analisis Perilaku Generasi X Dan Generasi Z Dalam Pemanfaatan Penggunaan E- Wallet Gopay. IKRAITH-HUMANIORA: Jurnal Sosial Dan Humaniora, 9(1), 93–118. https://doi.org/https://doi.org/10.37817/ikraith-humaniora.v9i1.4211

Riswandi, R., Permadi, I., Zainnudin Hamidi, D., & Tinggi Ilmu Ekonomi PGRI Sukabumi, S. (2021). Kesiapan Teknologi Pelaku Umkm Dalam Adopsi E-Commarce: Karateristik Demografi. Jurnal Ilmiah MEA (Manajemen, Ekonomi, Dan Akuntansi), 5(3), 1488–1501.

Rumjaun, A., & Narod, F. (2025). Social learning theory—Albert Bandura. In Science Education in Theory and Practice. https://doi.org/10.1007/978-3-031-81351-1_5

Saleh, Y., & Nurhilalia, N. (2025). Thriving through turbulence: How young entrepreneurs leverage marketing strategies to navigate crises and digital disruption. Golden Ratio of Mapping Idea and Literature Format, 5(2), 132–140. https://doi.org/10.52970/grmilf.v5i2.1536

Saputra, K., Muhammad, S., & Agung, A. (2024). Systematic Literature Review of Understanding Social Media Algorithms and Their Impacts on Online Experiences. https://doi.org/10.4108/eai.25-10-2023.2348715

Saura, J. R., Ratten, V., & Jeremic, V. (2026). Digital cognition in predictive marketing personalization: A conceptual framework. Psychology & Marketing, 43, 1228–1260. https://doi.org/10.1002/mar.70109

Sharma, V., Bray, K. E., Kumar, N., & Grinter, R. E. (2022). Romancing the algorithm: Navigating constantly, frequently, and silently changing algorithms for digital work. Proceedings of the ACM on Human-Computer Interaction, 6(CSCW2), 1–29. https://doi.org/10.1145/3555651

Shin, D., Kee, K. F., & Shin, E. Y. (2022). Algorithm awareness: Why user awareness is critical for personal privacy in the adoption of algorithmic platforms. International Journal of Information Management, 65, 102494. https://doi.org/10.1016/j.ijinfomgt.2022.102494

Udoudom, U., Brown, G., & George, K. (2024). Impact of Social Media Platform on Entrepreneurial Venture: A Technopreneurship Perspective. Journal of Business Management and Economic Development, 2(02), 543–552. https://doi.org/10.59653/jbmed.v2i02.595

Vaithilingam, S., Ong, C. S., Moisescu, O. I., & Nair, M. S. (2024). Robustness checks in PLS-SEM: A review of recent practices and recommendations for future applications in business research. Journal of Business Research, 173, 114465. https://doi.org/10.1016/j.jbusres.2023.114465

Waddington, J. (2023). Self-efficacy. ELT Journal, 77(2), 237–240. https://doi.org/10.1093/elt/ccad046

Xie, J. (2025). Consumer behavior in the age of algorithmic marketing: Insights from interaction with social commerce platforms. 2(4), 56–64. https://doi.org/10.71222/0nmra608

Yang, J., Casey, A., & Cale, L. (2025). The role of healthy lifestyle technologies in supporting young adults’ healthy active lifestyles. Sport, Education and Society, 1–20. https://doi.org/10.1080/13573322.2025.2497366

Yulianto, H., Rohani, & Jumarti. (2025). How does adaptive socio-cultural digital innovation model influence cultural sustainability of traditional craft SMEs in Makassar? 524–542. https://doi.org/10.36563/gqhspx75

Zhang, M. (2023). Older people’s attitudes towards emerging technologies: A systematic literature review. Public Understanding of Science, 32(8), 948–968. https://doi.org/10.1177/09636625231171677

Zhang, T., Stough, R., & Gerlowski, D. (2022). Digital exposure, age, and entrepreneurship. Annals of Regional Science, 69, 633–681. https://doi.org/10.1007/s00168-022-01130-0

Zhang, W., & Wang, Y. (2025). The impact of different recommendation algorithms on consumer search behavior and merchants competition. International Review of Economics and Finance, 98(August 2024), 103943. https://doi.org/10.1016/j.iref.2025.103943

Downloads

Published

2026-05-27

How to Cite

Gotama, M. F., & Subawa, N. S. (2026). Generational and Socio-Cultural Effects on Algorithmic Mastery in Denpasar Creative Industry Actors. Journal of Business Management and Economic Development, 4(02), 663–682. https://doi.org/10.59653/jbmed.v4i02.2468