Investigation the requirements of supply and distribution emergency logistics management and categorization its sub-criteria using AHP: a case study

Feizollahi, S.; Shirmohammadi, A.; Kahreh, Z.

Growing Science » Management Science Letters » Investigation the requirements of supply and distribution emergency logistics management and categorization its sub-criteria using AHP: a case study

Journals

MSL Volumes

Volume 1 (70)
- Issue 1 (10)
- Issue 2 (15)
- Issue 3 (20)
- Issue 4 (25)

Volume 2 (365)
- Issue 1 (51)
- Issue 2 (32)
- Issue 3 (40)
- Issue 4 (44)
- Issue 5 (42)
- Issue 6 (52)
- Issue 7 (53)
- Issue 8 (51)

Volume 3 (426)
- Issue 1 (40)
- Issue 2 (47)
- Issue 3 (40)
- Issue 4 (40)
- Issue 5 (27)
- Issue 6 (50)
- Issue 7 (51)
- Issue 8 (30)
- Issue 9 (24)
- Issue 10 (25)
- Issue 11 (25)
- Issue 12 (27)

Volume 4 (387)
- Issue 1 (34)
- Issue 2 (30)
- Issue 3 (34)
- Issue 4 (42)
- Issue 5 (33)
- Issue 6 (43)
- Issue 7 (42)
- Issue 8 (40)
- Issue 9 (39)
- Issue 10 (20)
- Issue 11 (18)
- Issue 12 (12)

Volume 5 (129)
- Issue 1 (15)
- Issue 2 (10)
- Issue 3 (10)
- Issue 4 (12)
- Issue 5 (14)
- Issue 6 (14)
- Issue 7 (8)
- Issue 8 (8)
- Issue 9 (11)
- Issue 10 (8)
- Issue 11 (9)
- Issue 12 (10)

Volume 6 (74)
- Issue 1 (9)
- Issue 2 (6)
- Issue 3 (6)
- Issue 4 (7)
- Issue 5 (6)
- Issue 6 (6)
- Issue 7 (8)
- Issue 8 (6)
- Issue 9 (5)
- Issue 10 (5)
- Issue 11 (5)
- Issue 12 (5)

Volume 7 (54)
- Issue 1 (5)
- Issue 2 (5)
- Issue 3 (5)
- Issue 4 (5)
- Issue 5 (5)
- Issue 6 (5)
- Issue 7 (4)
- Issue 8 (4)
- Issue 9 (4)
- Issue 10 (4)
- Issue 11 (4)
- Issue 12 (4)

Volume 8 (119)
- Issue 1 (5)
- Issue 2 (5)
- Issue 3 (5)
- Issue 4 (5)
- Issue 5 (22)
- Issue 6 (20)
- Issue 7 (6)
- Issue 8 (6)
- Issue 9 (8)
- Issue 10 (10)
- Issue 11 (11)
- Issue 12 (16)

Volume 11 (251)
- Issue 1 (36)
- Issue 2 (39)
- Issue 3 (40)
- Issue 4 (40)
- Issue 5 (29)
- Issue 6 (27)
- Issue 7 (20)
- Issue 8 (12)
- Issue 9 (8)

Volume 12 (33)
- Issue 1 (6)
- Issue 2 (6)
- Issue 3 (8)
- Issue 4 (13)

Volume 13 (27)
- Issue 1 (7)
- Issue 2 (8)
- Issue 3 (5)
- Issue 4 (7)

Volume 14 (22)
- Issue 1 (6)
- Issue 2 (6)
- Issue 3 (5)
- Issue 4 (5)

Volume 15 (15)
- Issue 1 (5)
- Issue 2 (5)
- Issue 3 (5)

Countries

Management Science Letters

ISSN 1923-9343 (Online) - ISSN 1923-9335 (Print) Quarterly Publication Volume 2 Issue 7 pp. 2335-2340 , 2012

Investigation the requirements of supply and distribution emergency logistics management and categorization its sub-criteria using AHP: a case study Pages 2335-2340 Download PDF

Authors: Sadegh Feizollahi, Alireza Shirmohammadi, Zahra Safari Kahreh

DOI: 10.5267/j.msl.2012.08.010

Keywords: Analytic-Hierarchy-process, Crisis management, Logistic emergency, Management preparation and distribution

Abstract: The management of procurement and distribution is one of the most important branches of the crisis management and events that, has great importance in the field of management. In this paper, we perform an empirical study to investigate important factors on emergency logistic emergency preparation distribution management among people who worked for governorship, hygiene and treatment, Red Crescent, electricity, water and sewage and transportation of central province of Ilam in west part of Iran. The survey distributed a questionnaire among some people and examined six hypotheses. The results of our survey indicate that employees who worked for these organizations maintained high levels of skills; they were able to access what they needed in their organization. In addition, the survey indicates that the access to the necessary information in their organizations; they are able to take care of their documentations. They could also execute their jobs based on good schedules and accomplished their tasks, properly. They survey also performed a multi-criteria decision making approach using AHP to prioritize important activities to improve logistic operations. The results indicate that having a good database is number one priority with relative weight of 0.51, followed by appropriate operating planning with relative weight of 0.295. Supply control came on the third position with relative weight of 0.134 and finally task assignment came as the last priority with relative weight of 0.061.

How to cite this paper

 Feizollahi, S., Shirmohammadi, A & Kahreh, Z. (2012). Investigation the requirements of supply and distribution emergency logistics management and categorization its sub-criteria using AHP: a case study.Management Science Letters , 2(7), 2335-2340.

Refrences

Caunhye, A.M., Nie, X., & Pokharel, S. (2012). Optimization models in emergency logistics: A literature review. Socio-Economic Planning Sciences, 46(1), 4-13.

Chang, M.S., Tseng, Y.L., & Chen, J. W. (2007). A scenario planning approach for the flood emergency logistics preparation problem under uncertainty. Transportation Research Part E: Logistics and Transportation Review, 43(6), 737-754.

Gong, B., Chen, X., & Hu, C. (2012). Fuzzy Entropy Clustering Approach to Evaluate the Reliability of Emergency Logistics System. Energy Procedia, 16(A), 278-283.

Hu, Z. H. (2011). A container multimodal transportation scheduling approach based on immune affinity model for emergency relief. Expert Systems with Applications, 38(3), 2632-2639.

Kaplan, R. S. & Norton, D. P. (1992). The balanced scorecard – measures that drive performance, Harvard Business Review, 70(1), 71-79.

Kaplan, R.S. & Norton, D.P. (1996). The balanced scorecard: translating strategy into action, Harvard Business School Press, Boston, MA.

Saaty, T. L. (1992). How to make a decision: the analytic hierarchy process. European Journal of Operational Research, 48, 9–26.

Sheu, J.B. (2010). Dynamic relief-demand management for emergency logistics operations under large-scale disasters. Transportation Research Part E: Logistics and Transportation Review, 46(1), 1-17.

Yuan, Y., & Wang, D. (2009). Path selection model and algorithm for emergency logistics management. Computers & Industrial Engineering, 56(3), 1081-1094.

Zhang, J., Dong, M., & Chen, F.F. (2012). A bottleneck Steiner tree based multi-objective location model and intelligent optimization of emergency logistics systems. Robotics and Computer-Integrated Manufacturing, In Press.