Research Article
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Year 2025, Volume: 8 Issue: 4, 664 - 676

Ahmet Kala , Cem Özkurt , Bilal Emre Yahyaoğlu

https://doi.org/10.35377/saucis...1704169

Abstract

References

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  • M. Ghobakhloo, "The future of manufacturing industry: A strategic roadmap toward Industry 4.0," Journal of Manufacturing Technology Management, vol. 29, no. 6, pp. 910-936, 2018. https://doi.org/10.1108/JMTM-02-2018-0057
  • P. Zawadzki and K. Żywicki, "Smart product design and production control for effective mass customization in the Industry 4.0 concept," Management and Production Engineering Review, vol. 7, no. 3, pp. 105-112, 2016. https://doi.org/10.1515/mper-2016-0030
  • G. Ken, H. Rajagopal, and S. Anjum, "Pharmacy warehouse management system," in Proceedings of International Conference on Artificial Life and Robotics, vol. 28, pp. 663-668, 2023. https://doi.org/10.5954/icarob.2023.os26-4
  • K. Nuengchamnong and T. Mahamud, "Optimization of KLT warehouse management," in *International Conference Proceedings PSETN-23, CBAES-23, LEHS2-23, PSETH-23 & ICCBES-23*, Pattaya, Thailand, May 29-31, 2023. https://doi.org/10.17758/eirai18.f0523411
  • J. Wang, B. Yin, X. Li, and H. Cui, "Research on intelligent electricity meter warehouse management system based on IoT technology," in Second International Conference on Advanced Manufacturing Technology and Manufacturing Systems (ICAMTMS 2023), 2023. https://doi.org/10.1117/12.2688959
  • Z. Sun, Z. Yue, X. Sun, W. Fan, and W. Zhou, "An intelligent cargo/warehouse management system," in Proceedings of International Conference on Artificial Life and Robotics, vol. 29, pp. 818-822, 2024. https://doi.org/10.5954/icarob.2024.os26-1
  • Y. Fu, Y. Qie, Y. Ding, S. Ma, Y. Cao, and Y. Li, "Research on the application of passive RFID technology in warehouse management," in Second International Conference on Digital Society and Intelligent Systems (DSInS 2022), 2023. https://doi.org/10.1117/12.2673413
  • D. Du, "RFID technology in a smart warehouse application study," in Sixth International Conference on Traffic Engineering and Transportation System (ICTETS 2022), 2023, p. 4. https://doi.org/10.1117/12.2668451
  • M. Phan and A. Tran, "Development a warehouse management information system," Applied Mechanics and Materials, vol. 907, pp. 131-143, 2022. https://doi.org/10.4028/p-78ah4r
  • X. Zhang, T. Mo, and Y. Zhang, "Optimization of storage location assignment for non-traditional layout warehouses based on the firework algorithm," Sustainability, vol. 15, no. 13, p. 10242, 2023. https://doi.org/10.3390/su151310242
  • S. Manoharan, D. Stilling, G. Kabir, and S. Sarker, "Implementation of linear programming and decision-making model for the improvement of warehouse utilization," Applied System Innovation, vol. 5, no. 2, p. 33, 2022. https://doi.org/10.3390/asi5020033
  • R. Carli, M. Dotoli, S. Digiesi, F. Facchini, and G. Mossa, "Sustainable scheduling of material handling activities in labor-intensive warehouses: A decision and control model," Sustainability, vol. 12, no. 8, p. 3111, 2020. https://doi.org/10.3390/su12083111
  • Z. Yao-qin, "Application of information system in warehouse management," DEStech Transactions on Computer Science and Engineering, no. cii, 2017. https://doi.org/10.12783/dtcse/cii2017/17309
  • W. Larutama, D. Bentar, R. Risdayanto, and R. Alvariedz, "Implementation of warehouse management system planning in finished goods warehouse," Journal of Logistics and Supply Chain, vol. 2, no. 2, pp. 81-90, 2022. https://doi.org/10.17509/jlsc.v2i2.62840
  • A. Jarašūnienė, K. Čižiūnienė, and A. Čereška, "Research on impact of IoT on warehouse management," Sensors, vol. 23, no. 4, p. 2213, 2023. https://doi.org/10.3390/s23042213
  • N. Batarlienė and A. Jarašūnienė, "Improving the quality of warehousing processes in the context of the logistics sector," Sustainability, vol. 16, no. 6, p. 2595, 2024. https://doi.org/10.3390/su16062595
  • D. Perkumienė, K. Ratautaitė, and R. Pranskūnienė, "Innovative solutions and challenges for the improvement of storage processes," Sustainability, vol. 14, no. 17, p. 10616, 2022. https://doi.org/10.3390/su141710616
  • G. May and D. Kiritsis, "Zero defect manufacturing strategies and platform for smart factories of Industry 4.0," in IFIP International Conference on Advances in Production Management Systems, pp. 142-152, 2019. https://doi.org/10.1007/978-3-030-18180-2_11
  • U. M. Dilberoglu, B. Gharehpapagh, U. Yaman, and M. Dolen, "The role of additive manufacturing in the era of Industry 4.0," Procedia Manufacturing, vol. 11, pp. 545-554, 2017. https://doi.org/10.1016/j.promfg.2017.07.148
  • L. A. Ocampo, T. A. G. Tan, and L. A. Sia, "Using fuzzy DEMATEL in modeling the causal relationships of the antecedents of organizational citizenship behavior (OCB) in the hospitality industry: A case study in the Philippines," Journal of Hospitality and Tourism Management, vol. 34, pp. 11-29, 2018. https://doi.org/10.1016/j.jhtm.2017.11.002
  • S. Altuntas and M. K. Yilmaz, "Fuzzy DEMATEL method to evaluate the dimensions of marketing resources: An application in SMEs," Journal of Business Economics and Management, vol. 17, no. 3, pp. 347-364, 2016. https://doi.org/10.3846/16111699.2015.1068220
  • Y. Beikkhakhian, M. Javanmardi, M. Karbasian, and B. Khayambashi, "The application of ISM model in evaluating agile suppliers selection criteria and ranking suppliers using fuzzy TOPSIS-AHP methods," Expert Systems with Applications, vol. 42, no. 15-16, pp. 6224-6236, 2015. https://doi.org/10.1016/j.eswa.2015.02.035
  • C.-T. Chen, "Extensions of the TOPSIS for group decision-making under fuzzy environment," Fuzzy Sets and Systems, vol. 114, no. 1, pp. 1-9, 2000. https://doi.org/10.1016/S0165-0114(97)00377-1
  • C. Li and G. Tzeng, "Identification of a threshold value for the DEMATEL method: Using the maximum mean de-entropy algorithm," in Communications in Computer and Information Science, pp. 789-796, 2009. https://doi.org/10.1007/978-3-642-02298-2_115
  • N. Chen and Z. Xu, "Hesitant fuzzy ELECTRE II approach: A new way to handle multi-criteria decision making problems," Information Sciences, vol. 292, pp. 175-197, 2015. https://doi.org/10.1016/j.ins.2014.08.054
  • R. Keshavarzfard and A. Makui, "An IF-DEMATEL-AHP based on triangular intuitionistic fuzzy numbers (TIFNs)," Decision Science Letters, vol. 4, no. 2, pp. 237-246, 2015. https://doi.org/10.5267/j.dsl.2014.11.002
  • J. Chen, "Improved DEMATEL-ISM integration approach for complex systems," PLoS ONE, vol. 16, no. 7, p. e0254694, 2021. https://doi.org/10.1371/journal.pone.0254694
  • H. Shakeri and M. Khalilzadeh, "Analysis of factors affecting project communications with a hybrid DEMATEL-ISM approach (A case study in Iran)," Heliyon, vol. 6, no. 8, p. e04430, 2020. https://doi.org/10.1016/j.heliyon.2020.e04430
  • S. Khan, R. Singh, A. Haleem, J. Dsilva, and S. Ali, "Exploration of critical success factors of Logistics 4.0: A DEMATEL approach," Logistics, vol. 6, no. 1, p. 13, 2022. https://doi.org/10.3390/logistics6010013
  • S. Esmaeili et al., "Optimizing in-store warehouse safety: A DEMATEL approach to comprehensive risk assessment," PLoS ONE, vol. 20, no. 2, p. e0317787, 2025. https://doi.org/10.1371/journal.pone.0317787
  • K. Hsia et al., "Development of auto-stacking warehouse truck," Journal of Robotics, Networking and Artificial Life, vol. 4, no. 4, p. 334, 2018. https://doi.org/10.2991/jrnal.2018.4.4.17
  • L. Abdullah, Z. Ong, and N. Rahim, "An intuitionistic fuzzy decision-making for developing cause and effect criteria of subcontractors selection," International Journal of Computational Intelligence Systems, vol. 14, no. 1, p. 991, 2021. https://doi.org/10.2991/ijcis.d.210222.001
  • D. Lee and S. Yoon, "Application of artificial intelligence-based technologies in the healthcare industry: Opportunities and challenges," International Journal of Environmental Research and Public Health, vol. 18, no. 1, p. 271, 2021. https://doi.org/10.3390/ijerph18010271
  • M. Zhou et al., "Machine learning for Industry 4.0 [From the Guest Editors]," IEEE Robotics & Automation Magazine, vol. 30, no. 2, pp. 8-9, 2023. https://doi.org/10.1109/MRA.2023.3266618

A Hybrid Fuzzy DEMATEL–ELECTRE Framework for Evaluating the Impact of Industry 4.0 Technologies on Warehouse Management Strategy Outcomes

Year 2025, Volume: 8 Issue: 4, 664 - 676

Ahmet Kala , Cem Özkurt , Bilal Emre Yahyaoğlu

https://doi.org/10.35377/saucis...1704169

Abstract

Integrating Industry 4.0 (I4.0) technologies into warehouse management critically enhances strategic performance. However, existing studies frequently neglect the causal relationships among strategic outcomes and the transparency of technology prioritization. This study proposes a hybrid multi-criteria decision-making (MCDM) framework integrating Fuzzy DEMATEL to determine the relative weights of strategic outcomes, Fuzzy ELECTRE II to rank technologies, and SHAP-based Explainable Artificial Intelligence (XAI) to enhance model transparency and interpretability. The analysis relies on Delphi-based expert evaluations from 12 senior industrial engineers across three manufacturing firms. The results reveal that Cost Reduction (weight = 0.225), Operational Efficiency (0.097), and Inventory Management (0.115) are the most critical strategic outcomes. Artificial Intelligence, Internet of Things, and Big Data Analytics emerged as the top-ranked technologies based on ELECTRE II scores. SHAP analysis further identified Cost Reduction (SHAP value: +1.62), Customer Satisfaction (+0.50), and Real-time Data Processing (+0.40) as the primary drivers behind the technology rankings. The proposed framework offers a transparent, interpretable, and causally grounded decision-support model for aligning digital transformation investments with strategic warehouse performance objectives.

Keywords

Industry 4.0 Warehouse Management Fuzzy DEMATEL Fuzzy ELECTRE Explainable Artificial Intelligence

References

  • G. L. Tortorella and D. Fettermann, "Implementation of Industry 4.0 and lean production in Brazilian manufacturing companies," International Journal of Production Research, vol. 56, no. 8, pp. 2975-2987, 2018. https://doi.org/10.1080/00207543.2017.1391420
  • M. Ghobakhloo, "The future of manufacturing industry: A strategic roadmap toward Industry 4.0," Journal of Manufacturing Technology Management, vol. 29, no. 6, pp. 910-936, 2018. https://doi.org/10.1108/JMTM-02-2018-0057
  • P. Zawadzki and K. Żywicki, "Smart product design and production control for effective mass customization in the Industry 4.0 concept," Management and Production Engineering Review, vol. 7, no. 3, pp. 105-112, 2016. https://doi.org/10.1515/mper-2016-0030
  • G. Ken, H. Rajagopal, and S. Anjum, "Pharmacy warehouse management system," in Proceedings of International Conference on Artificial Life and Robotics, vol. 28, pp. 663-668, 2023. https://doi.org/10.5954/icarob.2023.os26-4
  • K. Nuengchamnong and T. Mahamud, "Optimization of KLT warehouse management," in *International Conference Proceedings PSETN-23, CBAES-23, LEHS2-23, PSETH-23 & ICCBES-23*, Pattaya, Thailand, May 29-31, 2023. https://doi.org/10.17758/eirai18.f0523411
  • J. Wang, B. Yin, X. Li, and H. Cui, "Research on intelligent electricity meter warehouse management system based on IoT technology," in Second International Conference on Advanced Manufacturing Technology and Manufacturing Systems (ICAMTMS 2023), 2023. https://doi.org/10.1117/12.2688959
  • Z. Sun, Z. Yue, X. Sun, W. Fan, and W. Zhou, "An intelligent cargo/warehouse management system," in Proceedings of International Conference on Artificial Life and Robotics, vol. 29, pp. 818-822, 2024. https://doi.org/10.5954/icarob.2024.os26-1
  • Y. Fu, Y. Qie, Y. Ding, S. Ma, Y. Cao, and Y. Li, "Research on the application of passive RFID technology in warehouse management," in Second International Conference on Digital Society and Intelligent Systems (DSInS 2022), 2023. https://doi.org/10.1117/12.2673413
  • D. Du, "RFID technology in a smart warehouse application study," in Sixth International Conference on Traffic Engineering and Transportation System (ICTETS 2022), 2023, p. 4. https://doi.org/10.1117/12.2668451
  • M. Phan and A. Tran, "Development a warehouse management information system," Applied Mechanics and Materials, vol. 907, pp. 131-143, 2022. https://doi.org/10.4028/p-78ah4r
  • X. Zhang, T. Mo, and Y. Zhang, "Optimization of storage location assignment for non-traditional layout warehouses based on the firework algorithm," Sustainability, vol. 15, no. 13, p. 10242, 2023. https://doi.org/10.3390/su151310242
  • S. Manoharan, D. Stilling, G. Kabir, and S. Sarker, "Implementation of linear programming and decision-making model for the improvement of warehouse utilization," Applied System Innovation, vol. 5, no. 2, p. 33, 2022. https://doi.org/10.3390/asi5020033
  • R. Carli, M. Dotoli, S. Digiesi, F. Facchini, and G. Mossa, "Sustainable scheduling of material handling activities in labor-intensive warehouses: A decision and control model," Sustainability, vol. 12, no. 8, p. 3111, 2020. https://doi.org/10.3390/su12083111
  • Z. Yao-qin, "Application of information system in warehouse management," DEStech Transactions on Computer Science and Engineering, no. cii, 2017. https://doi.org/10.12783/dtcse/cii2017/17309
  • W. Larutama, D. Bentar, R. Risdayanto, and R. Alvariedz, "Implementation of warehouse management system planning in finished goods warehouse," Journal of Logistics and Supply Chain, vol. 2, no. 2, pp. 81-90, 2022. https://doi.org/10.17509/jlsc.v2i2.62840
  • A. Jarašūnienė, K. Čižiūnienė, and A. Čereška, "Research on impact of IoT on warehouse management," Sensors, vol. 23, no. 4, p. 2213, 2023. https://doi.org/10.3390/s23042213
  • N. Batarlienė and A. Jarašūnienė, "Improving the quality of warehousing processes in the context of the logistics sector," Sustainability, vol. 16, no. 6, p. 2595, 2024. https://doi.org/10.3390/su16062595
  • D. Perkumienė, K. Ratautaitė, and R. Pranskūnienė, "Innovative solutions and challenges for the improvement of storage processes," Sustainability, vol. 14, no. 17, p. 10616, 2022. https://doi.org/10.3390/su141710616
  • G. May and D. Kiritsis, "Zero defect manufacturing strategies and platform for smart factories of Industry 4.0," in IFIP International Conference on Advances in Production Management Systems, pp. 142-152, 2019. https://doi.org/10.1007/978-3-030-18180-2_11
  • U. M. Dilberoglu, B. Gharehpapagh, U. Yaman, and M. Dolen, "The role of additive manufacturing in the era of Industry 4.0," Procedia Manufacturing, vol. 11, pp. 545-554, 2017. https://doi.org/10.1016/j.promfg.2017.07.148
  • L. A. Ocampo, T. A. G. Tan, and L. A. Sia, "Using fuzzy DEMATEL in modeling the causal relationships of the antecedents of organizational citizenship behavior (OCB) in the hospitality industry: A case study in the Philippines," Journal of Hospitality and Tourism Management, vol. 34, pp. 11-29, 2018. https://doi.org/10.1016/j.jhtm.2017.11.002
  • S. Altuntas and M. K. Yilmaz, "Fuzzy DEMATEL method to evaluate the dimensions of marketing resources: An application in SMEs," Journal of Business Economics and Management, vol. 17, no. 3, pp. 347-364, 2016. https://doi.org/10.3846/16111699.2015.1068220
  • Y. Beikkhakhian, M. Javanmardi, M. Karbasian, and B. Khayambashi, "The application of ISM model in evaluating agile suppliers selection criteria and ranking suppliers using fuzzy TOPSIS-AHP methods," Expert Systems with Applications, vol. 42, no. 15-16, pp. 6224-6236, 2015. https://doi.org/10.1016/j.eswa.2015.02.035
  • C.-T. Chen, "Extensions of the TOPSIS for group decision-making under fuzzy environment," Fuzzy Sets and Systems, vol. 114, no. 1, pp. 1-9, 2000. https://doi.org/10.1016/S0165-0114(97)00377-1
  • C. Li and G. Tzeng, "Identification of a threshold value for the DEMATEL method: Using the maximum mean de-entropy algorithm," in Communications in Computer and Information Science, pp. 789-796, 2009. https://doi.org/10.1007/978-3-642-02298-2_115
  • N. Chen and Z. Xu, "Hesitant fuzzy ELECTRE II approach: A new way to handle multi-criteria decision making problems," Information Sciences, vol. 292, pp. 175-197, 2015. https://doi.org/10.1016/j.ins.2014.08.054
  • R. Keshavarzfard and A. Makui, "An IF-DEMATEL-AHP based on triangular intuitionistic fuzzy numbers (TIFNs)," Decision Science Letters, vol. 4, no. 2, pp. 237-246, 2015. https://doi.org/10.5267/j.dsl.2014.11.002
  • J. Chen, "Improved DEMATEL-ISM integration approach for complex systems," PLoS ONE, vol. 16, no. 7, p. e0254694, 2021. https://doi.org/10.1371/journal.pone.0254694
  • H. Shakeri and M. Khalilzadeh, "Analysis of factors affecting project communications with a hybrid DEMATEL-ISM approach (A case study in Iran)," Heliyon, vol. 6, no. 8, p. e04430, 2020. https://doi.org/10.1016/j.heliyon.2020.e04430
  • S. Khan, R. Singh, A. Haleem, J. Dsilva, and S. Ali, "Exploration of critical success factors of Logistics 4.0: A DEMATEL approach," Logistics, vol. 6, no. 1, p. 13, 2022. https://doi.org/10.3390/logistics6010013
  • S. Esmaeili et al., "Optimizing in-store warehouse safety: A DEMATEL approach to comprehensive risk assessment," PLoS ONE, vol. 20, no. 2, p. e0317787, 2025. https://doi.org/10.1371/journal.pone.0317787
  • K. Hsia et al., "Development of auto-stacking warehouse truck," Journal of Robotics, Networking and Artificial Life, vol. 4, no. 4, p. 334, 2018. https://doi.org/10.2991/jrnal.2018.4.4.17
  • L. Abdullah, Z. Ong, and N. Rahim, "An intuitionistic fuzzy decision-making for developing cause and effect criteria of subcontractors selection," International Journal of Computational Intelligence Systems, vol. 14, no. 1, p. 991, 2021. https://doi.org/10.2991/ijcis.d.210222.001
  • D. Lee and S. Yoon, "Application of artificial intelligence-based technologies in the healthcare industry: Opportunities and challenges," International Journal of Environmental Research and Public Health, vol. 18, no. 1, p. 271, 2021. https://doi.org/10.3390/ijerph18010271
  • M. Zhou et al., "Machine learning for Industry 4.0 [From the Guest Editors]," IEEE Robotics & Automation Magazine, vol. 30, no. 2, pp. 8-9, 2023. https://doi.org/10.1109/MRA.2023.3266618
There are 35 citations in total.

Details

Primary Language English
Subjects Computer Software
Journal Section Research Article
Authors

Ahmet Kala 0000-0002-0598-1181

Cem Özkurt 0000-0002-1251-7715

Bilal Emre Yahyaoğlu 0009-0000-5113-9959

Early Pub Date October 13, 2025
Publication Date October 16, 2025
Submission Date May 22, 2025
Acceptance Date August 22, 2025
Published in Issue Year 2025 Volume: 8 Issue: 4

Cite

APA Kala, A., Özkurt, C., & Yahyaoğlu, B. E. (2025). A Hybrid Fuzzy DEMATEL–ELECTRE Framework for Evaluating the Impact of Industry 4.0 Technologies on Warehouse Management Strategy Outcomes. Sakarya University Journal of Computer and Information Sciences, 8(4), 664-676. https://doi.org/10.35377/saucis...1704169
AMA Kala A, Özkurt C, Yahyaoğlu BE. A Hybrid Fuzzy DEMATEL–ELECTRE Framework for Evaluating the Impact of Industry 4.0 Technologies on Warehouse Management Strategy Outcomes. SAUCIS. October 2025;8(4):664-676. doi:10.35377/saucis.1704169
Chicago Kala, Ahmet, Cem Özkurt, and Bilal Emre Yahyaoğlu. “A Hybrid Fuzzy DEMATEL–ELECTRE Framework for Evaluating the Impact of Industry 4.0 Technologies on Warehouse Management Strategy Outcomes”. Sakarya University Journal of Computer and Information Sciences 8, no. 4 (October 2025): 664-76. https://doi.org/10.35377/saucis. 1704169.
EndNote Kala A, Özkurt C, Yahyaoğlu BE (October 1, 2025) A Hybrid Fuzzy DEMATEL–ELECTRE Framework for Evaluating the Impact of Industry 4.0 Technologies on Warehouse Management Strategy Outcomes. Sakarya University Journal of Computer and Information Sciences 8 4 664–676.
IEEE A. Kala, C. Özkurt, and B. E. Yahyaoğlu, “A Hybrid Fuzzy DEMATEL–ELECTRE Framework for Evaluating the Impact of Industry 4.0 Technologies on Warehouse Management Strategy Outcomes”, SAUCIS, vol. 8, no. 4, pp. 664–676, 2025, doi: 10.35377/saucis...1704169.
ISNAD Kala, Ahmet et al. “A Hybrid Fuzzy DEMATEL–ELECTRE Framework for Evaluating the Impact of Industry 4.0 Technologies on Warehouse Management Strategy Outcomes”. Sakarya University Journal of Computer and Information Sciences 8/4 (October2025), 664-676. https://doi.org/10.35377/saucis. 1704169.
JAMA Kala A, Özkurt C, Yahyaoğlu BE. A Hybrid Fuzzy DEMATEL–ELECTRE Framework for Evaluating the Impact of Industry 4.0 Technologies on Warehouse Management Strategy Outcomes. SAUCIS. 2025;8:664–676.
MLA Kala, Ahmet et al. “A Hybrid Fuzzy DEMATEL–ELECTRE Framework for Evaluating the Impact of Industry 4.0 Technologies on Warehouse Management Strategy Outcomes”. Sakarya University Journal of Computer and Information Sciences, vol. 8, no. 4, 2025, pp. 664-76, doi:10.35377/saucis. 1704169.
Vancouver Kala A, Özkurt C, Yahyaoğlu BE. A Hybrid Fuzzy DEMATEL–ELECTRE Framework for Evaluating the Impact of Industry 4.0 Technologies on Warehouse Management Strategy Outcomes. SAUCIS. 2025;8(4):664-76.
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