Showing 4 results for Supply Chain Performance
Laya Olfat, Maghsoud Amiri, Jjahanyar Bamdad Soofi, Mostafa Ebrahimpour Azbari,
Volume 25, Issue 2 (5-2014)
Abstract
Having a comprehensive evaluation model with reliable data is useful to improve performance of supply chain. In this paper, according to the nature of supply chain, a model is presented that able to evaluate the performance of the supply chain by a network data envelopment analysis model and by using the financial, intellectual capital (knowledge base), collaboration and responsiveness factors of the supply chain. At the first step, indicators were determined and explained by explanatory Factor Analysis. Then, Network Data Envelopment Analysis (NDEA) model was used. This paper is the result of research related to supply chain of pharmaceutical companies in Tehran Stock Exchange and 115 experts and senior executives have been questioned as sample. The results showed that responsiveness latent variable had the highest correlation with supply chain performance and collaborative, financial and intellectual capital (knowledge base) latent variables were respectively after that. Four of the twenty eight supply chains which were studied obtained 1 as the highest performance rate and the lowest observed performance was 0.43.
Amit Kumar Marwah, Girish Thakar, Ramesh Chandra Gupta,
Volume 25, Issue 3 (7-2014)
Abstract
The manufacturing organizations today are having a competition of supply chain versus supply chain. Existing research work fails to relate human metrics with supply chain performance. The authors intend to empirically assess the effects of human metrics on supply chain performance in the context of Indian manufacturing organizations. A rigorous literature review has identified 12 variables. The variables are individually measured and later on reduced in number by factor analysis. As a pilot study, primary data is collected from 100 manufacturing organizations by means of a questionnaire, both offline and online, which is administered across India and a scale is developed. t-test and factor analysis resulted in 3 factors related to human metrics. The outcomes of the research work provide valuable implications for the Indian manufacturing organizations to understand the factors affecting supply chain performance.
Tenaw Tegbar Tsega, Thoben Klaus-Dieter, Rao D.k.nageswara, Bereket Haile Woldegiorgis,
Volume 35, Issue 2 (6-2024)
Abstract
Ethiopia has made enormous efforts in the leather industry to gain manufacturing capabilities that can be scaled up to other sectors. Those efforts have resulted in the industry shifting its role from raw material supplier to producer of value-added products for the global supply chain (GSC). However, the industry has faced severe challenges in generating the expected revenue, utilizing capacity, and finally coping with the global competitive environment. Studies reveal that manufacturing firms tackle similar challenges by improving their supply chain performance (SCP). The challenges that appeared in the leather industry of Ethiopia could also be solved by improving its SCP. Nonetheless, there is a lack of study on the basic characteristics and SCP of the industry after it has shifted its role. The main objective of this study is, therefore, to measure the SCP to know where it stands using a bench mark and identify the elements that contribute considerably to the low overall SCP in order to lay the foundation for subsequent improvement. To achieve the research objective, data was collected from primary and secondary sources through a questionnaire, survey, observation, and focus group discussion. The data is analyzed using the supply chain operations reference model (SCOR version 12.0). Accordingly, the overall SCP is found to be 67.33%, suggesting an average rating as per the set benchmark. The source process is identified as the most influential element for the overall low SCP, with a percentage gap of 17.23%. Taking corrective action on the identified elements could help the industry overcome the existing challenges by improving its SCP.
Tenaw Tegbar Tsega, Thoben Klaus-Dieter, Rao D.k. Nageswara, Bereket Haile Woldegiorgis,
Volume 36, Issue 2 (6-2025)
Abstract
So far, several models for measuring supply chain performance (SCP) have been developed. The supply chain operation reference (SCOR) model is regarded as the most crucial in the manufacturing business. However, none of the models, including the SCOR model, are comprehensive enough to measure the overall SCP of manufacturing firms. In practice, the existing models are only used in a few of the numerous steps necessary to calculate the overall SCP. Furthermore, the existing models lack fundamental elements that a model should include. The objective of this research is to develop a powerful SCP measurement using a systematic literature review (SLR). Accordingly, this research has proposed a complete supply chain operations measurement (C-SCOM) model. The proposed model consists of four major components: the application of the SCOR model, the application of the AHP method, a template that enables overall SCP calculation, and a direction for linking supply chain management practices (SCMPS) with gap analysis. By having these features, the model provides users with the ability to calculate the overall SCP, conduct gap analysis, carry out benchmarking, and link the gap analysis outputs to existing SCMPs, which the previous models lack. The validation using the fuzzy Delphi technique reveals that the proposed model is unique in its explicitness and will be user-friendly for real-world industrial applications. Finally, this study contributes to the body of knowledge by providing a comprehensive model that could help solve the real challenges that manufacturing firms face when measuring SCP.
