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Showing 2 results for MAHMUD
Two DEA Models Employment in IS Project Selection for Iran Ministry of Commerce
Jafar Mahmudi, Soroosh Nalchigar , Seyed Babak Ebrahimi,
Volume 20, Issue 1 (IJIEPR 2009)
Abstract
Selection of an appropriate set of Information System (IS) projects is a critical business activity which is very helpful to all organizations. In this paper, after describing real IS project selection problem of Iran Ministry of Commerce (MOC), we introduce two Data Envelopment Analysis (DEA) models. Then, we show applicability of introduced models for identifying most efficient IS project from 8 competing projects. Then, in order to provide further insight, results of two introduced models are compared. It is notable that using basic DEA models -CCR and BCC- decision maker is not able to find most efficient Decision Making Unit (DMU) since these models identify some of DMUs as efficient which their efficiency scores equal to 1. As an advantage, the applied models can identify most efficient IS (in constant and variable return to scale situations) by solving only one linear programming (LP). So these models are computationally efficient. It is while using the basic DEA models requires decision maker to solve a LP for each IS.
Enhancing SMEs Automotive Manufacturing Performance through Human Factor Ergonomics: An Approach Towards Hybrid Working Environment
Norhana Aripin, Fatimah Mahmud, Gusman Nawanir, Suhaidah Hussain, Khai Loon Lee,
Volume 36, Issue 4 (IJIEPR- In Progress- Special Issue 2025)
Abstract
This study explores the impact of human factor ergonomics (HFE), considering physical, managerial, psychosocial, and work design factors on manufacturing performance in the SME automotive sector in Malaysia, and investigates the feasibility of hybrid work environments. Using a mixed-method approach, it collected quantitative data through a survey (132 responses) and qualitative data via semi-structured interviews with five informants from SME automotive manufacturers. The analysis supported three hypotheses, indicating that physical, managerial, and work design factors positively affect manufacturing performance, while psychosocial factors do not due to constraints within SMEs. The study also examined how hybrid work environments can enhance the relationship between psychosocial factors and manufacturing performance. Findings suggest that transitioning to hybrid work, especially for non-operational roles, is feasible with the right technology, policies, culture, and training. This research addresses the urgent need for targeted safety efforts in the automotive SME sector and offers practical insights into optimizing productivity while ensuring employee well-being. It contributes valuable insights into the dynamics of hybrid work environments within manufacturing settings, making it a valuable addition to empirical studies in the field.

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