Incorporating uncertainty into a supplier selection problem

Supplier selection is an important strategic supply chain design decision. Incorporating uncertainty of demand and supplier capacity into the optimization model results in a robust selection of suppliers. A two-stage stochastic programming (SP) model and a chance-constrained programming (CCP) model are developed to determine a minimal set of suppliers and optimal order quantities with consideration of business volume discounts. Both models include several objectives and strive to balance a small number of suppliers with the risk of not being able to meet demand. The SP model is scenario-based and uses penalty coefficients whereas the CCP model assumes a probability distribution and constrains the probability of not meeting demand. Both formulations improve on a deterministic mixed integer linear program and give the decision maker a more complete picture of tradeoffs between cost, system reliability and other factors. We present Pareto-optimal solutions for a sample problem to demonstrate the benefits of the SP and CCP models. In order to describe the tradeoffs between costs and risks in an analytical form, we use multi-parametric programming techniques to more completely analyze the alternative Pareto-optimal supplier selection solutions in the CCP model. This analysis gives insights into the robustness of the solutions with respect to number of suppliers, costs and probability of not meeting demand.     

Big data analytics for supply chain relationship in banking

This paper reports how a commercial bank in Asia uses big data analytic as a tool to explore the internal B2B data to improve supply chain finance and the efficiency of marketing tactics and campaigns. A case study was conducted by analyzing two types of supply chain relationships: (1) supply chain relationships in the credit reports; (2) e-wiring transactions among supply chain companies. The results show that big data analytics is very useful in terms of improving the commercial banks' marketing and risk management performances. The case study also set a good example for B2B firms seeking to understand how they could leverage big data analytics to differentiate customer solutions, sustain profitability and generate new business values. Theorical and practical implications are also discussed.     

基于Adaboost-DPSO-SVM模型的供应链金融信用风险评价研究

数字化赋能供应链金融创新是推动我国产业链、供应链持续稳定优化升级的重要内容,在全球金融风险急剧增加的背景下,供应链金融与大数据、区块链、物联网、人工智能等技术相融合,成为解决我国中小企业融资授信问题的有效方式之一。本文在对供应链金融信用风险评价指标进行特征选择的基础上,采用一种动态变异的粒子群算法(DPSO)和AdaBoost算法对SVM进行协同优化和集成,建立了Adaboost-DPSO-SVM模型,并将该模型应用于我国新能源汽车行业供应链金融信用风险评价中,实验结果表明所建立的模型相对其他评价模型具有更好的分类识别性能。     

Evaluation of robustness of supply chain information-sharing strategies using a hybrid Taguchi and multiple criteria decision-making method

The advances in information technology have prompted the development of many supply chain information-sharing strategies, including electronic point of sales (EPOS), vendor-managed inventory (VMI), e-shopping, emergency transshipments, and so on. However, variations in the business environment can produce uncertainty and increase decision-making complexity for enterprises selecting from various supply chain information-sharing strategies. An effective and efficient supply chain strategy should be capable of reducing costs and raising customer-service levels, and should be capable of enhancing the robustness of the supply chain. In this study, the robustness of different supply chain strategies under various uncertain environments is studied using the simulated beer game. Techniques included Taguchi methodology and multiple criteria decision-making methods (MCDMs), including simple multiple attribute rating technology (SMART), technique for order performance by similarity to ideal solution (TOPSIS), and grey relational analysis (GRA). The signal-to-noise (S/N) ratio for each criterion is calculated to indicate the robustness of performance. This S/N ratio is used to determine an overall evaluation among various supply chain information-sharing strategies. The simulation results show that e-shopping has the most robust performance in uncertain environments.     

An empirical analysis of supply chain risk management in the German automotive industry

The purpose of this paper is the empirical analysis of supply chain risk management practices. The analysis is based on a survey with 67 manufacturing plants conducted in the German automotive industry. After investigating the vulnerability of supply chains in general and examining key drivers of supply chain risks, the paper identifies supply chain risks by analyzing their likelihood to occur and their potential impact on the supply chain. The results are visualized in the probability-impact-matrix distinguishing between internal and external supply chain risks. Furthermore, instruments for dealing with supply chain risks are investigated. Therefore, the impact of supply chain risk management on performance is tested. In order to distinguish between companies with a high degree of supply chain risk management and those with no or only limited implementation the plants are grouped by means of a cluster analysis based on factors reflecting the instruments of supply chain risk management. In particular, groups are created representing two different approaches to deal with supply chain risks, i.e. reactive and preventive supply chain risk management. The clusters are investigated concerning differences in terms of performance criteria. The analyses reveal that companies with a high implementation degree show a better supply chain performance. Furthermore, the results show that the group using reactive supply chain risk management has higher average value in terms of disruptions resilience or the reduction of the bullwhip effect, whereas the group pursuing preventive supply chain risk management has better values concerning flexibility or safety stocks.     

Mean-downside-risk and mean-variance newsvendor models: Implications for sustainable fashion retailing

Newsvendor models have been well-established for studying supply chain management problems with fashionable products. In this paper, we explore the mean-downside-risk (MDR) and mean-variance (MV) newsvendor models under both the exogenous and endogenous retail price decision cases. We first construct analytical models with the MDR and MV objectives. We then show that the analytical solution schemes for both the MDR and MV problems are the same. With the measures for sustainability such as the expected quantity of goods leftover, the expected sales to expected goods leftover ratio, the rate of return on investment, and the probability of achieving a pre-determined profit target, we proceed to compare the levels of sustainability by the fashion retailers which employ the mean-risk and the risk neutral models. Insights are generated.     

The bullwhip effect in capacitated supply chains with consideration for product life-cycle aspects

This paper presents an analysis of the bullwhip effect and net-stock amplification in a three-echelon supply chain considering step-changes in the production rates during a product's life-cycle demand. The analysis is focused around highly complex and engineered products (e.g., automobiles), that have relatively long production life-cycles and require significant capital investment in manufacturing. Using a simulation approach, we analyze three stages of the product life-cycle including low volumes during product introduction, peak demand, and eventual decline toward the end of the life-cycle. Parts of the simulation model have been adopted by a major North-American automotive OEM as part of a scenario analysis tool for strategic supply network design and analysis. The simulation results show that performance of a system as a whole deteriorates when there is a step-change in the life-cycle demand. While restriction in production capacity does not significantly impact the bullwhip effect, it increases the net stock amplification significantly for the supply chain setting under consideration. Furthermore, a number of important managerial insights are presented based on sensitivity analysis of interaction effect of capacity constraints with other supply chain parameters.     

Risk,uncertainty, ignorance and myopia: Their managerial implications for B2B firms

Rare events are common: Even though any particular type of ‘rare event’ - a world war, global economic collapse, or pandemic for that matter - should only occur once every 100 years, there are enough of those types of ‘rare events’ that overall, they commonly occur about once every 10 years. As we are currently experiencing with the COVID-19 pandemic, we do not sufficiently leverage the rich toolset that risk management offers to prepare for and mitigate the resulting uncertainty. This article highlights four aspects of risk management, and their practical and theorical implications. They are: 1) Risk (in the narrower sense), where possible future outcomes can be captured through probability distributions. 2) A situation of uncertainty, where there is transparency regarding what is not known, but probability distributions are unknown, as well as causal relationships influencing the outcome in question. 3) A situation of ignorance, where there is no understanding that certain possible future developments are even relevant. And finally: 4) The emergence of organizational and inter-organizational myopia as an effect of risk, uncertainty and ignorance on collective human behaviour.     

Coordinated supply chain scheduling

A mixed integer programming approach is proposed for a long-term, integrated scheduling of material manufacturing, material supply and product assembly in a customer driven supply chain. The supply chain consists of three distinct stages: manufacturer/supplier of product-specific materials (parts), producer where finished products are assembled according to customer orders and a set of customers who generate final demand for the products. The manufacturing stage consists of identical production lines in parallel and the producer stage is a flexible assembly line. The overall problem is how to coordinate manufacturing and supply of parts and assembly of products such that the total supply chain inventory holding cost and the production line start-up and parts shipping costs are minimized. A monolithic approach, where the manufacturing, supply and assembly schedules are determined simultaneously, is compared with a hierarchical approach. Numerical examples modeled after a real-world integrated scheduling in a customer driven supply chain in the electronics industry are presented and some computational results are reported.     

Supplier selection-order allocation: A two-stage multiple criteria dynamic programming approach

This paper proposes a two-stage multiple criteria dynamic programming approach for two of the most critical tasks in supply chain management, namely, supplier selection and order allocation. In the first stage, to address multiple decision criteria in supplier ranking, the analytic hierarchy process (AHP) is employed. In the second stage, supplier ranks are fed into an order allocation model that aims at maximizing a utility function for the firm as well as minimizing the total supply chain costs, subject to constraints on demand, capacity, and inventory levels. A dynamic programming approach is crafted to solve the proposed bi-objective model.     

Designing a reverse logistics network for optimal collection, recovery and quality-based product-mix planning

This study proposes an integrated, reverse logistics supply chain planning process with modular product design that produces and markets products at different quality levels. A mixed integer programming (MIP) model formulates the overall planning process required to maximize profit by considering the collection of returned products, the recovery of modules and the proportion of the product mix at different quality levels. This paper proposes the collection of returnables (end-of life, defective, product under warranty) through retail outlets combined with the recovery of modules from the collected products using a network of recovery service providers. The proposed modular product design approach would create a design criterion that provides an improved recovery process at a lower cost. This study uses a total supply chain view that considers the production, transportation and distribution of products to customers, while a numerical problem illustrates the applicability of the models.     

Appointment scheduling of outpatient surgical services in a multistage operating room department

This article addresses the appointment scheduling of outpatient surgeries in a multistage operating room (OR) department with stochastic service times serving multiple patient types. We discuss many challenges, such as the limited availability of multiple resources (e.g., staff, operating rooms, surgeons, and recovery beds), and the compatibility of patient and surgeon types. In addition, availability of surgeons is restricted by time window constraints. Three simulation-based optimization methods have been proposed to minimize the patients’ wait time, patients’ completion time, and number of surgery cancellations. The first method is simulation-based tabu search (STS). It combines discrete-event simulation and tabu search to schedule surgery cases. The second and third methods are integer programming enhanced tabu search (IPETS) and binary programming enhanced tabu search (BPETS). IPETS and BPETS improve on STS by incorporating integer programming and binary programming models, respectively. This article includes a case study of an OR department in a major Canadian hospital. We further expand the actual data obtained in the case study to cover a wide range of parameters in sets of test problems, and provide analysis on the efficiency and effectiveness of the proposed methods in comparison with several scheduling rules. Finally, comments on the applications of the proposed methods are provided.     

全球价值链与中国地方产业集群的供应链式整合--以苏浙粤纺织服装产业集群为例

地方产业集群的发展不仅需要全球价值链嵌入和耦合的推动,同时集群的供应链式整合(即地方产业集群在同一地域形成完整或近乎完整的价值链)也是地方产业集群升级的关键,这样才能保证地方产业集群在与全球价值链耦合时获取价值链中高附加值、核心战略环节的竞争优势。文章阐述了全球价值链与地方产业集群的供应链整合的三种模式,并以中国纺织服装产业为实例,通过苏(横扇镇)、浙(织里镇)、粤(沙溪镇)三地的纺织服装产业集群,来分析在面对纺织服装产业“后配额时代”的到来,如何将全球价值链与进行集群供应链式整合并实现产业升级;在此基础上说明中国纺织服装产业集群在供应链式整合和嵌入全球价值链过程中所面临的障碍;最后提出地方产业集群的升级思路和途径。     

Applying activity-based costing in a supply chain environment

Traditional intra-firm cost accounting tools are not appropriate in the context of supply chain management, as there are no standards for the definition and composition of costs. This prohibits exchange and comparison of cost data among different supply chain members. Against this background, several activity-based costing models for inter-firm cost accounting have been proposed. Evaluating these models, a conceptual framework for activity-based costing in a supply chain has been developed. This also forms the basis for a single case study conducted at Europe's largest company for façade components. This demonstrates how significant inter-firm cost saving opportunities can be identified and offers a first step in assessing the suitability of the proposed model.     

Cross-border e-commerce firms as supply chain integrators: The management of three flows

Cross-border e-commerce is becoming increasingly popular around the world. With the development of technology, competition has gradually shifted from commodity-based attributes, such as cost and quality, to a supply chain's service capacity for e-commerce. Within this context, the present paper delineates how cross-border e-commerce firms can generate supply chain service capabilities that yield improvements in supply chain relationship quality to e-tailors and other platform users. Insights are derived through data collected via a multiple case study approach based on four Chinese cross-border e-commerce enterprises (OSell, Zongteng, BizArk and Linca); data were collected from 41 semi-structured interviews, field visits and secondary data. Relying on the service-dominant logic as the theoretical foundation, we identify three supply chain resources (flows related to information, logistics and finance) and their interplay as being critical for the development of supply chain service capabilities, which in turn lead to an improvement in the quality of supply chain relationships (assessed by the dimensions of trust improvement/commitment, risk mitigation, and customer satisfaction). The results offer important insights into how to best manage supply chain resources in relation to the three flows by cross-border e-commerce firms in order to foster relationship quality, an attribute that has become so critical today for competitive differentiation.     

Identifying risk issues and research advancements in supply chain risk management

The purpose of this paper is to investigate the research development in supply chain risk management (SCRM), which has shown an increasing global attention in recent years. Literature survey and citation/co-citation analysis are used to fulfil the research task. Literature survey has undertaken a thorough search of articles on selected journals relevant to supply chain operations management. Meanwhile, citation/co-citation analysis uses Web of Sciences database to disclose SCRM development between 1995 and 2009. Both the approaches show similar trends of rising publications over the past 15 years. This review has piloted us to identify and classify the potential risk associated with different flows, namely material, cash and information flows. Consequently, we identify some research gaps. Even though there is a pressing need and awareness of SCRM from industrial aspect, quantitative models in the field are relatively lacking and information flow risk has received less attention. It is also interesting to observe the evolutions and advancements of SCRM discipline. One finding is that the intellectual structure of the field made statistically significant increase during 2000-2005 and evolved from passively reacting to vague general issues of disruptions towards more proactively managing supply chain risk from system perspectives.     

Comparing CONWIP,synchronized CONWIP,and Kanban in complex supply chains

Three types of JIT ordering systems used for supply chain management were quality tested, the Kanban, the original constant work-in-process (CONWIP), and a synchronized CONWIP. The synchronized CONWIP system is described for its ability to handle complicated supply chains, which consist of assembly stages with different lead times. In the system, orders for each process are released while adjusting the lead time of the subsequent process, and the released and processed orders are synchronized during the assembly stages. Practical questions, that is, which system is superior and which parameter affects superiority, were investigated for the three types of systems.     

A multi-objective robust optimization model for multi-product multi-site aggregate production planning in a supply chain under uncertainty

Manufacturers need to satisfy consumer demands in order to compete in the real world. This requires the efficient operation of a supply chain planning. In this research we consider a supply chain including multiple suppliers, multiple manufacturers and multiple customers, addressing a multi-site, multi-period, multi-product aggregate production planning (APP) problem under uncertainty. First a new robust multi-objective mixed integer nonlinear programming model is proposed to deal with APP considering two conflicting objectives simultaneously, as well as the uncertain nature of the supply chain. Cost parameters of the supply chain and demand fluctuations are subject to uncertainty. Then the problem transformed into a multi-objective linear one. The first objective function aims to minimize total losses of supply chain including production cost, hiring, firing and training cost, raw material and end product inventory holding cost, transportation and shortage cost. The second objective function considers customer satisfaction through minimizing sum of the maximum amount of shortages among the customers’ zones in all periods. Working levels, workers productivity, overtime, subcontracting, storage capacity and lead time are also considered. Finally, the proposed model is solved as a single-objective mixed integer programming model applying the LP-metrics method. The practicability of the proposed model is demonstrated through its application in solving an APP problem in an industrial case study. The results indicate that the proposed model can provide a promising approach to fulfill an efficient production planning in a supply chain.     

Food health risk perceptions among consumers,farmers, and traders of leafy vegetables in Nairobi

Urban and peri-urban farming and supply chains are becoming increasingly important for delivering perishable produce to the urban centers of the developing world to meet the demands of a growing population. However, some production and handling practises and a short supply chain may expose consumers to substantial health risks. This study of consumers, peri-urban farmers, and traders attempts to quantify subjective risk judgments with regard to food safety hazards, and examines the extent of discrepancies in perceived risk relating to vegetables in domestic urban markets among the three groups. A conceptual model was developed to elicit subjective risk perceptions for a multidimensional construct. In general, differences were found between respondent categories in terms of both specific source risks and overall risks. Differences were also found with respect to the socio-demographic and structural determinants of the levels of perceived risks. These findings can help improve policies to promote food safety and reduce risky food handling along the supply chain, and present opportunities for change.     

Digitalization within food supply chains to prevent food waste. Drivers,barriers and collaboration practices

Food supply chains increasingly rely on big-data management solutions to foster collaboration across the food supply chain and improve business performance. However, little is known about collaboration practices that actors on the digital food supply chain adopt to solve problems such as food waste, or about the drivers and barriers related to the digital transformation of the food supply chain. Most of food waste studies rely on quantitative analysis, which cannot reveal relevant details about the tensions and dynamics of collaboration. We conducted a qualitative study drawing on eighteen in-depth interviews - of managers of large multinational and local organizations covering different and relevant roles on the digital food supply chain - to investigate how organizational and food supply chain processes are affected by the digitalization of the operations along the food supply chain. By triangulating emerging findings with literature on supply chain management we discuss different views about collaborative practices for food waste prevention in the food supply chain and provide insights on how supply chain design and firms' operations have been re-conceptualized with the usage of digital technologies and on the institutional forces both limiting (barriers) and fostering (drivers) the diffusion of the digital food supply chain.