Supply Chain Management Decisions Research Articles

Behavioral Tendencies in Newsvendor Decision Making: Capturing the Chinese Perspective

After many decades on focusing only on quantitative approaches for making decisions in manufacturing and supply chain management, researchers in operations management have recently acknowledged the importance of understanding the human behavior tendencies underlying these decisions. The result is a new stream of research in operations management focused on experiments using human subjects. However, most of these experiments were conducted in the US and Europe with the subject pool (students as well as practitioners) with western cultural and educational backgrounds. As the students and practitioners in China are culturally and educationally different from their western counterparts, it is conceivable that their behavioral tendencies are very different. Given that a large portion of the world’s industrial output comes from China, an understanding of the behavioral tendencies specific to those geographical regions is essential to achieve significant efficiency gains in the world economy. We compare results from experiments conducted in the US and China and observe that Chinese decision makers (i) ask a lot more questions before reaching their decision indicating that they are more worried about making the wrong decision; (ii) are more frequently able to come up with a new number as their decision whereas the American decision makers tend to use one of the given numbers as their decision; and (iii) are more cognizant of salvage values and as a result order more than the American decision makers.

A Hierarchical Decision Support System for Supplier Selection in Process Industry

Supplier selection is recognized as a critical decision in supply chain management in process industries. In such industries the procurement department plays an important role in reducing purchasing cost and selecting appropriate suppliers. The supplier selection problem is a multi criteria unstructured problem. Several key factors like quality, cost, delivery time and warranty etc., are commonly involved in the supplier selection decision making process. In this paper a hierarchical decision support system was developed for selecting the best supplier by using analytic hierarchy process model. This model was illustrated with a case study in a cement industry.

Are Indians ready to adopt online supply chain management?

E-commerce is the enabler of supply chain management (SCM). Indian industry is not using e-commerce tools for SCM to a great extent. The objective of this exploratory study is to understand the determinants of development of e-commerce in SCM within Indian industry and to test the value of supply chain functionalities and organisation strategies in explaining e-commerce development. The result confirmed with the literature that e-commerce functionalities and organisation functionalities influence the e-commerce development level. The study also showed that one of the factors of supply chain functionalities, SCM coordination level was significantly related to the e-commerce development level. Besides, e-commerce also facilitates e-bidding for sourcing decisions in SCM. Using the internet, reverse e-auctions allow suppliers to compete dynamically in real time for buyer's business. The buying organisations who have adopted reverse e-auctions and those not used e-auctions for sourcing decisions are also diffe...

How transfer prices can affect a supply chain strategic decision

One of the most important decisions in global supply chain management is whether to outsource or in-source production. This decision is made by reference to a set of quantitative and qualitative models. However, one factor has frequently been overlooked: the tax consequences that result from multi-national company transfer prices. The purpose of this paper is to fill the void by: 1) explaining how transfer prices affect tax obligations; 2) discussing the arm's length standard that governs global transfer pricing; 3) demonstrating how global tax differentials can affect the offshoring decision. We conclude with suggestions for future research.

A review on the role of activity-based costing information and costs structure integration in supply chain and operations

In recent times, activity-based costing (ABC) has been evolving to a managerial and cost accounting system rather than a mere cost accounting. The popularity of integration of the ABC in the mathematical models of supply chain management (SCM) for decision support further emphasises the managerial scope of ABC. In this paper, we review the significant role of ABC information and cost structure integration in supply chain mathematical decision support modelling, with the aim of comparing its applicability at different managerial hierarchy levels. The presented literature provides a framework for evaluating the suitability of ABC into different SCM decision making processes.

Simulating A State Of The Art Agent Based System With Fuzzy Reasoning For Supply Chain Coordination

With the emergence of high speed wireless networks and parallel advancements in Internet based technologies such as the Semantic Web, Web Services, Multi Agent Systems, and Context Awareness, the realization of the vision of the intelligent wireless web (IWW) has become a possibility. On the other side, recent developments in the field of multi criteria decision making, have led us to more accurate and applicable algorithms. In this paper, we are going to summarize the details and results of a multidisciplinary agent based software, namely SWESS that enables real-time supply chain coordination through taking advantage of different methods of different scientific areas such as computer science, supply chain management and multi criteria decision making.

Establishing the relationship between logistics complexity and supply chain objectives and decision areas in large companies operating in Brazil

This paper reports an attempt to explore the relationships between logistics complexity and supply chain management (SCM) objectives and decision areas in large manufacturing companies operating in Brazil. Literature review is conducted, followed by survey research data (using a sample of 108 large companies operating in Brazil) analysis using cluster analysis, factor analysis and binary logistic regression. Results suggest that the level of logistics complexity of companies is a driver of management choices in supply chain objectives and decision areas, confirming our initial proposition that a contingency approach for supply chain management would be more appropriate than the "best practice" one. At the end of the article some further conclusions are drawn and opportunities for further research are discussed.

Knowledge, values and internationalisation—introduction to the special edition

Internationalisation is increasingly being seen as an organisational learning process. However, entrepreneurial enterprises tend to be smaller, more innovative and more agile than their larger counterparts. When they internationalise, entrepreneurial firms often expand at a rapid rate. The cultures of so-called ‘born global’ firms also appear to differ from firms that internationalise in a more gradual, stepwise fashion. This raises interesting questions about how entrepreneurial firms acquire and manage knowledge about markets, networks and capabilities in turbulent and uncertain environments and how the values embedded in organisational cultures might influence strategic choices. The following articles in this special edition of the Journal of International Entrepreneurship focus specifically on how innovative firms—particularly small and medium-sized enterprises—recognise and exploit market opportunities, how they learn from international market entry and penetration experiences to improve core capabilities and how values may influence supply chain management and start-up decisions.

Transferring academic decision models to practitioners: a structured process

The decision support model presented in this paper is the result of a research project initiated by a large organisation operating in an emerging economy. The exotic business context of this company generated many reservations and questions about the applicability of traditional supply chain management models in terms of the decisions that should be made to design a supply chain. As supply chain management decisions are complex, decision makers often rely on approximate, ineffective decision making processes. Through a process rooted in decision analysis, this paper shows how apparently conflicting academic models of supply chain system design were successfully transferred, absorbed, customised and used by the company.

A modelling approach for outsourcing decisions in Supply Chain Management

The rapidly changing global market scenario is increasingly forcing manufacturing firms to pursue outsourcing as an important option. From a research viewpoint, one issue that has remained relatively unexplored is the effect that capacity expansion with availability of overtime option and upstream supplier cost structure has on outsourcing decisions. There is scant research exploring the circumstances in which mixed models (fraction of demand) might be appropriate (Harland et al., 2005). The suggested model explicitly considers pricing and outsourcing simultaneously by operationalising the outsourcing decision through a variable that captures the fraction of demand met by in-house manufacturing through overtime.

Aligning supply chain management and new product development: a theoretical framework

Product features are defined by new product development (NPD) process so to fulfil clients' requirements. Supply chain performances are affected by product features. The magnitude of this effect is determined by supply chain decisions. In order to satisfy client's needs, in terms of new products, service level and costs, supply chain management (SCM) decisions should be aligned to product features, i.e., to the output of NPD process. Literature analysis shows that external and internal product variety and product novelty are the main product features to be considered to align SCM decisions to NPD. We developed a framework for NPD-SCM alignment assessment that takes into account all these relevant variables. NPD-SCM alignment is reached when the level of variety/innovation that is created during NPD and the variety/innovation that is/can be transported by the supply chain is equal to clients needs. A case study is presented to support the framework.

BPM-based integration of supply chain process modeling, executing and monitoring

Due to increased competition in business environments, many companies implement Supply Chain Management (SCM), which utilizes advanced information technologies. Since the execution of the Supply Chain Process (SCP) requires interaction and information sharing among multiple organizations, there have been efforts to apply Business Process Management (BPM) techniques to SCM implementation. Whereas previous research has focused mainly on automated execution of the SCP, effective SCM requires the integrated lifecycle management of SCP that includes modeling, execution, and monitoring. Thus, in this research, we develop, based on the BPM system, an integrated architecture to support modeling, execution and monitoring of SCP. To model the SCP, we propose to use Business Process Execution Language (BPEL), which facilitates easy process sharing among supply chain members who adopt heterogeneous information systems. Since SCM decisions require complex analytical calculations concerning multiple different companies, it is necessary to separate the process logic and the decision algorithm. Thus, we developed an SCP execution structure in which the decision algorithm is implemented as an agent that is invoked using Web services. While BPM enables process monitoring, the multi-organizational environment considered here involves the important issue of the setting and controlling of access levels of each company's process information to be monitored. To address this problem, we propose a role-based supply chain process monitoring (RSCPM) model. A prototype system is implemented.

Logistical network design with robustness and complexity considerations

PurposeThis paper aims to propose a logistical network design framework with robustness and complexity considerations.Design/methodology/approachThe paper defines robustness, complexity, and normalised efficiency of a logistical network. A mathematical model is then constructed based on the conceptual framework and applied to a hypothetical case study with varying robustness requirements. The mathematical model is formulated as an Mixed‐Integer Linear Programming problem. Furthermore, the paper introduces a graph‐theoretic view of the logistical network and presents its topological properties such as average path length, clustering coefficient, and degree distribution.FindingsThe results show that logistical network configurations can be obtained with desirable robustness levels whilst minimising cost. The relationships of robustness versus normalised efficiency and complexity are also presented. The results show that relationships between logistical network topological properties and robustness exist, as in other real world natural and man‐made complex networks.Practical implicationsLogistical network design is one of the earliest strategic decisions in supply chain management that supply chain managers have to make. Practitioners and researchers typically focus on optimising efficiency and/or responsiveness of logistical networks. It is argued that logistical network designers should also consider robustness and complexity as they are important characteristics of logistical network functionality. The logistical network design frame work successfully incorporates robustness and complexity into design considerations.Originality/valueThis paper newly introduces other important performance measures, robustness and complexity, into the logistical network design objective. The design framework is highly relevant and adds value to logistical network designers and managers.

Solving four-echelon integrated inventory model using a heuristic approach

Supply chain management is the integration of logistics and information from the suppliers to the consumers where all members of the chain must work together for the benefit of the whole system. The objective of this study is to present a heuristic approach to solve a four-echelon integrated inventory model in order to minimize the total cost of the whole supply chain.We apply the heuristic approach to derive the global solution by means of branch-and-bound method. The numerical example demonstrates the proposed solution procedure and limitations of the proposed method. Finally, sensitive analysis is carried out to study the influence of different stocking strategies on the performance of the supply chain. This can provide some insight to the executives in the supply chain management decision.

Following the Thread: Industry Cluster Theory, the New England Cotton Textiles Industry, and Implications for Future Supply Chain Research

The purpose of this paper is to introduce supply chain management researchers to industry cluster theory within the context of supply chain management decisions. Industry cluster theory emphasizes the explicit and implicit benefits that accrue to various economic players due to geographic proximity. As such, it provides a contrasting view to the current pressure on supply chains to seek out the “best” partners, regardless of location. We review the theory behind industry clusters, and illustrate it using the example of the New England cotton textile industry. Incorporating these concepts into future research has the potential to improve our understanding of how decisions regarding supply chain location and sourcing decisions are currently made, and what role location‐based benefits should play in these decisions.

A Theoretical Framework of Risk Compensation in Supply Chain Management Decision Making

The goal of this study is to develop a theoretical framework for the study of decision makers within supply chains. Decision makers may compensate inappropriately by overstocking or overestimating lead times resulting in greater inventory costs. By leveraging the knowledge associated with risk compensation, better accountability of logistics and inventory holding costs can be achieved. Although there are conflicting views on risk compensation, the theory does provide insights into the complexities facing the decision maker in supply chain environments. More specifically, there has been relatively little research examining how human factors issues impact the supply chains' effectiveness. The risk compensation framework is tailored to represent and model the inventory management portion of the supply chain and can be validated through experimentation by evaluating the operator's perceived risks. In developing this model, the foundations for extending our knowledge of the human decision making in supply chain management can be established.

Enhancing supply chain solutions with the application of chaos theory

PurposeThe purpose of this article is to expand the base of supply chain knowledge by applying chaos theory principles to selected supply chain functions.Design/methodology/approachResearchers borrow chaos theory from the natural sciences, provide a basic explanation, and then examine how it may be applied to enhance supply chain management techniques.FindingsChaos theory principles are used to assist in the examination of forecasting, product design, and inventory management challenges currently facing supply chain practitioners.Research limitations/implicationsApplication of chaos theory to various supply chain issues and key functional areas may produce an increase in the level of understanding of supply chain ambiguity and how chaos theory may provide valuable insight into the effective management of supply chain networks.Practical implicationsWhen applied correctly, chaos theory shows potential to be a tool that can be instrumental in helping explain why unpredictability occurs within nonlinear systems. A better understanding of this phenomenon may help researchers to develop better, more accurate models to assist managers in making better supply chain management decisions, benefiting organizations and customers by simultaneously enhancing cost‐effectiveness and improving customer service levels.Originality/valueThe principles of chaos theory have been introduced as a method that shows early promise as a tool to enhance supply chain effectiveness. Specific applications must now be examined through empirical research.

Effectiveness and efficiency: the role of demand chain management

PurposeThe paper aims to focus on and discuss the differences between the demand chain led organization and the supply chain led organization.Design/methodology/approachThe paper uses a desk‐based approach to data collection and provides analysis and discussion of the issues.FindingsThe paper finds that the differences between the demand chain led organization and the supply chain led organization are ones of emphasis. Supply management is cost‐led and attempts to provide an adequate level of service. By contrast the demand chain approach is a broader view of relationship management taking a view that the two overlap and that effective management is to integrate the two.Originality/valueThe paper focuses on the increasing importance of demand chain and supply chain management decisions.

Quantifying the Environmental Footprint of Semiconductor Equipment Using the Environmental Value Systems Analysis (EnV-S)

Many environmental and health impacts from semiconductor processing are tied to the design of the manufacturing equipment. Evaluating solutions to properly treat effluents from semiconductor tools has become an increasingly important part of supply chain management and equipment procurement decisions. Accordingly, understanding the environmental footprint associated with equipment sets is essential for both equipment manufacturers and semiconductor manufacturers seeking to improve their products' environmental and financial performance. Equipment environmental performance must be evaluated within the context of the factory infrastructure and auxiliary equipment sets, with appropriate allocations of impacts from additional steps, both upstream and downstream of the wafer processing tools (chemical precursor delivery as well as byproduct treatment). Several challenges to environmental assessments arise from the nature of semiconductor manufacturing itself, due to short process life cycles, complexity of processes, and the need to track diverse inter-related impacts. Environmental value systems analysis (EnV-S) is an analytical tool to evaluate the environmental performance of semiconductor processing. EnV-S develops environmental assessments through a "bottom-up" analysis approach, assembling equipment environmental models to describe a system. This paper presents the use of EnV-S as a tool to quantify the environmental impact of a product or process by creating an operational signature along multiple dimensions of cost and environmental and health factors. The use of EnV-S is illustrated through a case study comparing systems that abate emissions from dielectric chemical vapor deposition processes.

A Use of Analytic Network Process for Supply Chain Management

Strategic decision analysis on Supply Chain Management (SCM) involves tangible and intangible factors and it needs to be evaluated by interdependent multiple criteria. Analytic Hierarchy Process (AHP) is a practical and popular decision-making tool for SCM. Interdependency among criteria becomes a source of difficulty in directly applying AHP to various SCM decision problems. Hence, the managerial issue is examined by Analytic Network Process (ANP), the general form of AHP. This study addresses a new use of ANP on SCM strategic decision analysis such as a supplier selection and improvement of supply chain performance.