Supply chain coordination: Perspectives, empirical studies and research directions

This chapter aims to go some way towards addressing the dearth of research into performance measurement systems and metrics of supply chains by critically reviewing the contemporary literature and suggesting possible avenues for future research. The article provides a taxonomy of performance measures followed by a critical evaluation of measurement systems designed to evaluate the performance of supply chains. The chapter argues that despite considerable advances in the literature in recent years, a number of important problems have not yet received adequate attention, including: the factors influencing the successful implementation of performance measurement systems for supply chains; the forces shaping their evolution over time; and, the problem of their ongoing maintenance. The chapter provides both a taxonomy of measures and outlines specific implications for future research.

Measuring Supply Chain Performance: Current Research and Future Directions

Improving supply chain performance has become one of the critical issues for gaining competitive advantages for companies. This paper proposes a framework using a systematic approach to improving the iterative key performance indicators (KPIs) accomplishment in a supply chain context. The proposed framework quantitatively analyzes the interdependent relationships among a set of KPIs. It can identify crucial KPI accomplishment costs and propose performance improvement strategies for decision-makers in a supply chain. A scenario of a large retail company is also discussed to explain the application of this framework.

Improving supply chain performance management: A systematic approach to analyzing iterative KPI accomplishment

The paper investigates the relationship between analytical capabilities in the plan, source, make and deliver area of the supply chain and its performance using information system support and business process orientation as moderators. Structural equation modeling employs a sample of 310 companies from different industries from the USA, Europe, Canada, Brazil and China. The findings suggest the existence of a statistically significant relationship between analytical capabilities and performance. The moderation effect of information systems support is considerably stronger than the effect of business process orientation. The results provide a better understanding of the areas where the impact of business analytics may be the strongest.

The Impact of Business Analytics on Supply Chain Performance

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The impact of business analytics on supply chain performance

Research on supply chain management can be broadly classified into three categories, namely, operational, design, and strategic. While many analytical and numerical models have been proposed to handle operational and design issues, formal models for strategic planning are scarce. The supply chain operations reference (SCOR) model, developed by the Supply Chain Council, is a strategic planning tool that allows senior managers to simplify the complexity of supply chain management. It is firmly rooted in industrial practices and is poised to become an industrial standard that enables next‐generation supply chain management. This paper gives a brief introduction to the SCOR model, analyzes its strength and weakness, and discusses how it can be used to assist managers for strategic decision making.

Ge Wang

Papers

A review and analysis of supply chain operations reference (SCOR) model