• ISSN: 2148-2225 (online)

Ulaştırma ve Lojistik Kongreleri

alphanumeric journal

The Journal of Operations Research, Statistics, Econometrics and Management Information Systems

The Evaluation of Humanitarian Supply Chain Performance Based On Balanced Scorecard-DEMATEL Approach

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Birdoğan Baki, Ph.D.

Nermin Abuasad


Abstract

Measuring the performance of the humanitarian supply chain (HSC) becomes a necessary nowadays regarding to the increasing wars around the world. This study aims to propose an integrated performance evaluation approach for the HSC in the context of war. The proposed framework includes two main stages. The first stage implicates determining the performance indicators by the literature review and classifies the indicators based on the Balanced Scorecard dimensions. The second stage involves prioritizing the Balanced Scorecard dimensions and performance indicators by DEMATEL. According to results of the study, the most important dimension in the performance measurement for the HSC in the context of war is the customer. Moreover, service quality has the highest impact in the HSC performance measurement. This study extends the current state of knowledge, which provides a novel combined method to measure the performance HSC in context of war disaster.

Keywords: Balanced Scorecard, DEMATEL, Humanitarian Supply Chain, Performance Indicators

Jel Classification: C46


Suggested citation

Baki, B. & Abuasad, N. (). The Evaluation of Humanitarian Supply Chain Performance Based On Balanced Scorecard-DEMATEL Approach. Alphanumeric Journal, 8(2), 163-180. http://dx.doi.org/10.17093/alphanumeric.736730

References

  • Abidi, H. and Scholten, K. (2015). Applicability of performance measurement systems to humanitarian supply chains. Humanitarian Logistics and Sustainability, Springer, Switzerland, 235-260.
  • Abidi, H., de Leeuw, S. and Klumpp, M. (2014). Humanitarian supply chain performance management: a systematic literature review. Supply Chain Management: An International Journal, 19(5/6), 592-608.
  • Abidi, H., de Leeuw, S. and Dullaert, W. (2020). Performance management practices in humanitarian organisations. Journal of Humanitarian Logistics and Supply Chain Management. DOI: 10.1108/JHLSCM-05-2019-0036.
  • Aksakal, E. and Dağdeviren, M. (2010). ANP ve DEMATEL yöntemleri ile personel seçimi problemine bütünleşik bir yaklaşim. Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi, 25(4), 905-913.
  • Anjomshoae, A., Hassan, A., Kunz, N., Wong, K.Y. and de Leeuw, S. (2017). Toward a dynamic balanced scorecard model for humanitarian relief organizations’ performance management. Journal of Humanitarian Logistics and Supply Chain Management, 7(2), 194-218.
  • Anjomshoae, A., Hassan, A. and Wong, K.Y. (2019). An integrated AHP-based scheme for performance measurement in humanitarian supply chains. International Journal of Productivity and Performance Management, 6(2), 118-140.
  • Bag, S. (2016). Humanitarian supply chain management: a bibliometric analysis of the literature. AIMS International Journal of Management, 10(3), 175-202.
  • Balcik, B., Haavisto, I. and Goentzel, J. (2015). Measuring humanitarian supply chain performance in a multi-goal context. Journal of Humanitarian Logistics and Supply Chain Management, 5(3), 300-324.
  • Banomyong, R., Varadejsatitwong, P. and Oloruntoba, R. (2019). A systematic review of humanitarian operations, humanitarian logistics and humanitarian supply chain performance literature 2005 to 2016. Applications of OR in Disaster Relief Operations, 283, 71-86.
  • Bardhan, A. and Dangi, H. (2016). Drivers and indicators of performance in relief chain: an empirical study. Global Business Review, 17(1), 88-104.
  • Beamon, B. (1999). Measuring supply chain performance. International Journal of Operations and Production Management, 19(3), 275-292.
  • Beamon, B. and Balcik, B. (2008). Performance measurement in humanitarian relief chains. International Journal of Public Sector Management, 21(1), 4-25.
  • Bhagwat, R. and Sharma, M. (2007). Performance measurement of supply chain management: A balanced scorecard approach. Computers & Industrial Engineering, 53(1), 43-62.
  • Bichou, K. and Gray, R. (2004). A logistics and supply chain management approach to port performance measurement. Maritime Policy & Management, 31(1), 47-67.
  • Blecken, A. (2010). Supply chain process modeling for humanitarian organization. International Journal of Physical Distribution and Logistics Management, 40(819), 675-692.
  • Bullinger, H.J., Kühner, M. and Van Hoof, A. (2002). Analyzing supply chain performance using a balanced measurement method. International Journal of Production Research, 40(15), 3533-3543.
  • Cakir, S. and Percin, S. (2013). Çok kriterli karar verme teknikleriyle lojistik firmalarinda performans ölçümü. Ege Akademik Bakis, 13(4), 449-460.
  • Celik, E. and Gumus, A. (2016). An outranking approach based on interval type-2 fuzzy sets to evaluate preparedness and response ability of non-governmental humanitarian relief organizations. Computers & Industrial Engineering, 101, 21-34.
  • Celik, E. and Gumus, A. (2018). An assessment approach for non-governmental organizations in humanitarian relief logistics and an application in Turkey. Technological and Economic Development of Economy, 24(1), 1-26.
  • Chandraprakaikul, W. (2010). Humanitarian supply chain management: literature review and future research. In: The 2nd International Conference on Logistics and Transport, Queenstown (18).
  • Chang, H. (2009). An empirical study of evaluating supply chain management integration using the balanced scorecard in Taiwan. The Service Industries Journal, 29(2), 185-202.
  • Chang, S. and Nojima, N. (2001). Measuring post-disaster transportation system performance: the 1995 Kobe earthquake in comparative perspective. Research Part A: Policy and Practice, 35(6), 475-494.
  • Dagdeviren, M. (2006). Tedarik zincirinin yönetimi performansının ölçülmesine yönelik bir model ve uygulaması. The Journal of Defense Science, 5(1), 50-72.
  • Davidson, A. (2006). Key performance indicators in humanitarian logistics. Thesis. Massachusetts University, Institute of Technology.
  • De Leeuw, S. (2010). Towards a reference mission map for performance measurement in humanitarian supply chains. Working Conference on Virtual Enterprises, Berlin 181-188.
  • D'Haene, C., Verlinde, S. and Macharis, C. (2015). Measuring while moving (humanitarian supply chain performance measurement–status of research and current practice). Journal of Humanitarian Logistics and Supply Chain Management, 5(2), 146-161.
  • Gabus, A. and Fontela, E. (1973). Perceptions of the world problem atique: Communication procedure, communicating with those bearing collective responsibility. DEMATEL Report No.1, Battelle Geneva Research Centre, Geneva, Switzerland.
  • Ganguly, K.K., Padhy, R.K. and Rai, S.S. (2017). Managing the humanitarian supply chain: a fuzzy logic approach. International Journal of Disaster Resilience in the Built Environment, 8(5), 521-536.
  • Gatignon, A., Van Wassenhove, L.N. and Charles, A. (2010). The Yogyakarta earthquake: Humanitarian relief through IFRC's decentralized supply chain. International Journal of Production Economics, 126(1), 102-110.
  • Gizaw, B., and Gumus, A. (2016). Humanitarian relief supply chain performance evaluation: A literature review. International Journal of Marketing Studies, 8(2), 105-120.
  • Huang, C. (2018). Assessing the performance of tourism supply chains by using the hybrid network data envelopment analysis model. Tourism Management, 65, 303-316.
  • Idris, A. Soh, C. and Nizam, S. (2014). The relative effects of logistics, coordination and human resource on humanitarian aid and disaster relief mission performance. Retrieved from http://repository.embuni.ac.ke/handle/123456789/1343, (Accessed Date:15.04.2020).
  • Janaćković, G.L., Stanković, M. and Pamučar, D. (2017). Multi-criteria model for disaster logistics performance assessment at strategic level. International conference Transport and Logistics, 6, 302-307.
  • Kaplan, R. and Norton, D. (1992). The Balanced Scorecard - measures that drive performance. Harvard Business Review, 70(7/8), 172-180.
  • Kaplan, R. and Norton, D. (1996). The Balanced Scorecard: translating strategy into action. Harvard Business Press, Boston.
  • Keebler, J. and Plank, R. (2009). Logistics performance measurement in the supply chain: a benchmark Benchmarking. An International Journal, 16(6), 785-798.
  • Kovács, G. and Spens, K. (2007). Humanitarian logistics in disaster relief operations. International Journal of Physical Distribution and Logistics Management, 37(2), 99-114.
  • Kumar, S., Niedan-Olsen, K. and Peterson, L. (2009). Educating the supply chain logistics for humanitarian efforts in Africa: a case study. International Journal of Productivity and Performance Management, 58(5), 480-500.
  • Larrea, O. (2013). Key performance indicators in humanitarian logistics in Colombia. 6th IFAC Conference on Management and Control of Production and Logistics, 46(24), 211-216.
  • Lee, A.H., Chen, W.C. and Chang, C.J. (2008). A fuzzy AHP and BSC approach for evaluating performance of IT department in the manufacturing industry in Taiwan. Expert Systems with Applications, 34(1), 6-107.
  • Leitenberg, M. (2006). Deaths in wars and conflicts in the 20th century, Cornell University, Peace Studies Program, Occasional Paper#29. 3rd ed., USA.
  • Li, Y., Hu, Y., Zhang, X., Deng, Y. and Mahadevan, S. (2014). An evidential DEMATEL method to identify critical success factors in emergency management. Applied Soft Computing, 22, 504-510.
  • Moe, T.L., Gehbauer, F., Senitz, S. and Mueller, M. (2007). Balanced scorecard for natural disaster management projects, Disaster Prevention and Management: An International Journal, 16(5), 785-806.
  • Lima-Junior, F.R. and Carpinetti, L.C.R. (2019). Predicting supply chain performance based on SCOR metrics and multilayer perceptron neural networks. International Journal of Production Economics. 212, 19-38.
  • Lima-Junior, F.R. and Carpinetti, L.C.R. (2020). An adaptive network-based fuzzy inference system to supply chain performance evaluation based on SCOR metrics. Computers & Industrial Engineering. 139, 106191.
  • Lin, C. and Tzeng, G. (2009). A value-created system of science (technology) park by using DEMATEL. Expert Systems with Applications, 36(6), 9683-9697.
  • Liu, W.H., Xie, D. and Xu, X.C. (2012). Research on the procedure joint process and synthesized performance evaluation of logistics service supply chain. African Journal of Business Management, 6(3), 908-923.
  • Lu, Q., Goh, M. and De Souza, R. (2016). A SCOR framework to measure logistics performance of humanitarian organizations. Journal of Humanitarian Logistics and Supply Chain Management, 6(2), 222-239.
  • Muhcu, U. (2016). İnsani yardım tedarik zincirini etkileyen kritik başarı faktörlerinin önem düzeyinin belirlenmesi: analitik ağ süreci uygulaması. (Yayımlanmamış Yüksek Lisans Tezi), Karadeniz Teknik Üniversitesi Sosyal Bilimler Enstitüsü, Trabzon.
  • Najjar, M.S., Dahabiyeh, L. and Nawayseh, M. (2018). Share if you care: the impact of information sharing and information quality on humanitarian supply chain performance-a social capital perspective. Information Development, 1-14.
  • Nurmala, N., de Leeuw, S. and Dullaert, W. (2017). Humanitarian-business partnerships in managing humanitarian logistics. Supply Chain Management: An International Journal, 22(1), 82-94.
  • Pettit, S. and Beresford, A. (2009). Critical success factors in the context of humanitarian aid supply chains. International Journal of Physical Distribution & Logistics Management, 39(6), 450-468.
  • Santarelli, G., Abidi, H., Klumpp, M. and Regattieri, A. (2015). Humanitarian supply chains and performance measurement schemes in practice. International Journal of Productivity and Performance Management, 64(6), 784-810.
  • Saur, A., Kraft, P., Rennhak, C., (2016). Humanitarian supply chain performance management: Development and evaluation of a comprehensive performance measurement framework based on the balanced scorecard, Munich Business School Working Paper Series.
  • Schiffling, S. and Piecyk, M. (2014). Performance measurement in humanitarian logistics: a customer-oriented approach. Journal of Humanitarian Logistics and Supply Chain Management, 4(2), 198-221.
  • Schulz, S. and Heigh, I. (2009). Logistics performance management in action within a humanitarian organization. Management Research News, 32(11), 1038-1049.
  • Shafiee, M., Lotfi, F.H. and Saleh, H. (2014). Supply chain performance evaluation with data envelopment analysis and balanced scorecard. Applied mathematical modelling, 38(21/22), 5092-5112.
  • Sutrisno, A., Handayani, D., Caesarendra, W. and Gunawan, I. (2020). Categorization of reliability performance indicators of humanitarian response supply chain. IOP Conference Series: Materials Science and Engineering, 722, DOI: 10.1088/1757-899X/722/1/012007.
  • Thunberg, M. and Persson, F. (2014). Using the SCOR model’s performance measurements to improve construction logistics. Production Planning & Control, 25(13-14), 1065-1078.
  • Torabi, S.A., Aghabegloo, M. and Meisami, A. (2012). A framework for performance measurement of humanitarian relief chains: a combined fuzzy DEMATEL-ANP approach. Production and Operations Management Society, 1(1), 1-10.
  • Tsai, W. and Chou, W. (2009). Selecting management systems for sustainable development in SMEs: A novel hybrid model based on DEMATEL, ANP, and ZOGP. Expert Systems with Applications, 36(2), 1444-1458.
  • Tuffa, E. (2016). Assessment of humanitarian supply chain performance of selected humanitarian organizations, Master Thesis, Addis Ababa University-School of Commerce, Ethiopia.
  • Tyagi, M., Kumar, P. and Kumar, D. (2014). A hybrid approach using AHP-TOPSIS for analyzing e-SCM performance. Procedia Engineering, 97, 2195-2203.
  • Tzeng, G.H., Chiang, C.H. and Li, C.W. (2007). Evaluating intertwined effects in e-learning programs: A novel hybrid MCDM model based on factor analysis and DEMATEL. Expert Systems with Applications, 32(4), 1028-1044.
  • Van der Laan, E.A., De Brito, M.P. and Vergunst, D.A. (2009). Performance measurement in humanitarian supply chains. International Journal of Risk Assessment and Management, 13(1), 22-45.
  • Van Wassenhove, L. (2006). Humanitarian aid logistics: supply chain management in high gear. Journal of the Operational Research Society, 57(5), 475-489.
  • Varma, S., Wadhwa, S. and Deshmukh, S.G. (2008). Evaluating petroleum supply chain performance: application of analytical hierarchy process to balanced scorecard. Asia Pacific Journal of Marketing and Logistics, 20(3), 343-356.
  • Vega, D. and Roussat, C. (2015). Humanitarian logistics: the role of logistics service providers. International Journal of Physical Distribution & Logistics Management, 45(4), 352-375.
  • Watson Institute. (2020). Costs of war. Summary of Findings. Retrieved from https://watson.brown.edu/costsofwar/papers/summary, (Accessed Date:19.04.2020).
  • Widera, A. and Hellingrath, B. (2011). Performance measurement systems for humanitarian logistics. Proceedings of the 23rd Annual NOFOMA Conference, Norway, 1327-1342.
  • Widera, A., Hellingrath, B. and Bubbich, C. (2015). Humanitarian logistics dashboards design-related requirements analysis. In Global Humanitarian Technology Conference (GHTC), Washington, 92-99.
  • World Bank (2011). World Development Report 2011. Conflict, Security, and Development. Washington DC.
  • Wu, W. (2008). Choosing knowledge management strategies by using a combined ANP and DEMATEL approach. Expert Systems with Applications, 35(3), 828-835.
  • Wu, W. and Lee, Y. (2007). Developing global managers’ competencies using the fuzzy DEMATEL method. Expert Systems with Applications, 32(2), 499-507.
  • Yadav, D. and Barve, A. (2018). Segmenting critical success factors of humanitarian supply chains using fuzzy DEMATEL. Benchmarking: An International Journal, 25(2), 400-425.
  • Yuanzhu, Z. and Hua, T.K. (2020). An analytic infrastructure for harvesting big data to enhance supply chain performance. European Journal of Operational Research, 281(3), 559-574.

Volume 8, Issue 2, 2020

2020.08.02.OR.01

alphanumeric journal

Volume 8, Issue 2, 2020

Pages 163-180

Received: May 13, 2020

Accepted: Dec. 21, 2020

Published: Dec. 31, 2020

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2020 Baki, B., Abuasad, N.

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