Kazim Sari

Exploring the impacts of radio frequency identification (RFID) technology on supply chain performance

This paper is aimed at providing a framework to help managers of a supply chain enterprise determine the appropriate operational and environmental conditions under which investing in radio frequency identification (RFID) technology is more beneficial. For this purpose, a four-echelon supply chain that is operated under different levels of collaboration is examined in a comprehensive simulation model. Results from the simulation model show that integrating RFID technology within a supply chain provides significantly greater benefits when the level of collaboration between the participants is more intensive. In addition, the results also show that these benefits are stronger when lead times are longer and/or when demand uncertainty in marketplace is lower.

Exploring the benefits of vendor managed inventory

Purpose – The purpose of this paper is to explore the performance increase achieved by vendor managed inventory (VMI) under different levels of outside supply capacity, demand uncertainty, and lead time.Design/methodology/approach – The study uses discrete event simulation to explore the performance increase achieved by VMI under different supply chain scenarios.Findings – The analysis suggests that when implementing a VMI program, the capacity restrictions of suppliers have to be taken into consideration even though they have not participated in the program. Furthermore, the results also show that unless the retailer provides additional information to the distributor to resolve the uncertainty, higher levels of uncertainty in market demand create significant reductions in the savings realized by VMI. Finally, this study proves that, regardless of lead time horizons, VMI provides nearly the same level of performance increase as long as the ratio of the retailers lead time to that of the suppliers remain...

Inventory inaccuracy and performance of collaborative supply chain practices

Purpose – This paper aims to explore the impact of inventory system inaccuracies on the benefits of collaborative supply chain practices under various supply chain scenarios. To achieve this purpose, two popular collaboration initiatives are considered in a four‐stage supply chain. The first practice is a vendor managed inventory program where the distributor takes the full responsibility of managing the retailers inventory. The second practice is a collaborative planning, forecasting, and replenishment program where all members work together to plan, forecast, and replenish the product.Design/methodology/approach – The study utilizes Monte Carlo computer simulation in an experimental design.Findings – The analysis suggests that while the inaccurate inventory records result in significant performance reductions for all supply chain configurations, their impact is substantially greater for the supply chains where members collaborate more closely on key supply chain management activities. In addition, the ...

A novel multi-criteria decision framework for evaluating green supply chain management practices

A novel hybrid fuzzy MCDM approach for evaluating GSCM practices is proposed.The proposed model combines AHP and VIKOR under fuzzy environment along with Monte Carlo simulation.An illustrative case is used to exemplify the proposed approach. This study proposes a novel decision framework to evaluate green supply chain management (GSCM) practices. The framework is developed by combining Monte Carlo simulation, AHP (Analytical Hierarchy Process) and VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje) methods under fuzzy environment. The AHP is used to obtain relative weights of evaluation criteria for GSCM practices. The VIKOR is used to generate the rankings according to GSCM performance, and then to recommend the best performing organizations. This framework offers a new way of dealing with uncertainties resulting from decision makers incomplete and/or vague information by utilizing the Monte Carlo simulation. An illustrative case is used as well to exemplify the proposed approach.

Selection of RFID solution provider: A fuzzy multi‐criteria decision model with Monte Carlo simulation

– The purpose of this paper is to provide a comprehensive framework to help managers of a business enterprise effectively evaluate candidate RFID solution providers and then select the most suitable one., – The selection of an RFID solution provider is modeled as a new hybrid fuzzy multi‐criteria decision making problem. The proposed decision model is based on integration of Monte Carlo simulation with fuzzy analytic hierarchy process (AHP) and fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. In addition, an illustrative case is used to exemplify the proposed approach., – A quantitative methodology based on a structured framework, for the selection of the most appropriate RFID solution provider., – This research study is a very useful source of information for managers of a business enterprise in making decisions about evaluation and selection of RFID solution providers or RFID system integrators., – This study addresses the evaluation and selection of RFID solution providers for the managers of a business enterprise and proposes a new hybrid decision‐making methodology for the problem.

Investigating the value of reducing errors in inventory information from a supply chain perspective

Purpose – The purpose of this paper is to investigate the value of reducing errors in inventory information from a supply chain perspective. To this end, the benefits of reducing errors in inventory information are compared with those of lead time reduction and supply chain collaboration. Design/methodology/approach – A simulation model is constructed to perform the analysis. Findings – Results show that lead time reduction is the most important strategy for a supply chain in reducing total supply chain cost. In terms of customer service level, on the other hand, strategy of reducing errors in inventory information is observed as the most considerable strategy. However, the results for supply chain collaboration are somewhat unexpected. Namely, in spite of its popularity, supply chain collaboration provides very limited contribution to the supply chain. Practical implications – This research provides useful knowledge for the managers of a business enterprise in prioritizing various supply chain strategies...

A Fuzzy Rule-Based Decision Support System for Determining the Level of Collaboration in a Supply Chain

Today making a decision on the level of collaboration in a supply chain is very important problem for the managers of a supply chain. For the purpose of helping them make better decisions, in this research, we aim to develop a fuzzy rule-based decision support system. To achieve this, firstly, the factors that are important for the level of collaboration in a supply chain are extracted. Later, the fuzzy rules are established by using the related literature in SCM area. At this point, expert opinions are also used. Finally, applicability of the proposed fuzzy rule-based decision support system is demonstrated with an illustrative example.

Modeling of a Fuzzy Expert System for Choosing an Appropriate Supply Chain Collaboration Strategy

AbstractNowadays, there has been a great interest for business enterprises to work together or collaborate in the supply chain. It is thus possible for them to gain a competitive advantage in the marketplace. However, determining the right collaboration strategy is not an easy task. Namely, there are several factors that need to be considered at the same time. In this regard, an expert system based on fuzzy rules is proposed to choose an appropriate collaboration strategy for a given supply chain. To this end, firstly, the factors that are significant for supply chain collaboration are extracted via an extensive review of literature. Then, a simulation model of a supply chain is constructed to reveal the performance of collaborative practices under various scenarios. Thereby, it is made possible to establish fuzzy rules for the expert system. Finally, feasibility and practicability of our proposed model is verified with an illustrative case.