Effectiveness of information systems in supply chain performance: a system dynamics study

Author(s):  
Ashish Agarwal ◽  
Ravi Shankar ◽  
Purnendu Mandal
2011 ◽  
Vol 66-68 ◽  
pp. 401-406
Author(s):  
Wei Qiang Jia ◽  
You Fang Huang ◽  
Yun Zhu Wang

Based on the Rate-Variable Fundamental In-tree Modeling Method of the System Dynamics, this paper discusses a problem that how to apply the system dynamics assessment Method based on Level and Rate Variable System in a determined Assessment Index System. It gives a method to determine the Level Variable and Rate Variable System method in the Assessment Index System, and then utilizes Rate-Variable Fundamental In-tree Models depicting the Assessment Index System. Based on this, it applies the System Simulation Assessment on the Supply Chain Performance of the Aviation Weapon Equipment Manufacturing, analyses the feedback dynamic complexity affecting the performance improvement; put forward the relevant Management Countermeasures, which achieves the purpose of analyzing Supply Chain Performance effectively utilizing the System Science Method.


2017 ◽  
Vol 7 (2) ◽  
pp. 1552-1558 ◽  
Author(s):  
F. H. Kashani ◽  
S. Baharmast

This study evaluates the effect of supply chain information systems on firm performance in IKAMCO as a empirical case study. For this purpose, The 132 IKAMCO employees selected by simple random sampling responded to a questionnaire. Content validity of the questionnaire has been confirmed by experts in this field; its reliability has been confirmed by using Cronbach's alpha and Fisher’s test. Kolmogorov-Smirnov test is used to ensure normality of the data obtained from questionnaire. The hypotheses are tested using SmartPLS software. Results show that the model is well fitted to the data. Findings show that a lean and agile supply chain is effective on supply chain performance and supply chain performance is effective on firm performance. Efficiency of information systems moderates the effect of lean supply chain on supply chain performance and firm performance. However, flexibility of information systems does not moderate the effect of agile supply chain on supply chain performance and firm performance.


2019 ◽  
Vol 14 (3) ◽  
pp. 610-627 ◽  
Author(s):  
Mehdi Poornikoo ◽  
Muhammad Azeem Qureshi

Purpose A plethora of studies focused on the cause and solutions for the bullwhip effect, and consequently many have successfully experimented to dampen the effect. However, the feasibility of such studies and the actual contribution for supply chain performance are yet up for debate. This paper aims to fill this gap by providing a holistic system-based perspective and proposes a fuzzy logic decision-making implementation for a single-product, three-echelon and multi-period supply chain system to mitigate such effect. Design/methodology/approach This study uses system dynamics (SD) as the central modeling method for which Vensim® is used as a tool for hybrid simulation. Further, the authors used MATLAB for undertaking fuzzy logic modeling and constructing a fuzzy inference system that is later on incorporated into SD model for interaction with the main supply chain structure. Findings This research illustrated the usefulness of fuzzy estimations based on experts’ linguistically and logically defined parameters instead of relying merely on the traditional demand forecasting based on time series. Despite the increased complexity of the calculations and structure of the fuzzy model, the bullwhip effect has been considerably decreased resulting in an improved supply chain performance. Practical implications This dynamic modeling approach is not only useful in supply chain management but also the model developed for this study can be integrated into a corporate financial planning model. Further, this model enables optimization for an automated system in a company, where decision-makers can adjust the fuzzy variables according to various situations and inventory policies. Originality/value This study presents a systemic approach to deal with uncertainty and vagueness in dynamic models, which might be a major cause in generating the bullwhip effect. For this purpose, the combination between fuzzy set theory and system dynamics is a significant step forward.


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