IDEAS home Printed from https://ideas.repec.org/a/eee/jomega/v105y2021ics0305048321001110.html
   My bibliography  Save this article

Risks associated with the implementation of big data analytics in sustainable supply chains

Author

Listed:
  • Kusi-Sarpong, Simonov
  • Orji, Ifeyinwa Juliet
  • Gupta, Himanshu
  • Kunc, Martin

Abstract

In the current era of unprecedented technological advancements, the effective use of big data analytics has become a fundamental requirement for organizations and provides opportunities for sustainable supply chains to increase competitiveness and enhance performance and productivity. However, implementing big data analysis entails risks so it is important that supply chain players develop deeper understanding of the risks in order to generate innovative strategies to overcome them. This paper therefore proposes a framework for the risks that may be encountered by organizations during the implementation of big data analytics within sustainable supply chains and further proposes overcoming strategies to control their occurrences. The best-worst method (BWM) is applied to assist in evaluating both the risks and overcoming strategies. The method is applied in the Indian automobile manufacturing industry which is the fifth-largest in the world, contributing 8% to Indian GDP and a major source of environmental pollution. The results indicate that technological risks followed by human and organizational risks are the major risks related to big data analytics implementation in supply chains. Moreover, the ‘presence of commoditized hardware’ coupled with ‘skill development strategies’ are considered the most significant strategies for overcoming risks related to big data analytics implementation. The results of this study provide a better understanding and controlling of the nature of the inherent risks and pathways to achieve successful big data analytics implementation within supply chains.

Suggested Citation

  • Kusi-Sarpong, Simonov & Orji, Ifeyinwa Juliet & Gupta, Himanshu & Kunc, Martin, 2021. "Risks associated with the implementation of big data analytics in sustainable supply chains," Omega, Elsevier, vol. 105(C).
    • Handle: RePEc:eee:jomega:v:105:y:2021:i:c:s0305048321001110
    DOI: 10.1016/j.omega.2021.102502
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0305048321001110
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.omega.2021.102502?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Tabesh, Pooya & Mousavidin, Elham & Hasani, Sona, 2019. "Implementing big data strategies: A managerial perspective," Business Horizons, Elsevier, vol. 62(3), pages 347-358.
    2. Hazen, Benjamin T. & Bradley, Randy V. & Bell, John E. & In, Joonhwan & Byrd, Terry A., 2017. "Enterprise architecture: A competence-based approach to achieving agility and firm performance," International Journal of Production Economics, Elsevier, vol. 193(C), pages 566-577.
    3. Liu, Yangyang & Shen, Zhongqi & Tang, Xiaowei & Lian, Hongbo & Li, Jiarui & Gong, Jinxia, 2019. "Worst-case conditional value-at-risk based bidding strategy for wind-hydro hybrid systems under probability distribution uncertainties," Applied Energy, Elsevier, vol. 256(C).
    4. Baozhuang Niu & Zongbao Zou, 2017. "Better Demand Signal, Better Decisions? Evaluation of Big Data in a Licensed Remanufacturing Supply Chain with Environmental Risk Considerations," Risk Analysis, John Wiley & Sons, vol. 37(8), pages 1550-1565, August.
    5. Lang, Matthias, 2017. "Legal uncertainty as a welfare enhancing screen," European Economic Review, Elsevier, vol. 91(C), pages 274-289.
    6. Nam, Taewoo, 2019. "Technology usage, expected job sustainability, and perceived job insecurity," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 155-165.
    7. Katsoulacos, Yannis & Ulph, David, 2017. "Regulatory decision errors, Legal Uncertainty and welfare: A general treatment," International Journal of Industrial Organization, Elsevier, vol. 53(C), pages 326-352.
    8. Gupta, Himanshu & Barua, Mukesh Kumar, 2016. "Identifying enablers of technological innovation for Indian MSMEs using best–worst multi criteria decision making method," Technological Forecasting and Social Change, Elsevier, vol. 107(C), pages 69-79.
    9. Sivarajah, Uthayasankar & Kamal, Muhammad Mustafa & Irani, Zahir & Weerakkody, Vishanth, 2017. "Critical analysis of Big Data challenges and analytical methods," Journal of Business Research, Elsevier, vol. 70(C), pages 263-286.
    10. Mangla, Sachin Kumar & Luthra, Sunil & Rich, Nick & Kumar, Divesh & Rana, Nripendra P. & Dwivedi, Yogesh K., 2018. "Enablers to implement sustainable initiatives in agri-food supply chains," International Journal of Production Economics, Elsevier, vol. 203(C), pages 379-393.
    11. Govindan, Kannan & Rajeev, A. & Padhi, Sidhartha S. & Pati, Rupesh K., 2020. "Supply chain sustainability and performance of firms: A meta-analysis of the literature," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 137(C).
    12. Gunasekaran, Angappa & Papadopoulos, Thanos & Dubey, Rameshwar & Wamba, Samuel Fosso & Childe, Stephen J. & Hazen, Benjamin & Akter, Shahriar, 2017. "Big data and predictive analytics for supply chain and organizational performance," Journal of Business Research, Elsevier, vol. 70(C), pages 308-317.
    13. Ali Jamshidi & Shahrzad Faghih‐Roohi & Siamak Hajizadeh & Alfredo Núñez & Robert Babuska & Rolf Dollevoet & Zili Li & Bart De Schutter, 2017. "A Big Data Analysis Approach for Rail Failure Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 37(8), pages 1495-1507, August.
    14. Orji, Ifeyinwa Juliet & Liu, Shaoxuan, 2020. "A dynamic perspective on the key drivers of innovation-led lean approaches to achieve sustainability in manufacturing supply chain," International Journal of Production Economics, Elsevier, vol. 219(C), pages 480-496.
    15. Peng, Yi & Kou, Gang & Wang, Guoxun & Shi, Yong, 2011. "FAMCDM: A fusion approach of MCDM methods to rank multiclass classification algorithms," Omega, Elsevier, vol. 39(6), pages 677-689, December.
    16. Chen, Yi-Ting & Sun, Edward W. & Lin, Yi-Bing, 2020. "Merging anomalous data usage in wireless mobile telecommunications: Business analytics with a strategy-focused data-driven approach for sustainability," European Journal of Operational Research, Elsevier, vol. 281(3), pages 687-705.
    17. Delic, Mia & Eyers, Daniel R., 2020. "The effect of additive manufacturing adoption on supply chain flexibility and performance: An empirical analysis from the automotive industry," International Journal of Production Economics, Elsevier, vol. 228(C).
    18. Arunachalam, Deepak & Kumar, Niraj & Kawalek, John Paul, 2018. "Understanding big data analytics capabilities in supply chain management: Unravelling the issues, challenges and implications for practice," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 416-436.
    19. Simonov Kusi-Sarpong & Himanshu Gupta & Joseph Sarkis, 2019. "A supply chain sustainability innovation framework and evaluation methodology," International Journal of Production Research, Taylor & Francis Journals, vol. 57(7), pages 1990-2008, April.
    20. Yadegaridehkordi, Elaheh & Hourmand, Mehdi & Nilashi, Mehrbakhsh & Shuib, Liyana & Ahani, Ali & Ibrahim, Othman, 2018. "Influence of big data adoption on manufacturing companies' performance: An integrated DEMATEL-ANFIS approach," Technological Forecasting and Social Change, Elsevier, vol. 137(C), pages 199-210.
    21. Duan, Yanqing & Cao, Guangming & Edwards, John S., 2020. "Understanding the impact of business analytics on innovation," European Journal of Operational Research, Elsevier, vol. 281(3), pages 673-686.
    22. Xiaoyan Su & Sankaran Mahadevan & Peida Xu & Yong Deng, 2015. "Dependence Assessment in Human Reliability Analysis Using Evidence Theory and AHP," Risk Analysis, John Wiley & Sons, vol. 35(7), pages 1296-1316, July.
    23. Wang, Zhenfeng & Xu, Guangyin & Lin, Ruojue & Wang, Heng & Ren, Jingzheng, 2019. "Energy performance contracting, risk factors, and policy implications: Identification and analysis of risks based on the best-worst network method," Energy, Elsevier, vol. 170(C), pages 1-13.
    24. Dubey, Rameshwar & Gunasekaran, Angappa & Childe, Stephen J. & Papadopoulos, Thanos & Luo, Zongwei & Wamba, Samuel Fosso & Roubaud, David, 2019. "Can big data and predictive analytics improve social and environmental sustainability?," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 534-545.
    25. Zhan, Yuanzhu & Tan, Kim Hua, 2020. "An analytic infrastructure for harvesting big data to enhance supply chain performance," European Journal of Operational Research, Elsevier, vol. 281(3), pages 559-574.
    26. Byun, Sang-Eun & Han, Siyuan & Kim, Hyejeong & Centrallo, Carol, 2020. "US small retail businesses’ perception of competition: Looking through a lens of fear, confidence, or cooperation," Journal of Retailing and Consumer Services, Elsevier, vol. 52(C).
    27. Ifeyinwa Juliet Orji & Simonov Kusi-Sarpong & Himanshu Gupta, 2020. "The critical success factors of using social media for supply chain social sustainability in the freight logistics industry," International Journal of Production Research, Taylor & Francis Journals, vol. 58(5), pages 1522-1539, March.
    28. Orji, Ifeyinwa Juliet & Kusi-Sarpong, Simonov & Gupta, Himanshu & Okwu, Modestus, 2019. "Evaluating challenges to implementing eco-innovation for freight logistics sustainability in Nigeria," Transportation Research Part A: Policy and Practice, Elsevier, vol. 129(C), pages 288-305.
    29. Nagesh Shukla & Senevi Kiridena, 2016. "A fuzzy rough sets-based multi-agent analytics framework for dynamic supply chain configuration," International Journal of Production Research, Taylor & Francis Journals, vol. 54(23), pages 6984-6996, December.
    30. Shirish Jeble & Rameshwar Dubey & Stephen J. Childe & Thanos Papadopoulos & David Roubaud & Anand Prakash, 2018. "Impact of big data and predictive analytics capability on supply chain sustainability," Post-Print hal-02061341, HAL.
    31. Mi, Xiaomei & Tang, Ming & Liao, Huchang & Shen, Wenjing & Lev, Benjamin, 2019. "The state-of-the-art survey on integrations and applications of the best worst method in decision making: Why, what, what for and what's next?," Omega, Elsevier, vol. 87(C), pages 205-225.
    32. Kusi-Sarpong, Simonov & Sarkis, Joseph & Wang, Xuping, 2016. "Assessing green supply chain practices in the Ghanaian mining industry: A framework and evaluation," International Journal of Production Economics, Elsevier, vol. 181(PB), pages 325-341.
    33. Kusi-Sarpong, Simonov & Bai, Chunguang & Sarkis, Joseph & Wang, Xuping, 2015. "Green supply chain practices evaluation in the mining industry using a joint rough sets and fuzzy TOPSIS methodology," Resources Policy, Elsevier, vol. 46(P1), pages 86-100.
    34. Amankwah-Amoah, Joseph, 2019. "Big data analytics and business failures in data-Rich environments: An organizing framework," MPRA Paper 91264, University Library of Munich, Germany.
    35. Tim, Yenni & Hallikainen, Petri & Pan, Shan L & Tamm, Toomas, 2020. "Actualizing business analytics for organizational transformation: A case study of Rovio Entertainment," European Journal of Operational Research, Elsevier, vol. 281(3), pages 642-655.
    36. Barceló, Cristina & Villanueva, Ernesto, 2016. "The response of household wealth to the risk of job loss: Evidence from differences in severance payments," Labour Economics, Elsevier, vol. 39(C), pages 35-54.
    37. Yadlapalli, Aswini & Rahman, Shams & Gunasekaran, Angappa, 2018. "Socially responsible governance mechanisms for manufacturing firms in apparel supply chains," International Journal of Production Economics, Elsevier, vol. 196(C), pages 135-149.
    38. Tzu Yang Loh & Mario P. Brito & Neil Bose & Jingjing Xu & Kiril Tenekedjiev, 2020. "Fuzzy System Dynamics Risk Analysis (FuSDRA) of Autonomous Underwater Vehicle Operations in the Antarctic," Risk Analysis, John Wiley & Sons, vol. 40(4), pages 818-841, April.
    39. Roßmann, Bernhard & Canzaniello, Angelo & von der Gracht, Heiko & Hartmann, Evi, 2018. "The future and social impact of Big Data Analytics in Supply Chain Management: Results from a Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 135-149.
    40. Sheng, Jie & Amankwah-Amoah, Joseph & Wang, Xiaojun, 2017. "A multidisciplinary perspective of big data in management research," International Journal of Production Economics, Elsevier, vol. 191(C), pages 97-112.
    41. Stefan Seuring & Martin Müller, 2008. "Core issues in sustainable supply chain management – a Delphi study," Business Strategy and the Environment, Wiley Blackwell, vol. 17(8), pages 455-466, December.
    42. Wilhelm, Miriam & Blome, Constantin & Wieck, Ellen & Xiao, Cheng Yong, 2016. "Implementing sustainability in multi-tier supply chains: Strategies and contingencies in managing sub-suppliers," International Journal of Production Economics, Elsevier, vol. 182(C), pages 196-212.
    43. Tan, Kim Hua & Zhan, YuanZhu & Ji, Guojun & Ye, Fei & Chang, Chingter, 2015. "Harvesting big data to enhance supply chain innovation capabilities: An analytic infrastructure based on deduction graph," International Journal of Production Economics, Elsevier, vol. 165(C), pages 223-233.
    44. Theißen, Sebastian & Spinler, Stefan, 2014. "Strategic analysis of manufacturer-supplier partnerships: An ANP model for collaborative CO2 reduction management," European Journal of Operational Research, Elsevier, vol. 233(2), pages 383-397.
    45. Nilashi, Mehrbakhsh & Ahmadi, Hossein & Ahani, Ali & Ravangard, Ramin & Ibrahim, Othman bin, 2016. "Determining the importance of Hospital Information System adoption factors using Fuzzy Analytic Network Process (ANP)," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 244-264.
    46. Giannakis, Mihalis & Papadopoulos, Thanos, 2016. "Supply chain sustainability: A risk management approach," International Journal of Production Economics, Elsevier, vol. 171(P4), pages 455-470.
    47. Van Nguyen, Truong & Zhou, Li & Chong, Alain Yee Loong & Li, Boying & Pu, Xiaodie, 2020. "Predicting customer demand for remanufactured products: A data-mining approach," European Journal of Operational Research, Elsevier, vol. 281(3), pages 543-558.
    48. Mikalef, Patrick & Boura, Maria & Lekakos, George & Krogstie, John, 2019. "Big data analytics and firm performance: Findings from a mixed-method approach," Journal of Business Research, Elsevier, vol. 98(C), pages 261-276.
    49. Rezaei, Jafar, 2016. "Best-worst multi-criteria decision-making method: Some properties and a linear model," Omega, Elsevier, vol. 64(C), pages 126-130.
    50. Rezaei, Jafar, 2015. "Best-worst multi-criteria decision-making method," Omega, Elsevier, vol. 53(C), pages 49-57.
    51. Zahiri, Behzad & Zhuang, Jun & Mohammadi, Mehrdad, 2017. "Toward an integrated sustainable-resilient supply chain: A pharmaceutical case study," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 103(C), pages 109-142.
    52. Mulliner, Emma & Malys, Naglis & Maliene, Vida, 2016. "Comparative analysis of MCDM methods for the assessment of sustainable housing affordability," Omega, Elsevier, vol. 59(PB), pages 146-156.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Matthew Quayson & Chunguang Bai & Lihua Sun & Joseph Sarkis, 2023. "Building blockchain‐driven dynamic capabilities for developing circular supply chain: Rethinking the role of sensing, seizing, and reconfiguring," Business Strategy and the Environment, Wiley Blackwell, vol. 32(7), pages 4821-4840, November.
    2. Himanshu Gupta & Manjeet Kharub & Kumar Shreshth & Ashwani Kumar & Donald Huisingh & Anil Kumar, 2023. "Evaluation of strategies to manage risks in smart, sustainable agri‐logistics sector: A Bayesian‐based group decision‐making approach," Business Strategy and the Environment, Wiley Blackwell, vol. 32(7), pages 4335-4359, November.
    3. Sharfuddin Ahmed Khan & Muhammad Shujaat Mubarik & Simonov Kusi‐Sarpong & Himanshu Gupta & Syed Imran Zaman & Mobashar Mubarik, 2022. "Blockchain technologies as enablers of supply chain mapping for sustainable supply chains," Business Strategy and the Environment, Wiley Blackwell, vol. 31(8), pages 3742-3756, December.
    4. Tufano, Alessandro & Zuidwijk, Rob & Van Dalen, Jan, 2023. "The development of data-driven logistic platforms for barge transportation network under incomplete data," Omega, Elsevier, vol. 114(C).
    5. Muhammad Adeel Munir & Amjad Hussain & Muhammad Farooq & Muhammad Salman Habib & Muhammad Faisal Shahzad, 2023. "Data-Driven Transformation: The Role of Ambidexterity and Analytics Capability in Building Dynamic and Sustainable Supply Chains," Sustainability, MDPI, vol. 15(14), pages 1-37, July.
    6. Ecer, Fatih & Pamucar, Dragan, 2022. "A novel LOPCOW‐DOBI multi‐criteria sustainability performance assessment methodology: An application in developing country banking sector," Omega, Elsevier, vol. 112(C).
    7. Ahmed Farouk Kineber & Ayodeji Emmanuel Oke & Mohammed Magdy Hamed & Ehab Farouk Rached & Ali Elmansoury & Ashraf Alyanbaawi, 2022. "A Partial Least Squares Structural Equation Modeling of Robotics Implementation for Sustainable Building Projects: A Case in Nigeria," Sustainability, MDPI, vol. 15(1), pages 1-24, December.
    8. El-Awady Attia & Ali Alarjani & Md. Sharif Uddin & Ahmed Farouk Kineber, 2023. "Determining the Stationary Enablers of Resilient and Sustainable Supply Chains," Sustainability, MDPI, vol. 15(4), pages 1-23, February.
    9. Abderahman Rejeb & Andrea Appolloni, 2022. "The Nexus of Industry 4.0 and Circular Procurement: A Systematic Literature Review and Research Agenda," Sustainability, MDPI, vol. 14(23), pages 1-21, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Orji, Ifeyinwa Juliet & Kusi-Sarpong, Simonov & Huang, Shuangfa & Vazquez-Brust, Diego, 2020. "Evaluating the factors that influence blockchain adoption in the freight logistics industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    2. Bag, Surajit & Rahman, Muhammad Sabbir & Srivastava, Gautam & Shore, Adam & Ram, Pratibha, 2023. "Examining the role of virtue ethics and big data in enhancing viable, sustainable, and digital supply chain performance," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).
    3. Yang, Miying & Fu, Mingtao & Zhang, Zihan, 2021. "The adoption of digital technologies in supply chains: Drivers, process and impact," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    4. Mohammadi, Majid & Rezaei, Jafar, 2020. "Bayesian best-worst method: A probabilistic group decision making model," Omega, Elsevier, vol. 96(C).
    5. Badri Ahmadi, Hadi & Kusi-Sarpong, Simonov & Rezaei, Jafar, 2017. "Assessing the social sustainability of supply chains using Best Worst Method," Resources, Conservation & Recycling, Elsevier, vol. 126(C), pages 99-106.
    6. 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.
    7. Ashrafi, Amir & Zare Ravasan, Ahad & Trkman, Peter & Afshari, Samira, 2019. "The role of business analytics capabilities in bolstering firms’ agility and performance," International Journal of Information Management, Elsevier, vol. 47(C), pages 1-15.
    8. Chukwuebuka M. U-Dominic & Ifeyinwa Juliet Orji & Modestus Okwu, 2021. "Analyzing the Barriers to Reverse Logistics (RL) Implementation: A Hybrid Model Based on IF-DEMATEL-EDAS," Sustainability, MDPI, vol. 13(19), pages 1-24, September.
    9. Kannan, Devika, 2021. "Sustainable procurement drivers for extended multi-tier context: A multi-theoretical perspective in the Danish supply chain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 146(C).
    10. Huynh, Minh-Tay & Nippa, Michael & Aichner, Thomas, 2023. "Big data analytics capabilities: Patchwork or progress? A systematic review of the status quo and implications for future research," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    11. Kumar, Anish & Mangla, Sachin Kumar & Kumar, Pradeep & Song, Malin, 2021. "Mitigate risks in perishable food supply chains: Learning from COVID-19," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    12. Amin Vafadarnikjoo & Madjid Tavana & Tiago Botelho & Konstantinos Chalvatzis, 2020. "A neutrosophic enhanced best–worst method for considering decision-makers’ confidence in the best and worst criteria," Annals of Operations Research, Springer, vol. 289(2), pages 391-418, June.
    13. Md Ahsan Uddin Murad & Dilek Cetindamar & Subrata Chakraborty, 2022. "Identifying the Key Big Data Analytics Capabilities in Bangladesh’s Healthcare Sector," Sustainability, MDPI, vol. 14(12), pages 1-21, June.
    14. 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.
    15. Raut, Rakesh D. & Mangla, Sachin Kumar & Narwane, Vaibhav S. & Dora, Manoj & Liu, Mengqi, 2021. "Big Data Analytics as a mediator in Lean, Agile, Resilient, and Green (LARG) practices effects on sustainable supply chains," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    16. Kazancoglu, Yigit & Sagnak, Muhittin & Mangla, Sachin Kumar & Sezer, Muruvvet Deniz & Pala, Melisa Ozbiltekin, 2021. "A fuzzy based hybrid decision framework to circularity in dairy supply chains through big data solutions," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
    17. Rajesh Chidananda Reddy & Biplab Bhattacharjee & Debasisha Mishra & Anandadeep Mandal, 2022. "A systematic literature review towards a conceptual framework for enablers and barriers of an enterprise data science strategy," Information Systems and e-Business Management, Springer, vol. 20(1), pages 223-255, March.
    18. Wilkin, Carla & Ferreira, Aldónio & Rotaru, Kristian & Gaerlan, Luigi Red, 2020. "Big data prioritization in SCM decision-making: Its role and performance implications," International Journal of Accounting Information Systems, Elsevier, vol. 38(C).
    19. Acciarini, Chiara & Cappa, Francesco & Boccardelli, Paolo & Oriani, Raffaele, 2023. "How can organizations leverage big data to innovate their business models? A systematic literature review," Technovation, Elsevier, vol. 123(C).
    20. Liang, Fuqi & Brunelli, Matteo & Rezaei, Jafar, 2020. "Consistency issues in the best worst method: Measurements and thresholds," Omega, Elsevier, vol. 96(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jomega:v:105:y:2021:i:c:s0305048321001110. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/375/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.