ALBERT

Description: 〈p〉Publication date: January 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 207〈/p〉 〈p〉Author(s): Xin Wen, Tsan-Ming Choi, Sai-Ho Chung〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Over the past decades, we have witnessed the rapid development of giant fashion brands in the retail market which inspires a lot of operational research (OR) studies in fashion retail supply chains (FRSCs). In fact, FRSCs are highly consumer-demand driven and face many operational challenges coming from high demand and supply side uncertainties. Realizing the significance of fashion retail supply chain management (FRSCM) and a lack of comprehensive review on the topic, we develop this paper which examines the operational models on FRSCM in the mainstream OR literature. We organize this review systematically with respect to the core functional areas of FRSCs, namely the manufacturer, retailer, consumer, and fashion retail supply chain system. In each functional area, insights regarding the related studies as well as the specific OR model features and assumptions are generated. Finally, we conclude the review by summarizing the major findings and proposing promising future research areas (from both OR modeling and practical perspectives).〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: January 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 207〈/p〉 〈p〉Author(s): Florian Sahling, Gerd J. Hahn〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Biopharmaceutical products involve high margins but are subject to quality controls during production and to limited product shelf life. Consequently, production planning becomes a challenging task: both inventory and obsolescence costs must be reduced while finding lot sizes that ensure cost-efficient operations. In this paper, we consider operational lot sizing for a multi-level biopharmaceutical manufacturing process that is organized as a flexible flow shop, i.e., parallel and non-identical resources at several production levels. The manufacturing process involves both batch and serial production stages. The problem at hand has two industry-specific requirements: extensive quality checks per lot produced and a restricted shelf life for products. We formulate a mathematical model of this multi-level capacitated lot sizing problem and apply a Fix-and-Optimize heuristic to find high-quality solutions in a reasonable time frame. Modeling challenges and numerical results are provided using a real-life case example from the biopharmaceutical industry.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 206〈/p〉 〈p〉Author(s): 〈/p〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 208〈/p〉 〈p〉Author(s): Shengya Hua, Jingchen Liu, T.C.E. Cheng, Xin Zhai〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉We study a two-echelon supply chain consisting of a capital-constrained retailer ordering via the option contract to satisfy uncertain demand from a single supplier. The retailer can apply for either a bank loan or trade credit from the supplier whenever necessary. In addition to economic revenue, the supplier has a relationship concern and takes the retailer's revenue into consideration. By developing a Stackelberg game, we analyze the ordering and financing problems in the supply chain. The results show that in the presence of the retailer's bankruptcy risk, the supplier should always finance the retailer at the risk-free interest rate. Given the supplier's offer, the retailer will always prefer to raise money from the supplier due to the lower interest rate. Meanwhile, under trade credit, the supply chain's efficiency is improved when the production cost is high but decreased when the production cost is low. Furthermore, our results show that the supplier's relationship concern can improve the supply chain's efficiency and the retailer's revenue most of the time, but increase the retailer's bankruptcy risk when the production cost is high, implying that the supplier's attempt to help the retailer eventually harms its long-run survival.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: January 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 207〈/p〉 〈p〉Author(s): Yefei Yang, Xiaofei Zhang, Peter K.C. Lee〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In the “internet plus” era, online healthcare platforms provide an effective way of easing the demand for hospitals, and their popularity among patients has been increasing sharply in recent years. Such platforms' effectiveness depends on whether there are adequate interactions between patients and doctors through multiple online consultations. Nonetheless, compared with face-to-face consultations, online patients' trust to the doctors and switching costs are often lower. Thus, many of them (in particular, those with chronic diseases) may terminate their cases after the very first consultation, jeopardizing the effectiveness of the online platforms. We adopt a trust development perspective to examine how doctors' online consultation behaviours can reduce patients' switching of doctors and how they enhance patient satisfaction, thereby offering insights to make such healthcare platforms more efficient and effective. By analyzing 77,248 patients' behaviours on an online healthcare platform covering the period 2014–2015, we find that the response time, the depth of interaction, and service content during the first consultation influence the patients' subsequent consultation behaviours significantly. Also, the effects of doctor response time, service content, and depth of interaction on patient satisfaction are different in different periods. Our findings offer managerial insights on managing patients' continuous consultation behaviours and enhancing their satisfaction by considering the time scope and service type. Also, they offer important insights into how online medical care can be delivered more effectively, so relieving the demand for traditional healthcare system capacity.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: January 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 207〈/p〉 〈p〉Author(s): Shahriar Akter, Samuel Fosso Wamba, John D’Ambra〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The increasing importance of service systems in the global economy prompts researchers to focus on quality to measure the critical interaction between human behavior, IT and society. Building on service-dominant logic and sociomaterialism, this study develops and validates a quality model and measures its overall impact on individual (value, satisfaction), organizational (i.e., continuance intentions) and social (e.g., quality of life) outcomes in the context of a transformative health service system in Bangladesh. The conceptual model is rooted in the traditional cognition (service quality) – affective (value, satisfaction)– conation (continuance, quality of life) chain but explicitly identifies three primary dimensions and nine sub-dimensions of quality. The study advances theory and practice in service systems quality research by focusing on individual, economic and social outcomes.〈/p〉〈/div〉

Description: 〈p〉Publication date: January 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 207〈/p〉 〈p〉Author(s): Baofeng Huo, Yuxiao Ye, Xiande Zhao, Kaihang Zhu〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Quality management has received increasing attention in supply chain management. The concept of supply chain quality integration (SCQI) is used to explain how a focal manufacturer integrates with its upstream suppliers and downstream customers for quality improvement. Although the contingent effects of SCQI on quality-related performance have been studied, SCQI patterns and their relationships with performance remain unknown. Using data collected from 317 manufacturers across 10 countries, this study adopts a configuration approach to identify SCQI patterns and their relationships with quality-related performance. Five SCQI patterns composed of different levels of supplier, internal, and customer quality integration are identified. We describe these SCQI patterns in terms of the strength and balance of manufacturers’ quality integration. The ANOVA results show that quality-related performance varies according to different SCQI patterns. Interestingly, product quality is not distinguishable across SCQI patterns. Delivery performance is improved in patterns with a high level of balance of quality integration. The cost of quality is lower in patterns with a high level of customer quality integration. Flexibility is achieved in patterns with high balance and strength of quality integration. This study contributes to the supply chain management and quality management literature, and provides suggestions for managers to adopt different SCQI configurations to improve different types of quality-related performance.〈/p〉〈/div〉

Description: 〈p〉Publication date: January 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 207〈/p〉 〈p〉Author(s): Min Zhang, Hangfei Guo, Baofeng Huo, Xiande Zhao, Jianbo Huang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Supply chain quality management has received increasing attention from researchers and practitioners in recent years. However, the knowledge about the effects of a manufacturer's design and production capabilities on supply chain quality management is limited. In this study, we propose a model to investigate the effects of mass customization and product modularity on supply chain quality integration (i.e. internal, supplier, and customer quality integration) and the impact of supply chain quality integration on competitive performance. We use data collected from 317 global manufacturers to empirically test the conceptual model. The results show that mass customization and product modularity directly improve internal quality integration, and product modularity also improves internal quality integration indirectly through mass customization. Product modularity improves supplier quality integration directly, and both mass customization and product modularity improve supplier quality integration indirectly through internal quality integration. Mass customization improves customer quality integration both directly and indirectly through internal quality integration, and product modularity improves customer quality integration indirectly through mass customization and internal quality integration. We also find that supplier quality integration directly enhances competitive performance, and internal quality integration enhances competitive performance both directly and indirectly through supplier quality integration. Our findings contribute to production and quality management literature and practices.〈/p〉〈/div〉

Description: 〈p〉Publication date: January 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 207〈/p〉 〈p〉Author(s): Hu-Chen Liu, Jian-Xin You, Chun-Yan Duan〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Failure mode and effect analysis (FMEA) is a systematic, multidisciplinary team-based risk management tool used in diverse industries to help improve the safety and reliability of systems, designs, processes and/or services. However, the traditional FMEA method, when applied in real situations, shows some important drawbacks regarding failure mode evaluations, risk factor weights and risk priority ranking, etc. In this paper, we aim to develop an integrated risk prioritization approach to improve the performance of FMEA by using interval-valued intuitionistic fuzzy sets (IVIFSs) and the multi-attributive border approximation area comparison (MABAC) method. Moreover, a linear programming model is developed to obtain the optimal weights of risk factors when the weight information is incompletely known a priori. Finally, a practical example is presented to illustrate the applicability and effectiveness of the proposed FMEA, and results show that the new integrated approach offers a useful and reliable tool for rational criticality analysis.〈/p〉〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 208〈/p〉 〈p〉Author(s): Dorota Stadnicka, Paweł Litwin〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Companies have to meet clients' requirements with regard to product quality and delivery time. In order to survive and have possibilities to develop, companies should do it at minimal cost. The lean manufacturing implementation approach together with lean tools, such as value stream mapping (VSM), is an efficient way for waste identification and elimination. However, since VSM enables only a static analysis of a manufacturing system, the authors present in this paper how the integration of VSM with a system dynamics analysis (SDA) may increase the possibilities for waste identification and elimination. At first, the methodology of extended VSM is described. Then, an extended value stream map (VSMap) is developed and a system dynamics model (SDM) for a case study from the automotive industry is presented. Next, simulations in Vensim software are performed considering the inventory limitations and disturbances such as delivery delays, machine failures and nonconformities. The results are related to inventory levels, a number of manufactured products and work stand load. The article proves that the proposed extended VSM may be used as the only source of data for the construction of a manufacturing line computer model. The paper also argues that the integration of VSM and SD allows not only to identify and eliminate waste, but also to understand the impact of the identified problems on WIP and the production volume.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: January 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 207〈/p〉 〈p〉Author(s): Rodney McAdam, Kristel Miller, Carmel McSorley〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The aim of this paper is to explore the role of Quality Management (QM) theory and practice using a contingency theory perspective. The study is grounded in the role of QM in improving strategic alignment within Small and Medium Sized Enterprises (SMEs) using Contingency Theory rather than adopting best practice approaches. An inductive theory building research methodology was used involving multiple case analyses of five SMEs, involving repeat interviews (〈em〉n〈/em〉=45), focus groups (〈em〉n〈/em〉=5) and document analysis. From the findings, it was found that Contingency Variables (strategy, culture, lifecycle and customer focus) and their respective typologies were found to interact with QM practices in helping to shape strategic alignment between the SMEs and their environments. This shaping process based on contingency approaches occurred in a manner unique to each SME and their respective environments rather than in an overarching best practice manner.〈/p〉〈/div〉

Description: 〈p〉Publication date: January 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 207〈/p〉 〈p〉Author(s): 〈/p〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 208〈/p〉 〈p〉Author(s): Ozgur M. Araz, David Olson, Adrian Ramirez-Nafarrate〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this paper, we investigate the predictive factors of hospital admissions from the emergency department (ED) in various classification models and evaluate their performance. We analyze data from a major hospital in a metro area in the United States with an approximately 50,000 ED visits per year using logistic regression, artificial neural network, decision tree, random forest, support vector machine and extreme gradient boosting methods. The predictive accuracy of the models are evaluated in multiple experiments in which data volume on training and validation varied with multiple years of data. The data set also included a set of observations from a year when an influenza pandemic occurred, which made the data set statistically different. The extreme gradient boosting algorithm (XGBoost) gives the highest area under curve (AUC) statistic and it stands out as one of the fastest algorithms. However, a less sophisticated model, such as simple logistic regression model, also performs well in a reasonable computational time. We also evaluate performance of models with correct classification of patient admission from the emergency department. In our experiments, increasing data volume for model training and validation do not change performances of models significantly, since we have used a large number of observations in initial training and validation experiments. However, support vector machines (SVM) show notable decrease in AUC statistic while model accuracy of the XGBoost algorithm increases. In addition, increasing the data volume slightly increases the AUC statistic for the XGBoost algorithm (i.e., from 83% to 86%) while other methods show slight decreases. Using the most accurate and efficient predictive model for ED admissions would help hospitals design a decision support systems for efficient information flow from the triage at the ED to both outpatient and inpatient units in case of admissions, as basic administrative data with patient acuity information can provide predictions for bed capacity planning.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 208〈/p〉 〈p〉Author(s): Pradipta Patra, U. Dinesh Kumar, David R. Nowicki, Wesley S. Randall〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Performance-based contracting (PBC) is becoming the favoured procurement strategy among suppliers and customers of sustainment dominant systems (SDS) such as aircraft, weapon systems, mining equipment, etc. Under a PBC, supplier profit is linked to how well the SDS meets customer expectations in terms of relevant performance metrics. System availability is a common, contractually agreed upon performance metric that measures customer expectations. In this paper, we analyse performance contracts from the perspective of the supplier, where system availability serves as the performance metric. We develop single-period and multi-period supplier performance models and demonstrate how these models are used to maximise a supplier's profit in the context of a PBC. We provide empirical evidence from a mining and construction equipment industry and demonstrate how PBC overcomes the information asymmetry and moral hazard that is common in SDS principal agent models. Practically, our models can be used to increase the likelihood of success for both the supplier and the customer when they embrace PBC. Our main contributions include establishing the optimal availability that an original equipment manufacturer (OEM) can provide by considering their own probability of loss; analysing the properties of an OEM's future net profit function using first order autoregressive moving average (ARMA) process; and performing marginal analysis and providing bounds for the net profit function for linear and non-linear revenue functions. We derive a relationship between macro-level availability and micro-level parameters such as failure rate, fleet size and base stock levels.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 208〈/p〉 〈p〉Author(s): Li Ma, Xin Zhai, Weiguo Zhong, Zhi-Xue Zhang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉We study how firms across different countries and regions deploy human capital for innovation. Based on survey data from 304 manufacturing firms across 13 economies, we find that both task-related training and employee participation improve firm innovation in terms of the commercial success of new product development and the percentage of firm revenue from newly developed products. More importantly, the effects of training on innovation are stronger when firms have a high (rather than low) centralization of authority and when firms are located in fast- (rather than slow-) growing economies; in contrast, the effects of employee participation remain the same across levels of firm centralization and rates of growth in the economy. Our findings contribute to the research on the deployment of human capital in an international context and offer practical implications for global managers.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 208〈/p〉 〈p〉Author(s): Yang Yu, Yuting Wu, Junwei Wang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉We investigate the bi-objective green ride-sharing problem (BGRSP) with consideration of the drivers' interests. The first objective is to minimize carbon emissions. The second objective is to maximize average ride profit so that every driver's interest can be satisfied. The average ride profit is the average profit of all used rides and it is non-linear due to the variable number of the used rides. The BGRSP is a nonlinear multi-objective problem. We develop an exact method with three steps to solve the BGRSP. The highlight of the exact method is to cut most of the non-Pareto-optimal solutions and use a decomposition method. First, we define the Pareto-optimal ride and prove that every Pareto-optimal solution of the BGRSP is composed of the Pareto-optimal rides; thus, the solution space is reduced by cutting the non-Pareto-optimal rides. Second, we define the partition (equivalent to the solution of BGRSP) based on the relationship matrix between customers and Pareto-optimal rides which is diagonalized into several submatrices, and prove that all partitions of the relationship matrix can be obtained by the partitions of the submatrices. Therefore, the larger-scale NP-hard problem is decomposed into several small-scale NP-hard problems, each of which produces partitions of each submatrix. Third, we define the Pareto-optimal partition and prove every Pareto-optimal solution of BGRSP is composed of the Pareto-optimal partitions of each submatrix. Thus, the solution space can be significantly reduced by cutting the non-Pareto-optimal partitions, even by (1-5.5E-42)*100%. The exact method is validated by solving a benchmark instance of pdp_100-lr101 from Li & Lim benchmark with 106 customers and 200 vehicle capacity. The proposed model and method can reduce carbon emissions and make every driver satisfied simultaneously.〈/p〉〈/div〉 〈/div〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0925527318304870-egi1088BNT35R7.jpg" width="434" alt="Image 1088357" title="Image 1088357"〉〈/figure〉〈/p〉〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 208〈/p〉 〈p〉Author(s): Raymond Treacy, Paul Humphreys, Ronan McIvor, Chris Lo〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Despite the growth of ISO 14001 a lot is still unknown about the impact of environmental management systems on firms' operating performance with much of the academic literature focusing on the financial, market and environmental benefits of ISO 14001. The research in this paper employs the practice-based view along with the event study methodology to determine whether firms can enhance operational efficiency through adopting replicable management practices prescribed under the ISO 14001 standard. This research involved examining performance for both certified and non-certified firms in the UK and Ireland. Whilst ISO 14001 was shown to have a positive and prolonged effect on certified firms' manufacturing cost efficiency, employee productivity, and return on assets, the sample firms' operating cycle displayed evidence of diminishing returns in the long-run. This study advances upon previous ISO 14001 research studies by applying the event study methodology and measuring the effect of environmental management system adoption through utilising operating performance metrics rather than relying on subjective measures of firm performance. Moreover, this research is important as few firms actually quantify the benefits of the ISO 14001 standard. However, the findings come with the caveat of diminishing returns for some operating indicators emphasising that firms can become overly efficient to the detriment of the initial operating speed gains.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 208〈/p〉 〈p〉Author(s): Cagatay Tasdemir, Salim Hiziroglu〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Impact of inventory leanness on financial performance has been well-documented by scientific community for various industries. However, its application in value-added wood products industry is relatively scarce when compared to other industry segments. The objective of the study was to investigate impact of increased inventory leanness on financial performance of a value-added wood products manufacturer. Outcomes of the study was also expected to contribute to the intersection zone of three research streams, namely Lean Inventory Management, Procurement Lot-Sizing and Demand Forecasting. To achieve stated objectives, research question and hypotheses were constructed around an un-capacitated single item raw material lot-sizing problem in the context of an SME. A six-step systematic optimization approach (SOA) was developed and followed to improve cost efficiency throughout the study. Time series and Regression based demand forecasting coupled with Dynamic and Statistical lot-sizing models to derive the optimal solution to the problem. At the end of exhaustive simulations, an optimized procurement strategy that could achieve 32.87%–60.90% raw material inventory management cost savings depending on desired buffer level was proposed. Consequently, increased inventory leanness led to less costly procurement activities within target supply chain, which indicated enhanced overall financial performance of the firm through proper risk management and mitigation.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 21 December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Jiajia Nie, Ling Zhong, Hong Yan, Wenjuan Yang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The development of e-commerce has motivated many traditional brick-and-mortar retailers to redesign their distribution strategies by adding a new online channel to supplement their retail channels. This online-and-offline channel (OOC) strategy is widely acknowledged as a promising strategy. However, when considering the cross-channel effect, i.e., online channel may have different impacts on the sales of the offline channel in different industries, retailers may not always prefer the OOC strategy even if the fixed cost of developing the online channel is negligible. In this paper, we investigate the impacts of cross-channel effect on the two competing traditional retailers’ distribution channel strategies. By a two-period game-theoretic model, we show that the retailers may give up the OOC strategy when the cross-channel effect is significant negative. By contrast, when the cross-channel effect is insignificant negative or positive, both retailers prefer the OOC strategy even if they may be involved into the prisoners’ dilemma. That is, although the Pareto equilibrium is to forego the OOC strategy, the optimal choice is to implement it. We later relax the assumption of simultaneous price game by allowing one retailer move first to determine its price. We find that our main results still hold but the prisoners’ dilemma is more likely to avoid under the sequential price game than under the simultaneous price game.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 208〈/p〉 〈p〉Author(s): Mohamad Darayi, Kash Barker, Charles D. Nicholson〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The multi-modal freight transportation network plays a vital role in maintaining commodity flows across multiple industries and multiple regions. As such, the effects of large-scale disruptive events could result in the closure of key transportation nodes and links, causing disruptions in commodity flows and larger disruptions to industries requiring those commodities for economic productivity. This work integrates a multi-commodity network flow formulation with an economic interdependency model to quantify the multi-industry impacts of a disrupted transportation network to devise contingent rerouting plans to strengthen the network's adaptive capacity. The formulation proposed here is illustrated with a freight transportation planning case study in the state of Oklahoma, considering disruptive scenarios in which a network component is lost and how the proposed approach improves total economic productivity following a disruption.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: January 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 207〈/p〉 〈p〉Author(s): Nachiappan Subramanian, Angappa Gunasekaran, Muhammad D. Abdulrahman, Crystal Qiao〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In today's dynamic environment, quality innovation and new product development (NPD) are the key factors in gaining competitive advantage. However, the quality innovation process is a complex procedure, because it may combine internal and external resource requirements to meet customer expectations. This paper reviews two quality innovation pathways and their respective NPD performances based on the joint supplier-buyer relationship within the fast consumer goods (FCGs) industry. Specifically, we study buyers’ quality innovation potential using ‘out-in,’ which is the identification of quality innovative suppliers, and ‘in-out,’ which is buyers’ quality knowledge transfer ability to suppliers. Our dyadic data from both buyers and suppliers reveal that the supplier's innovation ability and passion is the dominating factor, irrespective of quality innovation pathways, in the context of the Chinese consumer goods industry. However, cooperative attitude and the cost reduction ability of suppliers are the differentiating factors.〈/p〉〈/div〉

Description: 〈p〉Publication date: January 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 207〈/p〉 〈p〉Author(s): Mohamed Haffar, Wafi Al-Karaghouli, Zahir Irani, Ramdane Djebarni, Gbolahan Gbadamosi〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉A comprehensive literature review reveals a lack of empirical studies investigating the influence of individual readiness of change (IRFC) as a multidimensional construct on effective quality improvement programmes (often referred as TQM) implementation. Much of the normative literature is conceptual in nature. Moreover, there is very limited research investigating the mediating role of employee affective commitment to change (IACC) between IRFCs and TQM. Therefore, this study proposes to fill this gap by providing empirical evidence leading to advancement in the understanding of direct and indirect influences of IRFC components on TQM implementation. To achieve this, a questionnaire-based survey was developed and self-administered to 226 middle managers in Algerian manufacturing organisations (AMOs) with a good rate of return of 52%. The analysis of the collected data revealed that two of the IRFC components, namely personally beneficial and change self-efficacy are the most supportive IRFC dimensions for TQM implementation. Furthermore, the results of this study show support for the mediating role of IACC in the relationship between IRFCs and TQM implementation. Therefore, this paper makes a novel contribution by providing a refined and deeper comprehension of the relationships between IRFCs and TQM implementation.〈/p〉〈/div〉

Description: 〈p〉Publication date: January 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 207〈/p〉 〈p〉Author(s): Mehrdokht Pournader, Andrew Kach, Behnam Fahimnia, Joseph Sarkis〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The growth of vendor procurement and supply chain management simultaneously emerged as organizational outsourcing practices increased. Outsourcing, as an important strategic organizational practice, needs to be carefully examined from an organizational performance perspective to ensure satisfactory quality of services and goods from supply chains. This article provides a model for performance assessment of an outsourcer's processes in a supply chain comprised of several internal and external entities. Internal entities are entities in a supply chain that the outsourcer can manage and control. External entities are entities whose processes are not within the management sphere and control of the outsourcer, yet affect an outsourcer's performance. A slacks-based measure is incorporated into a hybrid network data envelopment analysis model to evaluate the outsourcer performance incorporating both entity types. A case study of a service supply chain in the banking industry comprised of a commercial bank, its sub-processes, and an external investment bank is used as an illustrative application of the model. Insights are presented and future research directions are identified.〈/p〉〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 208〈/p〉 〈p〉Author(s): Cynthia Waltho, Samir Elhedhli, Fatma Gzara〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉We review the literature on green supply chain network design between 2010 and mid 2017, focusing primarily on models and methodologies that explicitly include carbon emissions and environmental policies. We find that supply chain network design has mostly incorporated four policies: carbon cap, carbon offset, cap-and-trade and carbon tax. All four policies succeed to achieve substantial emission reductions with a slight increase in total cost; mostly by configuring the supply chain to use lower-emitting resources. We investigate the prevalent sources of emissions within the supply chain. As expected, transportation contributes about one third, followed by power-intensive processes such as manufacturing, storage and warehousing. Other sources are raw material extraction and sourcing, facility construction and operation, and disposal. We observe that there is a lack of models that capture the complex nature of emissions. Nonlinear tax rates, multivariate emission functions and uncertainty are only considered in few papers. But most importantly, we find that the effect of emissions on demand is rarely accounted for.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 208〈/p〉 〈p〉Author(s): Giovanni F. Massari, Ilaria Giannoccaro, Giuseppe Carbone〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Collective intelligence is defined as the collective ability of human groups in solving different tasks. It explains why some teams perform better than others by exploiting the power of social relationships, so motivating research on which features of social relationships can improve it. We contribute to this line of research by analyzing the effect of distrust relationships, in which individuals involved tend to make antagonistic decisions, on collective intelligence. Borrowing from previous studies that recognize consensus seeking among self-interested individuals as a critical process for the emergence of collective intelligence, we investigate the relationship between scope of distrust (i.e., the extent to which distrust relationships are spread in the group) and group performance (measured as efficacy to solve a decision making problem), in different conditions of strength and density of social relationships. To do this, we employ a simulation model coming from statistical physics, where collective dynamics is governed by a continuous-time Markov process. Results show that scope of distrust can be beneficial or not for group performance, depending on the value of the strength and the density of social interactions. When the strength (density) of social relationships is too low, any scope of distrust is detrimental for group performance, while when the strength (density) of social relationships is moderately high, low scope of distrust can be useful to improve group performance. Theoretical and managerial implications of these findings are finally discussed.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 7 December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Ifeyinwa Juliet Orji, Shaoxuan Liu〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In response to the ever-increasing consumer awareness on carbon emissions and government policies, firms consider adopting innovation-led lean approaches to achieve sustainability in the manufacturing supply chain. The behavior of the key drivers of innovation-led lean approaches to achieve sustainability can vary over time and these variations have the potential to significantly affect sustainable outcomes in the manufacturing supply chain. Currently, the study of the dynamic behavior of the key drivers of innovation-led lean approaches and their influence on sustainable performance over a long time in the manufacturing supply chain is still unexplored. Therefore, this study employed fuzzy logic and Technique for Order Performance by Similarity to Ideal Solution (Fuzzy TOPSIS) to prioritize the key drivers of innovation-led lean approaches to achieve sustainability in the manufacturing supply chain based on the evaluations of experts in the Chinese electronics sector. Then, a system dynamics model was developed in this study to investigate the dynamics of the key drivers of innovation-led lean approaches and their influence on sustainable performance over a long time in the manufacturing supply chain. According to the study outcomes, the dynamic behavior of ‘Government regulations’ and ‘Conducive working conditions’ influences sustainable performance exponentially over a long time in the manufacturing supply chain. Our study also reported the dynamics of ‘Cash availability’ and ‘Fundamental knowledge’ and indicate that they are not highly influential on sustainable performance over a long time. This study will insure the key drivers maintain their status to achieve sustainable performance over a long time during implementing innovation-led lean approaches in the manufacturing supply chain.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 11 August 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Min Yu, Jose M. Cruz, Dong "Michelle" Li〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper captures different environmental tax policies in a multi-tiered supply chain network competition context. We derive the governing equilibrium conditions for the noncooperative game theory models for each firm and provide the equivalent variational inequality formulations. The numerical examples investigate the impacts of emission tax policies and product differentiation on the competing firms, and compare the effects of different environmental policies (flat emission tax rates, progressive emission taxes, and the government command-and-control regulations with emission standards) on equilibrium product demands, prices, total emissions, and overall profits. The computational results indicate that the implementation of environmental tax policies along with an increase in consumers’ environmental concerns can not only motivate the firms to perform sustainable operations, but also reduce the total carbon footprint. Furthermore, the low-cost progressive emission tax policies can be as effective as the high flat emission tax rate in terms of reduction in carbon footprint. Therefore, the model developed in this paper can be used by the policymakers and the firms to evaluate the effects of different environmental tax policies in a supply chain competition context.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 205〈/p〉 〈p〉Author(s): Syed Asif Raza〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Corporate social responsibility is among the most desired features of global operations in supply chains. Despite there is a societal urge for socially responsible supply chains, yet the supply chain players (manufactures, and retailers) may only be motivated being socially responsible given it warrants them improved performance and profitability. In this paper, we have proposed supply chain coordination schemes for pricing inventory, and corporate social responsibility investments decisions for a single manufacturer-retailer supply chain. We developed quantitative models for joint pricing, inventory (order quantity), and investment for socially responsible decisions for a supply chain. Models are formulated for both the price-and-CSR investment dependent deterministic and price-and-CSR investment dependent stochastic demand situations. We also explore when the price-and-CSR investment dependent stochastic demand information is only be partially known in a supply chain, and players may have to anticipate the worst possible demand. It is assumed the demand distribution is unknown, and a distribution-free approach is utilized. We have presented various game-theoretic settings that analyze the decentralized, centralized, and a revenue sharing agreement through bargaining for each of three demand situations. We developed analytical (〈em〉closed-form〈/em〉) solutions for the control decisions for the players. In a detailed numerical study, the significance of each model, and how the societal responsiveness impacts the supply chain performance and the players' decision under varied game-theoretic settings is highlighted. The study also emphasizes the use of distribution-free approach to minimize the adverse impact of demand information distortion in a supply chain.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 205〈/p〉 〈p〉Author(s): Antonio Carlos Rodrigues, Ricardo Silveira Martins, Peter Fernandes Wanke, Janaina Siegler〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Economic growth increases the need for continuous improvement of logistic processes. In this context, comprehensive services and high-level operational performance are competitive advantages, with special attention to refrigeration services in the cold chain. This study's main objective is to determine the variables that significantly affect the efficiency of third-party logistics (3PL) providers of refrigeration services and propose ways to improve the competitiveness of specialized 3PLs. This study uses Data Envelopment Analysis (DEA) and robust regression approach in secondary data from the annual study published by 〈em〉Revista Tecnologística〈/em〉 (years 2008–2016). The aim is to measure the impact of contextual variables on the efficiency of Brazilian 3PL providers of refrigeration services. Results indicate that, in fact, pure, technical and scale efficiency levels are differently impacted by the type of technology adopted and the services offered, what leaves room opened for the adoption of different measures and operational practices to increase efficiency levels in its different dimensions. The study provides guidance for managers who wish to establish or adapt specialized 3PL structures and management systems in cold chains. Our study is the first to help identifying the main determinants of efficiency for 3PL providers of refrigeration services in an emerging economy. Further, it develops performance benchmarks for specialized logistics services.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 205〈/p〉 〈p〉Author(s): Stephan M. Wagner, Pan Theo Grosse-Ruyken, Feryal Erhun〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Sourcing flexibility is an increasingly important building block of supply chain flexibility. Our study which is grounded in information processing theory argues that two mechanisms can support firms in building up sourcing flexibility. Based on a survey of 336 manufacturing firms from Europe and the U.S. and using partial least squares (PLS) modeling as well as hierarchical regression analysis, we show that supplier evaluation and selection, and the integration of information systems at the buyer-supplier interface are positively related to sourcing flexibility. Sourcing flexibility, in turn, is curvilinearly related to delivery performance. Finally, delivery performance positively influences the product's financial performance. The strong associations between sourcing flexibility, delivery performance, and product financial performance underscore that sourcing flexibility merits the attention of supply chain managers during supplier selection and purchasing decisions.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 30 May 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Philipp C. Sauer, Stefan Seuring〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Triadic or tetradic multi-tier sustainable supply chain management (MT-SSCM) research emerged recently to reach out towards raw material suppliers and to address their often severe sustainability impacts. This is especially relevant in mineral supply chains (SCs) which consist of a commodity chain upstream and an end-product chain downstream. To comprehensively investigate the reach of MT-SSCM in mineral SCs, the extant Delphi study brought together 44 global authors on sustainability in mineral SCs. They contributed their professional knowledge in three questionnaire rounds, which systematically identify, evaluate and contrast the sustainability challenges in mineral SCs. As a result, a generic mineral SC structure is derived and 17 major sustainability issues are identified. Moreover, the findings reveal that all but two sustainability issues need to be addressed in the upstream SC. As mineral SCs might comprise up to nine tiers, the most impactful tiers lie outside the reach of current MT-SSCM concepts, which are limited to triads or tetrads by the visible horizon or lacking power of the focal firm. We thus propose a cascaded MT-SSCM approach which links the up- and downstream SC parts. Moreover, individual focal firms for each SC part are defined, which build a direct strategic link. This link enables that tailored managerial responses can be cascaded into the respective SC parts, where the individual sustainability issues can best be addressed. This cascaded design represents a novel approach in MT-SSCM which multiplies existing concepts. Moreover, the challenges and opportunities, which the cascaded approach raises for MT-SSCM research are discussed and outlined.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 5 June 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Amy Z. Zeng, Jing Hou〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The extremely short life cycles and rapid advent of new technologies are placing used phones at the forefront of reverse supply chain management. This research focuses on the incentive mechanisms in a supply chain of used mobile phones that are still usable and thus can be sold at a lower price to secondary markets where customers are more price-sensitive. Through an in-depth case study, we first explored the second-hand mobile phone supply chain structure and operational procedure. Then we investigated and compared two different incentive strategies between a take-back enterprise (referred to as a “distributor”) and a supplying firm with large quantities of used phones (referred to as a “supplier”), namely quantity discount scheme and coordinated quality improvement. The optimal order quantities and/or quality improvement levels are analyzed in both decentralized and centralized settings. Our results show that the quantity discount scheme may result in a centralized optimization, while the quality improvement scheme could benefit the entire supply chain when the initial imperfect ratio is not low. Moreover, the value of quality improvement decreases with the demand uncertainty under a decentralized system but increases in a centralized supply chain. This research provides an effective tool and guideline for evaluating different procurement and incentive strategies in reverse mobile supply chain management.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 205〈/p〉 〈p〉Author(s): Gilson Adamczuk Oliveira, Kim Hua Tan, Bruno Turmina Guedes〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉SMEs are crucial for economic health in both high and low-income economies worldwide. In Brazil, they are responsible for around 50% of the national GDP. However, SMEs face considerable barriers such as difficulties in financing international activity, identifying opportunities and making appropriate contacts in their target markets. This paper investigates the adherence of both lean and green practices for the development of new products (NPD), as means to improve their efficiency (lean perspective) and manufacture environment-friendly products (green perspective). Through a systemic review, we present 16 lean and green enablers for NPD operations. These elements comprise a structure of building blocks to evaluate lean and green practices. Thus, we propose a model that ranks the incidence of these practices regardless of the NPD organization level. Using two MCDM tools: AHP and fuzzy-TOPSIS, each enabler is evaluated considering the SMEs context in Brazil. Firstly, AHP defines the relative importance of six SMEs' characteristics. Secondly, we applied an expansion of the TOPSIS technique, adequate when the values of each alternative are not clearly determined. Therefore, we organized a structured interview consisting of 96 evaluation questions for NPD stakeholders. We carried out this diagnosis in three companies from southern Brazil, analysing their NPD operations, which is useful to establish a future improvement agenda.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 208〈/p〉 〈p〉Author(s): Shelby E. Koos, Nazrul I. Shaikh〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this paper, we quantify the effect that product stock-outs led consumer dissatisfactions have on consumer behavior. We (a) develop and calibrate a mathematical model that can track how an individual consumer's dissatisfaction evolves over time on account of one or more experiences of stock-outs during shopping trips to a retail store, (b) link the measure of dissatisfaction to the probabilities of various consumer actions such as substitution, postponement, and abandonment, and (c) aggregate the individual level models to yield a measure of the backorder costs of various products for the retailer. The study yields a practical solution that retailers could use to determine how a consumer is likely to respond to a stock-out situation and hence be proactive in relationship management. It also helps retailers in assortment planning.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 205〈/p〉 〈p〉Author(s): Franklin Djeumou Fomeni〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The blending problem is one of the oldest and well-known optimization problems. It is generally formulated as a linear program and has been applied in many industries. However, the blending problem encountered in the tea industry requires a lot more than a straight forward linear programming formulation. Indeed, the classical blending model would almost always be infeasible for the blending problem in the tea industry. This is because it is often not possible to match the characteristics of the blends as desired, which prompts the decision makers to search for solutions that are the closest possible to the targeted ones. In this paper, we develop and solve a multi-objective optimization model for the tea blending problem, wherein we minimise the total cost of the raw materials to be used, as well as the violations of the desired characteristic scores of the final blends. We also present a parametric model that is used as benchmark to compare the multi-objective optimization model. Both models are able to provide the decision maker with the flexibility to express their preferences in terms of determining acceptable solutions that will allow them to maintain the high quality of their brands. We employ Monte Carlo simulation approaches to solve both models and also provide the decision maker with an extra tool to analyse the existing trade-off between the violation of the characteristic scores and the total cost of raw materials. The models and solution approach have been tested with real data from a UK-based tea company who brought the problem to us in the first place. The results show that the proposed multi-objective optimization model dominates the parametric model and can usefully serve as decision support tools to select the best solution option from a set of acceptable ones. In fact, a decision support tool based on this research has now replaced their existing decision tool and with this new tool, they are able to save tens of thousands of pounds every week as well as significantly improving the quality of their tea blend.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 2 May 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Himanshu Rathore, Suresh Kumar Jakhar, Arijit Bhattacharya, E. Madhumitha〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Literature, heretofore, has assumed the relationship between ‘lean’ systems and their sustainable performance as direct and static. Researchers have explored this relationship from various perspectives and have taken clear sides, as to whether lean practices are favourable or inimical to the sustainable performance of a firm. We argue that the ‘for (or) against’ debate has been overstretched and has assumed some contingencies that are uncalled for. This study offers a novel perspective of gauging the relationship between lean practices and a firm’s sustainable performance from a dynamic stance. It recognizes that this relationship has both, synergistic and discordant phases. Synergistic phase revs up the sustainable performance and discordant phase is inimical to the sustainable performance of the firm. We propose that lean processes can positively (or) negatively affect a firm’s sustainable performance depending upon the state of innovative capability of the firm. In this regard, we present an iterative and recursive two-phase framework which draws upon the principles of a metaheuristics and is undergirded in dynamic capability theory. This framework discusses the ‘switching behaviour’ of the firm controlled by decoupling point. Switching behaviour determines how a firm should manoeuvre its innovation strategy. The framework was tested by using primary and secondary data (content analysis) in order to triangulate the results. This framework puts forth a set of generic guidelines, which the firms can decipher in their own idiosyncratic environments to bring about the required synergy between their lean processes and innovative capabilities. This synergy shall ensure that the ‘the engines of their sustainable growth’ are always fired up.〈/p〉〈/div〉 〈/div〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0925527318301919-egi106V4JM1342.jpg" width="162" alt="Image" title="Image"〉〈/figure〉〈/p〉〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 208〈/p〉 〈p〉Author(s): Erbao Cao, Lingxia Du, Junhu Ruan〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Many small and middle-sized enterprises (SMEs) with capital constraints have two primary short-term financing modes: internal financing (supplier) and external financing (bank). We consider an emission-dependent supply chain with one supplier and one emission-dependent manufacturer that are capital-constrained and in need of short-term financing. We investigate the financing preferences of the supply chain from a competitive bank or supplier when demand is uncertain and consumers have low-carbon preferences. Under the cap-and-trade system, we show that the existence of investments in carbon abatement will have no impact on the selection of financing mode. We find that the supplier's trade credit financing serves as a unique financing equilibrium for manufacturers regardless of whether investments in carbon abatement are considered. Irrespective of the chosen financing equilibrium, if a manufacturer chooses to invest in carbon abatement, the dominant supplier will offer a wholesale price to prompt the manufacturer to choose the largest feasible carbon emission reduction and maximize his profit. In addition, we present a set of numerical analyses to compare the results of different financing modes and the financing equilibrium with and without carbon abatement, and we analyze the impacts of key parameters on the performance of supply chain members.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 6 July 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Peter Ball, Peter Lunt〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Lean production systems dominate supply chain operations and are being enhanced through eco-efficient practices to further reduce waste and work towards sustainability. There have been advances in eco-efficiency through the reduction in energy, water and other resource consumption. Thus, wider sustainability programmes have improved the social and eco-efficiency performance in previously lean operations. Whilst eco-efficiency programmes have enhanced lean supply chains, they have usually been separate rather than integral to day-to-day innovation. Operational metrics deployed typically favour cost, quality and delivery with eco-efficiency being progressed as separate projects. In contrast, the organisation of maintenance to contribute to the sustainability dimension of innovation in supply chain operations is absent in theory and practice despite its inherently complementary role to maintain and enhance the performance of assets. Introducing innovation-led lean activity through maintenance to enhance eco-efficiency offers opportunities for new practices and technology. This paper considers current literature and presents the evolution of an energy efficiency programme into a programme across 11 sites in a lean supply chain supported by maintenance. The novelty is a framework showing how to embed eco-efficiency innovativeness into innovation-led lean operations through maintenance, overcome barriers to implementation and support others through a community of experts.〈/p〉〈/div〉 〈/div〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S092552731830272X-fx1.jpg" width="463" alt="Image 1" title="Image 1"〉〈/figure〉〈/p〉〈/div〉

Description: 〈p〉Publication date: November 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 205〈/p〉 〈p〉Author(s): Ibrahim Kucukkoc, Zixiang Li, Aslan D. Karaoglan, David Z. Zhang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Mixed-model assembly lines allow the production of different product variants in mass quantities on the same assembly line. In studies addressing mixed-model assembly with two-sided lines, assembly line (work)stations are classified as left-side or right-side stations depending on the operation side to which they are allocated. However, underground stations are also utilized in industry to perform tasks that need to be done underneath the product being assembled on the line. This paper introduces and mathematically formulates a mixed-model, two-sided assembly line balancing problem considering underground stations. The precedence relationships between tasks being performed in the three types of stations are defined and considered in the model. A numerical example is solved in GAMS (with CPLEX solver) and the detailed balancing solution is provided. A new ant colony optimization algorithm, in which the parameters are optimized using response surface methodology, is also developed to solve real-world problems. A total of 78 test problems are derived from the literature and their lower bounds are calculated to test the performance of the ACO algorithm. ACO finds optimum solutions for the majority of small and medium-sized test problems. In comparing the ACO results to the lower bounds for the large-sized problems, ACO finds near -optimum solutions in majority of the test cases.〈/p〉〈/div〉 〈/div〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0925527318303256-egi10H2D5RKWHP.jpg" width="500" alt="Image" title="Image"〉〈/figure〉〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 30 April 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Efrosini Siougle, Sophia Dimelis, Claire Economidou〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this study we investigate the performance dynamics of the ISO 9000 certification for varying time-frames and firm groupings by initiating a new dimension related to admission in the stock exchange market. We distinguish certified firms into two subgroups: the firms that adopted the certification before getting listed and those that adopted while being listed. The empirical results indicate that, in both cases, the ISO 9000 certification is associated with higher financial performance for adopting firms in comparison to the control group comprising non-certified firms. Higher operating performance versus the non-certified peers in terms of inventory turnover ratio was also found among high and low technology prototype certified manufacturing firms. Furthermore, the evidence suggests that the impact of the certification in terms of duration is higher for the group of firms initializing the certification after getting listed. Additionally, the robustness analysis indicates that the upgraded 2000 and 2008 versions of the ISO 9000 standard have consistently impacted in a significant way on firm performance. These results provide useful insights to managers, investors and regulators regarding the time decision for implementing the first ISO 9000 certification, the continuation of certification and its impact on the performance of adopting firms.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 7 September 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Charbel Jose Chiappetta Jabbour, Ana Beatriz Lopes de Sousa Jabbour, Joseph Sarkis〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Contemporary multi-tier supply chains are increasingly international, complex, and challenging for suppliers and focal companies. In addition to this, internal and external stakeholders, regulators, consumers and non-governmental organizations all now require firms to take responsibility for and action towards mitigating unsustainable practices and misconduct in their supply chains. In dealing with this complex supply chain context, quantitative modeling approaches are relevant in their ability to capture the complexity of problems in order to propose effective and sustainable solutions. The main objective of this study is to review selected literature on the effective management of sustainability in supply chains, and its attendant implications for multi-tier supply chain modeling problems. Previously published modeling research that may directly or indirectly provide lessons for multi-tier sustainable supply chains is investigated utilizing the Scopus database. After analyzing the relevant literature, we deliver the following contributions: (a) a systematization and classification of the selected papers; (b) a description of 16 research gaps that remain in the literature and that may be useful in expanding research efforts in this domain; (c) four lessons for both practitioners and managers dealing with sustainability in multi-tier supply chains; (d) an integrative framework which encapsulates key areas of focus to develop multi-tier sustainable supply chains. Implications for theory and practice are suggested, as well as limitations concerning the scope of this systematic review.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 2 July 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Armin Jabbarzadeh, Michael Haughton, Fahime Pourmehdi〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper presents a bi-objective robust optimization model for the integrated production and distribution planning of a supply chain with the postponement strategy. The two objectives are economic (cost minimization) and environmental (greenhouse gas emissions minimization), respectively. The robust model is capable of incorporating decision makers' risk attitudes in addressing demand uncertainties under conditions of very limited historical data. The application of the proposed approach is examined using real data of an actual pharmaceutical supply chain as well as a benchmark problem in the existing literature. Our analysis and investigation focuses on exploring the extent to which the tradeoffs between economic and environmental objectives are influenced by the decision makers’ risk preferences and postponement strategy. We find that independent of the amount of greenhouse gas emissions and degree of demand variability, the postponement strategy can consistently provide cost savings for the supply chain.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 7 May 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Shaofu Du, Li Wang, Li Hu〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉With the popularity of omnichannel retailing, consumers are sophisticated enough to make strategic channel decisions, considering the possible disappointment for an unexpected outcome induced by various uncertainties from online and offline channels. Value uncertainty online can trigger low-value disappointment, and availability uncertainty offline may cause stock-out disappointment. This study characterizes the effect of consumers' anticipated disappointment aversion behavior on the optimal pricing decisions of retailers with or without inventory constraint in the omnichannel environment. When a retailer operates in dual-channel and faces offline inventory constraint, the concern for consumers' homogeneous disappointment aversion changes the threshold above which the retailer implement different channel pricing strategies. Then, we show how the negative impact of disappointment on profit and market can be mitigated by physical showroom mechanism, which is increasingly adopted by omnichannel management. Introduction of a cost-effective physical showroom expands the market by relaxing the restriction of stock-out disappointment and improves profit as long as consumers' low-value disappointment is high enough. Interestingly, the low-value disappointment benefits the omnichannel in expanding the market coverage by alleviating the constraint exerted by stock-out disappointment. Further discussions regarding the disappointment behavior are derived from the extension of consumers’ heterogeneity in disappointment-aversion.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 206〈/p〉 〈p〉Author(s): Bin Zhang, Dongxia Duan, Yurui Ma〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper studies a purchasing problem with multiple products, resource constraints, demand forecast updates and expedited ordering. The retailer procures the initial quantities of multiple products before the selling season, which are restricted by limited resource, and the retailer can improve the demand forecasts through observing the initial sales. Based on the updated demand forecasts and inventories on hand, the retailer can place an expedited order at higher costs for products during the selling season, which is restricted by the minimum quantity of reordering. We analyze the retailer's optimal procurement policies by trading off between forecast reliability, procurement costs and resource availability. The bi-level programming is used to model the purchasing problem and the binary search solution method is developed for solving the optimal solution. We extend the proposed algorithm to the case with two resource constraints, and also replace the expedited ordering with option contract in the extended study. Numerical experiments are designed to show the value of expedited ordering with demand forecast updates and to obtain managerial insights in comparison with the model with the option contract.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 21 March 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Huiping Ding, Yanan Fu, Lucy Zheng, Zhu Yan〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this study, we use an evidence-based approach to examine the factors that determine the competitive advantage of dairy supply chains using evidence from the Chinese dairy industry. We focus on the quality assurance of dairy products, which is considered one of the fundamental influential factors. We investigate interrelationships among the identified determinants, which include dairy production behavior, dairy cow culture model, government regulations, corporate social responsibility, and quality assurance, and examine how these determinants influence the competitive advantage of dairy supply chains. We employ the structural equation modeling approach in which grouped observable variables that represent the identified determinants are extrapolated from primary data collected through a questionnaire survey. Our key findings show that by mediating the effects of dairy production behavior and the dairy cow culture model, government regulation and corporate social responsibility significantly affect the quality assurance of dairy products. In turn, dairy production behavior and the dairy cow culture model significantly affect the competitive advantage of the dairy supply chain via the fully mediated effects of the quality assurance of dairy products. Specifically, the dairy cow culture model helps ensure the safety and quality of milk supply, allowing core dairy firms to control product quality throughout the dairy supply chain. Our empirical study shows that the identified determinants interact to assure the quality of dairy products and enhance the competitive advantage of the dairy supply chain in China.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 14 May 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Zhou He, Guanghua Han, T.C.E. Cheng, Bo Fan, Jichang Dong〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In the booming online-to-offline (O2O) food ordering and delivery market, numerous independent restaurants are competing for orders placed by customers via online food ordering platforms. The food quality and location decisions are deemed to be the two principal considerations of restaurants in this emerging market. To investigate the evolutionary food quality and location behaviours of restaurants, we propose an agent-based O2O food ordering model (AOFOM) that consists of three types of agents, namely customers, restaurants, and the online food ordering platform. We explicitly model their adaptive behaviours by optimizing the agents' benefits. We find that customers' behaviours have significant impacts on the restaurants' food quality decisions. Besides, the relationship between the restaurant's location decisions and customers' waiting time is less significant in the O2O food ordering market due to the presence of an equalizing delivery service provided by the online platform. We also examine the characters of best restaurants, as well as the impacts of different delivery policies on the food quality and location decisions of restaurants.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 19 May 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Nikolaos Kourentzes, Devon Barrow, Fotios Petropoulos〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Forecast selection and combination are regarded as two competing alternatives. In the literature there is substantial evidence that forecast combination is beneficial, in terms of reducing the forecast errors, as well as mitigating modelling uncertainty as we are not forced to choose a single model. However, whether all forecasts to be combined are appropriate, or not, is typically overlooked and various weighting schemes have been proposed to lessen the impact of inappropriate forecasts. We argue that selecting a reasonable pool of forecasts is fundamental in the modelling process and in this context both forecast selection and combination can be seen as two extreme pools of forecasts. We evaluate forecast pooling approaches and find them beneficial in terms of forecast accuracy. We propose a heuristic to automatically identify forecast pools, irrespective of their source or the performance criteria, and demonstrate that in various conditions it performs at least as good as alternative pools that require additional modelling decisions and better than selection or combination.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 17 September 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Desheng Dash Wu, Lipo Yang, David L. Olson〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉To determine how carbon emissions reduction affects supply chain operations and financing decisions, this paper examines a green supply chain, which consists of one manufacturer (playing the leading role) and one capital-constrained retailer; in this supply chain, bank financing and trade credit financing are viable. This research explores the retailer's optimal order quantity, the manufacturer's optimal wholesale price, the optimal level of carbon emissions (for both bank financing and trade credit financing), and the design of the contract to coordinate the supply chain. We find that the supply chain achieves a win-win outcome in terms of production quantity and emissions reduction when the manufacturer invests in emissions reduction. In addition, we find that a supply chain with a contract outperforms a non-contract supply chain in production quantity and emissions reduction. Furthermore, the effect is more remarkable when trade credit financing is viable.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: January 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 207〈/p〉 〈p〉Author(s): Allen H. Tai, Yue Xie, Wanhua He, Wai-Ki Ching〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this paper, we consider inventory control problems for deteriorating items. Six practical models are developed for an inventory system with deterioration rate depending on the maximum lifetime of items. Due to the physical nature of items, the maximum lifetime of items is assumed to be random over a time period. Items exceeding the maximum lifetime are regarded as scarp and no longer serviceable. Two replenishment policies: (i) quantity-based policy and (ii) time-based policy, and two inspection scenarios: (i) one inspection and (ii) continuous monitoring have been discussed in these models. Examples and sensitivity analysis are given for each model. The results indicate that it may be beneficial for the inventory holder to adopt the quantity-based policy and drop the plan of continuous monitoring if the cost of continuous monitoring is too high. Otherwise, performing continuous monitoring is able to increase the optimal long-run average profit. These results provide useful insights for inventory holder in making managerial decisions.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 28 June 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Petros Boutselis, Ken McNaught〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉A problem faced by some Logistic Support Organisations (LSOs) is that of forecasting the demand for spare parts, corresponding to equipment failures within the system. Here we are particularly concerned with a final phase of operations and the opportunity to place only a single order to cover demand during this phase. The problem is further complicated when the service logistics context can change during this final phase, e.g. as the number of systems supported or the LSO's resources change. Such a problem is typical of the final phase of many military operations.〈/p〉 〈p〉The LSO operates the recovery and repair loop for the equipment in question. By developing a simulation of the LSO, we can generate synthetic operational data regarding equipment breakdowns, etc. We then split that data into a training set and a test set in order to compare several approaches to forecasting demand in the final operational phase. We are particularly interested in the application of Bayesian network models for this type of forecasting since these offer a way of combining hard observational data with subjective expert opinion.〈/p〉 〈p〉Different LSO configurations were simulated to create a test dataset and the simulation results were compared with the various forecasts. The BN that learned from training data performed best, followed by a hybrid BN design combining expert elicitation and machine learning, and then a logistic regression model. An expert-adjusted exponential smoothing model was the poorest performer and these differences were statistically significant. The paper concludes with a discussion of the results, some implications for practice and suggestions for future work.〈/p〉 〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 4 July 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): João Reis, Marlene Amorim, Nuno Melão〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This article aims to investigate how service providers are employing their channels to support the handling of customer complaints in an online to offline era. It provides a timely contribution by characterizing multichannel recovery practices, discussing its implications for customers, and discovering new trends. The study employs a qualitative multi-method research, which includes not only more than one method of collecting data, but also more than one method of analyzing data. Data collection involved 50 records of customer complaints, 10 semi-structured interviews, direct observation and internal bank reports. The results suggest that multichannel customers are not willing to interact with a large number of channels to solve their problems leading to a high number of interactions. Customers expect a complex recovery not in terms of interactivity but in terms of depth. Recovery solutions, such as apologizing and monetary compensations are non-permanent solutions, are inefficient in the long term and imply financial losses. Despite the investment that is required, this investigation advocates for permanent solutions. To avoid service failures and complex recovery processes, it is possible that companies are improving their operations management in search of new strategies that are blurring the boundaries of O2O into a mix of offline and online channels (O2).〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 9 June 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Krisztina Demeter, Levente Szász, Andrea Kő〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉When a research field achieves a certain maturity, it becomes useful for future research to obtain a structured overview of the field: how did it evolve in the past? Where does it currently stand? In what direction does it (possibly) evolve? The purpose of our paper is to offer an overview of inventory research published in the special issues of ISIR (International Society for Inventory Research) Symposia, one of the most important forums of leading inventory research. This paper focuses on the following two research questions: (1) what are the major topics of inventory research in ISIR special issues? and (2) how do important research topics within ISIR special issues evolve over time?〈/p〉 〈p〉We apply text mining as a novel method of content analysis, relying on the 12 special issues of ISIR published in the International Journal of Production Economics between 1994 and 2016, covering 566 papers. The relevance of text mining is based on a structured analysis of literature review type papers in the field of inventory research; this offers a basis for identifying the main topics and terms in the field. Text mining results are further investigated by statistical methods to identify key research areas and their evolution over time.〈/p〉 〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 4 June 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Abby Ghobadian, Irene Talavera, Arijit Bhattacharya, Vikas Kumar, Jose Arturo Garza-Reyes, Nicholas O'Regan〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In response to hypercompetition, globalisation and increasing consumer expectations, many manufacturing firms have embraced lean manufacturing (LM). The primary goal of LM is to reduce/eliminate waste (〈em〉muda〈/em〉). There is broad consensus as to what constitutes waste, but not on LM implementation. Implementation is not prescriptive with each firm relying on a different combination of administrative, process and routine change/innovation. Lean manufacturing brings about incremental change relying on administrative, process and routine levers. It best fits mass production where process variability is low and demand is high and stable. Lean manufacturing can significantly reduce waste but not eliminate waste, and the attained benefits have not always lived up to expectations. Additive manufacturing (AM) promises to revolutionise manufacturing beyond recognition by eliminating or drastically removing the waste thereby achieving sustainability. But AM is at its formative stage – the space between the concept and growth - where many promising breakthrough technologies fail. To reach its full potential, it needs to achieve high-scale adoption. In this paper, we examine how AM can significantly reduce/eliminate waste and how it can deliver triple bottom line on an unprecedented scale. We contend that AM, if adopted deeply and widely, will take LM to its final frontier, but there are a number of impediments to this end. We identify legitimation as critical to its wide diffusion and develop a number of propositions expediting AM's legitimation. Legitimation of AM will ensure its deep and broad diffusion and should this happen, waste will be a thing of the past an important stride towards sustainable future.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 205〈/p〉 〈p〉Author(s): Kim Sundtoft Hald, Jan Mouritsen〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Supply chain performance measurement systems are important because they are the central managerial mechanisms for achieving efficient and effective supply chain management. Therefore, it is relevant to add to the many conceptual contributions on the subject to explore how such systems unfold and develop in practice. The objective of the present study is to investigate how forces located outside focal firm boundaries influence the evolution of performance measurement systems in supply chains. An evolutionary and dialectic approach is applied, acknowledging that change may be the result of collective action and of opposing influences and forces. Using a longitudinal case study approach, the emergence, proliferation and reconfiguration of three varied yet interrelated performance measurement systems designed to manage a supply chain in the hearing aid industry are explored. The case shows how the evolution of performance measurement systems in supply chains may be informed by multiple influences, some of which are external to the firm. Specifically, ‘interconnectivity of performance measures’, ‘availability and ownership of performance information’ and ‘performance representations’ are all found to be important factors influencing the evolution of the observed performance measurement systems. The framework of the proposed factors here builds on and extends previous research, which has not explicitly incorporated the potential influences of external entities and the supply chain context. Thus, the findings expand our knowledge on how performance measurement systems develop over time in supply chains. With this new knowledge, managers should be better equipped to develop robust and enduring performance measurement systems in supply chains.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 7 May 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Jingxian Chen, Liang Liang, Dong-qing Yao〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Business practices have demonstrated that a contract manufacturer (CM) can introduce an own-label product and thus compete with its original equipment manufacturer (OEM), i.e., factory encroachment, which has not been obtained much attention in literature. Considering a three-level outsourced supply chain consisting of a CM, an OEM, and a retailer, this paper analyzes the impact of factory encroachment on players' gains. We show that factory encroachment could implement Pareto improvement, i.e., all supply-chain players' gains increase under encroachment. We also demonstrate that factory encroachment always offers more surplus to the entire supply chain and the consumer. In addition, the most preferred channel for the supply-chain players, the entire supply-chain system, and the consumer are investigated. We find that an encroachment strategy could be simultaneously favored by all involved parties, provided there is no integration between the OEM and the retailer. However, if the OEM and the retailer act as a single entity, only the no-encroachment strategy could be favored by all parties simultaneously.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: January 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 207〈/p〉 〈p〉Author(s): C.H. Glock, E.H. Grosse, T. Kim, W.P. Neumann, A. Sobhani〈/p〉 〈div xml:lang="en"〉〈div〉〈p〉This paper proposes a model for managing a packaging process of small products at a production line. The aim of the paper is to determine the optimal size of a box the products are stored in considering both financial (in terms of cost) and ergonomic (in terms of worker fatigue) aspects. The paper first develops a biomechanical model to estimate the expected fatigue-recovery parameters associated with the packaging process. Secondly, it proposes an optimization model that minimizes the total relevant cost of the packaging process consisting of the cost of packaging material and the cost of working time, which includes the time required for packing items, setting up and handling boxes, transporting boxes to the shipping area, and idle time cost. Thirdly, the fatigue-recovery approach is integrated into the optimization model to determine the optimal box size from a given set of alternative boxes as well as the work schedule that minimize the total relevant cost while satisfying the upper bound on the estimated total (accumulated) fatigue level. The developed model is then analysed in a numerical experiment inspired by a case observed in industry. The results of the numerical analysis show that smaller box sizes are less sensitive to changes in the maximum permitted fatigue level and that they lead to lower total relevant cost for low wage cost. Larger boxes, in turn, are recommended for higher wage cost. The maximum permitted fatigue level and the box sizes also influence the fatigue range experienced by the worker as well as the share of productive time the worker spends on the job.〈/p〉〈/div〉〈/div〉

Description: 〈p〉Publication date: Available online 14 May 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Yücel Gürel, Refik Güllü〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this paper, we consider inventory and pricing decisions for a system where the customer demand can be partitioned into two segments: a primary and a secondary market. These kinds of systems are observed, for instance, in technology intensive products or services where the primary market, being more loyal, is generally not too sensitive to the pricing of the product or service. While the primary market customer demand occurs right after the introduction of the product, the secondary market customer demand typically occurs after the product matures, and these customers are much more sensitive to changes in the sales price. The purchasing costs of technology intensive products very much depend on the spot currency exchange rate, and hence can be modelled as a stochastic process. Consequently, the sales price for the primary market customers can be assumed to be a mark-up of the spot purchasing cost of the product. On the other hand, as the secondary market customers are more sensitive to the sales price, a demand model, where the customer demand explicitly depends on the selling price would be more appropriate. We try to accomplish three objectives: (1) to model the described system, (2) to find the optimal initial quantity to stock, and (3) to determine the optimal sales price for the secondary market customers.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: January 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 207〈/p〉 〈p〉Author(s): Angappa Gunasekaran, Nachiappan Subramanian, Wai Ting Eric Ngai〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Quality management is an evergreen research theme in the contemporary world. Given the dominance of technological and turbulent environment with unprecedented customer expectations, the aim of this special issue to explore the developments in quality management in the era of Industry 4.0. In particular, our focus is to unravel the advancements in quality and their implications in terms of economics, decision models, business models, human and technological perspectives. This call for papers for the special issue of IJPE ended up in attracting ten high quality studies covering the above perspectives. In addition, the special issue recommends potential unattended future research pathways such as importance of human issues in quality management as per industry revolution and the alignment between technological revolution over time and involvement of human aspects in quality management.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 2 August 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Akshay Jadhav, Stuart Orr, Mohsin Malik〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Supply chain orientation (SCO) has the potential to contribute to supply chain sustainability performance. The literature, however, has not determined whether SCO has a direct effect on supply chain sustainability performance, nor has it differentiated between the effects of different categories of SCO on supply chain sustainability performance. A SEM analysis of data collected from supply chain managers determined that the SCO construct of supply chain collaboration and communication could directly affect both supply chain environmental and social sustainability performance. The SCO construct of internal supply chain coordination, however, affected only supply chain environmental sustainability performance and this effect was mediated by the organisation's internal supply chain sustainability practices. A second path between supply chain collaboration and communication and supply chain environmental sustainability performance, which was mediated by internal supply chain sustainability practices was also identified. These findings indicate that different SCO constructs have different effect pathways in relation to supply chain sustainability performance. The identification of the effects of different categories of SCO and the SCO – performance relationship has important implications for SCO research design.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 206〈/p〉 〈p〉Author(s): M. Arsalan Farooq, Richard Roth, Randolph Kirchain〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉High-pressure die-casting (HPDC) is a proven manufacturing technology to cast aluminum and magnesium alloys. Transportation industries are under increased pressure to reduce the mass of cast parts in order to cut fuel use and CO〈sub〉2〈/sub〉 emissions, and increase load. Reducing mass and improving mechanical properties with current HPDC is not practical due to processing limitations that result from air entrapped during metal filling as well as limitations on performing additional processes such as heat treatment that can expose the porosity or voids. Super vacuum die-casting (SVDC) is an innovation that aims to overcome this challenge by introducing a vacuum to draw air from the die cavity before filling. While there is a significant literature on the technical performance of vacuum assisted technology, the authors are unaware of previous work focused in analyzing short- and long-term cost-benefit tradeoffs. This manuscript's goal is to evaluate the strategic and economical implications of novel SVDC technology as well as its upstream and downstream processes, however, the cost implications of use-life and end-of-life is not considered in this study. To do this, we develop and describe an analytical model to map future scenarios, both production and product, to expected production cost difference between SVDC and conventional die-casting. Using these models we find that materials and die casting process costs dominated the cost in both HPDC and SVDC. From analysis of several case studies, these dominant costs translate directly into the strategic advantages and disadvantages of SVDC. SVDC can provide cost savings if a part can be redesigned to reduce mass. Some of that cost savings is lost, however, due to added heat treatment costs and added tooling and system costs. The effect means that SVDC can reduce cost particularly for larger parts and when production volumes are higher. The cost advantage of SVDC is strongly dependent on production volume, and realized mass savings. From a variance-based sensitivity analysis, it can be seen that at higher production volumes (around 100k per year or more) breakeven requires a mass savings of 15% for small parts and around 12.5% for medium and large parts. However, when production volumes are low (say around 5000 parts per year) these values rise to 45%, 35%, and 30%, respectively.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 3 September 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Daqiang Chen, Joshua Ignatius, Danzhi Sun, Shalei Zhan, Chenyu Zhou, Marianna Marra, Mehmet Demirbag〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The effectiveness of a reverse logistics strategy is contingent upon the successful execution of activities related to materials and product reuse. Green supply chain (GSC) in reverse logistics aims to minimize byproducts from ending up in landfills. This paper considers a retailer responsible for recycling and a manufacturer responsible for remanufacturing. Customer environmental awareness (CEA) is operationalized as customer word-of-mouth effect. We form three game theoretic models for two different scenarios with different pricing strategies, i.e. a non-cooperative pricing scenario based on Stackelberg equilibrium and Nash equilibrium, and a joint pricing scenario within a cooperative game model. The paper suggests that stakeholders are better off making their pricing and manufacturing decision in cooperation.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 205〈/p〉 〈p〉Author(s): Lonnie Turpin〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Various definitions of cycle time exist in literature. In this research, we discuss a select few and focus on cycle time as the average time between successive units of output. We test this definition using two simple derivations of throughput time validated by three numerical examples. The derivations and corresponding examples make use of the readers intuition when analyzing processes described by deterministic inputs.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 206〈/p〉 〈p〉Author(s): Tarun Jain, Jishnu Hazra, T.C.E. Cheng〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In supply chains the buyer and its suppliers are often overconfident in situations where they face demand uncertainties. In this paper we study the impact of such overconfidence bias on the buyer's supply-base design strategy. With overconfidence bias, the buyer and suppliers perceive lower demand variability as compared with reality. Characterizing the buyer's optimal reserved capacity and optimal number of suppliers in the supply base, we find a threshold policy for impact of the buyer's overconfidence bias. We also find that the suppliers' overconfidence bias decreases the buyer's reserved capacity and number of suppliers in the supply base.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 206〈/p〉 〈p〉Author(s): Adel A. Alamri, Aris A. Syntetos〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The classical formulation of a two-warehouse inventory model is often based on the Last-In-First-Out (LIFO) or First-In-First-Out (FIFO) dispatching policy. The LIFO policy relies upon inventory stored in a rented warehouse (RW), with an ample capacity, being consumed first, before depleting inventory of an owned warehouse (OW) that has a limited capacity. Consumption works the other way around for the FIFO policy. In this paper, a new policy entitled “〈em〉Allocation-In-Fraction-Out (AIFO)”〈/em〉 is proposed. Unlike LIFO and FIFO, AIFO implies simultaneous consumption fractions associated with RW and OW. That said, the goods at both warehouses are depleted by the end of the same cycle. This necessitates the introduction of a key performance indicator to trade-off the costs associated with AIFO, LIFO and FIFO. Consequently, three general two-warehouse inventory models for items that are subject to inspection for imperfect quality are developed and compared – each underlying one of the dispatching policies considered. Each sub-replenishment that is delivered to OW and RW incurs a distinct transportation cost and undertakes a 100 per cent screening. The mathematical formulation reflects a diverse range of time-varying forms. The paper provides illustrative examples that analyse the behaviour of deterioration, value of information and perishability in different settings. For perishable products, we demonstrate that LIFO and FIFO may not be the right dispatching policies. Further, relaxing the inherent determinism of the maximum capacity associated with OW, not only produces better results and implies comprehensive learning, but may also suggest outsourcing the inventory holding through vendor managed inventory.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 205〈/p〉 〈p〉Author(s): Hamed Jahani, Babak Abbasi, Farzad Alavifard, Srinivas Talluri〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉When new products are introduced into a supply chain, the existing logistics may no longer optimally meet the objectives of the enterprise. This paper provides an analytical approach to redesigning a supply chain network (SCN), considering its current infrastructure. While aiming to maximise total profit, we take into consideration the demand and price uncertainty and their correlation as two important risk factors, and formulate them using associated Brownian motions employed in a real options pricing approach. Our model captures multiple periods and cash flow aspects through a non-linear structure. In the solution approach, we apply a novel piecewise linear conversion. Our theoretical model is complemented by a realistic case study from the Australian cement industry. We demonstrate significant improvements in the financial position of the company after redesigning its SCN. For instance, SCN redesign increases total profit by 49%, while the profit from the existing product increases by 23%. The results also indicate that ignoring the effect of the correlation leads to profit overestimation.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 206〈/p〉 〈p〉Author(s): Yang Cheng, Sami Farooq〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Based on IMSS VI, this paper firstly revisits Ferdows' typology by simultaneously addressing multiple portfolios of its two dimensions, i.e. site competence and location advantage. It further complements this typology by developing a more objective, empirically derived taxonomy of plant role and accordingly proposes four new plant roles, i.e. Star Plant, Old School Plant, Expert Plant, and Replaceable Plant. These plant roles are different in terms of location advantages and site competences, as well as other characteristics, e.g. product, process, market, and location. Second, this paper extends our understandings on plant role by exploring the fit of a plant role with the differentiation of its management practices based on the developed taxonomy. It identifies three patterns regarding the fits between plant roles and their management practices and implies that plants that are strongly embedded in the manufacturing network are expected to play the high level of strategic role; plants with greater responsibility may sometimes correspond with less autonomy; plants in dilemma might have more motivation to coordinate with other plants and integrate with external customers; and plants managed in old styles might be more independent and thereby passive about coordination and integration with other partners. These results highlight that management practices need to be differentiated so that plants can pursue their roles effectively.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 205〈/p〉 〈p〉Author(s): Leonardo A. Banguera, Juan M. Sepúlveda, Rodrigo Ternero, Manuel Vargas, Óscar C. Vásquez〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper seeks to describe several features of the reverse logistics network design under extended producer responsibility, in which the collection goals and penalties for the management system are established by a regulatory legal framework. To address this design network challenge, the paper develops a mixed integer linear programming model for capacitated facility location, which meets recycling targets and minimize the cost of fines in case of infeasibility, through relaxation of constraints. Consequently, the optimal flows, the configuration of collection, reprocessing and recycling facilities, and the estimation of the monetary transfers necessary for the feasible operation of the optimal management system are computed. To illustrate the usefulness of the proposed model, a numerical example based on the case of out-of-use tires (OUT) in the Gran Santiago city of Chile is considered. Forty-two scenarios are defined by a specific offer of OUT for the year 2020 and a possible ratio of OUT to be collected in the reverse logistic network imposed by the authorities. The obtained results show the optimal sets of service center, collection centers and reprocessing plants for each scenario, allowing to study the maximum benefit/minimum investment to develop a management system under the EPR national law.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 206〈/p〉 〈p〉Author(s): Xun Tong, Jianghang Chen, Qinghua Zhu, T.C.E. Cheng〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract:〈/h5〉 〈div〉〈p〉Corporate social responsibility (CSR) issues in suppliers can affect the reputation of buyers or even result in supply chain disruption. Thus, buyer and supplier firms are urged to comply with CSR codes in a coordinated manner. In other words, multinational buyers are expected to extend CSR practices to their suppliers in emerging countries. This is particularly crucial when suppliers' CSR performance is screened under a regulatory agency's inspection regime. To this end, this study formulates an analytical model to understand the effects of buying firms' supportive schemes, i.e., technical assistance programmes, on their partner suppliers' CSR performance. Specifically, we develop a multi-period behavioural model to simulate a system consisting of multiple buyers and suppliers where the government regularly conducts inspections on suppliers' CSR performance. The results from the agent-based simulation analysis shed light on (1) how the dyadic risk preferences of suppliers and buyers affect suppliers' CSR performance; (2) how the gap between the perceived and actual CSR levels in a supplier interacts with the regulatory agency's tactics to influence suppliers' CSR performance; (3) the extent to which the overall suppliers' CSR performance improvement is attributable to the buyers' technical assistance programmes under the regulatory agency's inspection regime. This research contributes to the socially responsible supply chain management literature and provides innovative managerial insights for policy makers (e.g., CSR regulators) to promote CSR practices among suppliers.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 15 September 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Yenming J. Chen, Tsung-Hui Chen〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Recent regulations often mandate the recycling of scrap products, especially electrical wastes. This study demonstrates how this end-of-pipe enforcement can be converted to an effective policy tool in improving product design towards green product. We show that collective recycling can enhance producer responsibility whilst being affordable for coalition participants by adopting the proposed two-part allocation scheme, which is a particular solution of the underlying cooperative game and is closer to the nucleolus than the Owen set. Practically, our scheme is easier to implement than other core solutions. This scheme can establish institutional trust and promote environmental quality for companies participating in a recycling coalition. The goal of promoting green market is achieved through the implicit cooperation of participating companies.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 205〈/p〉 〈p〉Author(s): Hing Kai Chan, James Griffin, Jia Jia Lim, Fangli Zeng, Anthony S.F. Chiu〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉3D Printing (3DP) technology has been receiving increased public attention. Many companies are seeking ways to develop new means of creating and disseminating 3DP content, in order to capture new business opportunities. However, to date the true business opportunities of 3DP have not been completely uncovered. This research explores the challenges posed in the development and deployment of 3DP and focuses on China, which is still the main manufacturing hub of the world. The main purpose of this research is to uncover the obstacles that resist mass-scale applications of 3DP. By means of empirical semi-structured interviews with 3DP companies in China, it is found that many companies can see the benefits of 3DP, but its potential has not been delivered as promised. One reason is due to the fact that 3DP has not been integrated well in the supply chain. The other reason concerns potential intellectual property issues that cannot effectively prevent counterfeiting. To tackle the above issues, several areas have been identified that could be improved further. In particular, the legal complications concerning 3D-printed content could be overcome by a licensing platform.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 3 March 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): M. Hasni, M.Z. Babai, M.S. Aguir, Z. Jemai〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Many bootstrapping approaches have been proposed in the academic literature for non-parametric demand forecasting. Two approaches have been developed to deal particularly with intermittent demands. A first approach that samples demand data by using a Markov chain to switch between no demand and demand periods and a second approach that separately samples demand intervals and demand sizes. The relevant studies have claimed improvements over parametric approaches when estimating the lead-time demand distribution. However, it should be noted that the outperformance of the two bootstrapping approaches has been shown under a limited set of control parameters and assumptions. The purpose of this paper is to broaden the empirical and numerical settings when analyzing the performance of the two bootstrapping approaches and the parametric one. Hence, more exhaustive assumptions (i.e. generated demand distributions) and a wider range of control parameters (i.e. length of demand histories, length of lead-times, demand distribution parameters and cost parameters) are considered in the numerical analysis. More empirical data with a wider range of demand patterns are also used for the purpose of the empirical investigation. The results show that for highly intermittent demands and small values of lead-times, contrary to what has been claimed in the literature, the parametric approach outperforms the bootstrapping approach that separately samples demand intervals and sizes.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 205〈/p〉 〈p〉Author(s): Benyong Hu, Jiali Qu, Chao Meng〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉We consider a coordination problem under option contracts in a two-echelon supply chain, where the product retail price, option price, option exercise price, and order quantity are optimized. The market demand is random and sensitive to product retail price. Our analyses consider two types of contracts. One is a conventional option contract, where the supplier determines the option price and exercise price, and the retailer determines the product retail price and order quantity. Two cases are studied in terms of the supplier's decisions: (1) the supplier has option exercise price as its decision variable, and (2) has both the option price and option exercise price as its decision variables. The other type of contract is an option contract with a joint pricing mechanism, for which two supply chain players determine a relationship between the option exercise price and product retail price. For both types of contracts, we develop a newsvendor model to examine how joint pricing impacts supply chain coordination and decisions. We use sequential procedures to derive the optimal decisions for the supply chain players, including the retailer's order quantity and product retail price and the option exercise price set by the supplier. We then show that a conventional option contract cannot coordinate the supply chain on its own. We propose introducing joint pricing to option contacts and prove that it would benefit both supply chain players and induce them to voluntarily achieve coordination.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 206〈/p〉 〈p〉Author(s): Xiutian Shi, Ciwei Dong, T.C.E. Cheng〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Retailers nowadays increasingly adopt the buy-online-and-pick-up-in-store (BOPS) strategy with pre-orders for order fulfillment. In this paper we study such a strategy for a retailer in the presence of both informed and uninformed consumers. Under such a strategy, the retailer sells the product over two periods, where the informed consumers may make pre-orders with unknown valuations in the first period and pick up the pre-orders in store with realized valuations in the second period. We first derive the optimal price discount for the pre-orders and the optimal order quantity for the demands over the two periods. Then, we show that the BOPS strategy with pre-orders is not necessarily beneficial to the retailer in general. We identify the thresholds for the unit production cost and demand uncertainty, above which the BOPS strategy with pre-orders is beneficial. In addition, we derive the conditions under which the BOPS strategy with pre-orders and product returns is favourable to the retailer, even when the returned product cannot be re-sold. Moreover, studying the effects of the proportion of the informed consumers in the market, we show that under some conditions the BOPS strategy with pre-orders will generate more profit to the retailer when the proportion of the informed consumers increases.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 206〈/p〉 〈p〉Author(s): Tonci Grubic, Ian Jennions〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Outcome-based contracts (OBCs) are claimed to be the new business model for manufacturers. They have attracted a lot of research that identifies two types of OBCs: outcomes based on availability (aOBCs) and outcomes based on economic results (eOBCs). The first involve the sale of the availability of a product whereas in the second the customer purchases the functional result of the product. This characterisation is identical to the distinction between the use-oriented and result-oriented Product-Service System type. However, there are studies that seem to challenge the prevalence and even the existence of eOBCs in practice. We have set out to investigate whether eOBCs exist. This was done by addressing the following research question: what are the differences between aOBCs and eOBCs? The study employed research design that consists of three steps: identification, selection, and analysis of OBC cases as reported in journal articles. In relation to the case studies identified, our preliminary analysis suggested that all the case studies in the literature are of the aOBC type. The only case identified as the possible case of eOBC, and subsequently selected for further analysis, is that of Power-by-the-hour (PBTH) by Rolls-Royce. The analysis of PBTH was conducted from the Remote Monitoring Technology perspective. Our key contributions are: (1) a new theoretical perspective on OBCs, (2) the articulation of differences between OBC types and of what constitutes an outcome, and (3) doubt in the existence of eOBCs in practice.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 27 February 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Arya Sevgen, F. Zeynep Sargut〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉We study a continuous-review inventory problem of a retailer observing constant deterministic demand and ordering from a supplier. This is an extension of Economic Order Quantity model (EOQ), in which both supplier and retailer are subject to random disruptions. The supplier is assumed to be at two states, which are available and unavailable. When the retailer is disrupted, all on-hand inventory is destroyed, but the retailer recovers immediately to serve customers. All unsatisfied demand at retailer is assumed to be lost. We create a mathematical model to determine optimal parameters of an order-up-to type policy for the retailer and investigate the importance of a non-zero reorder point for the retailer. With computational experiments, we identify when a non-zero reorder point is cost saving, and compare our solution with classical EOQ.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 27 July 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Lohithaksha M. Maiyar, Jitesh J. Thakkar〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Escalating global food security concerns across several nations has shifted the focus of policy makers towards risk adaptive sustainable food grain operations. This paper builds a sustainable food grain transportation model for intermodal transportation operations between two Indian states, in the presence of hub disruption. A hub and spoke system is used to connect origin and destination warehouses through intermodal hubs in a multi-layered network. The problem is formulated as a multi-period mixed integer nonlinear single objective optimization problem considering minimization of transportation, hub location, rerouting, environmental and social costs with near optimal shipment quantities and hub allocations as the prime decisions. The proposed MINLP is solved using Particle Swarm Optimization with Differential Evolution (PSODE), a superior metaheuristic to deal with NP-hard problems. Convergence graphs and global optimal costs are reported for small, medium and large size instances consisting of 1824, 9768 and 28848 variables respectively, inspired from food grain industry in the southern part of India. Pareto plots are generated to capture the complementarity between economical and socio-environmental cost categories for all instances. The effect of hub location, hub disruption, cost consolidation and vehicle resource availability factors on individual and total costs is studied through sensitivity analysis. Results indicate that food grain demand is fulfilled with 14% increase in the mean total cost for single hub disruption case and with 40% increase for multiple hub disruption. Finally, managerial implications provide specific factor level recommendations for different strategic objectives.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 205〈/p〉 〈p〉Author(s): Qingyun Zhu, Purvi Shah, Joseph Sarkis〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Product management activities have typically focused on the innovation, acquisition, expansion and management of product lines and products. However, product deletion or discontinuation is also critical. Despite its strategic importance, product deletion has received relatively less attention in both academia and practice. Researchers have conceptually investigated product deletion, its influence on firm's resources, the factors influencing product deletion decisions, and the product deletion process. However, very few papers have related product deletion decisions to supply chain management, especially when leanness and sustainability are major objectives. This paper aims to integrate lean and sustainable supply chain dimensions with product deletion by proposing a multilevel decision model that can facilitate a product deletion decision with an objective of developing a leaner and more sustainable supply chain. The model has three major decision dimensions with 8 factors with 29 influencing determinants. The model uses an integrated analytical hierarchy/network process (AHP/ANP) and a benefits, opportunities, cost and risks (BOCR) analysis. An illustrative company scenario is provided for the model application. The paper contributes by filling an important gap by integrating lean and sustainable supply chain management and product deletion literature to formulate a product deletion decision making model which aids in enhancing the leanness and sustainability of supply chains. The model also allows for cross-functional participation involving marketing, operations, finance, and environmental sustainability fields.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 205〈/p〉 〈p〉Author(s): Charles X. Wang, Zhuang Qian, Yabing Zhao〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Many manufacturers are offering some form of supply chain incentives to motivate their retailers to increase customer satisfaction (CS). In this paper, we focus on the manufacturer's two main CS incentives for the retailer: 〈em〉customer satisfaction index bonus〈/em〉 (CSI bonus) and 〈em〉customer satisfaction assistance〈/em〉 (CS assistance). When both manufacturer and retailer have strong market pricing power, prior research has shown that the manufacturer should offer both CSI bonus and CS assistance to the retailer. In contrast with prior research results, we find if the manufacturer has weak market pricing power, then she should only offer CS assistance but not CSI bonus to the retailer when the market wholesale price is relatively low. We also quantify the value of the CS incentive programs to the manufacturer's performance improvement in different supply chain settings. In general, we find the manufacturer's CS incentive program is more valuable when demand is more sensitive to the retailer's CS effort. Finally, we obtain additional insights from a few supply chain model extensions.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 205〈/p〉 〈p〉Author(s): Mahdi Mahdiloo, Ojelanki Ngwenyama, Rens Scheepers, Ali Tamaddoni〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper presents an application of Data Envelopment Analysis (DEA) in ecological efficiency evaluation of electricity producers and allocation of the CO〈sub〉2〈/sub〉 emission allowances. Unlike two very popular approaches for allocating CO〈sub〉2〈/sub〉 emission allowances (based on most recent CO〈sub〉2〈/sub〉 emission or electricity generated data), we propose a model for allocating these allowances based on ecological efficiency scores of the electricity producers. Our model involves the influence strategy of rewarding ecological efficiency and penalizing ecological inefficiency behaviours of electricity producers. The model is tested and its usefulness is demonstrated using a real world problem of electricity producers in the US.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 206〈/p〉 〈p〉Author(s): Chi Kin Chan, Fei Fang, André Langevin〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper proposes a model of single-vendor multi-buyer supply chain coordination with stochastic demand in which the vendor's production cycle length and the buyers' ordering cycle lengths are synchronized. A mathematical model for the coordination policy considering possible stock-out and/or excessive stock is formulated, and a solution algorithm for the model is developed. The numerical results show that, under stochastic situation, our coordination model performs better than two other policies, the decentralized decision making model and the common cycle coordination model. Considering the difficulty of estimating shortage cost, trade-off curves are plotted along a range of service levels to further compare the models and reinforce our results.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 7 September 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Claire Hannibal, Katri Kauppi〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The paper examines the different third party approaches used to assess the social sustainability of global multi-tier supply chains. Information asymmetries between supply chain actors and stakeholders can result in uncertainty about how a good has been produced and traded, resulting in sustainability uncertainty. Third party social sustainability assessment is one mechanism used to monitor and communicate the credentials of everyday products to stakeholders. We frame our study using information processing theory to discuss how third party assessors can help to reduce sustainability uncertainty. As social sustainability is of particular importance in labor-intensive industries, empirical data is drawn from agriculture, textiles, handicrafts, footwear and consumer electronics supply chains. The analysis of semi-structured interviews with assessors reveals differing approaches to assessment. We show how these approaches utilize differing numbers of supply chain tiers. Some, for example, focus only on the farmer or raw material supplier when assessing social sustainability, which raises questions about the credentials of actors further downstream. The communities and livelihoods of supply chain actors, often located in the global South, can be dependent on the new, niche and potentially more profitable markets made available to goods that can demonstrate their social sustainability credentials. Robust assessment is therefore integral in accessing these new markets. The study offers a comparison between different assessors that will be of interest to scholars and also to supply chain actors considering engaging in social sustainability assessment.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 205〈/p〉 〈p〉Author(s): Malgorzata Plaza, Iulian David, Farid Shirazi〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉The study develops a hybrid inventory management model, which can be used to synchronize the supply of critical purchased components with the output rate of the end product manufactured to the level production strategy. The model combines the demand driven delivery of a “pull” strategy with forecasting techniques used by “push” systems. It consists of a “Pull Signal” (PS) and two cost effectiveness formulas (CEFs).〈/p〉 〈p〉PS triggers purchasing and determines the quantity and timing of supplies that are pulled by production. It is an inventory ordering algorithm, which determines “When and how many critical components should be ordered”. Inventory management can become expensive if PS is used to manage the low cost components so CEFs is required to determine “Which components should be managed as critical”.〈/p〉 〈p〉The hybrid model is most useful in situations where production lead time is short, purchasing lead time is long and demand patterns vary. It was successfully implemented by a Canadian firm from a computer industry and generated a 27% reduction in a total value of inventory within just 11 months. Additionally, the customer service, cycle times, and even warehouse handling were all significantly improved.〈/p〉 〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 7 August 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Kannan Govindan, Andreea Malomfalean〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉Over the past decade, a significant change has occurred in the way businesses progress, and that change is largely due to rapidly changing technology. The entire world depends on the online network that has radically changed our perspective of how business should be managed. The faster a company adapts, the more quickly that company can outpace its competitors, and a new approach that is attracting attention is called Online to Offline (O2O).〈/p〉 〈p〉This paper establishes a comparison based on O2O approach; our model considers two types of demand under three coordination mechanisms (revenue-sharing, buy-back, and quantity flexibility contracts). We demonstrate that the best outcome and the highest profit is achieved with the O2O deterministic demand under the quantity flexibility agreement. However, the stochastic demand case attains the same result. This paper presents a fruitful introduction to this emerging topic, and future research might compare several coordination mechanisms using the Stackelberg game theory.〈/p〉 〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 17 April 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Ata Allah Taleizadeh, Mohammad Sadegh Moshtagh〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper considers a multi-level closed loop supply chain (CLSC) including a supplier, a producer, a retailer, and a collector. Most of the works in the literature considered remanufactured products as-good-as newly produced items, while in the real world situations, some customers perceive remanufactured items as lower quality products than newly produced ones; so we assume that demands for manufactured and remanufactured items are different which leads to lost sales situations. To make the study more realistic, we assume the return rate of the second-hand items as a variable function which depends on the acceptance quality level of the returns. Also, producing and reproducing processes are assumed to be imperfect, so they can produce some defectives which are reworked in the same cycle. To address this problem, a mathematical model with single manufacturing/remanufacturing cycles is established and solved using two algorithms extended for the case of local (non-integrated) and global (integrated) optimization. The results of our analysis indicate that integration results in higher acceptance quality level of returns, higher replenishment cycle time for both manufactured and remanufactured items and less (higher) number of shipments to the retailer per manufacturing (remanufacturing) cycle. Furthermore, the results indicate that as the revenue of selling newly produced items (remanufactured items) increases, acceptance quality level of the returns decreases (increases) and the total number of shipments to the retailer per manufacturing (remanufacturing) cycle increases (decreases).〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 19 July 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Debashree De, Soumyadeb Chowdhury, Prasanta Kumar Dey, Sadhan Kumar Ghosh〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Lean and Sustainability Oriented Innovation both enhance competitiveness of small and medium enterprises (SMEs) in a sustainable way. Lean is efficiency focused, whereas Sustainability Oriented Innovation emphasizes on responsiveness. Although lean and sustainability oriented innovation have been separately researched, there is a gap in knowledge on the combined effect of lean and sustainability oriented innovation (SOI) on SMEs Supply Chain sustainability. SMEs have limited resources and face numerous competition. Therefore, their supply chain sustainability can only be achieved through most appropriate trade-off between economic, environment and social aspects of business. The purpose of this paper is to understand the combined effect of sustainability oriented innovation and lean practices, on supply chain sustainability performance of SMEs. The study uses a Data Envelopment Analysis (DEA) based framework and applies this to a group of SMEs within the Eastern part of India. Lean and sustainability oriented innovation are considered as input criteria, and economic, operational, environmental and social aspects are considered as output criteria of the proposed framework. DEA segregates inefficient SMEs and suggests at least a SME to benchmark. Subsequently, the study undertakes qualitative approach to suggest improvement measures for the inefficient SMEs. The results reveal that combined lean and SOI helps achieve SMEs' supply chain sustainability. The findings are useful for policy makers and Individual SMEs' owners and managers to undertake measures for improving sustainability. Theoretically this research contributes a DEA-based framework to study the effect of combined lean and SOI on sustainability that helps improving SMEs’ sustainability performance.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 27 March 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Imre Dobos, Gyöngyi Vörösmarty〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In today's competitive and dynamic world, the importance of supplier evaluation has become more widely recognized. When considering measurement of supplier performance and supply impact the literature identifies two sets of criteria: management criteria and green criteria. Management criteria can be extended with process cost criteria, which then poses new requirements to be met by the evaluation methodologies. This paper aims to present a methodology that can handle the different characteristics of these criteria. As a solution, a green supplier selection problem is generalized.A Data Envelopment Analysis (DEA)-type supplier selection method was developed, where green factors served as the output variables of a DEA model, and management variables were the inputs. This new methodology examines, in addition to managerial and green criteria, the effect of inventory-related costs, such as the EOQ costs of inventory holding or ordering costs on the selected supplier. The parametrical linear programming of technological coefficients is used in the DEA method. This paper draws attention to a new problem, namely, the literature fails to provide solutions for how to handle the nonlinearity of the cost functions in the most commonly used methodologies.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 206〈/p〉 〈p〉Author(s): Amirmohsen Golmohammadi, Majid Taghavi, Samira Farivar, Nader Azad〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The effectiveness of supplier development programs has resulted in a wide range of applications in various industries. By emphasizing on cooperative efforts of suppliers and buyers, these programs can significantly improve the suppliers' performance. This leads the suppliers to develop different strategies that increase the involvement of their buyers. In this study, we identify three strategies that a supplier can implement to facilitate the supplier development effort of its buyer: (1) wholesale price manipulation, (2) paying a share of investment, and (3) controlling the investment. We analyze the implementation of these strategies under uncertainties of supply and demand to expand the applicability of the models and results. In this study, we show that the optimal decisions of the players under all three strategies are unique. Our findings also indicate that the effectiveness of these strategies decreases as the profit margin of the buyer increases. In addition, we explore the effect of profit margins and demand uncertainty on the players' optimal decisions. Through numerical analysis, we indicate that for low buyer's and supplier's profit margins, the supplier prefers wholesale price manipulation strategy. On the other hand, when the profit margin of the supplier is relatively high, paying a share of investment strategy is more attractive. Moreover, our results demonstrate that uncertainties of supply and demand may have contradictory effects on players' optimal decisions.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 205〈/p〉 〈p〉Author(s): Voon-Hsien Lee, Keng-Boon Ooi, Alain Yee-Loong Chong, Amrik Sohal〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper investigates the relationships between supply chain management (SCM) practices (i.e. strategic supplier partnership, customer relationship, information sharing, information quality, postponement, internal operations) and technological innovation (TI) in a R&D manufacturing setting in Malaysia, with guanxi being the intervening variable. A conceptual model was developed and tested using data collected from 197 Malaysian manufacturing firms for the study. Data set was examined and hypotheses were tested by employing Partial Least Squares-Structural Equation Modelling (PLS-SEM) analysis. The results revealed that internal operations, postponement, strategic supplier partnership, and guanxi have positive and significant relationships with TI; while guanxi mediates the relationships between four SCM practices (i.e. strategic supplier partnership, information quality, postponement, and internal operations) with TI. Findings show that through proper implementation of SCM practices, firms are able to achieve better TI performance. These findings are useful for decision-makers when formulating SCM strategies and focusing on practices that will help them achieve greater TI. This paper also contributes to existing operations management research by empirically validating guanxi as the mediator between SCM practices and TI. From a developing nation perspective, this paper identifies the important relationships that exist between SCM, guanxi and TI. The findings will be of interest to both emerging and other developing nations.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 206〈/p〉 〈p〉Author(s): Qinghua Huang, Shilei Yang, Victor Shi, Yibin Zhang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Convention wisdom suggests that it is detrimental for a firm to decentralize its sales channel or supply chain structure. However, a persistent research stream has shown that competing firms can benefit from strategic decentralization under one of the two conditions: 1) their products have exogenous quality levels with high substitutability; or 2) their products have endogenous quality levels and decentralization can lead to more quality differentiation. In this paper, we uncover a new strategic benefit of channel decentralization when both conditions are violated. In our model settings, a leader firm (she) and a follower firm (he) first choose their channel structures and then choose from low and high quality levels, which are set so that the two products have low or moderate substitutability. We find that if the leader centralizes, the follower benefits from strategic decentralization only if he has cost 〈em〉advantage〈/em〉 in quality development. If the leader decentralizes, the follower benefits from strategic decentralization only if he has cost 〈em〉disadvantage〈/em〉. In short, the follower with cost asymmetry can strategically decentralize his sales channel to influence the leader's quality choice. We also show the robustness of our results by allowing for a general form of quality development cost function and a positive variable production cost.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 21 July 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Fu Jia, Yu Gong, Steve Brown〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Sustainable Supply Chain Management (SSCM) has been considered increasingly important by both industry and academia in recent years. Among the main streams of SSCM research, little is known on how multi-national corporations (MNCs), assuming leadership in their supply chain, have been able to facilitate their supply chain members to learn sustainability practice in an emerging economy context. To answer this research question, a multiple-case study was designed. Multi-tier supply chains of three MNCs were selected to investigate their proactive sustainability projects in China. A framework was proposed based on the constructs of supply chain leadership, multi-tier supply chain governance, multi-tier supply chain structure and supply chain learning. We found that the combined effect of supply chain leadership and governance mechanisms affects both supply chain structure and supply chain learning and MNCs change their supply chain structure to facilitate supply chain learning. Three sets of propositions are advanced and implications for future research are elucidated.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 30 April 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Nooshin Nekoiemehr, Guoqing Zhang, Esaignani Selvarajah〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper studies reliable due date quotation for online customer orders in a two-echelon dual-channel supply chain when there is a threshold on quoted due dates. In this problem, there exist two delivery options for the e-tail customers with different cost and availability intervals, i.e., directly shipping by the manufacturer or through the retail store. The manufacturer has the capacity constraint for processing online orders. We adopt an online optimization perspective and propose algorithms to determine due date quotation coordinated with scheduling for e-tail customer with the objective of maximizing the total profit of completed orders considering linear due-date-sensitive revenue function and delivery costs. The approach of “competitive analysis” is performed to evaluate the proposed algorithms. We provide parametric bounds on the competitive ratio of any arbitrary online strategy, and investigate the competitive ratio of a specific online algorithm for single-type e-tail channel orders. Computational experiments illustrate the effectiveness of the proposed algorithms and analysis.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 206〈/p〉 〈p〉Author(s): Yiran Yang, Lin Li〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Additive manufacturing has obtained widespread and continuously increasing interest, owing to its distinguished advantages (e.g., reduced material waste and enhanced manufacturing complexity) compared to traditional manufacturing processes. Currently, the implementation of additive manufacturing in the industrial sector is limited to small-scale production with high customization level. In current literature, the cost analysis for complex production layouts especially with mixed geometries are not fully studied, and some popular additive manufacturing processes are not well investigated for cost performance. Therefore, in this paper, a comprehensive cost model is established to theoretically evaluate the cost performance of the Mask Image Projection Stereolithography process for simultaneously fabricating multiple mixed geometries. In addition, an optimization problem is formulated to reduce the additive manufacturing costs considering the set of decision variables (layer thickness and surface stratification angle) under the constraints of production throughput and part quality. The case study results indicate that 26% of cost savings can be achieved by solving the proposed optimization problem. Furthermore, a sensitivity analysis is conducted which shows that the raw material unit price and the initial investment on additive manufacturing hardware and software are the main cost drivers.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 15 October 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): F. Ciardiello, A. Genovese, A. Simpson〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This study introduces a cooperative game theory approach aimed at addressing the problem of allocating pollution responsibility across partners collaborating in supply networks. The proposed framework includes three different allocation rules through which companies can share pollution responsibility across complex supply networks. A case study in the context of a supply network for the manufacturing of construction materials is illustrated for demonstrating the real-world applicability of the approach.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 25 June 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Manjot Singh Bhatia〈/p〉

Description: 〈p〉Publication date: November 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 205〈/p〉 〈p〉Author(s): Yixuan Xiong, Gang Du, Roger J. Jiao〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Modular product platforming empowers product family design by identifying the common product platform and configuration of product variants for mass customization. The prevailing practice of fulfilling product families is to postpone certain customization modules in the downstream supply chain. Product platforming and postponement decisions are inherently coupled in terms of developing a modular product architecture to leverage product variety and the supply chain. This paper is motivated towards integrated decision making underlying modular product platforming (MPP) with supply chain postponement (SCP). The paper formulates integrated MPP and SCP decisions as a Stackelberg game that entails joint optimization for interactive evaluation of product modularity and supply chain fulfillment costs. A bilevel mixed 0–1 programming model is developed to characterize the leader-follower decision making process. Virtual compound modules are introduced to justifying which modules should be postponed. An upper level optimization problem is established for identification of basic modules and compound modules by maximizing customer-perceived utilities and postponement utilities of product families, whereas a lower level optimization problem deals with the selection of most appropriate postponement service providers for a minimal total supply chain cost. A nested genetic algorithm is developed to solve the bilevel joint optimization model. A case study of laser printer product platforming and supply chain postponement is reported to illustrate the feasibility and potential of the proposed decision model.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 19 September 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Ali Diabat, Armin Jabbarzadeh, Amir Khosrojerdi〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The emergency supply of products in disasters is a crucial task in humanitarian aid supply chain management. This paper presents a bi-objective robust optimization model for the design of supply chains which are resilient to disaster scenarios. The proposed model aims to minimize the time and cost of delivering products to customers after the occurrence of a disaster, while considering possible disruptions in facilities and routes between them. A solution approach based on Lagrangian relaxation and ɛ-constraint is developed to efficiently solve the bi-objective model. To validate the formulation and derive practical insights, we apply the proposed approach to a real case study.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 205〈/p〉 〈p〉Author(s): Siyu Li, Xiande Zhao, Baofeng Huo〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This study investigates relationships among various types of supply chain coordination, innovativeness, and financial performance. Social contagion theory is mainly used to construct a research framework. Two underlining contagion mechanisms, cohesion and structural equivalence, were identified for various supply chain relationships. Data was collected from 617 Chinese manufacturers and employed to test the theoretical model. The results show that supplier coordination positively influences manufacturer, customer coordination, and supplier innovativeness. Manufacturer coordination promotes customer coordination and manufacturer innovativeness. Supplier innovativeness directly improves manufacturer innovativeness and indirectly enhances financial performance through manufacturer innovativeness. Customer coordination and manufacturer innovativeness positively influence financial performance. This study contributes significantly to theories and practices of supply chain coordination.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: January 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 207〈/p〉 〈p〉Author(s): Jing Hu, Qiying Hu, Yusen Xia〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉We have observed four modes of cost reduction in supply chains from practice. In particular, considering a supply chain with one manufacturer and one retailer, we identify four modes: the manufacturer solely invests, the retailer solely invests, or both firms collaboratively or independently invest to reduce the manufacturer's production cost. A question that arises naturally is which one is preferred by the manufacturer, the retailer, and the chain. With iso-elastic demand being sensitive to retail price and sales effort, we define channel powers (in addition to cost factors) for both firms to characterize the firms' investments and identify the best mode. We show that both firms are better off by investing collaboratively rather than independently if and only if the two firms have comparable channel powers and comparable cost factors. Moreover, a firm prefers to invest by itself solely rather than invest by its partner or both firms collaboratively if and only if its cost factor is sufficiently smaller than its partner's. We apply our results to supplier development and get some new insights. As a byproduct, the retailer may get less from the chain profit, which contradicts the retailer-dominant property in the literature under consignment contracts with revenue sharing. Finally, we show that our results are robust to different contract forms and whether the two firms have symmetric or asymmetric impacts on cost reduction.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 206〈/p〉 〈p〉Author(s): Yunchao Zhang, Md Monirul Islam, Zeyi Sun, Sijia Yang, Cihan Dagli, Haoyi Xiong〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Onsite electricity generation system in manufacturing has been traditionally considered an effective backup energy source to support the manufacturing operations when external power is not available due to natural disasters and/or power blackouts. Recently, with the increasing concerns of climate change and environmental protection, the contribution of using onsite generation system (OGS) to the manufacturing end use customers when they enroll in specific electricity demand response programs has also been gradually recognized. In this paper, we investigate the cost-effective OGS sizing problem for manufacturing practitioners when participating in Critical Peaking Pricing (CPP) demand response program. A Mixed Integer Non-Linear Programming (MINLP) formulation is proposed to identify the optimal size and utilization strategy of the OGS, as well as the corresponding production plan of the manufacturing system to minimize the overall energy related cost. Linearization strategy and metaheuristic algorithm are discussed for solving the proposed formulation with a reasonable computational cost and a good solution quality. A case study based on a real auto component manufacturing system and an existing CPP program is implemented to examine the effects of the proposed model. The results show that when utilizing the OGS appropriately sized, the total electricity related cost of the manufacturing system can be significantly reduced when participating in the CPP program.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: January 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 207〈/p〉 〈p〉Author(s): Antonio C. Caputo, Girolamo Di Salvo〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In case of assemblies requiring a close fit, strict tolerances must be specified resulting in high manufacturing costs. In such cases, selective assembly may be adopted as a cheaper alternative to traditional interchangeable parts assembly. In selective assembly wider tolerances can be specified, thus reducing processing cost, and manufactured parts are sorted into groups by dimensions so that only parts from matching groups are assembled. The choice between selective and traditional assembly, however, requires comparing the cost of the two options, but literature is lacking as far as selective assembly cost models are concerned. In this paper a managerial economic model is developed to quickly compare cost of traditional and selective assembly in order to identify the lower cost option. The model includes machining and materials cost, including scrapped parts, as well as gauging/sorting cost and work in process holding cost. A sensitivity analysis as well as a numerical case study exemplifies model application also showing trade-offs between the relevant parameters.〈/p〉〈/div〉 〈/div〉