How to cite this paper
Siagian, H., Palumian, Y., Basana, S., Tarigan, Z & Doro, R. (2025). The human-machine interface enables collaborative decision-making and supply chain flexibility to boost operational performance.Decision Science Letters , 14(2), 493-506.
Refrences
Ali, B.M., Majeed, M.A., Latif, N., & Aldrickzler, R. (2024). Sustainable supply chain management practices for environmental and social integrity. Journal of Ecohumanism, 3(5), 1000–1016, https://doi.org/10.62754/joe.v3i5.39511000
Alsubaie, F., & Aldoukhi, M. (2024). Using machine learning algorithms with improved accuracy to analyze and predict employee attrition. Decision Science Letters, 13(1), 1-18, DOI: 10.5267/j.dsl.2023.12.006
Ansari, F., Erol, S. & Sihn, W. (2018). Rethinking human machine learning in Industry 4.0: how dos the paradigm shift treat the role of human learning? Procedia Manufacturing, 23, 117-122, https://doi.org/10.1016/j.promfg.2018.04.003
Arikat, Z.M.A. (2024). The Role of business intelligence in enhancing the performance of supply chains in Jordan. Journal of Ecohumanism, 3(8), 2040-2053, DOI: https://doi.org/10.62754/joe.v3i8.4885
Basana, S.R., Malelak, M.I., Suprapto, W., Tarigan, Z.J.H., Tarigan, Z.V.B., & Doron, R.O. (2025). The influence of information technology integration on firm performance through supply chain quality and supply chain resilience. Decision Science Letters, 14(1), 225-238, DOI: 10.5267/j.dsl.2024.9.004
Beltramini, E. (2018). Human vulnerability and robo-advisory: An application of Coeckelbergh’s vulnerability to the machine-human interface. Baltic Journal of Management, 13(2), 250-263. https://doi-org/10.1108/BJM-10-2017-0315
Bouyam, C., & Punsawad, Y. (2022). Human–machine interface-based wheelchair control using piezoelectric sensors based on face and tongue movements. Heliyon, 8 (11), e11679, https://doi.org/10.1016/j.heliyon.2022.e11679
Cao, S., Bryceson, K., & Hine, D. (2021). Collaborative risk management in decentralized multi-tier global food supply chains: an exploratory study. The International Journal of Logistics Management, 32(3), 1050–1067. https://doi.org/10.1108/IJLM-07-2020-0278
Cao, S., Powell, W., Foth, M., Natanelov, V., Miller, T., & Dulleck, U. (2021). Strengthening consumer trust in beef supply chain traceability with a blockchain-based human-machine reconcile mechanism. Computers and Electronics in Agriculture, 180, 105886, https://doi.org/10.1016/j.compag.2020.105886
Chaudhuri, A., Boer, H. & Taran, Y. (2018). Supply chain integration, risk management and manufacturing flexibility. International Journal of Operations & Production Management, 38(3), 690-712. https://doi.org/10.1108/IJOPM-08-2015-0508
Daghar, A., Alinaghian, L., & Turner, N. (2021). The role of collaborative interorganizational relationships in supply chain risks: a systematic review using a social capital perspective. Supply Chain Management, 26(2), 279-296. https://doi.org/10.1108/SCM-04-2020-0177
Dubey, R., Gunasekaran, A. & Childe, S.J. (2019). Big data analytics capability in supply chain agility: The moderating effect of organizational flexibility. Management Decision, 57(8), 2092-2112. https://doi.org/10.1108/MD-01-2018-0119
Falandays, J.B., Spevack, S., Pärnamets, P. & Spivey, M. (2021). Decision-making in the human-machine interface. Frontier Psychology, 12, 624111. doi: 10.3389/fpsyg.2021.624111
Haesevoets, T., De Cremer, D., Dierckx, K., & Van Hiel, A. (2021). Human-machine collaboration in managerial decision making. Computers in Human Behavior, 119, 106730, https://doi.org/10.1016/j.chb.2021.106730
Hao, X., Demir, E., & Eyers, D. (2024). Exploring collaborative decision-making: A quasi-experimental study of human and Generative AI interaction. Technology in Society, 78, 102662, https://doi.org/10.1016/j.techsoc.2024.102662
Harianto, K.J., Tarigan, Z.J.H., Siagian, H., Basana, S.R. & Jie, F. (2024). The effect of digital ERP implementation, supply chain integration and supply chain flexibility on business performance. International Journal of Data and Network Science, 8(4), 2399-2414, DOI: 10.5267/j.ijdns.2024.5.017
Jain, R., Garg, N., & Khera, S.N. (2023). Effective human–AI work design for collaborative decision-making. Kybernetes, 52(11), 5017-5040. https://doi.org/10.1108/K-04-2022-0548
Jain, N., Gupta, V., Temperini, V., Meissner, D., & D’angelo, E. (2024). Human machine interactions: from past to future- a systematic literature review. Journal of Management History, 30(2), 263–302. https://doi.org/10.1108/JMH-12-2022-0085
Jeng, S.-L., Chieng, W.-H., & Chen, Y. (2021). Web-based human-machine interfaces of industrial controllers in single-page applications. Mobile Information Systems, 2021, 6668843. https://doi.org/10.1155/2021/6668843
Kosicki, T. & Thomessen, T. (2013). Cognitive human-machine interface applied in remote support for industrial robot systems. International Journal of Advanced Robotic Systems. 10(10). doi:10.5772/56296
Kumar, G., Subramanian, N., & Arputham, R.M. (2018). Missing link between sustainability collaborative strategy and supply chain performance: Role of dynamic capability. International Journal of Production Economics, 203, 96-109, https://doi.org/10.1016/j.ijpe.2018.05.031
Lai, P.-L., Su, D.-T., Tai, H.-H., & Yang, C.-C. (2020). The impact of collaborative decision-making on logistics service performance for container shipping services. Maritime Business Review, 5(2), 175-191. https://doi.org/10.1108/MABR-12-2019-0061
Levalle, R.R., & Nof, S.Y. (2015). A resilience by teaming framework for collaborative supply networks. Computers & Industrial Engineering, 90, 67-85, http://dx.doi.org/10.1016/j.cie.2015.08.017
Li, J.-M., Wu, T.-J., Wu, Y.J., & Goh, M. (2023). Systematic literature review of human-machine collaboration in organizations using bibliometric analysis. Management Decision, 61(10), 2920-2944, https://doi-org/10.1108/MD-09-2022-1183
Jiang, H. F. (2020). A collaborative decision-making system for production operation. American Journal of Industrial and Business Management, 10, 804–814. doi: 10.4236/ajibm.2020.104054.
Liu, T., You, H., Gkiotsalitis, K. & Cats, O. (2024). Human-Machine collaborative decision-making approach to scheduling customized buses with flexible departure times. Transportation Research Part A: Policy and Practice, 187, 104184, https://doi.org/10.1016/j.tra.2024.104184
Long (2016). A flow-based three-dimensional collaborative decision-making model for supply-chain networks. Knowledge-Based Systems, 97, 101-110, https://doi.org/10.1016/j.knosys.2016.01.012
Morgan, J., Halton, M., Qiao, Y., & Breslin, J.G. (2021). Industry 4.0 smart reconfigurable manufacturing machines. Journal of Manufacturing Systems, 59, 481–506. https://doi.org/10.1016/j.jmsy.2021.03.001
Mourtzis, D., Angelopoulos, J., & Panopoulos, N. (2023). The Future of the Human–Machine Interface (HMI) in Society 5.0. Future Internet, 15(5), 162. https://doi.org/10.3390/fi15050162
Mustafa, F.E., Ahmed, I., Basit, A., Alvi, U., Malik, S.H., Mahmood, A. and Ali, P.R. (2023). A review on effective alarm management systems for industrial process control: Barriers and opportunities. International Journal of Critical Infrastructure Protection, 41, 100599, https://doi.org/10.1016/j.ijcip.2023.100599
Nagarajan, V., Savitskie, K., Ranganathan, S., Sen, S., & Alexandrov, A. (2013). The effect of environmental uncertainty, information quality, and collaborative logistics on supply chain flexibility of small manufacturing firms in India. Asia Pacific Journal of Marketing and Logistics, 25(5), 784–802. https://doi.org/10.1108/APJML-09-2011-0065
Nematollahi, M., Hosseini-Motlagh, S.-M., & Heydari, J. (2017). Coordination of social responsibility and order quantity in a two-echelon supply chain: A collaborative decision-making perspective. International Journal of Production Economics, 184, 107–121, https://doi.org/10.1016/j.ijpe.2016.11.017
Rojo, A., Stevenson, M., Lloréns Montes, F.J. & Perez-Arostegui, M.N. (2018). Supply chain flexibility in dynamic environments: The enabling role of operational absorptive capacity and organizational learning. International Journal of Operations & Production Management, 38(3), 636-666. https://doi.org/10.1108/IJOPM-08-2016-0450
Sarkar, M. & Seo, Y.W. (2021). Renewable energy supply chain management with flexibility and automation in a production system. Journal of Cleaner Production, 324, 129149, https://doi.org/10.1016/j.jclepro.2021.129149
Shahab, M.A., Srinivasan, B., & Srinivasan, R. (2023). Enhancing human-machine interface design using cognitive metrics of process operators. Computer Aided Chemical Engineering, 52, 3513-3518, https://doi.org/10.1016/B978-0-443-15274-0.50561-8
Shukor, A.A.A., Newaz, M.S., Rahman, M.K. & Taha, A.Z. (2021). Supply chain integration and its impact on supply chain agility and organizational flexibility in manufacturing firms. International Journal of Emerging Markets, 16(8), 1721-1744. https://doi.org/10.1108/IJOEM-04-2020-0418
Siagian, H., Tarigan, Z.J.H., & Jie, F. (2021). Supply chain integration enables resilience, flexibility, and innovation to improve business performance in the COVID-19 era. Sustainability, 13, 4669. https://doi.org/10.3390/su13094669
Singh, H.P., & Kumar, P. (2021). Developments in the human-machine interface technologies and their applications: A review. Journal of Medical Engineering & Technology, 45(7), 552-573, https://doi.org/10.1080/03091902.2021.1936237
Sitompul, T.A. (2022). Human-machine interface for remote crane operation: a review. Multimodal Technologies and Interaction. 6(6),45. https://doi.org/10.3390/mti6060045
Soesetyo, Z.E., Tarigan, Z.J.H., Siagian, H., Basana, S.R. & Jie, F. (2024). The role of top management commitment to improve operational performance through IT adoption, supply chain integration, and green supply chain management. Decision Science Letters, 13(3), 647-662, DOI: 10.5267/j.dsl.2024.4.007
Somon, B., Campagne, A., Delorme, A., & Berberian, B. (2019). Human or not human? Performance monitoring ERPs during human agent and machine supervision. Neurolmage, 186, 266-277, doi.org/10.1016/j.neuroimage.2018.11.013
Tarigan, Z.J.H. (2018). The impact of organization commitment to process and product innovation in improving operational performance. International Journal of Business and Society, 19(2), 335-346
Tarigan, R.S., Tarigan, Z.V.B., Maer, M.N.D., Tarigan, Z.J.H., & Ferry Jie, F. (2024). The influence of information technology on supply chain resilience through purchasing strategy, production flexibility, and supply chain responsiveness. Decision Science Letters, 13(4), 791-806, DOI: 10.5267/j.dsl.2024.9.001
Tarigan, Z.J.H., & Siagian, H. (2021). The effects of strategic planning, purchasing strategy and strategic partnership on operational performance. Uncertain Supply Chain Management, 9(2), 363-372, DOI: 10.5267/j.uscm.2021.2.006
Truong, H.Q., Sameiro, M., Fernandes, A.C., Sampaio, P., Duong, B.A.T., Duong, H.H., & Vilhenac, E. (2017). Supply chain management practices and firms' operational performance. International Journal of Quality & Reliability Management, 34 (2), 176-193, https://doi.org/10.1108/IJQRM-05-2015-0072
Wang, B-J, Lin C-H, Lee W-C, & Hsiao C-C. (2023a). Development of a bamboo toothbrush handle machine with a human-machine interactive interface for optimizing process conditions. Sustainability, 15(14):11459. https://doi.org/10.3390/su151411459
Wang, H., Long, Z., Chen, J., Guo, Y., & Wang, A. (2023b). Collaborative decision-making in supply chain management: A review and bibliometric analysis. Cogent Engineering, 10(1). https://doi.org/10.1080/23311916.2023.2196823
Willis, G., Genchev, S.E., & Chen, H. (2016). Supply chain learning, integration, and flexibility performance: an empirical study in India. The International Journal of Logistics Management, 27(3), 755-769. https://doi.org/10.1108/IJLM-03-2014-0042
Wu, I.-L., Chuang, C.-H., & Hsu, C.-H. 2014. Information sharing and collaborative behaviors in enabling supply chain performance: A social exchange perspective. International Journal Production Economics, 148,122-132. http://dx.doi.org/10.1016/j.ijpe.2013.09.016
Wu, T.-J., Li, J.-M., & Wu, Y.J. (2022). Employees' job insecurity perception and unsafe behaviours in human–machine collaboration. Management Decision, 60(9), 2409-2432. https://doi.org/10.1108/MD-09-2021-1257
Xiong, Y., Tang, Y., Kim, S., & Rosen, D.W. (2023). Human-machine collaborative additive manufacturing. Journal of Manufacturing Systems, 66, 82-91. https://doi.org/10.1016/j.jmsy.2022.12.004
Yu, K., Luo, B.N., Feng, X., & Liu, J. (2018). Supply chain information integration, flexibility, and operational performance: An archival search and content analysis. The International Journal of Logistics Management, 29(1), 340-364. https://doi.org/10.1108/IJLM-08-2016-0185
Zhang, Y., Hu, Z., Hang, P., Lou, S., & Chen Lv. (2024). Human–machine cooperative decision-making and planning for automated vehicles using spatial projection of hand gestures. Advanced Engineering Informatics, 62, Part C, 102864, https://doi.org/10.1016/j.aei.2024.102864
Alsubaie, F., & Aldoukhi, M. (2024). Using machine learning algorithms with improved accuracy to analyze and predict employee attrition. Decision Science Letters, 13(1), 1-18, DOI: 10.5267/j.dsl.2023.12.006
Ansari, F., Erol, S. & Sihn, W. (2018). Rethinking human machine learning in Industry 4.0: how dos the paradigm shift treat the role of human learning? Procedia Manufacturing, 23, 117-122, https://doi.org/10.1016/j.promfg.2018.04.003
Arikat, Z.M.A. (2024). The Role of business intelligence in enhancing the performance of supply chains in Jordan. Journal of Ecohumanism, 3(8), 2040-2053, DOI: https://doi.org/10.62754/joe.v3i8.4885
Basana, S.R., Malelak, M.I., Suprapto, W., Tarigan, Z.J.H., Tarigan, Z.V.B., & Doron, R.O. (2025). The influence of information technology integration on firm performance through supply chain quality and supply chain resilience. Decision Science Letters, 14(1), 225-238, DOI: 10.5267/j.dsl.2024.9.004
Beltramini, E. (2018). Human vulnerability and robo-advisory: An application of Coeckelbergh’s vulnerability to the machine-human interface. Baltic Journal of Management, 13(2), 250-263. https://doi-org/10.1108/BJM-10-2017-0315
Bouyam, C., & Punsawad, Y. (2022). Human–machine interface-based wheelchair control using piezoelectric sensors based on face and tongue movements. Heliyon, 8 (11), e11679, https://doi.org/10.1016/j.heliyon.2022.e11679
Cao, S., Bryceson, K., & Hine, D. (2021). Collaborative risk management in decentralized multi-tier global food supply chains: an exploratory study. The International Journal of Logistics Management, 32(3), 1050–1067. https://doi.org/10.1108/IJLM-07-2020-0278
Cao, S., Powell, W., Foth, M., Natanelov, V., Miller, T., & Dulleck, U. (2021). Strengthening consumer trust in beef supply chain traceability with a blockchain-based human-machine reconcile mechanism. Computers and Electronics in Agriculture, 180, 105886, https://doi.org/10.1016/j.compag.2020.105886
Chaudhuri, A., Boer, H. & Taran, Y. (2018). Supply chain integration, risk management and manufacturing flexibility. International Journal of Operations & Production Management, 38(3), 690-712. https://doi.org/10.1108/IJOPM-08-2015-0508
Daghar, A., Alinaghian, L., & Turner, N. (2021). The role of collaborative interorganizational relationships in supply chain risks: a systematic review using a social capital perspective. Supply Chain Management, 26(2), 279-296. https://doi.org/10.1108/SCM-04-2020-0177
Dubey, R., Gunasekaran, A. & Childe, S.J. (2019). Big data analytics capability in supply chain agility: The moderating effect of organizational flexibility. Management Decision, 57(8), 2092-2112. https://doi.org/10.1108/MD-01-2018-0119
Falandays, J.B., Spevack, S., Pärnamets, P. & Spivey, M. (2021). Decision-making in the human-machine interface. Frontier Psychology, 12, 624111. doi: 10.3389/fpsyg.2021.624111
Haesevoets, T., De Cremer, D., Dierckx, K., & Van Hiel, A. (2021). Human-machine collaboration in managerial decision making. Computers in Human Behavior, 119, 106730, https://doi.org/10.1016/j.chb.2021.106730
Hao, X., Demir, E., & Eyers, D. (2024). Exploring collaborative decision-making: A quasi-experimental study of human and Generative AI interaction. Technology in Society, 78, 102662, https://doi.org/10.1016/j.techsoc.2024.102662
Harianto, K.J., Tarigan, Z.J.H., Siagian, H., Basana, S.R. & Jie, F. (2024). The effect of digital ERP implementation, supply chain integration and supply chain flexibility on business performance. International Journal of Data and Network Science, 8(4), 2399-2414, DOI: 10.5267/j.ijdns.2024.5.017
Jain, R., Garg, N., & Khera, S.N. (2023). Effective human–AI work design for collaborative decision-making. Kybernetes, 52(11), 5017-5040. https://doi.org/10.1108/K-04-2022-0548
Jain, N., Gupta, V., Temperini, V., Meissner, D., & D’angelo, E. (2024). Human machine interactions: from past to future- a systematic literature review. Journal of Management History, 30(2), 263–302. https://doi.org/10.1108/JMH-12-2022-0085
Jeng, S.-L., Chieng, W.-H., & Chen, Y. (2021). Web-based human-machine interfaces of industrial controllers in single-page applications. Mobile Information Systems, 2021, 6668843. https://doi.org/10.1155/2021/6668843
Kosicki, T. & Thomessen, T. (2013). Cognitive human-machine interface applied in remote support for industrial robot systems. International Journal of Advanced Robotic Systems. 10(10). doi:10.5772/56296
Kumar, G., Subramanian, N., & Arputham, R.M. (2018). Missing link between sustainability collaborative strategy and supply chain performance: Role of dynamic capability. International Journal of Production Economics, 203, 96-109, https://doi.org/10.1016/j.ijpe.2018.05.031
Lai, P.-L., Su, D.-T., Tai, H.-H., & Yang, C.-C. (2020). The impact of collaborative decision-making on logistics service performance for container shipping services. Maritime Business Review, 5(2), 175-191. https://doi.org/10.1108/MABR-12-2019-0061
Levalle, R.R., & Nof, S.Y. (2015). A resilience by teaming framework for collaborative supply networks. Computers & Industrial Engineering, 90, 67-85, http://dx.doi.org/10.1016/j.cie.2015.08.017
Li, J.-M., Wu, T.-J., Wu, Y.J., & Goh, M. (2023). Systematic literature review of human-machine collaboration in organizations using bibliometric analysis. Management Decision, 61(10), 2920-2944, https://doi-org/10.1108/MD-09-2022-1183
Jiang, H. F. (2020). A collaborative decision-making system for production operation. American Journal of Industrial and Business Management, 10, 804–814. doi: 10.4236/ajibm.2020.104054.
Liu, T., You, H., Gkiotsalitis, K. & Cats, O. (2024). Human-Machine collaborative decision-making approach to scheduling customized buses with flexible departure times. Transportation Research Part A: Policy and Practice, 187, 104184, https://doi.org/10.1016/j.tra.2024.104184
Long (2016). A flow-based three-dimensional collaborative decision-making model for supply-chain networks. Knowledge-Based Systems, 97, 101-110, https://doi.org/10.1016/j.knosys.2016.01.012
Morgan, J., Halton, M., Qiao, Y., & Breslin, J.G. (2021). Industry 4.0 smart reconfigurable manufacturing machines. Journal of Manufacturing Systems, 59, 481–506. https://doi.org/10.1016/j.jmsy.2021.03.001
Mourtzis, D., Angelopoulos, J., & Panopoulos, N. (2023). The Future of the Human–Machine Interface (HMI) in Society 5.0. Future Internet, 15(5), 162. https://doi.org/10.3390/fi15050162
Mustafa, F.E., Ahmed, I., Basit, A., Alvi, U., Malik, S.H., Mahmood, A. and Ali, P.R. (2023). A review on effective alarm management systems for industrial process control: Barriers and opportunities. International Journal of Critical Infrastructure Protection, 41, 100599, https://doi.org/10.1016/j.ijcip.2023.100599
Nagarajan, V., Savitskie, K., Ranganathan, S., Sen, S., & Alexandrov, A. (2013). The effect of environmental uncertainty, information quality, and collaborative logistics on supply chain flexibility of small manufacturing firms in India. Asia Pacific Journal of Marketing and Logistics, 25(5), 784–802. https://doi.org/10.1108/APJML-09-2011-0065
Nematollahi, M., Hosseini-Motlagh, S.-M., & Heydari, J. (2017). Coordination of social responsibility and order quantity in a two-echelon supply chain: A collaborative decision-making perspective. International Journal of Production Economics, 184, 107–121, https://doi.org/10.1016/j.ijpe.2016.11.017
Rojo, A., Stevenson, M., Lloréns Montes, F.J. & Perez-Arostegui, M.N. (2018). Supply chain flexibility in dynamic environments: The enabling role of operational absorptive capacity and organizational learning. International Journal of Operations & Production Management, 38(3), 636-666. https://doi.org/10.1108/IJOPM-08-2016-0450
Sarkar, M. & Seo, Y.W. (2021). Renewable energy supply chain management with flexibility and automation in a production system. Journal of Cleaner Production, 324, 129149, https://doi.org/10.1016/j.jclepro.2021.129149
Shahab, M.A., Srinivasan, B., & Srinivasan, R. (2023). Enhancing human-machine interface design using cognitive metrics of process operators. Computer Aided Chemical Engineering, 52, 3513-3518, https://doi.org/10.1016/B978-0-443-15274-0.50561-8
Shukor, A.A.A., Newaz, M.S., Rahman, M.K. & Taha, A.Z. (2021). Supply chain integration and its impact on supply chain agility and organizational flexibility in manufacturing firms. International Journal of Emerging Markets, 16(8), 1721-1744. https://doi.org/10.1108/IJOEM-04-2020-0418
Siagian, H., Tarigan, Z.J.H., & Jie, F. (2021). Supply chain integration enables resilience, flexibility, and innovation to improve business performance in the COVID-19 era. Sustainability, 13, 4669. https://doi.org/10.3390/su13094669
Singh, H.P., & Kumar, P. (2021). Developments in the human-machine interface technologies and their applications: A review. Journal of Medical Engineering & Technology, 45(7), 552-573, https://doi.org/10.1080/03091902.2021.1936237
Sitompul, T.A. (2022). Human-machine interface for remote crane operation: a review. Multimodal Technologies and Interaction. 6(6),45. https://doi.org/10.3390/mti6060045
Soesetyo, Z.E., Tarigan, Z.J.H., Siagian, H., Basana, S.R. & Jie, F. (2024). The role of top management commitment to improve operational performance through IT adoption, supply chain integration, and green supply chain management. Decision Science Letters, 13(3), 647-662, DOI: 10.5267/j.dsl.2024.4.007
Somon, B., Campagne, A., Delorme, A., & Berberian, B. (2019). Human or not human? Performance monitoring ERPs during human agent and machine supervision. Neurolmage, 186, 266-277, doi.org/10.1016/j.neuroimage.2018.11.013
Tarigan, Z.J.H. (2018). The impact of organization commitment to process and product innovation in improving operational performance. International Journal of Business and Society, 19(2), 335-346
Tarigan, R.S., Tarigan, Z.V.B., Maer, M.N.D., Tarigan, Z.J.H., & Ferry Jie, F. (2024). The influence of information technology on supply chain resilience through purchasing strategy, production flexibility, and supply chain responsiveness. Decision Science Letters, 13(4), 791-806, DOI: 10.5267/j.dsl.2024.9.001
Tarigan, Z.J.H., & Siagian, H. (2021). The effects of strategic planning, purchasing strategy and strategic partnership on operational performance. Uncertain Supply Chain Management, 9(2), 363-372, DOI: 10.5267/j.uscm.2021.2.006
Truong, H.Q., Sameiro, M., Fernandes, A.C., Sampaio, P., Duong, B.A.T., Duong, H.H., & Vilhenac, E. (2017). Supply chain management practices and firms' operational performance. International Journal of Quality & Reliability Management, 34 (2), 176-193, https://doi.org/10.1108/IJQRM-05-2015-0072
Wang, B-J, Lin C-H, Lee W-C, & Hsiao C-C. (2023a). Development of a bamboo toothbrush handle machine with a human-machine interactive interface for optimizing process conditions. Sustainability, 15(14):11459. https://doi.org/10.3390/su151411459
Wang, H., Long, Z., Chen, J., Guo, Y., & Wang, A. (2023b). Collaborative decision-making in supply chain management: A review and bibliometric analysis. Cogent Engineering, 10(1). https://doi.org/10.1080/23311916.2023.2196823
Willis, G., Genchev, S.E., & Chen, H. (2016). Supply chain learning, integration, and flexibility performance: an empirical study in India. The International Journal of Logistics Management, 27(3), 755-769. https://doi.org/10.1108/IJLM-03-2014-0042
Wu, I.-L., Chuang, C.-H., & Hsu, C.-H. 2014. Information sharing and collaborative behaviors in enabling supply chain performance: A social exchange perspective. International Journal Production Economics, 148,122-132. http://dx.doi.org/10.1016/j.ijpe.2013.09.016
Wu, T.-J., Li, J.-M., & Wu, Y.J. (2022). Employees' job insecurity perception and unsafe behaviours in human–machine collaboration. Management Decision, 60(9), 2409-2432. https://doi.org/10.1108/MD-09-2021-1257
Xiong, Y., Tang, Y., Kim, S., & Rosen, D.W. (2023). Human-machine collaborative additive manufacturing. Journal of Manufacturing Systems, 66, 82-91. https://doi.org/10.1016/j.jmsy.2022.12.004
Yu, K., Luo, B.N., Feng, X., & Liu, J. (2018). Supply chain information integration, flexibility, and operational performance: An archival search and content analysis. The International Journal of Logistics Management, 29(1), 340-364. https://doi.org/10.1108/IJLM-08-2016-0185
Zhang, Y., Hu, Z., Hang, P., Lou, S., & Chen Lv. (2024). Human–machine cooperative decision-making and planning for automated vehicles using spatial projection of hand gestures. Advanced Engineering Informatics, 62, Part C, 102864, https://doi.org/10.1016/j.aei.2024.102864