A Behavioral Fuzzy Decision Support Framework for Optimizing Sectoral Work Models in the Life 3.0 Era

Öznur Gülen Ertosun; Serkan Eti; Özge Doğuç; Serhat Yüksel; Hasan Dinçer; Onur Kardeş

doi:10.31181/dma412026211

Authors

Öznur Gülen Ertosun School of Business, Istanbul Medipol University, Istanbul, Turkey https://orcid.org/0000-0001-9339-2610
Serkan Eti 1) Faculty of Applied Sciences, Marmara University, Istanbul, Turkey; 2) ARUCAD Research Centre, Arkin University of Creative Arts and Design, Northern Cyprus, Mersin 10, Turkey https://orcid.org/0000-0002-4791-4091
Özge Doğuç School of Business, Istanbul Medipol University, Istanbul, Turkey https://orcid.org/0000-0002-5971-9218
Serhat Yüksel 1) School of Business, Istanbul Medipol University, Istanbul, Turkey; 2) Department of Economics and Management, Khazar University, Baku, Azerbaijan https://orcid.org/0000-0002-9858-1266
Hasan Dinçer 1) School of Business, Istanbul Medipol University, Istanbul, Turkey; 2) Department of Economics and Management, Khazar University, Baku, Azerbaijan; 3) University College, Korea University, Republic of Korea https://orcid.org/0000-0002-8072-031X
Onur Kardeş Faculty of Engineering, Istanbul Beykent University, Istanbul, Turkey https://orcid.org/0000-0002-5342-9316

DOI:

https://doi.org/10.31181/dma412026211

Keywords:

Life 3.0 paradigm, Robotic Process Automation, Behavioral Leadership Fuzzy Sets, Transformation of Working Life

Abstract

In the context of the Life 3.0 paradigm, where digitalization is accelerating, determining the most appropriate innovative working model for different sectors has become a strategic imperative. However, the literature lacks integrated multi-criteria approaches for evaluating the effectiveness of alternative working models, such as freelance, hybrid, remote, and metaverse-based models, within a sectoral context. This study aims to determine the most appropriate working model based on the structural, digital, and operational characteristics of different sectors and to identify the criteria that should be prioritized in this decision-making process. The Information and Technology, Education and Consulting, Marketing and E-Commerce, and Finance and Insurance sectors are analyzed. First, 17 criteria affecting the selection of working models are identified. Publications indexed in the Web of Science (WoS) database are scanned using a Robotic Process Automation (RPA) approach, and the eight most frequent and relevant criteria are selected using text mining techniques. Data obtained from interviews with five experts are then weighted according to the experts' demographic characteristics using a dimensionality reduction method. The criteria weights are determined using the SITDE method, while the alternatives are ranked using the RATGOS algorithm. In addition, a novel fuzzy set system, Behavioral Leadership Fuzzy Sets (BLFSs), is developed and integrated into the model to analyze the impact of decision-maker behaviors on managerial reflexes. The proposed framework integrates artificial intelligence and multi-criteria decision-making techniques, reduces subjectivity through data-driven criteria selection and expert weighting, and incorporates behavioral leadership characteristics into the decision process. The findings indicate that the hybrid model is the most appropriate working model across all four sectors. However, sectoral priorities differ: career and development opportunities are the most important criterion in the IT sector, whereas market access and ethical responsibilities are prioritized in the finance sector.

Downloads

Download data is not yet available.

References

Azim, A. B., Alballa, T., Alhabeeb, S. A., Albely, M. S., & Khalifa, H. A. E. W. (2025). Advanced Decision-Making Strategies in Life 3.0 Through q-Spherical Fuzzy Rough Dombi Aggregation Operators. Cognitive Computation, 17(3), 93. https://doi.org/10.1007/s12559-025-10434-0

Rulo, K. (2026). LLMs and literary history: precursors and pathways. AI & SOCIETY, 41(3), 2557-2567. https://doi.org/10.1007/s00146-025-02558-6

Osorio, M. L., & Madero, S. (2025). Explaining Gen Z’s desire for hybrid work in corporate, family, and entrepreneurial settings. Business Horizons, 68(1), 83-93. https://doi.org/10.1016/j.bushor.2024.02.008

John, B., Alsamarra'i, Z., & Panteli, N. (2025). Reconfiguring digital embeddedness in hybrid work: The case of employee experience management platforms. Information Systems Journal, 35(2), 450-479. https://doi.org/10.1111/isj.12545

Zhang, G., Ali, J., Du, Z., Kim, D. W., & Kim, W. (2025). Virtual teamwork coordination and performance: integrating the metaverse and situation-organism-behavior-consequence (SOBC) frameworks through intellectual capital lens. Journal of Intellectual Capital, 1-23. https://doi.org/10.1108/JIC-02-2025-0029

Anand, A. (2025). Marketing Strategies in the Gig Economy: Challenges and Opportunities for Freelance Marketers. Sustainability and Adaptability of Gig Economies in Global Business, 107-140. https://doi.org/10.4018/979-8-3693-9385-7.ch005

Karaagac, E. A., & Worth, N. (2025). Making space for work: understanding freelancers’ hybrid work identities through work from home practices. Social & Cultural Geography, 26(10), 1137-1157. https://doi.org/10.1080/14649365.2025.2503239

Sahoo, D. K., Pandey, A., Mittal, S., & Luu, T. M. N. (2025). Work-Life Balance of Hybrid Entrepreneurs: Balancing Demands of Personal and Professional Lives. In Entrepreneurial Ecosystems Driving Economic Transformation and Job Creation (pp. 409-432). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3693-9486-1.ch015

Ammirato, S., Felicetti, A. M., Linzalone, R., Corvello, V., & Kumar, S. (2023). Still our most important asset: A systematic review on human resource management in the midst of the fourth industrial revolution. Journal of Innovation & Knowledge, 8(3), 100403. https://doi.org/10.1016/j.jik.2023.100403

Apostolidis, C., Devine, A., Jabbar, A., Kayikci, Y., & Christofi, M. (2025). Ctrl+ Alt+ Sustain: the role of algorithmic and organisational trust in sustainable digital transformation. Business Process Management Journal, 31(5), 1614-1635. https://doi.org/10.1108/BPMJ-10-2024-0967

Kolade, O., & Owoseni, A. (2022). Employment 5.0: The work of the future and the future of work. Technology in Society, 71, 102086. https://doi.org/10.1016/j.techsoc.2022.102086

Lauring, J., & Jonasson, C. (2025). What is hybrid work? Towards greater conceptual clarity of a common term and understanding its consequences. Human Resource Management Review, 35(1), 101044. https://doi.org/10.1016/j.hrmr.2024.101044

Zhao, T., Gasiba, T., Lechner, U., & Pinto-Albuquerque, M. (2024). Thriving in the era of hybrid work: Raising cybersecurity awareness using serious games in industry trainings. The Journal of Systems and Software, 210, 111946. https://doi.org/10.1016/j.jss.2023.111946

Wells, J., Scheibein, F., Pais, L., Rebelo dos Santos, N., Dalluege, C. A., Czakert, J. P., & Berger, R. (2023). A systematic review of the impact of remote working referenced to the concept of work–life flow on physical and psychological health. Workplace health & safety, 71(11), 507-521. https://doi.org/10.1177/21650799231176397

Ríos Villacorta, M. A., Ramos Farroñán, E. V., Alarcón García, R. E., Castro Ijiri, G. L., Bravo-Jaico, J. L., Minchola Vásquez, A. M., Ganoza-Ubillús, L. M., Escobedo Gálvez, J. F., Ríos Yovera, V. R., & Durand Gonzales, E. J. (2025). Telework for a sustainable future: Systematic review of its contribution to global corporate sustainability (2020–2024). Sustainability, 17(13), 5737. https://doi.org/10.3390/su17135737

Aprilina, R., & Martdianty, F. (2023). The Role of Hybrid-Working in Improving Employees' Satisfaction, Perceived Productivity, and Organizations' Capabilities. Jurnal Manajemen Teori dan Terapan, 16(2), 206. http://dx.doi.org/10.20473/jmtt.v16i2.45632

Wu, D., & Huang, J. L. (2024). Gig work and gig workers: An integrative review and agenda for future research. Journal of Organizational Behavior, 45(2), 183-208. https://doi.org/10.1002/job.2775

Pilatti, G. R., Pinheiro, F. L., & Montini, A. A. (2024). Systematic literature review on gig economy: Power dynamics, worker autonomy, and the role of social networks. Administrative Sciences, 14(10), 267. https://doi.org/10.3390/admsci14100267

Wardhana, V. H. K., Herlina, M. G., Bangsawan, S., & Tuori, M. A. (2020). Regulatory developments in the gig economy: A literature review. The Winners, 21(2), 141-153. https://doi.org/10.21512/tw.v21i2.6758

Frenken, K., van Waes, A., Pelzer, P., Smink, M., & van Est, R. (2020). Safeguarding public interests in the platform economy. Policy & Internet, 12(3), 400-425. https://doi.org/10.1002/poi3.217

Koehler, M., & Sauermann, H. (2024). Algorithmic management in scientific research. Research Policy, 53(4), 104985. https://doi.org/10.1016/j.respol.2024.104985

Kim, S., Khoreva, V., & Vaiman, V. (2025). Strategic human resource management in the era of algorithmic technologies: key insights and future research agenda. Human Resource Management, 64(2), 447-464. http://dx.doi.org/10.1002/hrm.22268

Meijerink, J., & Bondarouk, T. (2023). The duality of algorithmic management: Toward a research agenda on HRM algorithms, autonomy and value creation. Human Resource Management Review, 33(1), 100876. https://doi.org/10.1016/j.hrmr.2021.100876

Beheshti, M., Mladenović, D., Sadraei, R., & ZareRavasan, A. (2025). From the final frontier to the metaverse: exploring the role of sharing economy principles in revolutionizing space tourism. International Journal of Contemporary Hospitality Management, 37(4), 1350-1383. https://doi.org/10.1108/IJCHM-09-2023-1487

Antonietti, R., Burlina, C., & Rodríguez-Pose, A. (2025). Digital technology and regional income inequality: Are better institutions the solution?. Papers in Regional Science, 104(2), 100079. https://doi.org/10.1016/j.pirs.2025.100079

Rizana, A. F., Wiratmadja, I. I., & Akbar, M. (2025). Exploring capabilities for digital transformation in the business context: Insight from a systematic literature review. Sustainability, 17(9), 4222. https://doi.org/10.3390/su17094222

Van Veldhoven, Z., & Vanthienen, J. (2023). Best practices for digital transformation based on a systematic literature review. Digital Transformation and Society, 2(2), 104-128. http://dx.doi.org/10.1108/DTS-11-2022-0057

Zirar, A., Ali, S. I., & Islam, N. (2023). Worker and workplace Artificial Intelligence (AI) coexistence: Emerging themes and research agenda. Technovation, 124, 102747. https://doi.org/10.1016/j.technovation.2023.102747

Hasani, S., Rezania, D., & Mohammadi, M. (2024). Towards a framework for successful metaverse adoption in small and medium-sized enterprises: An exploratory study. International Journal of Engineering Business Management, 16. https://doi.org/10.1177/18479790241257118

Parker, S. K, Ballard, T, Billinghurst, M, Collins, C, Dollard, M, Griffin, M. A, Johal, W, Jorritsma, K, Kowalkiewicz, M, Kyndt, E, Lusher, D, McLennan, C, Miller, T, Neal, A, Paterson, J. M, Vetere, F, & Walsh, T. (2026). Quality work in the future: New directions via a co-evolving sociotechnical systems perspective. Australian Journal of Management, 51(2), 534-560. https://doi.org/10.1177/03128962251331813

Richter, A., & Richter, S. (2024). Hybrid work–a reconceptualisation and research agenda. i-com, 23(1), 71-78. http://dx.doi.org/10.1515/icom-2023-0027

Cherep, A., Voronkova, V., & Androsova, O. (2022). Transformational changes in organizational management and human resources in the digital age. Baltic Journal of Economic Studies, 8(3), 210–219. https://doi.org/10.30525/2256-0742/2022-8-3-210-219

Bertolini, M., Mezzogori, D., Neroni, M., & Zammori, F. (2021). Machine Learning for industrial applications: A comprehensive literature review. Expert Systems with Applications, 175, 114820. https://doi.org/10.1016/j.eswa.2021.114820

Salari, N., Beiromvand, M., Hosseinian-Far, A., Habibi, J., Babajani, F., & Mohammadi, M. (2025). Impacts of generative artificial intelligence on the future of labor market: A systematic review. Computers in Human Behavior Reports, 18, 100652. https://doi.org/10.1016/j.chbr.2025.100652

Brenk, K., Tomini, N., Kanbach, D. K., Stubner, S., & Pinelli, M. (2025). From virtual vision to business reality: embracing the metaverse revolution. Review of Managerial Science, 20(1), 81-107. https://doi.org/10.1007/s11846-025-00878-x

Omar, N., & Jamil, R. (2025). A systematic literature review of the gig economy: Insights into worker experiences, policy implications, and the impact of digitalization. International Journal of Research and Innovation in Social Science (IJRISS), 9(2), 2136–2156. https://dx.doi.org/10.47772/IJRISS.2025.9020170

Lima, Y., Barbosa, C. E., dos Santos, H. S., & de Souza, J. M. (2021). Understanding technological unemployment: A review of causes, consequences, and solutions. Societies, 11(2), 50. https://doi.org/10.3390/soc11020050

Hwang, I., & Seo, R. (2025). Organizational support for digital transformation in the metaverse: a contingent pathway from user experience to digitalization resistance. R&D Management, 55(2), 420-437. https://doi.org/10.1111/radm.12706

Toscano, F., Alessandri, G., & Zappalà, S. (2025). Examining job performance in work from home considering job concentration and social isolation: The moderating role of emotional stability in a diary study. Computers in Human Behavior Reports, 18, 100654. https://doi.org/10.1016/j.chbr.2025.100654

Khan, Z, Hussain, F, Ullah, I, Rahim, T, Khan, M, Jan, R, Mekawy, I, & Alharbi, A. (2025). Some novel properties of complex intuitionistic fuzzy ideals in classical ring. Partial Differential Equations in Applied Mathematics, 100811. https://doi.org/10.1016/j.padiff.2024.100811

Yüksel, S., Eti, S., Dinçer, H., Gökalp, Y., Olaru, G. O., & Oflaz, N. K. (2025). Innovative financial solutions for sustainable investments using artificial intelligence-based hybrid fuzzy decision-making approach in carbon capture technologies. Financial Innovation, 11(1), 20. https://doi.org/10.1186/s40854-024-00671-x

Yalçın, G. C., Kara, K., Özekenci, E. K., Simic, V., & Pamucar, D. (2025). Green maritime transport performance analysis of G-7 countries using an interval-valued Fermatean fuzzy ARLON-based decision model. Applied Soft Computing, 184, 113677. https://doi.org/10.1016/j.asoc.2025.113677

Eti, S, Yüksel, S, Dinçer, H, Pamucar, D, Deveci, M, Antucheviciene, J, Gökalp, Y, & Meral, H. (2025). Optimizing parametric insurance for renewable energy investments: Integrating fuzzy decision-making and artificial intelligence techniques. Renewable Energy, 246, 122856. https://doi.org/10.1016/j.renene.2025.122856