Jc Jan Fransoo

Operations management research methodologies using quantitative modeling

Gives an overview of quantitative model‐based research in operations management, focusing on research methodology. Distinguishes between empirical and axiomatic research, and furthermore between descriptive and normative research. Presents guidelines for doing quantitative model‐based research in operations management. In constructing arguments, builds on learnings from operations research and operations management research from the past decades and on research from a selected number of other academic disciplines. Concludes that the methodology of quantitative model‐driven empirical research offers a great opportunity for operations management researchers to further advance theory.

Measuring the bullwhip effect in the supply chain

Increased demand variability in supply chains (the bullwhip effect) has been discussed in the literature. The practical measurement of this effect, however, entails some problems that have not received much attention in the literature and that have to do with the aggregation of data, incompleteness of data, the isolation of demand data for defined supply chains that are part of a greater supply web. This paper discusses these conceptual measurement problems and discusses experiences in dealing with some of these problems in an industrial project. Also presents empirical results of measurements of the bullwhip effect in two supply chains.

A Typology of Production Control Situations in Process Industries

Discusses the variety of production control situations within process industries. Following a literature review, a typology is introduced which discriminates between two extreme types of process industries: batch/mix and process/flow businesses. Reviews the research in production and inventory control in each of the extreme types. Identifies a control framework for operations management in process/flow businesses. Notes that although detailed scheduling approaches for batch/mix businesses exist, a control framework for the latter is missing. Concludes that operations management in batch process industries needs considerable research attention.

Cooperation between multiple news-vendors with transshipments

We study a situation with n retailers, each of them facing a news-vendor problem, i.e., selling to customers over a finite period of time (product with a short life cycle, such as fashion). Groups of retailers might improve their expected joint profit by coordinating their orders, followed by transshipments after demand realization is known. We analyze these situations by defining a cooperative game, called a general news-vendor game, for such a situation with n retailers. We concentrate on whether it makes sense to cooperate by studying properties of general news-vendor games. Our main result states that general news-vendor games have non-empty cores.

Planning supply chain operations: definition and comparison of planning concepts

Publisher Summary This chapter discusses the supply chain operations planning (SCOP) problem. The objective of SCOP is to coordinate the release of materials and resources in the supply network under consideration such that customer service constraints are met at minimal cost. The chapter discusses the material aspect and resource aspects of the SCOP problem. It also discusses the concept of planned lead times, in which two optimization problems are used as a basis for comparison among different supply chain planning (SCP) concepts. The SCOP function is responsible for the coordination of activities along the supply chain, by making decisions on the quantities and timing of material and resource releases. This chapter explicitly models the supply chain as a network—that is, the activities that transform inputs into outputs using available resources are preceded by multiple transformation activities and succeeded by multiple transformation activities. A transformation activity is a general designation of any type of relationship between two items in a supply chain.

Planning and control of rework in the process industries: A review

For all kinds of reasons, rework, i.e. the transformation of products not fulfilling preset specifications into products that do, is an important issue in process industries. Despite a considerable amount of published research on planning and control of rework, and in addition many papers referring to the existence of rework in the process industries, hardly any attention has been paid to the consequences of many process industries specific characteristics for execution, planning and control of rework operations. Here are identified the characteristics of the process industries that influence the possibilities for rework in these industries, based on a framework provided by Flapper and Jensen ( International Journal of Production Research , 1999, to be published). How the available operations management literature assists in determining operational strategies for planning and control of rework in process industries is assessed. It is concluded that many relevant and interesting problems have not been addressed.

Drivers of close supply chain collaboration: one size fits all?

Purpose – The purpose of this paper is to investigate the antecedents of close supply chain collaboration and to develop a multi‐variable conceptual model of factors that drive the need for close supply chain collaboration.Design/methodology/approach – A multi‐variable conceptual model is developed based on literature and on a series of dyadic mini‐cases in the electronics, fashion and consumer‐packaged goods industry.Findings – This paper confirms that close supply chain collaboration is influenced by a multitude of factors. It reveals a need to integrate findings from analytical and empirical disciplines that study supply chain collaboration. The results suggest that collaborative initiatives are predominantly initiated with suppliers and not with customers, and that close supply chain collaboration may lead to inertia in business relations.Research limitations/implications – This paper is based on dyadic case studies in three different make‐to‐stock industries; future research may include a large‐scale...

Capacity reservation and utilization for a manufacturer with uncertain capacity and demand

We consider an original equipment manufacturer (OEM) who has outsourced the production activities to a contract manufacturer (CM). The CM produces for multiple OEMs on the same capacitated production line. The CM requires that all OEMs reserve capacity slots before ordering and responds to these reservations by acceptance or partial rejection, based on allocation rules that are unknown to the OEM. Therefore, the allocated capacity for the OEM is not known in advance, also because the OEM has no information about the reservations of the other OEMs. Based on a real-life situation, we study this problem from the OEM’s perspective who faces stochastic demand and stochastic capacity allocation from the contract manufacturer. We model this problem as a single-item, periodic review inventory system, and we assume linear inventory holding, backorder, and reservation costs. We develop a stochastic dynamic programming model, and we characterize the optimal policy. We conduct a numerical study where we also consider the case that the capacity allocation is dependent on the demand distribution. The results show that the optimal reservation policy is little sensitive to the uncertainty of capacity allocation. In that case, the optimal reservation quantities hardly increase, but the optimal policy suggests increasing the utilization of the allocated capacity. Further, in comparison with a static policy, we show that a dynamic reservation policy is particularly useful when backorder cost and uncertainty are low. Moreover, we show that for the contract manufacturer, to achieve the desired behavior, charging little reservation costs is sufficient.

Consumer responses to shelf-out-of-stocks of perishable products

Purpose – This paper aims to identify customer behavior with regard to out‐of‐stocks (OOS) of perishable products (focused on bakery bread) and the resulting inventory performance for these perishable products.Design/methodology/approach – Insights on how consumers behave when their preferred bread product is OOS are derived based on 3,800 customer interviews performed in three stores of a large Dutch grocery retail chain. Next to this, additional logistical information was measured on regular moments with respect to the shelf availability per stock‐keeping unit during the day and to waste at the end of the day.Findings – The customer behavior with regard to perishables is observed to be different from that for the non‐perishable items. The key observation is that customers have a high willingness to substitute. The incorporation of the obtained knowledge of the observed consumer buying behavior into the existing automated store ordering (ASO) systems is discussed. In the current ASO systems, no distincti...

Identification of Employment Concentration Areas

This article presents a method to identify “Absolute and Relative Employment Concentration (AREC) areas” for a particular industry. Two novel characteristics of the method are that it simultaneously analyses AREC, and that it combines spatial concentration per area with the spatial concentration in neighbouring areas. The method is easy to understand and apply. It is developed to assist regional policy makers and corporate decision-makers with their investment decisions related to new infrastructure or plants. The identification of concentration areas also allows for analysing the performance of these areas in relation to characteristics such as infrastructure availability and the housing and labour market. This can yield new academic insights that are relevant for regional planners. An application of the newly developed method to five industries in a Dutch province subdivided into 502 areas illustrates the value of the method in comparison to other methods.