• Luvanyaa Kumaran School of Quantitative Sciences, UUM College of Arts and Sciences, Universiti Utara Malaysia
  • Sahubar Ali Mohamed Nadhar Khan School of Quantitative Sciences, UUM College of Arts and Sciences, Universiti Utara Malaysia
  • MD Azizul Baten Department of Statistics, School of Physical Sciences, Shahjalal University of Science and Technology, Sylhet, Bangladesh




AHP method, allocation criteria, glove industry, order allocation


Malaysia is the world’s leading producer of rubber gloves, among over 150 manufacturers worldwide. Based on current practice among the manufacturer of rubber gloves, there is no fixed guideline in planning for the orders based on various criteria as each criterion has its importance, and the orders are planned based on the real-time situation. Therefore, in this study, the criteria to be considered for order allocation to factories and their importance were determined using Analytical Hierarchical Process (AHP) technique. Six criteria, namely quality, cost, lead time, capacity, special requirement, and regulation compliance, were identified based on the literature search of past studies in the field and supported by the expert’s opinion. Later, the experts ranked the importance of each criterion using a specifically designed questionnaire employing the AHP method. The pairwise comparison matrix was consistent with a consistency ratio (CR) value of 0.0495. Thus, the six criteria by ranking top to bottom with respective weightage are quality (25.81%), cost (21.7%), lead time (20.73%), regulation compliance (16.86%), special requirement (7.86%), and capacity (7.04%). In summary, the objectives of this research have been successfully met, according to the findings, and the criteria ranking can be used as a guideline by rubber glove manufacturers in planning for order allocation.


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Author Biography

Sahubar Ali Mohamed Nadhar Khan, School of Quantitative Sciences, UUM College of Arts and Sciences, Universiti Utara Malaysia

UUM College of Arts and Sciences

School of Quantitative Sciences


Afzali, A., Rafsanjani, M., & Saeid, A. (2016). A fuzzy multi- objective linear programming model based on interval-valued intuitionistic fuzzy sets for supplier selection. International Journal of Fuzzy Systems, 18(5), 864-874. doi:10.1007/s40815- 016-0201-1

Alegoz, M., & Yapicioglu, H. (2019). Supplier selection and order allocation decisions under quantity discount and fast service options. Sustainable Production and Consumption, 18, 179-19. doi:10.1016/j.spc.2019.02.006

Arikan, F. (2013). A fuzzy solution approach for multi-objective supplier selection. Expert Systems with Applications, 947-952. doi:10.1016/j.eswa.2012.05.051

Bellman, R., & Zadeh, L. (1970). Decision-Making in a Fuzzy Environment. Management Science, 17(4), B-141.doi:10.1287/mnsc.17.4.b141

Bhutta, K., & Huq, F. (2002). Supplier selection problem: a comparison of the total cost of ownership and analytic hierarchy process approaches. Supply Chain Management: An International Journal, 7(3), 126-135. doi:10.1108/13598540210436586

Hallowell, M., & Gambatese, J. (2010). Qualitative Research: Application of the Delphi Method to CEM Research. Journal of Construction Engineering and Management, 136(1), 99- 107. doi:10.1061/(asce)co.1943-7862.0000137

Kazemi, N., Ehsani, E., & Glock, C. (2014). Multi-objective supplier selection and order allocation under quantity discounts with fuzzy goals and fuzzy constraints. International Journal of Applied Decision Sciences, 7(1), 66. doi:10.1504/ ijads.2014.058035

Khemiri, R., Elbedoui-Maktouf, K., Grabot, B., & Zouari, B. (2017). A fuzzy multi-criteria decision-making approach for managing performance and risk in integrated procurement–production planning. International Journal of Production Research, 55(18), 5305-5329. doi:10.1080/00207543.2017.1308575

Lavanpriya, C., Muthukumaran, V., & Manoj Kumar, P. (2022). Evaluating suppliers using AHP in a fuzzy environment and allocating order quantities to each supplier in a supply chain. Mathematical Problems in Engineering, 2022, Article ID 869983, 1-13. https://doi.org/10.1155/2022/8695983

Malaysian Rubber Glove Manufacturers Association. (2020). MARGMA Industry Brief 2020 on the Rubber Glove Industry. Malaysian Rubber Glove Manufacturers Association. https:// www.margma.com.my/about-us/

Malaysian Rubber Glove ManufacturersAssociation. (2021). Potential Areas of Research in the Rubber Glove Industry. MRC Industry Linkage Fund: Industry-University Interaction Session. chrome- extension://efaidnbmnnnibpcajpcglclefindmkaj/viewer. html?pdfurl=https%3A%2F%2Fwww.myrubbercouncil.com%2Findustrylinkagefund%2Fdocument%2Fcompanies%2Fm argma.pdf&clen=1265072&chunk=true

Meena, P. L., Katiyar, R., & Kumar, G. (2022). Supplier performance and selection from sustainable supply chain performance perspective. International Journal of Productivity and Performance Management. https://doi.org/10.1108/ IJPPM-01-2022-0024

Molinè, J., & Coves, A. (2013). Order allocation in a multi-supplier environment: review of the literature since 2007. Journal of Industrial Engineering and Management, 6(3). doi:10.3926/ jiem.556

Nguyen, N. T. (2021). Applying AHP in evaluation the distribution science of suppliers for retails in Vietnam: Case of Saigon Co- op Mart. Journal of Distribution Science, 19(3), 35-47. https:// doi.org/10.15722/jds.19.3.202103.35

Omair, M., Noor, S., Tayyab, M., Maqsood, S., Ahmed, W., Sarkar, B., & Habib, M. (2021). The selection of the sustainable suppliers by the development of a decision support framework based on analytical hierarchical process and fuzzy inference system. International Journal of Fuzzy Systems, 23(7), 1986- 2003. doi:10.1007/s40815-021-01073-2

Rogers, M., & Lopez, E. (2002). Identifying critical cross-cultural school psychology competencies. Journal of School Psychology, 40(2), 115-141. doi:10.1016/s0022-4405(02)00093-6

Saaty, T. (1980). The Analytic Hierarchy process: Planning, priority setting, resource allocation (Decision Making Series). McGraw-Hill.

Salim, S. (2022). MARGMA expects demand for gloves in 2022 and 2023 to be 10%-15% higher than pre-pandemic level. theedgemarkets.com. https://www.theedgemarkets.com/ article/margma-expects-demand-gloves-2022-and-2023-be- 1015-higher-prepandemic-level

Singh, A. (2014). Supplier evaluation and demand allocation among suppliers in a supply chain. Journal of Purchasing and Supply Management, 20(3), 167-176. doi:10.1016/j. pursup.2014.02.001

Sultana, I., Ahmed, I., & Azeem, A. (2015). An integrated approach for multiple criteria supplier selection combining Fuzzy Delphi, Fuzzy AHP & Fuzzy TOPSIS. Journal of Intelligent & Fuzzy Systems, 29(4), 1273-1287. doi:10.3233/ifs-141216

Ting, S., & Cho, D. (2008).An integratedapproach for supplier selection and purchasing decisions. Supply Chain Management: An International Journal, 13(2). doi:10.1108/13598540810860958 Weber, C., Current, J., & Benton, W. (1991). Vendor selection criteria and methods. European Journal of Operational Research,50(1). doi:10.1016/0377-2217(91)90033-r

You, S., Zhang, L., Xu, X., & Liu, H. (2020). A new integrated multi- criteria decision making and multi-objective programming model for sustainable supplier selection and order allocation. Symmetry, 12(2), 302. doi:10.3390/sym12020302




How to Cite

Kumaran, L., Mohamed Nadhar Khan, . S. A., & Baten, M. A. . (2023). RANKING OF CRITERIA FOR ORDER ALLOCATION IN A RUBBER GLOVE MANUFACTURING FACTORY USING ANALYTIC HIERARCHY PROCESS (AHP). Journal of Computational Innovation and Analytics (JCIA), 2(1), 107–121. https://doi.org/10.32890/jcia2023.2.1.6