C. H. Glock

Supply chain coordination with emissions reduction incentives

The European Union Emissions Trading System (EU-ETS) is considered one of the main legislative systems that are set up to reduce emissions and protect the environment. Most of the works in the literature approach this system from a legislation and/or global point of view. Little has been done to examine this system from the perspective of the user. This work is believed to be the first to consider the EU-ETS system in a supply chain and operations management context. A two-level (vendor–buyer) supply chain model with a coordination mechanism is presented while accounting for greenhouse gas (GHG) emissions from manufacturing processes. Different emissions trading schemes are considered, and possible combinations between these schemes are presented. The developed model could be found useful by mangers who wish to jointly minimise the inventory-related and GHG emissions costs of their supply chains when penalties for exceeding emissions limits are considered. Numerical examples are presented, and results are discussed.

A multiple-vendor single-buyer integrated inventory model with a variable number of vendors

Supply chain management is concerned with the coordination of material and information flows in multi-stage production systems. A closer look at the literature reveals that previous research on the coordination of multi-stage production systems has predominantly focused on the sales side of the supply chain, whereas problems that arise on the supply side have often been neglected. This article closes this gap by studying the coordination of a supplier network in an integrated inventory model. Specifically, we consider a buyer sourcing a product from heterogeneous suppliers and tackle both the supplier selection and lot size decision with the objective to minimise total system costs. First, we provide mathematical formulations for the problem under study, and then suggest a two-stage solution procedure to derive a solution. Numerical studies indicate that our solution procedure reduces the total number of supplier combinations that have to be tested for optimality, and that it may support initiatives which aim on increasing the efficiency of the supply chain as a heuristic planning tool.

Sustainability strategies in an EPQ model with price‐ and quality‐sensitive demand

This paper studies a manufacturer producing a single product which is sold on a market where demand is sensitive to price and quality. The production process of the manufacturer is assumed to impact the environment, for example by producing emissions or scrap or by consuming non-renewable resources. The environmental impact of the production process is treated as a quality attribute in this paper, and it is assumed that environmentally conscious customers are willing to pay a higher price for the product in case the environmental impact of the production process is reduced (or, likewise, a higher degree of sustainability is achieved). The model developed in this paper studies the trade-off between sustainability, costs and demand and proposes strategies to maximise the manufacturer’s profit. INTRODUCTION There is a growing recognition that corporations play a critical role in achieving global sustainability (Shrivastava, 1995). Over the last two decades, individual corporations and industry associations in virtually all economic sectors have developed policies, plans, and programs to address sustainability issues. These initiatives typically focus on addressing the “triple bottom line” of corporate economic, environmental, and social performance (Elkington, 1997). One industry that has been particularly active in implementing sustainability initiatives is the manufacturing sector. There are ongoing debates on what sustainability means in a manufacturing context. There is no universally accepted definition of sustainable manufacturing or sustainable production. However, one widely-used definition of sustainable production defines it as “creating goods by using processes and systems that are non-polluting, that conserve energy and natural resources in economically viable, safe and healthy ways for employees, communities, and consumers which are socially and creatively rewarding for all stakeholders in the shortand long-term future” (Glavic and Lukman, 2007). Although each corporation will define sustainability according to its own needs, this definition provides insight into the goals, objectives, and targets typically associated with sustainability initiatives in the manufacturing sector. To help measure the success or failure of their sustainability initiatives, many corporations in the manufacturing sector have developed sustainability indicators. The development of sets of sustainable production indicators has also been the subject of several academic publications, including Veleva and Ellenbecker (2001), Krajnc and Glavic (2003), and Fan et al. (2010). Many other papers have explored the development of sustainability indicators for specific companies within the manufacturing sector. An extensive review of the state-of-the-art of industrial sustainability indicators was provided by Arena et al. (2009). However, while the literature shows that many meaningful contributions have been made, work remains. In particular, none of the indicators in the publications noted above have explicitly explored the link between a corporation’s sustainability performance and demand for its products. A recent systematic review of 91 articles showed that the research on consumer willingness to pay for ethically produced goods – encompassing issues such as environmental and labour practices – has yielded mixed results (Cotte and Trudel, 2009). However, the overall findings of the systematic review suggested that consumers were

The effect of worker learning and forgetting on storage reassignment decisions in order picking systems

Order picking is a time-intensive and costly logistics activity as it involves a high amount of manual work. Prior research has mostly neglected the influence of human factors on the efficiency of order picking systems. This paper develops a mathematical model that investigates the impact of learning and forgetting of a heterogeneous workforce on order picking time and, consequently, on storage assignment decisions. In particular, the paper investigates when to change a storage assignment and when to keep it if learning and forgetting occur among the members of an order picking workforce. The results show that learning and forgetting should be considered in order to achieve a proper planning of storage assignment strategies.

Purchasing Organization and Design: a literature review

This paper presents the results of a comprehensive literature review of the organization of purchasing covering the period from 1967 to 2009. The review provides a structured overview of prior research topics and findings and identifies gaps in the existing literature that may be addressed in future research. The intention of the review is to a) synthesize prior research, b) provide researchers with a structural framework on which future research on the organization of purchasing may be oriented, and c) suggest promising areas for future research.

Production planning for a ramp-up process with learning in production and growth in demand

This paper presents a production-planning model for a manufacturing process that undergoes a ramp-up period with learning in production and growth in demand. The labour production and demand functions assumed in this paper are validated using available empirical data. A mathematical programming model is developed with numerical examples presented. The results of the paper indicate that the total costs of production can be minimised if the facility produces without interruption during the ramp-up phase and if the production and demand rates are synchronised as much as possible. The latter can be achieved by producing with the lowest possible production rate and by frequently re-structuring the workforce assigned to the production line.

Human factors in order picking: a content analysis of the literature

Order picking (OP) is one of the most labour- and time-intensive processes in internal logistics. Over the last decades, researchers have developed various mathematical planning models that help to increase the efficiency of OP systems, for example, by optimising storage assignments or by specifying routes for the order pickers that minimise travel distance in the warehouse. Human characteristics that are often a major determinant of OP system performance have, however, widely been ignored in this stream of research. This paper systematically evaluates the literature on manual OP systems and conducts a content analysis to gain insights into how human factors (HF) have been considered and discussed in the scientific literature. The results of the analysis indicate that management-oriented efficiency criteria dominated prior research on OP, and that there is a clear lack of attention to HF in the design and management of OP systems. This poses an opportunity for research and design of manual OP systems.

Systematic literature reviews in purchasing and supply management research: a tertiary study

This paper studies systematic literature reviews (SLRs) in purchasing and supply management (PSM) research. First, a process-oriented framework for conducting SLRs in PSM research is developed and criteria for evaluating SLRs in this domain are defined. Subsequently, the framework is applied in a case study and the state of the art of reviewing the literature in PSM research is presented and evaluated. The results of our study show that literature reviews are becoming more and more popular in the PSM domain, but that reviews in this area often lack methodological rigour. The framework presented in this paper may assist researchers in writing high-quality SLRs in PSM research in the future.

Reducing lead time risk through multiple sourcing: the case of stochastic demand and variable lead time

This paper studies a buyer sourcing a product from multiple suppliers under stochastic demand. The buyer uses a (Q, s) continuous review, reorder point, order quantity inventory control system to determine the size and timing of orders. Lead time is assumed to be deterministic and to vary linearly with the lot size, wherefore lead time and the associated stockout risk may be influenced by varying the lot size and the number of contracted suppliers. This paper presents mathematical models for a multiple supplier single buyer integrated inventory problem with stochastic demand and variable lead time and studies the impact of the delivery structure on the risk of incurring a stockout during lead time.

Technical Note: A learning curve for tasks with cognitive and motor elements

This paper develops a new learning curve model that has cognitive and motor components. The developed model is fitted to experimental data of a repetitive manual assembly-and-disassembly task. The fits are compared to those of two other known models from the literature, which are the renowned power form learning curve and its aggregated version. The model developed in this paper performed the best. The fits of the models are evaluated using the mean squared error method. Furthermore, the developed learning curve model is investigated by incorporating it into the economic production quantity model, a topic which has been frequently studied by researchers. The results show that assuming an inappropriate learning curve may produce biased inventory policies by over- or underestimating production rates and consequently inventory levels.