ALBERT

Description: 〈p〉Publication date: Available online 6 July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): W.W. Nasr, M.Y. Jaber〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Companies have to account for continuously evolving technologies that are driven by the consumer's appetite for new and innovative products, requiring them to modify their production systems to become flexible, where items do not have standard features and specifications. It is normal though that new products and processes would result in a considerable proportion of non-conforming items produced by the supplier and rejected by the buyer (a company). We consider a two-level joint production system that investigates the behavior of the supplier and the buyer's production systems. We assume that the proportion of non-conforming items produced by the supplier is a random variable whose mean and variance reduce due to learning effects. We examine investing in the supplier's process to speed up the learning process and propose a mathematical framework to quantify the effectiveness of an investment. Heuristics are developed to solve those mathematical models. We consider a finite planning horizon since products, today, have short lives, and we present a numerical study to show that the proposed action can be economically beneficial to the system.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 5 July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Philipp Wetzel, Erik Hofmann〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this paper, we examine the functional form of the relationship between working capital assets and corporate performance beyond the traditional single-company perspective. In particular, we explore how a focal company's adequate level of working capital is influenced by the presence of limited financial resources along the supply chain. Moreover, we investigate the performance impact of supply chain finance (SCF)-oriented working capital management (WCM) approaches. Based on the SCF-oriented school of thought, we subject propositions regarding the relationship between working capital and corporate performance from prior WCM research to explorative empirical testing. In doing so, we raise awareness of factors that have yet to be tested. We derive methodological implications for conducting interorganizational studies in the field of SCF and outline a future research agenda. The explorative results indicate (i) the existence of a profit-maximizing level of working capital, (ii) superior performance of companies adopting an SCF-oriented WCM approach, (iii) higher profit-maximizing levels of working capital for focal companies facing financially constrained supply chain partners, (iv) a positive performance impact of efficient inventory management, and (v) differentiated payment strategies toward up- and downstream supply chain partners.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 29 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Tsan-Ming Choi, Lipan Feng, Rong Li〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In platform operations for rental services, product information disclosure (supported by the blockchain technology) is critical to attract customers. By building a stylized duopoly basic analytical model, we conduct a game-theoretic analysis to explore the product information disclosure game between two rental service platforms. We derive the optimal level of product information disclosure and identify the theoretical conditions in which it is optimal to disclose or not to disclose information, which actually means two different types of supply chains. Under the basic model with the two competing platforms scenario, we uncover that from each platform's perspective, there exists a critical threshold on the proportion of information sensitive consumers in the market with which the platform can decide whether it is optimal to disclose product information or not. If the information auditing cost is sufficiently small, it is optimal for the platform to disclose the product information as much as possible. We find that when the product's rental service profit margin increases, the likelihood that both competing platforms will disclose information (including full information) for their products is higher. We also explore the impacts brought by product information disclosure on consumer surplus and seller benefits, and discuss the roles played by the blockchain technology. To check robustness of the results as well as to examine different supply chain configurations, we extend the analysis to the cases when (i) the platforms are risk averse in decision making, (ii) rather than selling the product, the seller (owner of the product to be shared) consigns the product to the platform and shares a revenue, (iii) there is a common rental service platform which receives and provides rental services for two substitutable products. We find that the core qualitative managerial insights remain valid in the basic and all the extended models. Managerial implications are discussed.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 29 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Kimitoshi Sato, Kenichi Nakashima〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In recent years, pay-per-use (PPU) services have been introduced that involve metered billing based on data collected from sensor devices. Although such a PPU service provides benefits to customers who are not planning to use the product frequently, the company is exposed to uncertainty regarding the amount of revenue that will be generated. This study examines the conditions under which a PPU service will be effective at increasing a firm's profit in the presence of uncertainty regarding customers' expected and actual usage frequencies. We consider two pricing problems. First, we formulate a single-period model for when the selling price of the product is given and derive an optimal PPU fee to maximize the expected profit. Then, we analytically show that the PPU service has higher profits than the case without the service when the actual usage is higher than the expected usage. Second, we formulate a joint pricing model in which the firm determines jointly the PPU fee and the selling price to maximize the expected profit. Then, we numerically show that the firm benefits from the PPU service when both the customers' valuation and the actual usage are high.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 1 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Xing Bao, Ali Diabat, Zhongliang Zheng〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this paper, we study the manager's decisions in mitigating the disruption of the operation system when its operating units (OUs) were crippled by the unexpected event. Manager's ambiguity in making decision during the recovery phase might rise in two aspects: first, the level of remaining OUs might fluctuate due to uncontrollable ripple effects, and second, the lack of sufficient historic disruption data. In this study, the ambiguous manager is described as the Choquet one whose ambiguity belief is represented by the Choquet expect utility. Through the single- and multi-periods recovery models, we show that the Choquet manager consistently procures more short-term OUs from his capacity-shared partners than the rational one, and tends to build a higher redundant inventory level in the pre-disruption phase. To investigate the impact of insufficient demand data on the decisions of the Choquet manager in the recovery phase, we adopt two Bayesian learning methods to dynamically update the ambiguity belief in a multi-periods setting: first, the Beta method (a parametric method), and second, the minimum relative entropy (MRE) method (a nonparametric, also a data-driven method). Numerical results present findings in three aspects: First, the MRE method provides more robust estimations than the Beta one, and hence, it leads to a lower disruption cost because of its better approximation to the distribution of the uncertainty. Second, the initial redundant inventory does not contribute as much to lower the disruption cost as shortening the recovery time. Third, there is an “〈em〉anchoring effect〈/em〉” when the manager's follow-up decisions are anchored on previous estimations of the uncertainties mean value.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 2 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Xinfang (Jocelyn) Wang, Jomon A. Paul〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper applies the concept of social cost (i.e., logistic, deprivation, and fatality costs) to analyze the optimal deployment time, location and capacities of stockpiles for Points of Distribution (PODs) in hurricane preparedness. We first propose a single-stage, adaptive robust model to determine the optimal deployment time, given the time-variant characteristics of hurricanes. The model is nested in an optimal stopping-time framework that captures the trade-offs between increasing deployment costs and reduced uncertainty as the hurricane approaches landfall. Once the optimal deployment time has been determined, we then propose a less conservative, two-stage robust optimization model with recourse actions to determine the PODs’ location, stockpile capacities and flow. Tested on a case study, results show that 1) a non-adaptive model leads to poor decisions about the optimal deployment time; 2) improperly modeled deprivation costs pose significant hidden risks to decisionmakers; 3) deprivation costs increase $3–5 for every dollar cut when the available budget is strictly binding; and 4) significant savings in social cost result from the wait-and-see strategy implemented through the two-stage robust model.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 16 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Luca Fraccascia, Devrim Murat Yazan, Vito Albino, Henk Zijm〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Sustainability of Industrial Symbiosis (IS) businesses plays a key role in supporting the circular economy. Industrial symbiosis networks (ISNs) can survive in the long run if they have high resilience to perturbations that lead to operational uncertainties. The literature highlights that the resilience of ISNs can be enhanced by ensuring high redundancy of IS relationships: accordingly, firms should exchange the same waste with more symbiotic partners. However, the impact of increasing redundancy on economic and environmental performance of IS has not been investigated so far. This paper proposes a theoretical framework to understand the effect of the redundancy strategy on the performance of companies involved in IS. Accordingly, the optimal redundancy strategy refers to an optimal number of partners to (from) which waste producers (users) should send (receive) wastes to maximize the IS performance. An agent-based model is designed to explore the proposed framework and an agent-based simulation is applied to a marble-concrete IS case. The analysis shows that the optimal redundancy strategy is influenced by the combined effect of waste market dynamicity and transaction costs, and is usually different when viewed from an economic versus an environmental perspective. The paper provides a theoretical contribution based upon the integration of operational aspects of IS with the redundancy concept in IS-based businesses. The adopted methodology is innovative as it integrates willingness to cooperate, bargaining power, and inter-company trust development into the business decision-making process. Finally, how to overcome trade-off challenges between environmental and economic performance is discussed from managerial and practical perspectives.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 8 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Jukka Partanen, Marko Kohtamäki, Pankaj C. Patel, Vinit Parida〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Organizational ambidexterity is the simultaneous act of exploiting existing competences and exploring new opportunities. Prior studies suggest that resource-constrained SMEs cannot successfully pursue simultaneous interorganizational ambidexterity but need to rely on functionally separated alliances (i.e., alliances based on their value chain function such as explorative R&D alliances or exploitative commercialization alliances) to achieve ambidexterity. Yet, others propose that ambidexterity can occur within the functional domain of a supply chain. We investigate the relationships among supply chain ambidexterity, network capabilities, strategic information flow, and firm performance. In a sample of manufacturing SMEs in Sweden, we hypothesize the direct association between supply chain ambidexterity and performance and the moderating effect of network capabilities and strategic information flow. By testing our hypotheses in a sample of 200 manufacturing SMEs, we show that supply chain ambidexterity decreases firm performance; however, network capabilities and strategic information flow with their supply chain partners help mitigate this negative relationship. The present study advances understanding of ambidextrous interorganizational collaboration and alliances in general and supply chain ambidexterity of manufacturing SMEs in particular. In contexts where supply chain ambidexterity is negatively associated with performance, network capabilities and strategic information flow may be necessary to lower the negative effects.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 7 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Ryosuke Tomohiro, Ikuo Arizono, Yasuhiko Takemoto〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this papers, we address a double samplimg 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.svg"〉〈mrow〉〈msub〉〈mrow〉〈mi〉C〈/mi〉〈/mrow〉〈mrow〉〈mi〉p〈/mi〉〈mi〉m〈/mi〉〈/mrow〉〈/msub〉〈/mrow〉〈/math〉 control chart. It is well known that a double sampling scheme can reduce average sampling number in comparison with a single sampling scheme in sampling inspection. However, it is complicated and difficult to design the double sampling 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.svg"〉〈mrow〉〈msub〉〈mrow〉〈mi〉C〈/mi〉〈/mrow〉〈mrow〉〈mi〉p〈/mi〉〈mi〉m〈/mi〉〈/mrow〉〈/msub〉〈/mrow〉〈/math〉 control chart because a judgment rule of the 2nd sampling stage depends on a record of 1st sampling stage. Therefore, this paper proposes a double sampling 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.svg"〉〈mrow〉〈msub〉〈mrow〉〈mi〉C〈/mi〉〈/mrow〉〈mrow〉〈mi〉p〈/mi〉〈mi〉m〈/mi〉〈/mrow〉〈/msub〉〈/mrow〉〈/math〉 control chart incorporating the feature that a judgment rule of 2nd sampling stage is independent of a record of 1st sampling. The design algorithm for the proposed double sampling 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.svg"〉〈mrow〉〈msub〉〈mrow〉〈mi〉C〈/mi〉〈/mrow〉〈mrow〉〈mi〉p〈/mi〉〈mi〉m〈/mi〉〈/mrow〉〈/msub〉〈/mrow〉〈/math〉 control chart is constructed by taking the economical operation of this control chart into the consideration. That is, the economic design of the double sampling 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.svg"〉〈mrow〉〈msub〉〈mrow〉〈mi〉C〈/mi〉〈/mrow〉〈mrow〉〈mi〉p〈/mi〉〈mi〉m〈/mi〉〈/mrow〉〈/msub〉〈/mrow〉〈/math〉 control chart is addressed. Through some numerical comparison, it has been confirmed that the proposed double sampling 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.svg"〉〈mrow〉〈msub〉〈mrow〉〈mi〉C〈/mi〉〈/mrow〉〈mrow〉〈mi〉p〈/mi〉〈mi〉m〈/mi〉〈/mrow〉〈/msub〉〈/mrow〉〈/math〉 control chart has an advantage in the expected total operating cost over the traditional single sampling 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.svg"〉〈mrow〉〈msub〉〈mrow〉〈mi〉C〈/mi〉〈/mrow〉〈mrow〉〈mi〉p〈/mi〉〈mi〉m〈/mi〉〈/mrow〉〈/msub〉〈/mrow〉〈/math〉 control chart.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 28 September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Maik J.A. Havinga, Bram de Jonge〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉We consider the cyclic patrolling repairman problem combined with condition-based preventive maintenance. In the traditional cyclic patrolling repairman problem, one repairman inspects and repairs a set of machines in a fixed sequence. We introduce the possibility of performing preventive maintenance on the machines based on condition information. In order to determine optimal policies, we provide a Markov decision process formulation of the problem. Furthermore, this Markov decision process is used to analyze the performance of a control-limit policy, which is a commonly used heuristic for condition-based maintenance problems. The control-limit policy significantly outperforms the traditional policy for the patrolling repairman problem with only corrective maintenance. The optimal policy uses a higher maintenance threshold for a machine if the repairman expects to be back at that machine quite fast, or if failure of another machine is imminent. The benefit of the optimal policy compared to the control-limit policy is largest for sufficiently detailed condition information, for relatively stable deterioration processes, and for medium corrective maintenance costs.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 6 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): J. Stip, G.J. Van Houtum〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉For advanced capital goods with high system availability requirements, it is common that all customers have service contracts with the Original Equipment Manufacturer (OEM). These service contracts include service level agreements on spare parts supply. The OEM operates a service network to support these logistic contracts. To determine spare parts stock levels the OEM needs to forecast spare parts demand. An important input for this forecast is the service Bill Of Material (BOM) per installed machine in the field, which specifies the applicable spare parts for a machine, and is usually derived from the machine configuration. Because of a growing installed base, increasing machine complexity, and an increasing number of machine variants, companies face a challenge in defining and maintaining machine configurations, which is why the service BOM is not always in line with the actual installed machine. An incorrect service BOM results in either a too low or a too high forecast for spare parts demand, and will result in under- or overstock.〈/p〉 〈p〉In this paper we study the service BOMs at ASML, a large OEM in the semiconductor industry. We develop a method to generate alerts for possible errors. This method builds on multiple sources of machine information. Our method was tested in a pilot study, and found to be very effective. 95% of the generated alerts were correctly triggered and did result in actions that improved the service BOM. As a result, the method has been implemented by ASML. By this method, ASML reduced spare part non-availabilities by approximately 4–5 percent per year.〈/p〉 〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 1 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Lijian Chen〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉We present an optimization-based method to evaluate the financial impact of denying boarding to the lowest-fare customers under airline network overbooking. Airlines are demanding quantitative support to evaluate the impact on revenue when facing the decision to deny boarding to customers. Although overbooking is a well-regulated operation for decades, it has drawn considerable criticism due to, at least partially, disagreement regarding compensation. Usually, airlines deny boarding to the lowest-fare customers to assure seat availability for customers in higher-paying booking classes. We model such an assurance by chance-constrained optimization, and we gain managerial implications for overbooking practices, for low-cost airlines in particular. We conclude that low-cost airlines are vulnerable regarding revenue growth under network overbooking in comparison to other airlines. We explore possible revenue-improving suggestions, which will ease the effects of network booking for airlines both analytically and numerically.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 1 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Peter-J. Jost, Theresa Süsser〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉In a game-theoretic model of mass customization, we integrate consumers into a manufacturer's production process and define the degree of company-customer interaction as level of mass customization. Adjusting an individually customized product to her preferences implies opportunity costs for the consumer. We study how the manufacturer's trade-off between diseconomies of scale and higher profit margins is affected by each consumer's trade-off between tailoring the product to her need and her interaction costs.〈/p〉 〈p〉Several key insights are offered: First, we find that the manufacturer finds it always optimal to offer customization and show how the optimal degree of customization is affected by the interplay of marketing and production factors. Second, we find that the degree of customization chosen by the manufacturer also maximizes consumer surplus so that customizing products is welfare enhancing. Third, we find that the manufacturer has an incentive to additionally offer a lower priced standard product given the costs of customization are sufficiently high.〈/p〉 〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 2 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Mohannad Kabli, Md Abdul Quddus, Sarah G. Nurre, Mohammad Marufuzzaman, John M. Usher〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The projected and current adoption rates of electric vehicles are increasing. Electric vehicles need to be recharged continually over time, and the energy required to ensure that is immense and growing. Given that existing infrastructure is insufficient to supply the projected energy needs, models are necessary to help decision makers plan for how to best expand the power grid to meet this need. A successful power grid expansion is one that enables charging stations to service the electric vehicle community. Thus, plans for power expansion need to be coordinated between the power grid and charging station investors. In this paper, we present a two-stage stochastic programming approach that can be used to determine a power grid expansion plan that supports the energy needs, or load, from an uncertain set of electric vehicles geographically dispersed over a region. The first stage determines where to expand the power grid, and the second stage determines where to locate charging stations. The key link between the first and second stage decisions is that charging stations can only be located in areas with sufficient power supply enabled by an expanded power grid. To solve the model, we utilize a hybrid approach that combines Sample Average Approximation and an enhanced Progressive Hedging algorithm. We enhance the Progressive hedging algorithm by applying rolling horizon and variable fixing techniques. To validate the proposed model and gain key insights, we perform computational experiments using realistic data representing the Washington, DC area. Our computational results indicate the robustness of the proposed algorithm while providing a number of managerial insights to the decision makers.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 26 March 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Paolo Roma, Umberto Panniello, Giovanna Lo Nigro〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this paper, we examine how the emergence of sharing economy platforms influences incumbents’ price responses. Grounding on the literature on price reactions to new entrants and on the unique characteristics of the sharing economy, we argue that the effect of the penetration of the sharing economy on incumbents’ prices is not straightforward, and actually depends on the type of incumbents as well as certain product/service offer characteristics. Indeed, relying on a large sample of hotel price offerings from the Italian market, we find that the effect of the growing relevance of the sharing economy (exemplified by Airbnb) on incumbents’ prices depends on the type of incumbents (low/medium-end versus high-end hotels) as well as on the accommodation period (weekend versus weekdays), and thus on the type of consumers looking for accommodation. Specifically, low/medium-end incumbents set lower prices in geographical areas where sharing economy has a higher penetration, but this occurs only for weekend accommodation search. In contrast, high-end incumbents tend to set higher prices in geographical areas where sharing economy has a higher penetration, irrespective of the accommodation period. We discuss the important implications of our findings for incumbents, sharing economy platforms, consumers, and policy makers.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 28 March 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Daniel Rodrigues, Rafael Teixeira, Jeff Shockley〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This research examines the role of the food inspection agency in detecting contamination among producers in the global beef supply chain, focusing on regulations and inspection practices for Brazilian beef slaughterhouses. Research on food safety has suggested that several factors, at both the agency and location levels, may explain the effectiveness of regulatory efforts to detect foodborne contamination in producer processes. In emerging economies, such factors may include the resources available to both the agency inspection units and the processing plants, the overall capacity utilization in the industry, the number of interactions between the inspection agency and the processing plants, and the heterogeneity of the slaughterhouses under a single inspection regime. Using regional inspection unit agency data from the state of Rio Grande do Sul in Brazil, we conduct a multilevel analysis of the agency and location factors that may reduce the number of localized contamination cases in the beef supply chain. Our evidence suggests that federal agency and local resource availability and the heterogeneity of the slaughterhouses under inspection are critical institutional factors for the effective regulatory control and detection of contamination incidents among beef source producers in Brazil. We draw on both institutional theory (DiMaggio and Powell, 1983, Zucker, 1987) and the extant food supply chain literature to explain our findings, and we offer some guidance for improving food safety in this critical food industry. Finally, we generalize our findings to other food inspection contexts and offer some ideas for further research.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 14 November 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Jafar Heydari, Kannan Govindan, Amin Aslani〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper addresses the problem of optimal and coordinated decision making for a three-tier dual-channel green supply chain (SC). In the investigated SC, the manufacturer produces a good with an arbitrarily green level and sells it to the distributor. The distributor has two choices: (1) selling product through a direct e-channel, or (2) selling product to a retailer. Demand in both e-channel and retail channel depends on price and green level of the product. The manufacturer, the distributor, and the retailer decide on the green level of product, the price in e-channel, and the retail price of the product, respectively. The problem is investigated in three different decision-making structures. At first, the open triad and the closed triad decision structures are analyzed and optimal decisions for all SC members are extracted. This study contributes to the literature by developing a coordinated, environmentally friendly decision model for a multi-tier dual-channel SC structure. According to the findings, compared to the open triad, the closed triad structure is profitable for the SC at the expense of one or more members, who will thus not adopt it. Secondly, a mathematical programming model, labeled as transitional model, is proposed to achieve coordination. The transitional triad guarantees the manufacturer's profit, while keeping customer prices lower and greenness higher than the open triad. The numerical studies and sensitivity analyses show that the proposed model not only is profitable for all SC members, but also increases green level of the product and reduces prices in both the e-channel and retail channel.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: April 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 210〈/p〉 〈p〉Author(s): David Bogataj, Daria Battini, Martina Calzavara, Alessandro Persona〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In Europe, the number of people aged 65 or older is about to grow from 85 million today to more than 151 million in 2060, with a decrease of 20 million in the number of workers. To keep the public finances and pension funds sustainable, the retirement age of industrial workers in national pension schemes is rising. However, workers in some specific workplaces are not able to work until they have reached the increased retirement age. Often they are producing fewer products, in some workplaces also with lower quality, and they are causing substantial delays in the multi-echelon system mostly because of response latency. On the other hand, value-added, personalised products/services often demand skilled and experienced older workers, who need better ergonomic support. To solve this problem, companies have two options: (a) to develop new supplementary occupational pension schemes which would compensate the required increase in retirement age or (b) to invest in ergonomic improvements of the working places/processes, to provide a better working environment and reduce the response latency. In this paper, the trade-off between these two options is investigated, by introducing a model based on MRP theory for evaluating the Net Present Value (NPV) of activities and investments of a multi-echelon system. The numerical example related to the production of cars in Italy shows that even varying the cost of labour and the investment in collaborative robots, the model demonstrates that investments in ergonomics in case of ageing workforce increases the total NPV of the multi-echelon system.〈/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): Mlouka Farhat, Ayse Akbalik, Atidel B. Hadj-Alouane, Nathalie Sauer〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉We study the deterministic single-item lot sizing problem with batch ordering under the buyback contract (LSP-BB) in a system with one retailer and one supplier. We consider a fixed cost per batch replenished in addition to the classical lot sizing costs, making the procurement cost structure stepwise. We also consider lost sales option with a lost sales cost incurred for each unit of demand not satisfied. The buyback contract considered here consists in returning unused units at the end of every 〈em〉w〈/em〉 periods, with a buyback revenue for each unit returned back. We study this problem under both FTL (full truck load) cost structure and only full batch replenishment assumption. We propose efficient and exact polynomial time algorithms for different extensions of this problem which is known to be NP-hard in the general case. To the best of our knowledge, it is the first time that the buyback contract is introduced in a multi-period lot sizing problem (LSP) in the literature. Moreover, batch ordering and lost sales issues have never been tackled in the same LSP model before our study. Hence, this paper provides efficient algorithms to solve the LSP with batch ordering and lost sales under the buyback contract not yet addressed in the literature.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 212〈/p〉 〈p〉Author(s): Leila Schwab, Stefan Gold, Gerald Reiner〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The purpose of this pa\per is to understand the impact of financial key performance indicators (KPIs)—namely customer accounts receivable flow time and credit limit allowed by financial partners—on the financial sustainability of small and medium sized enterprises (SMEs) during business growth trajectories from an operations management perspective. This study explores the impact of a financing scheme on company performance during business growth, since new banking constraints for credit risk reduction have been introduced (such as BASEL III regulations). Based on qualitative and quantitative data from a longitudinal empirical case study of a Swiss family-owned SME during a phase of intense growth, we have built a simulation model by combining agent-based with system dynamics modelling that comprehensively represents the growing firm, its decision-making, and enables the impact evaluation of relevant financial KPIs on financial sustainability. Our analysis shows that the baseline scenario entails 80% risk of bankruptcy for high-growth SMEs; featuring 30 days customer accounts receivable flow time target and a credit limit allowed by the financial partner of 25% of last period turnover. However, if customer accounts receivable flow time is reduced to ten days, and credit limit increased to 65% of last turnover, the risk of bankruptcy drops to 30%. Our findings point to the detrimental unanticipated side effects of macro-level banking regulation on micro-level firm performance, and hence have implications for policy-making. Moreover, our study guides managers and financial service providers in anticipating risky situations, and in taking corrective actions by effectively managing financial KPIs.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: May 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 211〈/p〉 〈p〉Author(s): Mohsen Reisi, Steven A. Gabriel, Behnam Fahimnia〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉We develop a bilevel optimization model with two manufacturers at the top level and a common retailer at the bottom level to analyze the merits of integrated vs. non-integrated supply chains. The resulting model is an instance of an equilibrium problem with equilibrium constraints (EPEC), a notoriously computationally challenging model to solve. We provide a closed-form expression for the approximate solution to the lower-level problem determining the retail prices and the allocated shelf spaces. This solution then is incorporated into the manufacturers' profit resulting in a single-level optimization problem which is easier to solve. Numerical results from a real soft drink supply chain involving two beverage suppliers selling their major products through a common retailer shows the applicability of the proposed model for supply chain planning. We then analyze the integrated model where the manufacturers and the retailer work together to maximise profit without any competition between the manufacturers. Comparing the profits in the integrated and non-integrated supply chains finds that centralization benefits all of the players if the two brands are almost identical, but it hurts the weaker brand if the two brands exhibit different characteristics in terms of costs or brand loyalty. In addition, we run several sensitivity analyses with regard to variations in the exogenous parameters including the price and shelf-space elasticities and explore the changes in the profits in both non-integrated and integrated supply chains.〈/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): Muhammad Shafiq, Matteo M. Savino〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this study a commitment-based revenue-sharing and penalty model is proposed to coordinate a supply chain with one manufacturer and a retailer facing stochastic demand. Because of short time to respond to demand and long capacity procurement lead time, the manufacturer needs to procure capacity in advance. As capacity procurement involves monetary investment, it may lead to under-estimation if the risk has to be solely borne by the manufacturer. In contrast, the approach developed within this study induces the retailer to commit not less than the expected demand. At the same time, under-purchase penalty is also introduced to avoid over-commitment. Furthermore, as regards to the existing contract approaches, the retailer is provided of a certain flexibility in terms of under-purchase penalty to avoid transferring the whole demand uncertainty risk on the retailer. On the other hand, the manufacturer is also motivated to produce more through reward in terms of higher revenue percentage for the products demanded more than the commitment. The proposed model is compared with those models based on prevailing revenue-sharing with penalty contracts, in terms of commitment and capacity procurement decisions. Numerical experiments and sensitivity analysis are presented to demonstrate the usefulness of the model and the relative managerial insights.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 14 September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Daqing Gong, Shifeng Liu, Jun Liu, Long Ren〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The growth of sharing economy platforms is reshaping the boundaries between different market participants and leading to the development of innovative business models, raising numerous questions for both academics and practitioners. In this paper, we consider an online sharing economy system consisting of a powerful e-tailing platform and a budget-constrained small and medium-sized seller (SMS). As a reflection of the current practices adopted by Amazon and Tmall, the seller and platform engage through a consignment revenue-sharing contract, whereby for each successful sale, the platform takes a predetermined cut of the sales revenue. Due to factors such as information asymmetry and high degrees of operational risk, the SMS cannot usually access commercial banking loans, thus lacking working capital for further growth. To bridge this liquidity gap, an innovative financing scheme called platform-based financing has been launched by platforms to alleviate the financing issues that SMSs face. We establish a theoretical model to investigate the value of this innovative platform-based financing scheme and present several findings. First, we show that the optimal sales price can decrease when budget constraints exist. Second, we identify a threshold under which an SMS should accept a loan. Third, a platform should always provide financial aid to a seller who is short on funds, which always benefits the platform itself. Moreover, we show that both a seller and a platform will benefit from this innovative financing plan, improving the performance of the online sharing economy.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 11 September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Muzaffer Alım, Patrick Beullens〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper develops a strategy to jointly optimize the inventory and distribution for an online sales firm. The firm has to decide how to distribute the products from its warehouse to customers: this can either be done by using a company-owned vehicle, or by outsourcing to a third-party transportation company. The online sales environment includes a flexible delivery option that gives a discount to customers in return. This option is offered when the inventory level in the warehouse is lower than a threshold level. Customers accepting flexible delivery pay a deposit at the time they place the order and pay the remaining reduced price at the time of delivery. By offering the flexible delivery option, the firm aims to reduce the cost of distribution to the customers as well as postpone the timing of paying an outside supplier for stock replenishment. Additionally, this allows the firm to use on hand stock effectively to respond to more urgent customer requests. As the timing of cash-flows are dependent on the customer behaviour and the inventory and distribution strategy, the profit function is the Net Present Value of future cash-flows. We analyze the benefit of flexible delivery to the firm and perform sensitivity analysis with respect to various parameters. The profitability of flexible delivery depends on price setting and customer behaviour. Flexible delivery, in this model, has great potential to reduce transport distances and emissions when firms use their own vehicles.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 10 September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Nahid Jabarzare, Morteza Rasti-Barzoki〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this study, a dual-channel supply chain (SC) comprising one manufacturer and one packaging company is considered under price and quality dependent demand. The manufacturer and packaging company compete on offered selling price and quality decisions. For the first time, this study investigates how the packaging company can influence the quality of products through packaging products. We also analyze how different game structures affect the optimal pricing and quality decisions as well as SC members' profit. In doing so, we model the investigated SC under three scenarios: (1) non-cooperative game, (2) cooperative game through revenue-sharing contract, and (3) cooperative game through profit-sharing contract. The results show that the competitive game of manufacturer and packaging company is highly beneficial for price-seeking customers. Moreover, from quality-seeking customers’ perspective, the cooperation of manufacturer and packaging company under profit-sharing contract is more preferable. Furthermore, when the customers' demand is highly sensitive to the products quality, the cooperation of manufacturer and packaging company through profit-sharing contract is more beneficial for them.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 2 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Xin Wen, Tana Siqin〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The sharing economy is of increasing importance for various aspects of our society by providing people with cost-efficient and convenient access to services or products. However, the profitability and healthy development of the sharing economy platforms are greatly restricted by the intensive uncertainties arising from product quality. How to determine the optimal product quality improvement efforts and the optimal prices for the sharing platforms becomes crucial. Moreover, it is reasonable that many sharing economy platforms and consumers are holding a risk-averse attitude during decision making in the highly volatile market. In this paper, we employ the Mean-Variance theory to model the risk-averse attitudes of decision makers, and analytically derive the optimal average quality levels and prices that the platform should provide for the market. We also explore how the critical factors like product quality uncertainty and risk sensitivity affect the platform's equilibrium decisions and consumer surplus. Our analytical results reveal the importance of reducing the difficulty of improving product quality for enhancing the platforms' profitability and consumer surplus. Besides, we identify that it is not always wise for platforms to invest in improving product quality, especially when the related cost becomes increasingly expensive. Moreover, it is shown that the increasing risk aversion or product quality volatility will induce the platform to reduce his quality improvement efforts. Finally, we interestingly find that the platform will always suffer if he becomes risk averse from risk neutral, while consumers may benefit from this attitude change.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 11 October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Abolfazl Gharaei, Eman Almehdawe〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The essence of some items is continuously growing and gaining weight over time. These are known as growing items, which their weights and values increase over time. This paper provides a new generation of inventory models, entitled Economic Growing Quantity (EGQ), which is designed by focusing on growing items of agricultural industries such as fisheries, poultry, and livestock. Our EGQ inventory model considers the probability density functions of survival and mortality for a growing item. It also considers the growth functions of live and dead grown items. Accordingly, the total cost for EGQ model consists of the costs of purchasing process, the disposal cost of dead items, the holding cost, the feeding cost, and the setup costs for both the live and the dead items. Our goal is to determine the optimal economic growth/slaughter cycle and the economic growing quantity in order to minimize the total costs. Subsequently, we optimize the weight of slaughtering, the Utility of Growth Functions (UGF), and other important performance metrics of the system. The applicability and validity of our model is demonstrated based on numerical examples of the poultry industry. The results of sensitivity analyses recommend some strategic implications and insights for the managers of growing items.〈/p〉〈/div〉 〈/div〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉The optimal status of the EGQ inventory system, when 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.svg"〉〈mrow〉〈mi mathvariant="normal"〉G〈/mi〉〈mrow〉〈mo〉(〈/mo〉〈mrow〉〈mi mathvariant="normal"〉t〈/mi〉〈/mrow〉〈mo〉)〈/mo〉〈/mrow〉〈mo linebreak="goodbreak" linebreakstyle="after"〉≠〈/mo〉〈mi mathvariant="normal"〉V〈/mi〉〈mrow〉〈mo〉(〈/mo〉〈mrow〉〈mi mathvariant="normal"〉t〈/mi〉〈/mrow〉〈mo〉)〈/mo〉〈/mrow〉〈/mrow〉〈/math〉.〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S092552731930338X-egi10DC0HV6R5P.jpg" width="471" alt="Image 10065" title="Image 10065"〉〈/figure〉〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 7 October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Xin Li, Jose A. Ventura〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper considers the scenario where a manufacturer receives multiple orders that are characterized by the revenue, processing time, due date, and tardiness penalty per time unit. The manufacturer can be seen as a single-machine system that adopts a make-to-order strategy. Due to the capacity limitation and tardiness penalty, the manufacturer cannot accept all orders. It needs to determine the optimal set of accepted orders and the corresponding production schedule that maximizes the total revenue minus tardiness penalty. Three different mathematical formulations are presented to model the problem: sequential relation-based formulation (SBF), assignment formulation (ASF), and time-index formulation (TIF). The first two models use both continuous and binary variables while (TIF) only uses binary variables but requires order processing times to be integer. Three exact algorithms are proposed to solve the problem. The first algorithm, denoted by DPA, follows a pure dynamic programming (DP) approach. The second algorithm, denoted by DPIA-SR, solves the problem in multiple stages. In the first stage, it solves a relaxed version of (TIF) using DP; then, in the following stages, the relaxed constraint is gradually recovered, and the resulting models are solved using DP until an optimal solution to the original model is found. The results of one stage are used to eliminate unnecessary states in the DP algorithm for the next stage. The third algorithm, denoted by DPIA-LRSR, improves DPIA-SR by incorporating Lagrangian relaxation to achieve higher computational efficiency. The numerical experiment shows that, when using CPLEX to solve the models, (ASF) and (TIF) take much less CPU time than (SBF); the last two algorithms and their variations significantly outperform CPLEX regarding computational time; and DPIA-LRSR shows the highest efficiency.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 7 October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Ming-Lang Tseng, Kuo-Jui Wu, Anthony SF. Chiu, Ming K. Lim, Kimhua Tan〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Sustainable product service systems enable firms that are operating under resource limitations to deliver the best possible outcomes in terms of social well-being and economic growth. However, prior studies have not yet investigated the function of service innovation in sustainable product service systems or analyzed the convergence of importance and performance weighting in maximizing resource utilization in the supply chain. Moreover, prior studies have not yet integrated and proposed a complex interrelationship-driven hierarchical model including qualitative preferences or identifying weighting under linguistic preferences. This study applied the fuzzy Delphi method, fuzzy importance performance analysis and an analytical network process to analyze an interrelationship-driven hierarchical model of service innovation in sustainable product service systems. Hence, this study provides a set of attributes and a hybrid method to assess the model as well as linguistic preferences to weight the importance and performance measures. The results present four features that are included in the model: sustainable consumption, collaborative advantage, innovation activities and service innovation capabilities. Therefore, when building sustainable product service systems, firms should maintain operations and aim for business synergy in self-generated innovative products/services along with high-quality products/services, collaboration innovation and product and service innovations. Managerial and theoretical implications are discussed.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 3 October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Yoshinori Suzuki〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Material convergence (MC) in humanitarian logistics refers to the movement of relief supplies from donor sites to distribution centers in disaster areas, from which the final deliveries are made to survivors (last-mile distribution). We investigate how the choice of MC strategy (approach) affects the effectiveness of last-mile distribution. Specifically, we investigate the relative performance of the two frequently used MC approaches in terms of their ability to facilitate (propel) effective last-mile distribution. These two approaches are: (1) 〈em〉p〈/em〉–method (in which the most-urgent material always flows into disaster areas first) and (2) 〈em〉m〈/em〉–method (in which every shipment bound to disaster areas is comprised of a mix of urgent and less-urgent materials). We first analyze advantages and disadvantages of each approach from the theory perspective, and then perform numerical experiments to examine the specific conditions under which each approach performs most, or least, effectively. Results indicate that, in 83.3% of cases, the 〈em〉m〈/em〉–method (less widely used approach in practice) works more effectively than the 〈em〉p〈/em〉–method (more widely used approach).〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 1 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Alok Raj, Gourav Dwivedi, Ankit Sharma, Ana Beatriz Lopes de Sousa Jabbour, Sonu Rajak〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper examines barriers to the implementation of Industry 4.0 technologies in the manufacturing sector in the context of both developed and developing economies. A comprehensive literature review, followed by discussions with industry experts, identifies 15 barriers, which are analyzed by means of a Grey Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach. The ‘lack of a digital strategy alongside resource scarcity’ emerges as the most prominent barrier in both developed and developing economies. The influencing barriers identified suggest that improvements in standards and government regulation could facilitate the adoption of Industry 4.0 technologies in developing country case, whereas technological infrastructure is needed to promote the adoption of these technologies in developed country case. This study is one of the first to examine the implementation of Industry 4.0 in both developing and developed economies. This article highlights the difficulties in the diffusion of technological innovation resulting from a lack of coordinated national policies on Industry 4.0 in developing countries, which may prevent firms from fully experiencing the Industry 4.0 revolution. The results of this study may help decision makers and practitioners to address the barriers highlighted, paving the way for successful implementation of Industry 4.0 across the manufacturing sector.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 1 November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Bianca Maria Colosimo, Simona Cavalli, Marco Grasso〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The paper presents a cost model to evaluate the economic impact of defects and process instability in metal Additive Manufacturing (AM). The proposed model formulation adopts the main framework of previous seminal studies and extends it by considering the contribution of scrap fractions and in-situ monitoring performances on process and material costs, including pre- and post-processing operations. Three real industrial case studies (from dental, aerospace, and machinery sectors) were assessed to determine how the model can be used in the real industrial practice to (i) enhance the economic advantages of metal AM technologies by tackling process instability issues, (ii) assess the effectiveness of in-situ monitoring in the development of next generation metal AM systems, and (iii) define the performance specifications of in-situ monitoring solutions that yield sustainable cost savings in specific industrial applications. A further experimentation is presented to validate the cost model with respect to a benchmark reference.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 213〈/p〉 〈p〉Author(s): Saeed Zamanzad Gavidel, Jeremy L. Rickli〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Extremely large core returns can destabilize remanufacturing systems and is reported as a nuisance for remanufacturers. In this paper, extreme core returns are targeted by investigating the Operation Transition Threshold (OTT) criterion that signals a remanufacturing system's transition from normal operation mode to extreme operation mode. The threshold parameter of the Generalized Pareto Distribution (GPD) is used to signal this transition. The threshold of the GPD can be estimated by different statistical techniques that return different thresholds that can impact the performance of remanufacturing systems. To investigate the OTT of remanufacturing systems, candidate OTTs are first estimated by statistical techniques, then, using vote-counting, proper OTT(s) are identified. Finally, the efficiency of the statistical analysis and effectiveness of the estimated OTTs is validated by remanufacturing system technical requirements. A case study is presented that focuses on remanufacturing end-of-use industrial valves returning to valve shop of a chemical complex. The devised approach is applied to analyze the potential impacts of different OTT estimators on remanufacturing operations. Results of this work indicate that choosing improper OTTs can impose heavy costs on the remanufacturing system. Thus, the OTT can be a critical remanufacturing system parameter should extreme scenarios be a possibility.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 12 March 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Seyyed-Mahdi Hosseini-Motlagh, Kannan Govindan, Mohammadreza Nematollahi, Abbas Jokar〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Recently, significant research attention has been paid to supply chain (SC) coordination. However, previous studies assume that the market demand is deterministic or has a certain probability distribution. Taking a new approach, this paper analytically addresses the coordination of an SC under a scenario-based demand and proposes an adjustable bi-level wholesale price contract. To analyse the coordination problem under a scenario-based demand, we focus on corporate social responsibility (CSR) investment as an important decision in the SC context and consider a three-tier SC (one manufacturer, one distributor, and one retailer) where the retailer faces a scenario-based stochastic CSR-sensitive demand. Considering a manufacturer-Stackelberg game model, the manufacturer as a leader determines the amount of investment in the CSR issues and the retailer as a follower decides on the order quantity by considering possible demand scenarios. First, we propose the decentralized and centralized decision-making models using a scenario-based approach. Afterward, to resolve the channel conflict in each possible demand scenario, an adjustable bi-level wholesale contract is proposed to entice all SC actors to take part in the coordination scheme. Moreover, a profit-sharing plan is developed based on the Nash-bargaining model to fairly share the extra profits among SC actors. Finally, in order to analyse the efficacy of proposed models, a numerical example and a set of sensitivity analyses are carried out. The results indicate that the proposed contract not only coordinates the three-level SC under a scenario-based stochastic demand, but also improves the CSR level in comparison with the decentralized structure.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 213〈/p〉 〈p〉Author(s): Tsan-Ming Choi, Shu Guo, Na Liu, Xiutian Shi〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉For many food products, such as fresh vegetable and fruit, proper handling of product leftovers is critical. In recent years, food leftover sharing (FLS) platforms that can provide a means to collect the unsold food products from individual retailers and create values from them have emerged. Motivated by this real world observation, we build a single supplier multi-retailer analytical supply chain model to explore the value of this kind of FLS platform. In the decentralized supply chain setting, we prove that the presence of FLS platform is beneficial to the retailers, the supplier, the consumers and the environment. Whether it benefits the supply chain economically depends on the logistics costs (incurred from the food product leftover collection by the FLS platform). We extend the analysis to the case with a centralized supply chain and show that the FLS platform is guaranteed to help improve the environment, but the consumers and the supply chain are only benefited when the logistics costs are sufficiently small. Sensitivity analyses are conducted which show that for both centralized and decentralized supply chain settings, the FLS platform is especially helpful in enhancing social welfare when the unit food product leftover cost is higher, the unit benefit derived from reusing the food product leftovers is higher, or the unit logistics cost is lower. We further consider the case when the logistics cost with the use of platform is high and propose the use of government sponsors to help and provide the conditions under which this sponsor is well-justified with respect to social welfare enhancement.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 213〈/p〉 〈p〉Author(s): Uğur Özcan〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Parallel assembly lines are special flow type production systems where two or more neighbouring assembly lines are balanced together. In some industries such as automobile and household appliances industries, neighbouring lines are frequently used. In parallel assembly lines, a setup can be defined as a set of activities to perform a task, such as movements, selecting a new assembly tool and/or taking a position in order to using the most suitable installation procedure. Setups in a workstation on the same line may occur in two ways; forward setup and backward setup. And also, a setup in a workstation on two neighbouring lines may occur. In this study, this is named as line-switching setups. In this paper, the problem of balancing and scheduling tasks in parallel assembly lines with sequence-dependent setup times (PALBPS) is introduced and characterised. A binary linear mathematical programming (BLP) model and a simulated annealing (SA) algorithm are proposed to model and solve the PALBPS. A computational study is performed in order to test the proposed SA algorithm. The computational results show that the proposed algorithm is very effective and successful for the PALBPS.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 6 March 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Meng Wu, Stuart X. Zhu, Rudd H. Teunter〈/p〉

Description: 〈p〉Publication date: July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 213〈/p〉 〈p〉Author(s): Qinghua Zhu, Kee-hung Lai〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Extending corporate social responsibility (CSR) to manage global supply chains has become strategically important for multinational enterprises (MNEs) to keep long-term relationships with suppliers in emergent countries. However, whether and how suppliers in developing countries respond to pressures from MNEs for CSR practices is lacking related studies. Built on the value of formal control through contracts and monitoring for diffusing CSR practices, this study further argues that evolving relational ties, which usually happen in multi-periods, with MNEs at both corporate and individual levels can be helpful or even necessary for suppliers to implement CSR practices from the social capital and guanxi theory perspective. Using survey data collected from 211 suppliers of MNEs in China, which is an emergent country characterized with the world's largest supplier base servicing MNEs, our hierarchical regression analysis demonstrates that relational ties including reciprocity, cooperation, and interaction at the corporate level have mediation and moderation effects on the formal control-CSR practices implementation link for these suppliers. Furthermore, personal trust is important and even necessary to motivate CSR practices implementation among the Chinese suppliers. Researching CSR from the supplier perspective, this study contributes new theoretical insights for MNEs to cultivate relational ties with their emergent-country suppliers in support of their formal control for CSR practices adoption by the latter.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 212〈/p〉 〈p〉Author(s): Livio Agnew Bacci, Luiz Gustavo Mello, Taynara Incerti, Anderson Paulo de Paiva, Pedro Paulo Balestrassi〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper proposed a new multi-objective approach to find the optimal set of weight's combination of forecasts that were jointly efficient with respect to various performance and precision metrics. For this, the residues' series of each previously selected forecasts methods were calculated and, to combine them through of a weighted average, several sets of weights were obtained using Simplex - Lattice Design {m,q}. Then, several metrics were calculated for each combined residues' series. After, Principal Components Factor Analysis (PCFA) was used for extracting a small number series' factor scores to represent the metrics selected with minimal loss of information. The extracted series' factor scores were mathematically modeled with Mixture Design of Experiments (DOE-M). Normal Boundary Intersection method (NBI) was applied to perform joint optimization of these objective functions, allowing to obtain different optimal weights set and the Pareto frontier construction. As selection criteria of the best optimal weights' set were used the Shannon's Entropy Index and Global Percentage Error (GPE). Here, these steps were successfully applied to predict coffee demand in Brazil as a case study. In order to test the applicability and feasibility of the proposed method based on distinct time series, the coffee's Brazilian production and exportation were also foreseen by new method. Besides, the simulated series available in Montgomery et al. (2008) were also used to test the viability of the new method. The results showed that the proposed approach, named of FA-NBI combination method, can be successfully employed to find the optimal weights of a forecasts' combination.〈/p〉〈/div〉 〈/div〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0925527319300878-fx1.jpg" width="358" alt="Image 1" title="Image 1"〉〈/figure〉〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 13 March 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Yan Shuang, Ali Diabat, Yi Liao〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Carbon emission control policies have emerged in response to the growing global concerns of environmental problems. These regulations should to be considered when operational level decisions on production, inventory, and routing are being made as emissions cost is incurred. In this study, we consider a reverse logistics supply chain model with remanufacturing options under different carbon emission control policies. We aim at selecting the optimal carbon control policy to follow along with optimal production, inventory, and delivery quantities under the selected carbon control policy. We provide a mathematical formulation of the problem that considers heterogeneous transportation fleets and allows for lost sales. The proposed mathematical model is provided in a deterministic and in a two-stage stochastic version to account for demand uncertainty. Proposed formulations are demonstrated through two case studies, a simulated reverse logistics supply chain and a real home appliances production supply chain with remanufacturing options. Model sensitivity analyses to test for the effect of modeling parameters on the optimal solution are illustrated. Results indicate that the carbon policy selected has significant effect on the supply chain performance with carbon price being the most significant parameter.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 11 March 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Roberto Ivo da Rocha Lima Filho〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The main question of the paper is to add an additional explanation to an economic empirical causality between PPI (Producer Price Index) and CPI (Consumer Price Index), that is, does PPI’s final stage of processing, also known as final goods, is a lead indicator for the CPI in the Brazilian economy? If so, how strong or weak this relationship is? Is there a one-way or two-way causality? How does exogenous shocks affect both variables in terms of future trajectories? This is analysed empirically through a traditional VAR (Vector Autoregressive) and BVAR (Bayesian Vector Autoregressive) models so as to understand the dynamics of both PPI and CPI - inertial and principal components - and also out-of-sample forecasting. We conclude that it can be verified that PPI final goods can be a good leading indicator for the domestic CPI , purging ex - in natura foods.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 11 March 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Xun Xu, Jonathan E. Jackson〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The ever-evolving omni-channel retail environment provides customers with a variety of channels to select from when making purchases and returns. Despite the growing number of product returns, there is limited research that focuses on customers’ perception of the return process in an omni-channel retail environment. To fill this gap, via an empirical analysis, this paper examines the influential factors on customers’ return channel loyalty. Our structural equation modeling results found that perceived risk, purchase-return channel consistency, monetary cost, and hassle cost influence customers’ return channel loyalty. Comparatively, perceived risk has the highest impact on customers’ return channel loyalty. Additionally, hassle cost has more influence than monetary cost on customers’ return channel loyalty. We also found that both internal (ambiguity tolerance, patience, and familiarity) and external (return policy flexibility) factors influence customers’ perceived risk. Comparatively, channel familiarity has a higher influence on reducing customers’ perceived risk compared with patience and the channel’s return policy flexibility. Understanding customers’ perceptions of a return channel is the first step in the implementation of an effective return management strategy in an omni-channel retail environment. This first step will provide retailers with opportunities to better understand the needs of targeted customers, offer improved post-sales services, and optimize their handling of product returns.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 9 March 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Xiaofan Lai, Yi Tao, Fan Wang, Zongbao Zou〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉To comply with the stricter emission control regulations of recent years, shipping carriers, who may be risk averse, need to make decisions regarding their investments in environmental sustainability before market uncertainty is realized. The ports, as service providers of the carriers, may help the carriers on making such decisions through sharing market forecast information. In this study, we aim to examine the incentives of forecast information sharing from port and the effect of carrier's risk behavior on such sustainability investment decisions in a maritime supply chain. For this, we propose a two-period game-theoretic model framework. In this framework, both the port and the carrier face market uncertainty during the first period. The port determines whether to share its market forecast information with the carrier, and the carrier needs to decide her sustainability investment level. Then, in the second period, the port determines the service fee, and the carrier determines the freight rate to the customers. We analyze four different scenarios, based on the types of carrier's risk behavior and on whether the port decides to share the forecast information.〈/p〉 〈p〉We find that the relationship between sustainability investment level, and the port's service fee/the carrier's freight rate can be either positive or negative. We also show that the risk averse behavior reduces the carrier's profit, and lowers the level of sustainability investment, which in turn either positively or negatively influences the carrier's freight rate as before. Interestingly, the risk averse behavior always lowers the port's service fee. Moreover, we find that the forecast sharing from the port can not only improve the profits for both parties, but also facilitate the sustainability investment, even when the carrier is risk averse. We also find that the port always receives a larger percentage of the profit than the carrier.〈/p〉 〈/div〉 〈/div〉

Description: 〈p〉Publication date: June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 212〈/p〉 〈p〉Author(s): Peter Köchel, Bernd Kirstein〈/p〉

Description: 〈p〉Publication date: Available online 20 March 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Patricia Rogetzer, Lena Silbermayr, Werner Jammernegg〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Critical raw materials like rare-earth elements are essential inputs for the production process of many electronic products, but also for environmentally-friendly green-energy technology products. The market for these materials faces high uncertainty associated with their supply. The use of recovered raw materials can help to mitigate the risk and simultaneously pave the way towards a circular economy. We investigate a sourcing strategy faced by a manufacturer considering the possibility to source critical raw materials from a supplier offering recycled material. As the recycling efficiency of these materials is still an ongoing research, and return flows from end-of-life products are highly volatile, we also rely on virgin material. We develop a single-period inventory model with procurement from a supplier offering recycled material according to a capacity reservation contract and a reactive supplier (spot market) offering virgin material. We consider uncertainties of demand, prices and recycling quantities as well as potential dependencies, in particular dependencies between prices for virgin and recycled materials and prices and demand. We provide results on the optimal policy structure and obtain a closed-form solution as a bound of the optimal procurement quantity. Our analysis gives us first insights on the effect of different economic parameters on the ordering decision. In an extensive numerical analysis we then study the impact of correlation on our results in order to derive managerial implications. We show that considering correlation when using such a sourcing strategy is especially important in environments with high demand uncertainty, high virgin material prices and yield uncertainty.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 213〈/p〉 〈p〉Author(s): Sarah Van der Auweraer, Robert Boute〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉We focus on the inventory management of critical spare parts that are used for service maintenance. These parts are commonly characterised by a large variety, an intermittent demand pattern and oftentimes a high shortage cost. Specialized service parts models focus on improving the availability of parts whilst limiting the investment in inventories. We develop a method to forecast the demand of these spare parts by linking it to the service maintenance policy. The demand of these parts originates from the maintenance activities that require their use, and is thus related to the number of machines in the field that make use of this part (known as the active installed base), in combination with the part's failure behaviour and the maintenance plan. We use this information to predict future demand. By tracking the active installed base and estimating the part failure behaviour, we provide a forecast of the distribution of the future spare parts demand during the upcoming lead time. This forecast is in turn used to manage inventories using a base-stock policy. Through a simulation experiment, we show that our method has the potential to improve the inventory-service trade-off, i.e., it can achieve a certain cycle service level with lower inventory levels compared to the traditional forecasting techniques for intermittent spare part demand. The magnitude of the improvement increases for spare parts that have a large installed base and for parts with longer replenishment lead times.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 25 June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Sobhan Asian, Ashkan Hafezalkotob, Jubin Jacob John〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Increasing operational and logistical costs, lower yields, and market barriers adversely impact the competitiveness of organic farmers compared with conventional food producers in developing countries. While agricultural cooperatives have recently gained significant popularity in organic food supply chains (OFSCs), there remains a considerable degree of skepticism regarding their contributions toward sustainable development. The current study investigates the role of the sharing economy (SE) in enabling organic smallholders to overcome their specific set of challenges by sharing resources and aggregating peer-to-peer activities using an SE-based cooperative platform. Using a cooperative game theory (CGT) modelling approach, we jointly address the production-inventory planning and pricing problems of multiple competing OFSCs in two scenarios: the non-cooperative (benchmark) and the SE-based cooperative. We present a novel solution algorithm to solve the formulated mathematical models and to characterize the behavior of key decision-makers. After computing the coalitional synergy achieved with the SE-based mechanism, we implement different CGT models to fairly distribute the generated profit among OFSC coalition members. The results reveal that, if designed and implemented appropriately, the proposed SE-based mechanism is capable of concurrently delivering greater financial gains with higher sustainable development benefits due to its underlying innovative peer-to-peer sharing features.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 214〈/p〉 〈p〉Author(s): Xin Wang, Zhiying Tao, Liang Liang, Qinglong Gou〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉Live streaming, a recently emerged service in the sharing economy era, is already very popular in China and is growing in the US market. Besides streamers (those who make the content) and the platform itself, unions of streamers are important stakeholders in live streaming platforms because they act as the streamers' agents. Because the union's salary mechanism will significantly influence the behavior of streamers, in this paper, we investigate the interaction between the streamers and unions from the perspective of salary mechanism.〈/p〉 〈p〉Specifically, we introduce a salary mechanism denoted by 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si2.gif" overflow="scroll"〉〈mrow〉〈mo stretchy="true"〉(〈/mo〉〈mi〉θ〈/mi〉〈mo〉,〈/mo〉〈mi〉R〈/mi〉〈mo〉,〈/mo〉〈mi〉T〈/mi〉〈mo stretchy="true"〉)〈/mo〉〈/mrow〉〈/math〉 for the union and then set up a game model between the union and streamers. While the proceeds of streamers depend on their efforts, the union's salary mechanism also significantly influences the efforts of streamers in the union. Streamers determine whether to join the union or not, as well as their efforts under the two alternatives. The union's goal is to optimize its salary mechanism, as well as to determine its effort level in the streamer's virtual room.〈/p〉 〈p〉Our results show that: (i) whether a streamer will join the union depends on both the union's salary mechanism and the streamer's ability; (ii) the salary mechanism 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si2.gif" overflow="scroll"〉〈mrow〉〈mo stretchy="true"〉(〈/mo〉〈mi〉θ〈/mi〉〈mo〉,〈/mo〉〈mi〉R〈/mi〉〈mo〉,〈/mo〉〈mi〉T〈/mi〉〈mo stretchy="true"〉)〈/mo〉〈/mrow〉〈/math〉 can be used to implement either the elite talent strategy or the huge-crowd strategy; and (iii) the union's optimal salary mechanism is significantly influenced by the platform's share rates to the union and streamers. In this paper, the properties of the union's optimal salary mechanism are analyzed. This paper contributes to the literature by being the first to incorporate a salary mechanism into studies of the live streaming economy.〈/p〉 〈/div〉 〈/div〉

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 214〈/p〉 〈p〉Author(s): Huiping Ding, Xiangbo Chen, Kuanhai Lin, Yunbing Wei〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The framework of implementing oilfield project is viewed as an engineering service chain consisting of serial different links supplied by multiple service providers in their specialized technical fields. It is the challenge for an oilfield project proprietor to ensure the consistency of accountability for quality performance of engineering services and acceptance of time limit for the project. This paper, from the view of general contractor as a group company, focuses on the tradeoff analysis of two different business strategies that are independent integration strategy and customized integration strategy, in which the factors affecting their comparative advantages are studied. The mechanism of how to distribute project profits between members of the engineering service chain is investigated. Our findings show that the optimal solution presents win-win profit distribution through the negotiation of outsourcing prices between the general contractor and multiple service providers (subcontractors) under coopetition strategy which characterizes the development trend of petroleum industry.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 214〈/p〉 〈p〉Author(s): Shao Hung Goh, Stephen Eldridge〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Sales and Operations Planning (S&OP) is a means of facilitating cross-functional coordination, such as across the marketing-operations interface, but adopters of S&OP have not all benefited from S&OP to the same extent. This paper investigates the effect of S&OP on supply chain performance using the perspective of coordination and contingency theories. A structural equation model was developed in which six S&OP coordination mechanisms were hypothesized to contribute to improved supply chain performance. The model was tested using a global survey of 568 experienced S&OP practitioners. Our results indicate that Strategic Alignment and Information Acquisition/Processing are the mechanisms that most significantly enable superior S&OP outcomes. However, we find that a highly formalized S&OP Procedure inhibits supply chain performance. Furthermore, using a contingency theory perspective, increasing firm size and increasing experience in S&OP amplify the negative effect of a standardized S&OP Procedure upon supply chain performance. Our results suggest that organizational bricolage may be a coordinating mechanism of effective S&OP programs and that managers should empower ambidextrous S&OP teams to maintain balance using self-governing event-driven processes. This paper makes a novel contribution to the S&OP literature by providing evidence of a theoretical construct (organizational bricolage), which may trigger a re-evaluation of the efficacy of prescriptive S&OP procedures that have been advocated by some researchers and practitioners.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 26 June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Ming-Lang Tseng, Ming K. Lim, Kuo-Jui Wu〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Prior studies in sustainable development have been conducted since its introduction, however, there is evidence in the literature that sustainable supply chain finance is still lacking, in particular, in relation to developing measurements to analyze the benefit and cost attributes. Furthermore, these studies did not also identify an ideal hierarchical structure, which is key for accuracy of decisions making. Hence, this paper contributes to the literature by constructing a set of measurements and analyzing the benefits and costs in the textile industry. In this paper, a fuzzy interpretive structural model was developed to build a hierarchical model, and a fuzzy TODIM was applied to determine the linguistic preferences and identify the benefits and costs. The results obtained show that sustainable supply chain finance improves firms’ competitive advantages through multiple attributes, which imply that collaboration value innovation, strategic competitive advantage and financial attributes are the most important aspects for improving firm’s performance. The results also indicate that to build a successful sustainable supply chain finance, firms should upgrade the synchronization of financial-related decisions, obtain price and cost information, focus on product and service quality, and ensure the dispersion of dependent and interdepartmental interactions.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: December 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 218〈/p〉 〈p〉Author(s): Yann Truong, Jonatan Pinkse〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Although firms widely use product preannouncements as a signaling strategy to influence external audiences’ perceptions and decisions, environmental scholars have rarely investigated this medium as a legitimation strategy. This study explores the impact of environmental performance on firms' propensity to use symbolic green new product preannouncements to signal their green actions. Building on a sample of 503 green product preannouncements from 2008 to 2012, the findings show that firms with lower environmental performance tend to issue more symbolic green preannouncements. We also found that the level of concentration in the industry moderates the relationship between environmental performance and symbolic green preannouncements, such that firms tend to issue more symbolic preannouncements in highly concentrated industries independently of their environmental performance to deter- or respond to competitive signals. This study contributes to the environmental literature by unraveling the determinants of symbolic green product preannouncements.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 19 June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Gazi Bilal Yıldız, Banu Soylu〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this paper, we consider a biobjective post-sales guarantee and repair services network design problem. One of the objective functions minimizes the total transportation cost of the network, while the other one minimizes the total tardiness of returned products from the targeted delivery duration. Although the motivation of our problem emanates from the repair services network of a mobile phone company, proposed models and algorithms can easily be adapted to any type of products. The mobile phone customers are sensitive to delays and thus decreasing the tardiness improves the customer satisfaction. However, due to intense competition among mobile phone companies, the total cost of the repair services network should also be minimized. We analyze the tradeoff between these objective functions and discuss the properties of the Pareto frontier. We are able to find the Pareto frontier exactly for small size networks. For large size networks, we propose a variable neighborhood search (VNS) based heuristic to approximate the Pareto frontier. We perform an application and experiments on the current network of a mobile company and present alternatives to the decision maker.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 219〈/p〉 〈p〉Author(s): Wantao Yu, Roberto Chavez, Mengying Feng, Chee Yew Wong, Brian Fynes〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This study examines the value of green human resource management (GHRM) in supporting environmental cooperation with customers and suppliers, and the moderating roles of internal green supply chain management (GSCM). A survey of 126 automobile manufacturers in China is analysed using moderated regression analysis, based on a proposed conceptual model grounded in ability–motivation–opportunity (AMO) theory and contingency theory (CT). The results reveal that GHRM is significantly and positively related to environmental cooperation with customers and suppliers, and that the relationships are significantly moderated by internal GSCM. HRM practitioners are advised to develop GHRM practices that provide training (ability), incentive (motivation), and conductive environment (opportunity) to help implement environmental collaboration, while SCM practitioners may improve internal GSCM to strengthen the effects of GHRM. This study clarifies key GHRM practices that contribute to GSCM, and advances related research by developing and testing an overarching model to explain such synergies and the moderating role of internal GSCM.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: December 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 218〈/p〉 〈p〉Author(s): Joonhwan In, Randy V. Bradley, Bogdan C. Bichescu, Antoinette L. Smith〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The use of group purchasing organizations (GPOs) as a supply chain intermediary is a long-standing and strategic approach to enhancing supply cost efficiency in U.S. hospitals. As a consequence, a hospital's decision to reconfigure its GPO network can have critical ramifications for the hospital's supply cost performance. In this study, we conceptualize possible GPO changes as structural and relational and investigate the impact of GPO changes on supply cost efficiency. To this end, we employ archival, panel data from multiple sources that track the performance of 2,391 U.S. hospitals between 2009 and 2014. Our findings indicate that, whereas hospitals that make a structural GPO change experience a decrease in supply cost efficiency, hospitals that enact a relational change are shown to experience improvements in supply cost efficiency. Our findings have important theoretical and managerial implications for supply chain management and hospital administrators.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 20 June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Hongjun Peng, Tao Pang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉We consider a three-level contract-farming supply chain with a risk-averse farmer, a risk-neutral supplier and a risk-neutral distributor, in which the farmer faces a yield uncertainty and the government offers agricultural subsidy to the farmer. The CVaR criterion is used to describe the risk-averse behavior of the farmer. We derive the optimal strategies of the supply chain and perform some sensitivity analysis to investigate the effects of the government subsidy and other factors. The results indicate that, as the subsidy increases, the farmer's total target production increases. Further analysis shows that the total production increase is mainly from the increased farm size, and the farmer's endeavor actually decreases. In addition, the results indicate that the profits of the supplier and the distributor both increase with respect to the subsidy. However, the impact of the subsidy on the farmer's profit depends on the farmer's degree of risk-averse. In particular, the impact of the subsidy to the farmer's profit tends to be positive for farmers with high degree of risk-averse, and the impact tends to be negative for those with low degree of risk-averse. The sensitivity analysis is also performed for the level of yield uncertainty in term of the standard deviation.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: December 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 218〈/p〉 〈p〉Author(s): Na Zhao〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The paper proposes the mega project supply chains infectious risks (MPSCIRs) synergy theory, defines the risk propagation speed, propagation density, and risk interconnectivity, distinguishes conventional risks from infectious risks, and identifies the risks facing major projects when passing through the “secret channel” of supply chains based on system dynamics theory and stability theory, and combining the new characteristics of major project supply chain risks after new technology reforms. Diverse research methods are used to conduct a three-dimensional analysis of MPIRs and major project supply chains (MPSCs) transverse, cutting, and in a hoop. The results suggest that infectious risks in the MPSC system are periodic. Based on the propagation speed, pressure, and direction, the infectious risk propagation capability and propagation energy distribution can be identified. The MPSC can be decomposed into N interactive subsystems. The infectious risks of various subsystems within the load scope should be diffused and coordinated in time. The theory helps in identifying risks and strategies specific to the decision major projects’ risk category. The research is demonstrated through an experiment study conducted in major projects' supply chain involving interviews, questionnaires, field observations and focus group meetings through case comparison and simulation study in the supply chain of major projects. In addition, the research can not only prevent major project infection risks (MPIRs) but also ensure the orderly production of major projects.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 28 April 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Christian Linder〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The discovery and development of new operations and manufacturing routines are marked by some controversy regarding how small- and medium-sized enterprises (SMEs) benefit from external knowledge inflows. This study investigates the practice-performance link between external knowledge utilisation and the discovery and development of manufacturing capabilities, which lead to operation performance. Based on a partial least squares analysis, a moderated mediation model is tested using Community Innovation Survey (CIS) data from 1663 SMEs. Results show that information inflow can be used to increase flexibility in production, and reduce costs of production mediated/moderated through new operations and manufacturing routines, as well as minimise liabilities resulting from SMEs' small size. The findings of this study contribute to a better under-standing of how manufacturing capabilities increase flexibility and cost efficiency by identifying main mediating and moderating effects. Further, this study adds clarification to the practice-performance link by highlighting that this link is only effective under certain conditions. In addition, contributions are made to the discussion on manufacturing capabilities by demonstrating how small business can benefit from external knowledge.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 26 April 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Mustapha Ouhimmou, Mustapha Nour El Fath, Mathieu Bouchard, Naji Bricha〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The design of a supply chain network helps companies in dealing with variability and uncertain evolution of demand over time. An efficient supply chain network may contribute to fulfill the customers’ demands in a quick and least cost manner. Therefore, it is important to solve the problem dealt with in this article concerning the design of the distribution network under demand uncertainty. The problem is to determine which warehouses to open and how much space to rent (outsource) in warehouses owned by third-party logistics providers. This paper presents the development and application of the robust optimization methodology to distribution network design problem under demand uncertainty. The proposed method allows the designer to find a network configuration having a total cost that is robust to typical changes in the geographical distribution of the demand. The Algorithm is an iterative process based on Benders decomposition. At each iteration, the following two steps are performed. In the first step, the global design problem (master problem) is solved to decide on the best use of warehouses according to the information provided by the previous iterations. For a given warehouse configuration and under some restrictions on demand variations, the second step determines the demand that incurred the largest transportation cost, granted that the transportation cost is optimal. These steps are repeated until finding the warehouses configuration that gives the smallest worst-case transportation cost. At each iteration the worst-case transportation cost sub-problem provides new information to the global design problem, such that the latter can improve its robustness. We report numerical results for real size network problems. The main results show that a high level of robustness of the distribution network can be achieved at a relatively low cost.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 24 April 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Barnabe Walheer, Marek Hudik〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Recently, increasing research attention has been paid to studying and modelling the efficiency behaviour of multidivisional firms. In this paper, we propose a simple and intuitive nonparametric approach for cost minimising in multidivisional firms when resources can be reallocated across firms and/or divisions. In particular, we consider that resource reallocation occurs through the price system. One distinguishing feature of our approach is that no price information is required to evaluate cost efficiency. This feature clearly increases the practical usefulness of our methodology given that prices are generally unknown when resource reallocation is possible. We consider various extensions of our framework, present a simulation, and apply our methodology to the Chinese manufacturing sector using a firm-level dataset.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 212〈/p〉 〈p〉Author(s): Maxim A. Dulebenets〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Nowadays, supply chain stakeholders have to successfully address a large number of challenges in order to ensure an efficient distribution of products within supply chains. These challenges include uncertainties in the supply chain operations, strict delivery deadlines, perishability of the transported products, partnership termination, and others. Cross-docking facilities have been widely used to tackle some of these challenges and improve effectiveness of the product distribution. This study aims to enhance scheduling of the inbound and outbound trucks at a cross-docking facility. The truck scheduling problem is formulated as a mixed integer linear programming model, minimizing the total truck service cost. A novel Delayed Start Parallel Evolutionary Algorithm is proposed to solve the problem. The algorithm executes separate Evolutionary Algorithms on its islands in a sequential manner and exchanges the promising solutions among the active islands based on an adaptive migration criterion. The computational experiments showcase superiority of the proposed algorithm in terms of the key algorithmic performance indicators against the other five metaheuristic algorithms, which have been commonly used in the cross-docking literature. Furthermore, this study demonstrates how the developed algorithm can be effectively used for the analysis of important managerial insights from the transportation perspective.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 27 February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Shota Hasegawa, Yuki Kinoshita, Tetsuo Yamada, Stefan Bracke〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Global warming is the major global environmental issue. To achieve less greenhouse gas emissions with circular economy for manufacturing assembly products, the key is to recovery including reuse and recycling End-of-life (EOL) products. Since reuse and recycling can avoid manufacturing of virgin materials, life cycle options such as reuse, recycling and disposal for each part entailing manual disassembly which is in high cost, the disassembly parts selection is carried out to decision for reuse and recycling the EOL assembly product environmentally and economically. Additionally, in the reuse of an assembly product, the revenue by reusing are different by each country owing to the differences of the second-hand market prices and labor cost by disassembly among the countries. This paper proposes a life cycle option selection of disassembly parts for material-based CO〈sub〉2〈/sub〉 saving rate and recovery cost with different market value. Each part is selected from reuse, recycling and disposal to harmonize the material based CO〈sub〉2〈/sub〉 saving rate and the cost. First, the procedures for designing the disassembly parts selection is presented, and life cycle option selection using 0–1 integer programming with the ε constraint method is formulated. Next, a numerical experiment of the results of the disassembly parts selection in the case of a computer is conducted. Finally, owing to the differences of sales revenue by parts reuse in the second-hand market prices, cases of Japan and Germany are examined for establishing multi-value circulation.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 27 April 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): David Gligor, Nichole Gligor, Michael Maloni〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Market orientation has been well studied within the firm but not across the supply chain. While firms rely more so on their suppliers for value creation in today's markets, research has not yet investigated the role of the supplier's market orientation relative to the focal firm's own market orientation and performance. Consequently, the current study seeks to expand the concept of market orientation from the level of the firm to the supply chain with dyadic archival and survey data from 482 firms (241 focal firm-supplier dyads). Our findings indicate that the supplier's market orientation has a direct and positive impact on the focal firm's ROA and that the strength of this relationship increases when firms operate in more uncertain (munificent, dynamic, and complex) business environments. Further, the supplier's market orientation partially mediates the relationship between the focal firm's market orientation and the focal firm's ROA, and the focal firm's market orientation also directly impacts its supplier's market orientation. These results therefore establish the complexity of market orientation within the supply chain to drive firm performance, thereby extending extant literature. As such, several noteworthy theoretical and managerial implications are presented.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 24 April 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Sumeer Chakuu, Donato Masi, Janet Godsell〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Supply Chain Finance (SCF) deals with the management of financial flows along the supply chain. Its core objective is to facilitate the reduction of financial risk in a supply chain by improving the collaborative cash-to-cash cycle and working capital. In order to fulfil its objective, SCF involves the coordination of supply chain actors, SCF instruments, and supply chain processes. Existing studies focus either on SCF actors, such as buyers, suppliers, banks, and logistics service providers (LSPs), or on specific SCF instruments, such as reverse factoring, inventory financing and discounting. However, an analysis of the relationship between actors and instruments, as well as of the factors influencing this relationship, requires further development. In light of this gap, this paper systematically reviews the literature on SCF with the objective of clarifying the relationship between SCF actors, instruments, and contextual factors. The review identified three main archetypes for this relationship: fixed-asset financing (fixed asset-centric), inventory financing (inventory-centric), accounts receivable/accounts payable financing (buyer-centric and supplier-centric). Based on the results of the review, the authors discuss the implications for practitioners and further research for academics.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 22 April 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Byung-Gak Son, Chang-Hun Lee, Byoung-Chun Ha, Hyunjeong Nam〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉An increasing number of companies have begun to make efforts to treat their suppliers fairly as a part of wider corporate social responsibility (CSR) initiatives. Few studies, however, have investigated the performance implications of such efforts for buying firms. This paper uses both organisational climate theory and social exchange theory to investigate (1) if buying firms' efforts in the form of a code of conduct for its procurement practitioners pay off, and (2) its mechanisms from the perspectives of procurement practitioners. We use a multi-method approach, combining analysis of survey data complemented by results from a behavioural experiment. First, survey data were gathered from 327 Korean manufacturing companies and analysed using structural equation modelling. Second, the findings were complemented by a behavioural experiment involving 120 subjects. The results support the positive performance implications of fair supplier treatment in the form of codes of conduct for procurement practitioners. The paper also offers insights into how such efforts benefit buying firms, which is due to the trust in the buyer-supplier relationship fostered by the resulting ethical behaviours of procurement practitioners.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 25 April 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Robin Kleer, Frank T. Piller〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Additive manufacturing (AM) allows to build components and finished series products directly from 3D data, without the need for tooling or other setup cost. An often discussed, but hardly investigated opportunity of AM is to establish economical and scalable local production facilities for innovating consumers (who turn into “prosumers”). In this paper, we investigate the effect of such a local production (enabled by AM) on consumer welfare, market structure, and competitive dynamics. Doing so, we provide a new perspective on the fundamental trade-off between the instant availability of (perfectly fitting) products manufactured by and in close proximity to a consumer and the efficiency gains of realizing economies of scale by producing standard products in a central facility. We analyze AM from the perspective of the established theories of user innovation and spatial competition. Building on two game-theoretical (Hotelling) models, we show that there is scope for the improvement of consumer welfare arising from local production by consumer producers. Our analysis allows us to make a number of propositions concerning the effects of AM on market structure when adopted by local users, and to identify the specific conditions of these shifts.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 25 April 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Aldona Kluczek〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Currently growing concerns about energy efficiency and sustainability across the manufacturing sector 〈strong〉have spurred〈/strong〉 researchers to spend their efforts on improving energy efficiency. A recent study on sustainability assessment does not provide any real measurement linkages between energy matters and sustainability dimensions at the plant level. Simultaneously, a few papers that deal with technologies, not taking the sustainability associated with optimized energy intensity as a whole into account, still attempt to include LCA-based methods into the integrated sustainability methods. Thus, an energy-led approach for sustainability assessment is adopted using all-in-one methodology: SBM-DEA + energy LCA-LCC-SLCA. In accordance with the goal of the article, this approach will be performed by improving the energy efficiency of twelve production systems. This sustainability-oriented methodology is presented in the form of relative, aggregated sustainability indicators for production systems, I〈sub〉ESUS,〈/sub〉 comparing quantitatively two scenarios: a baseline and a future scenario. The overall results in sustainability terms show, that improving the energy efficiency of production systems contributes significantly to energy sustainability. For the improvement scenario, the indicator amounts to I〈sub〉ESUS〈/sub〉 = (2.565; 2.475; 2.264) compared with I〈sub〉ESUS〈/sub〉 = (1.450; 2.937; 2.368) as baseline. This sustainable-oriented methodology will enable the implementation of a suitable performance measurement tool for supporting industrial energy policy-makers. If followed, the approach will allow for the improvement of energy-intensive manufacturer-dependent performance, guiding it towards energy sustainability. The robustness of the results is guaranteed by a sensitivity analysis.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 213〈/p〉 〈p〉Author(s): Seyedmohsen Hosseini, Nazanin Morshedlou, Dmitry Ivanov, M.D. Sarder, Kash Barker, Abdullah Al Khaled〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Resilient supplier selection is a key strategic decision in the context of the supply chain (SC) disruption management. We offer an efficient solution to the resilient supplier selection and optimal order allocation problem. We first show how to compute the likelihood of disruption scenarios for the supplier selection problem using a probabilistic graphical model. That model can capture (i) a large number of disruptive events with no computational burden, and (ii) the dependencies among disruptive events and their impacts on supplier performance, i.e., the ripple effect. We then propose a stochastic bi-objective mixed integer programming model to support the decision-making in how and when to use both proactive and reactive strategies in supplier selection and order allocation. The outcomes of this research, if utilized properly, can benefit suppliers to find the optimal set of operational decisions (e.g., the optimal level of surplus capacity and restorative capacity) that enhance their resilience capabilities. Finally, the proposed model can be utilized as a decision support tool to assist manufacturers in performance assessment of supplier alternatives when costs and resilience are considered simultaneously, which helps to build up both efficient and resilient 〈span〉〈/span〉SC (i.e., to achieve the 〈span〉〈/span〉SC resilience) to ensure the operations continuity. These outcomes can help SC managers organize their disruption risk mitigation efforts with balancing the efficiency and resilience while focusing on critical suppliers and order (re)-allocation that will have a more significant impact on the performance of the SC when disrupted.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 213〈/p〉 〈p〉Author(s): Tiantian Zhang, Cherry Yi Zhang, Qifan Pei〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Supply chain management aims to facilitate the flows of goods, information, and money. The first two flows have been studied extensively. Supply chain finance is the last piece of this puzzle. However, little empirical evidence can be found to support the benefits, if any, of practicing supply chain finance. In this study, we empirically test the relationship between supply chain finance and not only the firm's financial performance, but also extend the knowledge of this discipline by studying the relationship between supply chain finance and inventory performance and bankruptcy risk for the focal firm. We use a large size longitudinal data of 18,448 US listed firms spread out 8 broadly defined industries over 48 years. The results of this study support that supply chain finance is effective but not on firm's financial performance and inventory management efficiency. Its role is to stabilise supply chain through reducing the bankruptcy of the focal firm. The effect varies in different industries. In particular, mining, manufacturing and transportation industries receive the most benefit.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 20 March 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Lipan Feng, Kannan Govindan, Xiong Zheng, Qianzhou Deng〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Firms have increasingly adopted the design for the environment (DfE) strategy because environmental regulations are gradually becoming more stringent. This can make products more recyclable and environmentally-friendly. In this study, we consider two cases, namely, a monopolistic case in which the original equipment manufacturer (OEM) and an independent remanufacturer (IR) are integrated and a competitive case in which OEM and IR are independent. A theoretical model is proposed to explore the impacts of DfE on firms’ quantity decisions, as well as the impacts of competition on the DfE decision. Comparisons of the optimal decisions in the two scenarios yield some interesting results. In the monopolistic case, DfE reduces the OEMs’ willingness to engage in remanufacturing, but the outcome is completely reversed in the competitive case in which DfE will incentivize IR to enter the market and cannibalize OEM’s market share. Second, the optimal DfE effort level can be higher (or lower) in the competitive case than that in the monopolistic case, which relies on the relationship between the scale parameter of the investment cost of DfE and the profitability of remanufacturing. In addition, we find that under some conditions a high level of DfE may hurt the environment through the greatly increased total sales, although DfE can help reduce the environmental impact of unit product.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 29 January 2013〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): M.A. Hoque〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Hoque (2011. International Journal of Production Economics 131 (2), 463–472) developed two generalized single-vendor multi-buyer integrated inventory models to minimize the joint total cost of ordering, set up, inventory holding and transportation. The production flow was synchronized by transferring the lot with unequal– and/or —equal sized batches (sub-lots). A common minimal joint total cost solution technique to the models was presented. Potential significance of the developed methods was shown by reductions in the joint total cost for some numerical problems. However, there arise some deficiencies in obtaining a proper solution to the problem in two cases. In this note, we provide a simple modification to the methods in order to obtain a right solution to the problem.〈/p〉〈/div〉

Description: 〈p〉Publication date: July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 213〈/p〉 〈p〉Author(s): Haidar Almohri, Ratna Babu Chinnam, Mark Colosimo〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Growing competition and increasing availability of data is generating tremendous interest in data-driven analytics across industries. In the retail sector, stores need targeted guidance to improve both the efficiency and effectiveness of individual stores based on their specific locations, demographics, and environment. We propose an effective data-driven framework for internal benchmarking that can lead to targeted guidance for individual automotive dealerships. In particular, we propose an objective method for segmenting automotive dealerships using a model-based clustering technique that accounts for similarity in store performance dynamics. The proposed method relies on an effective Finite Mixture of Regressions technique based on competitive learning for carrying out the model-based clustering with ‘must-link’ constraints and modeling store performance. We also propose an optimization framework to derive tailored recommendations for individual dealerships within store clusters that jointly improves profitability for the store while also improving sales to satisfy manufacturer requirements. We validate the methods using synthetic experiments as well as a real-world automotive dealership network study for a leading global automotive manufacturer.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 16 May 2017〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Tsan-Ming Choi, Yue Chen, Sai Ho Chung〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Online-offline operations are known to induce channel conflicts if the same products are offered by them. Under many franchising arrangements in the fashion industry, to avoid channel conflicts and cannibalization between the franchisee and the brand owner, the brand owner will first supply the product for the franchisee to sell offline in the first period. After that, the brand owner will sell the product online directly in the second period. We explore this online-offline model with the focal points on the choice of franchising contract and the ordering time. By modelling the choices under four different scenarios, we derive the analytical conditions in which one scenario is preferred to another scenario with respect to contract type and ordering time option. We examine the problem from the perspectives of the brand owner, the franchisee and the supply chain. We identify the situations in which the optimal choices of the brand owner and the supply chain are the same, as well as the conditions when Pareto improvement is achievable.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 26 February 2016〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Christopher S. Dodd, James Scanlan, Steve Wiseall〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Consider a production system where products are continuously manufactured and their features inspected for conformance within specification limits. If features are produced above or below the specification limits, they are either subject to rework or the product scrapped. Optimal mean setting may be applied to adjust the manufacturing means to influence the amount of rework or scrap produced, maximising profit. Within the production system, manufacturing and then inspecting each feature in turn is termed serial production, whereas manufacturing multiple features before inspection is termed parallel production. This paper develops a generalised expression to optimise the mean values of each feature (optimal mean setting), where n number of features are produced in any combination of serial and parallel operations. Previous literature is restricted to considering two features in parallel. The production of multiple features in combinations of serial and parallel operations is not fully considered. The new generalised expression is validated by showing it is consistent with specific cases from past literature. The approach is then applied to a practical example of a gearbox shaft, considering the expected profit of eight possible manufacturing sequences, as well as the deviation of the manufactured means relative to the design intent. The generalised expression is widely applicable in component design and manufacturing planning where the process capability index 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si0064.gif" overflow="scroll"〉〈mo〉(〈/mo〉〈msub〉〈mrow〉〈mi〉C〈/mi〉〈/mrow〉〈mrow〉〈mi mathvariant="normal"〉pk〈/mi〉〈/mrow〉〈/msub〉〈mo〉)〈/mo〉〈/math〉 of features is below one. The generalised expression also forms the basis for trade-offs between profitability and minimising deviations of manufactured means, which is the subject of further development.〈/p〉〈/div〉

Description: 〈p〉Publication date: July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 213〈/p〉 〈p〉Author(s): Baozhuang Niu, Lei Chen, Yaoqi Liu, Yong Jin〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Variety seeking behavior indicates that customers get boredom of the products they purchased before, and prefer new products when they want to purchase again. Considering this, firms have to adjust their price and quality decisions to keep “old” and find “new” customers. In this paper, we build a two-period stylized model by assuming firms' cost is effort-dependent, which characterizes the tradeoff between managing variety seeking customers and the cost of quality improvement. We show that, customers' variety seeking behavior leads to a mild competition in period 1 but a fierce competition in period 2, and the existence of variety seeking customers reduces firms' incentives to improve the quality levels. Regarding price decision, we find that firms charge a low retail price in period 2, but in period 1 the price depends on the effort cost coefficient. Interestingly, we find that firms may be worse off in a mixed market of both regular and variety seeking customers, when the effort cost coefficient is small. That is, firms' highly efficient quality improvement can be harmful when customers are variety seeking.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 19 November 2016〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Tomoaki Shimada, Luk N. Van Wassenhove〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉We investigate the impact of the home appliance recycling law on closed-loop supply chain activities in the electric home appliance industry of Japan. The recycling rates have experienced a basically constant growth since the home appliance recycling law went into effect in April 2001. This implies that the extended producer responsibility (EPR) scheme compelled the home appliance manufacturers to make efforts toward the efficient recycling of their end-of-life products. The results support Michael Porter's hypothesis that "properly designed environmental standards can trigger innovations that lower the total cost of a product or improve its value." We also conducted semi-structured interviews with five major home appliance/personal computer (PC) manufacturers. All the managers agreed that although the recycling business is not profitable for home appliance/PC manufacturers in Japan, government legislation and corporate social responsibility (CSR) force them to be active in the recycling of their products.〈/p〉〈/div〉

Description: 〈p〉Publication date: July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 213〈/p〉 〈p〉Author(s): Rogerio de Ávila Ribeiro Junqueira, Reinaldo Morabito〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Sugarcane harvest front scheduling is a complex process that affects the main activities of sugarmill supply logistics and it should simultaneously consider the available harvest and transport capacities, which are sometimes neglected. This paper models this scheduling problem, exploring an analogy to the well-known general lotsizing and scheduling problem with parallel production lines, and presents a heuristic method to solve it, involving an aggregation process, a constructive MIP heuristic based on relax-and-fix and an improving MIP heuristic based on fix-and-optimize. This optimization approach is applied to solve a large-sized real problem instance of a Brazilian mill whole season. To validate the approach, a validation process of the literature is applied by consulting a selected group of Brazilian harvest planning specialists. The results highlight the potential of the approach and how it can change the current harvest planning practices, enabling plans that consider the balance of harvest and transport capacities without using sectorization.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 213〈/p〉 〈p〉Author(s): Peng He, Yong He, Henry Xu〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper considers a dual-channel closed-loop supply chain (CLSC) where a manufacturer can distribute new products through an independent retailer and sell remanufactured products via a third-party firm or platform (3P) in the presence of possible government subsidy. The two main themes of this research are to explore channel structure and pricing decisions for the manufacturer and government's subsidy policy with competing new and remanufactured products. Three possible channel structures for manufacturer are investigated: (1) no direct sales (Structure D); (2) selling new products directly but distributing remanufactured products through the 3P (Structure MN); (3) selling remanufactured products directly but distributing new products via the retailer (Structure MR). We derive the manufacturer's optimal channel structure and pricing decisions, and government's optimal subsidy level under these three channel structures. We find that government can encourage the manufacturer to adopt desired channel structures by setting appropriate subsidy levels. Furthermore, higher subsidy level always benefits consumers and the whole supply chain, but not always so to the environment. Moreover, when government aims to minimize the environmental impact and subsidy expenditure, the manufacturer and government have different channel structure preferences when the cost saving from remanufacturing is very low or high. However, under a moderate cost saving, they have identical channel structure preference: both prefer Structure MN when the environmental impact discount is relatively high; otherwise, both prefer Structure MR.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 14 March 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Biswajit Sarkar, Rekha Guchhait, Mitali Sarkar, Leopoldo Eduardo Cárdenas-Barrón〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The optimized cash flow may affect any smart production system to control a material requirement planning and to reduce the carbon footprint within the environment. An automation policy is utilized within a smart production system under a forward and a backward logistics system. Such logistic network generally consists of a well-structured transportation system, which may increase the carbon footprint. This study deals how carbon footprint can be controlled by a smart production system and it obtains the net present value of products for the four sub-systems associated with the logistics system. To investigate this, four sub-systems as manufacturing, distribution, consumption, and remanufacturing are implemented. A solution methodology is designed with an integral transformation through the frequency domain. This smart logistics system can be used by an associated matrix through an input-output analysis based on the distribution center. An illustrative numerical experiment is conducted and the study reveals that the discounted sale in disposal subsection at the end of the logistic cycle gives high positive impact, where the efficiency is increased due to discarding defective products by the automation policy. Graphical studies on the effect of transportation time for the total net present value and the net present value for disposal items are compared. It is found that two-stage inspection process reveals less amount of defective items and less pollution. As the closed-loop supply chain management is considered and due to transportation, huge amount of carbon emissions are passing through the environment, this study gives the reduced amount of carbon and more perfect products by an optimum cash-flow within a smart production system under advanced logistics management.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 213〈/p〉 〈p〉Author(s): Lipan Feng, Xiong Zheng, Kannan Govindan, Kelei Xue〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉With the rapid development of technology, it becomes increasingly common that consumers buy used products through secondary market platforms. In this way, consumers can directly buy or sell used products without intermediaries. In this paper, we propose a two-period model that captures the critical feature that consumers can independently purchase or sell used products through a secondary market platform. We explore how the firm should strategically decide its production and quality respond to the anticipated trade of used products among consumers through the platform. The results show that two factors, i.e., the depreciation rate and service percentage fee, play an essential role in driving optimal decisions for the firm. First, the presence of a secondary market platform reduces the total production quantity, but the service percentage fee has a positive effect on it. Second, when the firm solely decides its production, regardless of the depreciation rate, the presence of a secondary market platform can increase the firm's gross profit in some situations. Third, when the firm can endogenously determine product quality and production, we obtain a case in which the presence of a secondary market platform is beneficial to the firm and eventually increases product quality. Furthermore, we derive that the above results can be reproduced even when the service percentage fee charged by the platform is endogenous.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 219〈/p〉 〈p〉Author(s): Mehran Ullah, Biswajit Sarkar〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Due to the accelerated expansion of technology and improved living standards, the use of electronic products is increasing exponentially. Unfortunately, the improper disposal of used electronic products, such as cell phones, has resulted in rapid degradation of the environment and is, therefore, posing a great threat to human health. Meanwhile, proper recycling is also likely to generate high profits; thus, recycling of electronic products is a necessity of the time. However, the profitability of recycling and remanufacturing depends upon the return rate, which is very low in the cell phones industry. In this paper, we first identify the root causes of low return rate and, then, develop a novel Radio Frequency Identification (RFID) based return channel to increase the recycling rate. A dual-recovery-channel hybrid manufacturing-remanufacturing production model is proposed, which procure used products of different quality from both the traditional market-driven recovery channel as well as the new RFID based channel. A mathematical model is developed considering the cost of implementation and the design of the proposed RFID based recovery channel. Recovery-channel selection is studied, and results show that a hybrid collection strategy with 85% share of channel-1 and 15% of channel-2 is the optimal one. Moreover, the collection from the proposed RFID based channel increases as the demand increases. For the proposed RFID based system, reader sensing power is found more significant compared to the cost of readers. A numerical example is given with three different cases and impacts of different input parameters are studied to draw important results. Managerial insights are given to assist the designer of the system in some critical decisions.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 16 July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Mansoor Shekarian, Seyed Vahid Reza Nooraie, Mahour Mellat Parast〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper examines the effect of flexibility and agility on improving supply chain responsiveness. We examine a supply chain with multiple sites, multiple transportation channels, and multiple product planning, over multiple periods, under supply risk and demand risk. Using a numerical example, we determine the relationship between three objective functions related to responsiveness, risk, and the cost of new and seasonal products, then discuss the impact of flexibility and agility on mitigating supply chain disruptions. To show a trade-off among objective functions in our numerical example, we solve the multi-objective mixed integer programming (MOMIP) model using three multi-objective optimization methods: the weighted goal programming (WGP) method, the augmented ε-constraint (AUGMECON) method, and the non-dominated sorting genetic algorithm (NSGA-Ⅱ). Our findings help decision makers with these two tasks: anticipate how much improvement in flexibility and agility will lead to an improvement in responsiveness; and create an investment plan to minimize the negative impact of supply chain disruptions by an examination of the trade-offs among responsiveness, risk, and cost. The results show that the NSGA-Ⅱ method outperforms the AUGMECON method in several metric indexes: the spacing metric, the diversity metric, and simple additive weighting.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 16 July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Dara G. Schniederjans, Carla Curado, Mehrnaz Khalajhedayati〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The rapid digitisation of industry, or industry 4.0, is trending in supply chain management. While the amount of data made available through digitisation has enabled supply chain benefits, there still exist challenges regarding the rapid digitisation of the field. Therein lies opportunities for scholars to leverage the growing amount of data through knowledge management to cultivate valuable information for organisations. The purpose of this paper is to understand future inquiries for scholars to broaden their perspectives and leveraging knowledge management to enhance the supply chain digitisation research paradigm. This is done through both a large-scale literature review as well as a textual analysis and forecasting on industry- and field-applications, technologies and topics in digitisation. Utilizing textual data as well as google trends data from 2010-2018, comparisons are conducted on two measurements (prevalence and growth) to determine significant differences between the scholarly publications and practitioner (news and video) media to compare scholarly vs. practitioner activity in the aforementioned areas of supply chain digitisation. Applying the field of knowledge management to supply chain management through a knowledge management theoretical framework, this paper provides future research inquiries pertaining to how scholars can utilize the largely ignored areas of supply chain digitisation as well as the growing areas to explain how the human dimension of supply chain management can be further explored for the purposes of optimizing supply chain digital performance.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 12 July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Yuanjie He, Maryam Esmaeili, Marjan Zare〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Nowadays, supply chain management cannot be overlooked with the existence of uncertainties caused by both the random demand and the random production yield. This paper considers a supply chain which includes a supplier facing random yield and multiple downstream retailers dealing with random demands. Under a 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.svg"〉〈mrow〉〈mi〉S〈/mi〉〈mi〉t〈/mi〉〈mi〉a〈/mi〉〈mi〉c〈/mi〉〈mi〉k〈/mi〉〈mi〉e〈/mi〉〈mi〉l〈/mi〉〈mi〉b〈/mi〉〈mi〉e〈/mi〉〈mi〉r〈/mi〉〈mi〉g〈/mi〉〈/mrow〉〈/math〉 game structure, several analytical models are presented in order to investigate the supply risk sharing mechanism within the supply chains. Under the first scenario, the same contracts (either risk-sharing contract (〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si2.svg"〉〈mrow〉〈mi〉R〈/mi〉〈mi〉S〈/mi〉〈/mrow〉〈/math〉) or no risk-sharing contract (〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si3.svg"〉〈mrow〉〈mi〉N〈/mi〉〈mi〉R〈/mi〉〈mi〉S〈/mi〉〈/mrow〉〈/math〉)) are non-discriminatively used for all involving retailers. Then, both 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si2.svg"〉〈mrow〉〈mi〉R〈/mi〉〈mi〉S〈/mi〉〈/mrow〉〈/math〉 and 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si3.svg"〉〈mrow〉〈mi〉N〈/mi〉〈mi〉R〈/mi〉〈mi〉S〈/mi〉〈/mrow〉〈/math〉 contracts are offered to the retailers (namely as a non-identical strategy), which results in the segmentation of the retailer groups. Under both scenarios, the analytical solutions to the retailers' optimal order decisions and the supplier's production decisions are obtained. The random yield impact of the supplier is investigated especially on supply chain performances. The effects of demand uncertainty, production costs' sharing, and wholesale price reduction approaches are explored. The key findings include, first, 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si2.svg"〉〈mrow〉〈mi〉R〈/mi〉〈mi〉S〈/mi〉〈/mrow〉〈/math〉 contract may significantly reduce supplier's holding costs; second, 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si2.svg"〉〈mrow〉〈mi〉R〈/mi〉〈mi〉S〈/mi〉〈/mrow〉〈/math〉 contract benefit both the supplier and the retailers in comparison with 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si3.svg"〉〈mrow〉〈mi〉N〈/mi〉〈mi〉R〈/mi〉〈mi〉S〈/mi〉〈/mrow〉〈/math〉 contract; third, by process improvement and technology advancement, if the supplier may reduce the supply random yield effect, supply chain performances can be improved. Numerical examples and managerial insights are presented to illustrate the presented models. The findings may benefit both private companies and government agencies regarding decision making and policy setting in industries with high supply risks such as agriculture and farming related industries.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 9 July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Hussain Abualkhair, Emmett J. Lodree, Lauren B. Davis〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Disaster relief centers (DRCs) are the retailers of disaster relief supply chains. Also known as Points of Distribution (PODs), disaster relief centers are ad hoc distribution sites set up in shopping mall parking lots, schools, churches, or warehouses where relief supplies are distributed to beneficiaries. Perhaps the most significant challenges that DRCs face are volunteer and material convergence, which refer to the mass movement of people and supplies, respectively, into affected areas following large-scale disaster events. The handling of donated supplies at DRCs and their subsequent distribution to beneficiaries are carried out almost exclusively by volunteers who also show up and abandon DRCs at random points in time. This paper concerns the assignment of volunteers to tasks at DRCs and takes the following three sources of uncertainty into account: (i) beneficiary arrival and service times, (ii) donation arrival and service times, and (iii) volunteer arrival and abandonment times. We represent the DRC as a queuing system with two parallel queues, one for donors/donations and the other for beneficiaries, and analyze the system in an agent-based simulation environment. In particular, we examine the effectiveness of heuristic policies for assigning volunteers to parallel queues in which performance metrics related to the average time donors and beneficiaries spend in the DRC are minimized. Through extensive computational experimentation, we identify the most effective assignment policies under a variety of experimental conditions.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 15 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Yongjian Li, Xuanming Bai, Kelei Xue〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The sharing economy has changed not only the purchasing and use behaviour of consumers but also the operating mode of original equipment manufacturers (OEMs). For OEMs, the sharing economy represents a challenge and an opportunity. In the car market, some OEMs (e.g., General Motors and Toyota) choose to cooperate with peer-to-peer (P2P) sharing platforms, while others (e.g., Nissan and Haima〈sup〉1〈/sup〉) choose to work with business-to-consumer (B2C) sharing platforms. This paper develops an analytical framework to study how the OEM selects business modes under the sharing economy. Considering participation concerns inherent in the sharing economy, including renters' perceived value of shared products and owners’ maintenance costs, which depend on the marginal cost of products, we first study how the profit-maximising sharing platforms of the P2P and B2C modes affect the OEM. Then, we analyse the mode decision of the OEM. We find that the OEM should choose to cooperate with the B2C platform if the value perception factor is higher or the marginal cost is lower. If the value perception factor is in the middle range and the marginal cost is higher, the OEM should choose the P2P platform. The OEM should not cooperate with any sharing platforms if the value perception factor is lower and the marginal cost is higher.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 7 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Andrew Charles Lyons, Juneho Um, Hossein Sharifi〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This research presents findings from a sequential, mixed qualitative and quantitative method comprising five case studies and a survey of 162 different manufacturing sites where we examined how increases in product variety influence the performance of a wide range of business processes within and across the value chain of engineering, manufacturing, procurement, logistics and sales. We also identified the advantages associated with an increase in product variety and investigated the relationships between business process performance and degree of customisation. Drawing on value chain and resource-based logic, a product variety increase was found to have a differential impact on business processes and was partly contingent on the levels of customisation offered. The results provide both a better understanding of the implications and relative costs associated with product variety increases on key business processes and activities and highlight key areas of business process capability development in order to mitigate the effects of variety increases. The study also provides an example for researchers on the process and advantages of using mixed methods. The results are valuable for manufacturers considering extending their product range in order to provide more choice for customers.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 6 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Tim Baines, Ali Ziaee Bigdeli, Rui Sousa, Andreas Schroeder〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The concept of servitization is well established in the literature, and yet the processes of organisational change that manufacturers undergo to compete through services have received much less attention. Therefore, this paper develops a model that enables a 〈em〉description〈/em〉 of the servitization processes, the principal stages of organisational change, and the forces impacting these processes. It is based on a series of 14 case studies of the process of servitization over time in multinational manufacturers. Evidence and analysis from these cases are used to establish that manufacturers undergo four stages of organisational maturity (〈em〉Exploration〈/em〉, 〈em〉Engagement〈/em〉, 〈em〉Expansion〈/em〉 and 〈em〉Exploitation〈/em〉), through which an organisation progresses according to the pressures of five principal forces (customer pull, technology push, value network positioning, organisational readiness, and organisational commitment). This progression can be characterised as a business growth model with multiple crises or tipping points. This research contributes to our understanding of the process of servitization and proposes a model which can be used to explain progression. It also forms the basis to better prepare manufacturers as to what to expect as they embark on a servitization journey.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 16 July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Tal Avinadav, Tatyana Chernonog, Tal Ben-Zvi〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Virtual products, such as mobile apps, 3D print files, e-music, etc., are produced with ample capacity and supplied with zero lead-time. We consider a two-echelon supply chain of a virtual product whose parties, a manufacturer and a retailer, operate under a revenue-sharing contract and face information asymmetry about demand. Demand is sensitive to the selling price and to the levels of sales effort and product quality. The manufacturer, who is more informed party, applies a strategic information-sharing policy. Assuming that the retailer is unaware of the manufacturer's information superiority, we find that when the retailer is risk-neutral, different beliefs regarding the distribution of the base demand will not affect the manufacturer's and the retailer's decisions as long as they share the same belief regarding the mean demand. In addition, we show that, given an actual base demand, the retailer is better off when her forecast is pessimistic, whereas the manufacturer is better off when the retailer's forecast is optimistic. Measuring the expected value of hidden manufacturer's information superiority compared with known and probabilistic superiorities, we prove that known superiority is better off for the retailer, whereas hidden superiority is better off for the manufacturer. Moreover, we prove that known superiority results in non-strategic information sharing, whereas probabilistic superiority may lead to strategic information sharing. We further extend our analysis and show that, under hidden superiority, interacting with a risk-averse retailer is more profitable for the manufacturer than interacting with a risk-neutral retailer, despite the risk-averse retailer's reduced investment in sales effort.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: December 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 218〈/p〉 〈p〉Author(s): Yuanguang Zhong, Zhaozhan Lin, Yong-Wu Zhou, T.C.E. Cheng, Xiaogang Lin〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Ride-sharing platforms, as a new travel service, yield substantial benefit by effectively matching drivers and passengers. We consider ride-sharing platforms that recruit permanent and/or temporary, i.e., self-scheduling, agents to provide on-demand services requested by riders. The permanent agents of a platform are paid a fixed wage by the platform, whereas the temporary agents are self-scheduling and offered a subsidy by the platform for the services they provide. In this paper we assume that the market is supply-dominant, i.e., the number of riders seeking on-demand services is sufficiently large and the price charged to each served rider is determined by the number of agents available on the platforms. In both monopoly and duopoly competition environments, we determine the subsidy level for the temporary agents and/or the employment level of the permanent agents that balance the agents' supply and the riders' demand to maximize the platforms' profits. Furthermore, we examine the impacts of both the employment of permanent agents and platform competition on the platforms' subsidy strategies and profitability, participants’ surpluses, and social welfare. We also discuss the managerial implications of the research findings.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: December 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 218〈/p〉 〈p〉Author(s): Wantao Yu, Mark A. Jacobs, Roberto Chavez, Jiehui Yang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Supply chains are becoming increasingly dynamic in response to changing business environments and technology. This has created challenges in managing the flow of materials and created greater risk of disruption. As such this study investigates the impact of such dynamism on disruption orientations, resilience, and financial performance. Herein an integrated conceptual framework is developed and then tested using survey data from a cross section of 241 Chinese companies and structural equation modelling. The results of the study reveal that supply chain dynamism has a significant positive effect on supply chain disruption orientation and supply chain resilience. Supply chain resilience is also affected by supply chain disruption orientation. However, the financial performance impacts of supply chain disruption orientation are strictly through supply chain resilience.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 219〈/p〉 〈p〉Author(s): Tingting Tong, Hongyan Dai, Qin Xiao, Nina Yan〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This study attempts to identify the pricing strategy of three most-commonly used on-demand food service platforms in China based on detailed information of more than 240,000 orders, and further evaluates the impact of pricing strategy on platform performance. We find that some platforms adopt dynamic pricing strategies, while other platforms adopt static pricing strategies. Considering the unique structure of the O2O on-demand food service market in China, we develop a dyadic two-sided market theory and demonstrate that compared with static pricing strategies, dynamic pricing strategies perform better. Consistent with our theory, our empirical analysis also suggests that platforms adopting dynamic pricing strategies have a significantly higher level of demand compared with platforms adopting static strategies. In addition, our results indicate the importance of delivery speed, red envelopes, and ratings in promoting demand.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 219〈/p〉 〈p〉Author(s): Fatemeh Mohebalizadehgashti, Hossein Zolfagharinia, Saman Hassanzadeh Amin〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Traditional logistics management has not focused on environmental concerns when designing and optimizing food supply chain networks. However, the protection of the environment is one of the main factors that should be considered based on environmental protection regulations of countries. In this paper, environmental concerns are considered in formulating a mathematical model to design and configure a multi-period, multi-product, multi-echelon green meat supply chain network. We develop a multi-objective mixed-integer linear programming formulation to optimize three objectives simultaneously: minimization of the total cost, minimization of the total CO〈sub〉2〈/sub〉 emissions released from transportation, and maximization of the total capacity utilization of facilities. To demonstrate the efficiency of the proposed optimization model, we design a green meat supply chain network for Southern Ontario, Canada. A solution approach based on augmented 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.svg"〉〈mrow〉〈mi〉ε〈/mi〉〈/mrow〉〈/math〉-constraint method is employed to solve the proposed model. As a result, a set of Pareto-optimal solutions is obtained. The set of Pareto-optimal solutions gives decision-makers the opportunity to make a trade-off between economic, environmental, and capacity utilization objectives. Our example shows that it is possible to keep emissions reasonably low without incurring high total costs. Finally, the impacts of uncertainty on the proposed model are investigated using several decision trees. Optimization of a food supply chain, particularly a meat supply chain, based on multiple objectives under uncertainty using decision trees is a new approach in the literature.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 219〈/p〉 〈p〉Author(s): Zuoming Liu〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Many business managers start to adopt environmental-friendly activities due to pressures and concerns regarding the potential adverse environmental impacts from their regular activities. However, there is no consensus regarding whether better environmental performance can lead to superior financial performance. Academic research also shows mixed or even contradictory results, possibly due to various limitations and problems. This study builds a multilevel framework to study the complicated relationship between environmental performance and financial return and synthesize those non-consensus results in many previous studies. An overall positive relationship is found between environmental and financial performance with variations across companies and industries due to the company- and industry-level heterogeneities. A negative relationship is also identified for some firms in some industry sectors. Moreover, the bi-directional causal relationship between environmental and financial performance also implies that it is necessary for companies to have sufficient financial resources in order to implement proactive environmental strategies and initiatives. The findings in this study make contributions to the literature, provide guidelines for managers and investors, and give implications for policymakers.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 16 July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Jing Huang, Wensheng Yang, Yiliu Tu〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Small and medium sized enterprises (SMEs) often have challenges to obtain bank financing for their operations, due to strict risk control of banks and low credit rating of SMEs. In recent years supply chain finance (SCF) has become promising solutions to alleviate SMEs’ financing problem, which takes advantage of supply chain integrity and relies on core enterprises to promote SMEs’ financing. In this paper, by taking the risk of financing participants into account, we set up a framework of SCF based on a general supply chain contract. We discuss the equilibrium strategies under three financing modes respectively and the bank’s decision-making, thereafter we analyze the financing mode decision under the general financing framework. We show that the wholesale price decision is related to the initial working capital of the retailer. Also, the critical initial working capital is affected by demand distribution, supply chain contract and interest rate. Moreover, reasonable wholesale price can eliminate SCF risk and guide the retailer’s ordering and the bank’s interest rate decision. Finally, the efficient working capital management can help the retailer to select reasonable financing mode, and all three financing modes have their own applicability.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: December 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 218〈/p〉 〈p〉Author(s): Alfonso Hernandez-Vivanco, Pedro Domingues, Paulo Sampaio, Merce Bernardo, Claudio Cruz-Cázares〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In a dynamic environment where organizations are continuously exposed to change, being robust, strong and competitive is a major managerial task. The aim of this article is to study the impacts of adopting multiple certifications on firm performance, by considering the dynamics involved in this process. A sample of 247 Portuguese firms that had adopted multiple certifications by 2015 encompassing the ISO 9001, ISO 14001 and OHSAS 18001 standards were studied by means of a longitudinal analysis. Their historical certification records were matched with their performance indicators to create a panel dataset from 2007 to 2015. The research into the causal effects of the certifications on firm performance was based on a panel dynamic approach, namely the system generalized method of moments. The following three combinations show consistent leverage on firm performance: ISO 9001, ISO 9001 + ISO 14001 and ISO 9001 + ISO 14001 + OHSAS 18001. Being ISO 9001 the common factor of these combinations and also the first standard adopted by most firms, results suggest that it might be a relevant driver towards improving firm performance. This research reveals new insights in this field by analyzing a changing environment where firms can be expected to certify dynamically according to the requirements of different standards.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 15 July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics〈/p〉 〈p〉Author(s): Vahid Roshanaei, Kyle E.C. Booth, Dionne M. Aleman, David R. Urbach, J. Christopher Becky〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉We develop the first exact decomposition approaches for a multi-level operating room planning and scheduling problem that integrates case mix planning, master surgical scheduling, and surgery sequencing in the presence of multiple surgical specialties. Our approaches consist of novel uni-level and bi-level branch-and-check algorithms that solve the problem using a hybridization of integer programming and constraint programming. We demonstrate that our approaches outperform an existing time-indexed integer programming model, yielding significant improvements on solution quality. Our methods are competitive with an existing genetic algorithm while providing provable bounds on solution quality. We conduct an investigation into the impact of time discretization on our algorithms, illustrating that our decompositions, unlike the previously proposed integer programming approach, are much less sensitive to time discretization and produce more accurate solutions as a result. Finally, we introduce and investigate benchmark instances with a more diverse case mix. Overall, we conclude that our decompositions are the most appropriate approaches for this multi-level operating room planning and scheduling problem.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 219〈/p〉 〈p〉Author(s): Hoi-Lam Ma, Z.X. Wang, Felix T.S. Chan〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Supply chain finance (SCF) aims to improve the overall creditability of the entire supply chain, including buyers, suppliers, and financial service providers, through an inter-organizational approach. In SCF, companies will collaborate with each other to maximise the mutual benefits. Companies, such as those involving suppliers, may sell their invoices to banks or any other financial service provider at a discount in order to cash in the invoices immediately for achieving better cash flow. Accordingly, the role of financial service providers becomes the most critical because they control the discount rates offered, while bearing all the risks, which is why they are also known as the risk takers. In existing literature and in practice, the discount rate is usually determined by the relationship between buyers and financial service providers. Therefore, it is necessary to understand what factors are considered during decision-making and whether the traditional collaborative factors considered in the literature on supply chain collaboration are still valid. So far, the supply chain collaborative factors have not been studied scientifically from the point of view of financial service providers. Therefore, in this work, we investigated how important these factors are for financial service providers. We identified the most important factors from the literature on supply chain collaboration and conducted interviews with many experienced practitioners in financial service industries in China. We employed interpretive structural modelling to model the relationship between collaborative factors and understand the importance of each factor. The results revealed that top management support, trust, and IT infrastructure are the factors considered the most important by financial service providers. Interestingly, we also found that incentives are the least important factors in SCF.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 219〈/p〉 〈p〉Author(s): Guilherme Luz Tortorella, Alejandro Mac Cawley Vergara, Jose Arturo Garza-Reyes, Rapinder Sawhney〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This article aims at examining the mediating role played by Organizational Learning (OL) capabilities at different contextualization levels on the association between Industry 4.0 (I4.0) technologies and operational performance. For that, we gathered information from 135 firms that have initiated their digital transformation towards the fourth industrial revolution era. Data was analyzed by means of multivariate data techniques. Our results show that learning capabilities at an organization level positively mediate the impact of I4.0 for achieving higher operational performance levels. However, OL at a team and individual level may not present a significant effect on such mediation. As I4.0 is claimed to facilitate a faster and more efficient identification and solution of manufacturing problems, our research provides empirical evidence to indicate that companies that systematically foster learning and knowledge sharing at an organization level can obtain greater benefits from I4.0 technologies adoption.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: December 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 International Journal of Production Economics, Volume 218〈/p〉 〈p〉Author(s): Shuyun Ren, Fengji Luo, Lei Lin, Shu-Chien Hsu, Xuran Ivan LI〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉With promising benefits such as traffic emission reduction, traffic congestion alleviation, and parking problem solving, Electric Vehicle (EV)-sharing systems have attracted large attentions in recent years. Different from other business modes, customers in sharing economy systems are usually price sensitive. Therefore, it is possible to shift the usage of shared EVs through a well-designed Dynamic Pricing Scheme (DPS), with the objective of maximizing the system operator's total profit. In this study, we propose a novel DPS for a large-scale EV-sharing network to address the EV unbalancing issue and satisfy the vehicle-grid-integration (VGI) service based on accurate station-level demand prediction. The proposed DPS is formulated as a complex optimization problem, which includes two Price Adjustment Level (PAL) decision variables for every origin-destination pair of stations. The two PALs are employed to affect the EV-sharing demand and travel time between each station pair, respectively. Physical and operational constraints from both EV demand and VGI service aspects are also included in the proposed model. Two case study are conducted to validate the effectiveness of the proposed method.〈/p〉〈/div〉 〈/div〉