The integration of the global market makes the supply chain more complex and has great impacts on efficient supplier management strategies. The aim of this study is to present a systematic supplier management framework to integrate supplier selection and monitoring phases, which are not independent of each other. However, only a few previous studies have pointed out the differences between the two phases. The proposed methodology integrates a quantitative and qualitative approach, formulating multi-criteria decision making (MCDM) using the analytic hierarchy process (AHP) to evaluate the priorities of these criteria. This research explores the difference in the set of criteria for supplier selection and supplier monitoring. The results provide comprehensive insights into the criteria to help decision-makers, managers, and practitioners select appropriate suppliers and monitor suppliers’ performances in the automotive industry. Based on the result, it can be said that a company should integrate the supplier selection and monitoring process. Furthermore, the purchasing and manufacturing manager should continuously collaborate and synchronize the relative weights for the critical factors.

Purpose -The purpose of this paper is to propose a novel risk assessment approach that considers the inter-relationship between supply chain risks and the structure of network at the same time. To reduce the impact of the supply chain risk and enhance the flexibility of transportation route finding during the product delivery, the authors propose a way to model the risk propagation and how to integrate it with the supply chain network using Bayesian Belief Network (BBN). The key risk indicators (KRI) of each vertex and edge of the supply chain network which are measured or computed by the proposed approach can be utilized to develop the optimal transportation route in the execution phase. Design/methodology/approach -BBN is utilized to illustrate the relations among supply chain risks which may take place in a certain vertex. To apply the BBN to the supply chain network, the authors develop the framework to integrate BBN and the supply chain network by using the general functions that describe the characteristics of the risk factors and inter-relationships between vertices. Findings -By using the proposed risk assessment and dynamic route-finding approach, it is possible to reduce the unexpected cost from the supply chain risk and overcome the limitations of previous risk management strategies which focus on developing counter plans and assume the independency of supply chain risks. Practical implications -The proposed approach describes how to develop KRI-BBN to model the risk propagation and to integrate the KRI-BBN and supply chain network. The KRIs directly measured or computed by KRI-BBN in real time can be utilized to alternate supply chain execution plans such as inventory management, demand management and product flow management. Transportation problem considering risk is developed to show how to apply the proposed approach and numerical experiments are conducted to prove the cost effectiveness. Originality/value -The contribution of this paper lies in the way of developing KRI-BBN to assess the supply chain risk and modelling of the risk propagation by integrating KRI-BBN with supply chain network. With the proposed risk assessment approach, it is able to alternate the transportation route to minimize the unexpected cost and transportation cost simultaneously.

A cold chain for perishable fresh products aims to preserve the quality of the products under the control of a predefined temperature range. To satisfy the delivery conditions within appropriate time windows, the most critical operations in cold chain management is the transportation and distribution of fresh products. Due to rapid population growth and increasing demand for high-quality fresh foods, it becomes critical to develop advanced transportation and distribution networks for fresh products, particularly in urban areas. This research aims to design different scenarios based on mathematical models for fresh products transportation and distribution network in the Bangkok metropolitan area using Geographic Information system (GIS). The proposed methodology integrates location–allocation and vehicle routing problem analysis. The performance of all possible scenarios is evaluated and compared by considering the number of required distribution centers and trucks, total travel time, total travel distance, as well as fairness among drivers. The results of the scenario analysis highlight that the alternative scenarios show a better performance as compared to the current network. In addition, the administrator can make a different decision among several alternatives by considering different aspects, such as investment cost, operating cost, and balance of using available resources. Therefore, it may help a public officer to design the fresh products logistics network considering actual demand and traffic conditions in Bangkok.

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