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Analytics-based decision-making for service systems: A qualitative study and agenda for future research

Author

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  • Akter, Shahriar
  • Bandara, Ruwan
  • Hani, Umme
  • Fosso Wamba, Samuel
  • Foropon, Cyril
  • Papadopoulos, Thanos

Abstract

While the use of big data tends to add value for business throughout the entire value chain, the integration of big data analytics (BDA) to the decision-making process remains a challenge. This study, based on a systematic literature review, thematic analysis and qualitative interview findings, proposes a set of six-steps to establish both rigor and relevance in the process of analytics-driven decision-making. Our findings illuminate the key steps in this decision process including problem definition, review of past findings, model development, data collection, data analysis as well as actions on insights in the context of service systems. Although findings have been discussed in a sequence of steps, the study identifies them as interdependent and iterative. The proposed six-step analytics-driven decision-making process, practical evidence from service systems, and future research agenda, provide altogether the foundation for future scholarly research and can serve as a step-wise guide for industry practitioners.

Suggested Citation

  • Akter, Shahriar & Bandara, Ruwan & Hani, Umme & Fosso Wamba, Samuel & Foropon, Cyril & Papadopoulos, Thanos, 2019. "Analytics-based decision-making for service systems: A qualitative study and agenda for future research," International Journal of Information Management, Elsevier, vol. 48(C), pages 85-95.
    • Handle: RePEc:eee:ininma:v:48:y:2019:i:c:p:85-95
    DOI: 10.1016/j.ijinfomgt.2019.01.020
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    Cited by:

    1. Ashrafi, Amir & Zareravasan, Ahad, 2022. "An ambidextrous approach on the business analytics-competitive advantage relationship: Exploring the moderating role of business analytics strategy," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
    2. Ranjan Chaudhuri & Sheshadri Chatterjee & Demetris Vrontis & Alkis Thrassou, 2024. "Adoption of robust business analytics for product innovation and organizational performance: the mediating role of organizational data-driven culture," Annals of Operations Research, Springer, vol. 339(3), pages 1757-1791, August.
    3. Borghi, Matteo & Mariani, Marcello M., 2022. "The role of emotions in the consumer meaning-making of interactions with social robots," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    4. Showimy Aldossari & Umi Asma’ Mokhtar & Ahmad Tarmizi Abdul Ghani, 2023. "Factor Influencing the Adoption of Big Data Analytics: A Systematic Literature and Experts Review," SAGE Open, , vol. 13(4), pages 21582440231, December.
    5. Ahmad Ibrahim Aljumah & Mohammed T. Nuseir & Md. Mahmudul Alam, 2021. "Traditional marketing analytics, big data analytics and big data system quality and the success of new product development," Post-Print hal-03538161, HAL.
    6. H. Kava & K. Spanaki & T. Papadopoulos & S. Despoudi & O. Rodriguez Espindola & M. Fakhimi, 2024. "Data analytics diffusion in the UK renewable energy sector: an innovation perspective," Post-Print hal-04478933, HAL.
    7. Mariani, Marcello M. & Borghi, Matteo & Laker, Benjamin, 2023. "Do submission devices influence online review ratings differently across different types of platforms? A big data analysis," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    8. Harkaran Kava & Konstantina Spanaki & Thanos Papadopoulos & Stella Despoudi & Oscar Rodriguez-Espindola & Masoud Fakhimi, 2021. "Data Analytics Diffusion in the UK Renewable Energy Sector: An Innovation Perspective," Post-Print hal-03781046, HAL.
    9. Agag, Gomaa & Shehawy, Yasser Moustafa & Almoraish, Ahmed & Eid, Riyad & Chaib Lababdi, Houyem & Gherissi Labben, Thouraya & Abdo, Said Shabban, 2024. "Understanding the relationship between marketing analytics, customer agility, and customer satisfaction: A longitudinal perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 77(C).
    10. Maryia Zaitsava & Elona Marku & Maria Chiara Guardo & Azar Shahgholian, 2023. "A fine-grained perspective on big data knowledge creation: dimensions, insights, and mechanism from a pilot study," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 27(2), pages 547-573, June.
    11. Balakrishnan, Janarthanan & Abed, Salma S. & Jones, Paul, 2022. "The role of meta-UTAUT factors, perceived anthropomorphism, perceived intelligence, and social self-efficacy in chatbot-based services?," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    12. Shahriar Akter & Katina Michael & Muhammad Rajib Uddin & Grace McCarthy & Mahfuzur Rahman, 2022. "Transforming business using digital innovations: the application of AI, blockchain, cloud and data analytics," Annals of Operations Research, Springer, vol. 308(1), pages 7-39, January.
    13. Boccali, Filippo & Mariani, Marcello M. & Visani, Franco & Mora-Cruz, Alexandra, 2022. "Innovative value-based price assessment in data-rich environments: Leveraging online review analytics through Data Envelopment Analysis to empower managers and entrepreneurs," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    14. Aljumah, Ahmad Ibrahim & Nuseir, Mohammed T. & Alam, Md. Mahmudul, 2021. "Organizational Performance and Capabilities to Analyze Big Data: Do the Ambidexterity and Business Value of Big Data Analytics Matter?," OSF Preprints an8er_v1, Center for Open Science.
    15. Sudhanshu Singh & Rakesh Verma & Saroj Koul, 2022. "A data-driven approach to shared decision-making in a healthcare environment," OPSEARCH, Springer;Operational Research Society of India, vol. 59(2), pages 732-746, June.
    16. Mihalis Giannakis & Rameshwar Dubey & Shishi Yan & Konstantina Spanaki & Thanos Papadopoulos, 2022. "Social media and sensemaking patterns in new product development: demystifying the customer sentiment," Annals of Operations Research, Springer, vol. 308(1), pages 145-175, January.

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