An approach for analysing supply chain complexity drivers through interpretive structural modelling

被引:19
|
作者
Piya, Sujan [1 ]
Shamsuzzoha, Ahm [2 ]
Khadem, Mohammad [1 ]
机构
[1] Sultan Qaboos Univ, Dept Mech & Ind Engn, Muscat, Oman
[2] Univ Vaasa, Sch Technol & Innovat, Vaasa, Finland
关键词
Supply chain complexity; complexity drivers; driver classification; interpretive structural modelling (ISM); ISM digraph; PRODUCT VARIETY; GLOBAL COMPLEXITY; PERFORMANCE; MANAGEMENT; IMPACT; RISK; SYSTEM; COMPETITIVENESS; ARCHITECTURE; INTEGRATION;
D O I
10.1080/13675567.2019.1691514
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Today's greater product variety, shorter product life cycle, and lower production costs are pushing companies to look beyond their own boundaries, thereby, creating complexity in the management of the supply chain. To manage such complexity, it is imperative that the management understand the associated complexity drivers and their interrelationships. This study identified twenty-three drivers responsible for supply chain complexity and classified them by using various criteria. In addition, the study presents a structural model using interpretive structural modelling (ISM) methodology to understand the inter-relationships between one driver to another. The research findings showed that drivers such as customer need, competitor action, and government regulation are beyond the control of supply chain partners, and have found the highest dominance with respect to supply chain complexity. Conversely, drivers related to tactical issues such as production planning and control, logistics and transportation, forecasting error, and marketing and sales are found to be the dependent drivers. Remaining drivers, such as company culture, number of suppliers, product variety, and organisational structure fall between the former two classifications. These drivers are related to strategic issues and require action from the upper level of the management hierarchy.
引用
收藏
页码:311 / 336
页数:26
相关论文
共 50 条
  • [21] An interpretive structural modeling of drivers and barriers of sustainable supply chain management A case of stone industry
    Soni, Gunjan
    Prakash, Surya
    Kumar, Himanshu
    Singh, Surya Prakash
    Jain, Vipul
    Dhami, Sukhdeep Singh
    MANAGEMENT OF ENVIRONMENTAL QUALITY, 2020, 31 (05) : 1071 - 1090
  • [22] Interpretive structural modeling of supply chain risks
    Pfohl, Hans-Christian
    Gallus, Philipp
    Thomas, David
    INTERNATIONAL JOURNAL OF PHYSICAL DISTRIBUTION & LOGISTICS MANAGEMENT, 2011, 41 (09) : 839 - 859
  • [23] Modelling the drivers of intention to use energy-efficient appliances through interpretive structural modelling technique
    Arora, Manita
    Gupta, Neha
    Gupta, Srikant
    Dangi, Amit
    INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT, 2024, : 5314 - 5328
  • [24] Application of Interpretive Structural Modelling to establish Interrelationships among the Enablers of Supply Chain Competitiveness
    Verma, Ajay
    Seth, Nitin
    Singhal, Nisha
    MATERIALS TODAY-PROCEEDINGS, 2018, 5 (02) : 4818 - 4823
  • [25] Modelling challenges of blockchain technology enabled healthcare sustainable supply chain management: a modified-total interpretive structural modelling approach
    Vishwakarma, Amit
    Dangayach, G. S.
    Meena, M. L.
    Jindal, Manish Kumar
    Gupta, Sumit
    Jagtap, Sandeep
    OPERATIONS MANAGEMENT RESEARCH, 2023, 16 (04) : 1781 - 1790
  • [26] Modelling challenges of blockchain technology enabled healthcare sustainable supply chain management: a modified-total interpretive structural modelling approach
    Amit Vishwakarma
    G. S. Dangayach
    M. L. Meena
    Manish Kumar Jindal
    Sumit Gupta
    Sandeep Jagtap
    Operations Management Research, 2023, 16 : 1781 - 1790
  • [27] Identification and evaluation of the contextual relationship among barriers to the circular supply chain in the Pakistani context - an interpretive structural modelling approach
    Shaikh, Abdul Rehman
    Qazi, Asad Ali
    Appolloni, Andrea
    PRODUCTION PLANNING & CONTROL, 2024, 35 (10) : 1148 - 1163
  • [28] Interpretive Structural Modelling Approach to Evaluate Knowledge Sharing Enablers in Circular Supply Chain: A Study of The Indian Manufacturing Sector
    Ganguly, Anirban
    Farr, John V.
    JOURNAL OF INFORMATION & KNOWLEDGE MANAGEMENT, 2024,
  • [29] Analysing the Antecedents of Entrepreneurial Bootstrapping and Bricolage: A Modified Total Interpretive Structural Modelling and MICMAC Approach
    Singh, Mansi
    Dhir, Sanjay
    Mishra, Harsh
    JOURNAL OF ENTREPRENEURSHIP, 2023, 32 (01): : 7 - 38
  • [30] Knowledge Sharing in the Supply Chain Networks: A Perspective of Supply Chain Complexity Drivers
    Ahmed, Hareer Fatima
    Hosseinian-Far, Amin
    Khandan, Rasoul
    Sarwar, Dilshad
    E-Fatima, Khushboo
    LOGISTICS-BASEL, 2022, 6 (03):