دانلود رایگان مقاله انگلیسی مدیریت ریسک زنجیره تامین - نشریه امرالد

Abstract

Purpose – A risk, when it occurs, causes negative effects on outputs. Typically, risks are not independent as multiple risks occur simultaneously. The purpose of this paper is to compare the impact various risks have on the performance of manufacturing-oriented and service-oriented firms from a supply chain (SC) perspective. Design/methodology/approach – First, SC risks were identified and classified into two criteria: context and probability. Then, the different characteristics between manufacturing- and service-oriented firms were distinguished by the theory of goods-dominant logic (GDL) and service-dominant logic (SDL). Structural equations modeling and multiple-group analysis were then used to validate research hypotheses and compare the two groups. Findings – The empirical evidence, gathered from the Vietnamese construction sector, indicated that in a serious situation all of the five risks proposed occur at the same time, thus the remarkable 87.1% variance in SC performance was explained. Furthermore, this rate is significant when the two groups are compared: manufacturing-oriented firms (88.3 percent) and service-oriented firms (85.6 percent), implying that risks in the manufacturing-oriented group have a greater effect on SC performance. While manufacturing-oriented companies should pay close attention to the operational and demand risks that adversely affect SC performance, they should treat information risk as an opportunity to improve. Service-oriented companies, however, need to manage supply risk which, in their case, can be attributed to a 51.2 percent variance in SC performance. Moreover, service quality can also be improved remarkably if information risk is well managed. Research limitations/implications – This study provides a detailed picture of the relationship between risks and performance in the SC. Risks are illustrated as affecting the SC performance simultaneously, (not separately) and so the approach outlined here will give firms a comprehensive view of their SCs and provide guidelines for predicting the impact risks will have on the SC performance. Moreover, by comparing manufacturing- and service-oriented firms, a thorough overview of risk behaviors is provided and appropriate solutions for each type of company can be determined. Originality/value – The “novelty of approach” of this study is in applying GDL and SDL theory to classify the manufacturing-oriented and service-oriented firms. The different characteristics between the two groups are identified and explained in terms of resources, value, network, effectiveness vs efficiency and communication, thus providing an insight into risk management activities in the SC network.

7. Conclusions

This research provides an extensive illustration of the relationship between SC risks and SC performance and clearly depicts that risks do not affect SC performance separately, but simultaneously. According to the results, when all of the five proposed risks happen in unison, they can explain an 87.1 percent variance in SC performance. It is worthwhile noting that the impact risks have on SC performance varies between manufacturing- and service-oriented firms. In fact, the risks occurring in manufacturing-oriented firms have stronger negative effects on SC performance than those in service-oriented firms do. Therefore, manufacturing-oriented firms should pay careful attention to operational and demand risks that adversely affect SC performance and “treat” information risk as an opportunity to improve SC performance. Service-oriented firms, on the other hand, must manage supply risks which can be attributed to a 51.2 percent variance in SC performance. Furthermore, service quality can be improved remarkably if information risk is well managed.

One of the “original contributions” of this study has been to use GDL and SDL theory to identify the different characteristics between the two groups being compared. This approach provides an insight into the differences between the two groups because the two types of business were classified based on resources, value, networks, effectiveness vs efficiency and communication. Future studies could apply this approach to their own contexts to verify these results. In this work, finance risk having an impact on SC performance is not found. This risk is defined as an “infrastructure” factor that might indirectly affect SC performance throughout the other risks/factors. Thus, further research is needed to examine any mutual interaction between SC risks to consolidate this statement. Moreover, for a more comprehensive view, some risk factors from the external perspective of SC, e.g. natural disasters, political uncertainty, economic downturns, etc., also need to be added into the research model.