Remanufacturing has been studied extensively from an economic modelling perspective. However, the number of studies focusing on models that consider the implementation difficulties in industry, such as data availability and model transparency, is low in comparison. This paper aims to identify how an initiation of remanufacturing can be economically assessed with models particularly suitable for implementation in industry. These models should contribute to spreading the know-how about initiating remanufacturing to transit industries towards more circular resource flows. To target the aim, a systematic literature review was conducted. The search resulted in a total of 964 papers published through August 2021. The relevant papers were categorised into a two-dimensional framework indicating the level of computer support needed to handle the model and the level of requirements to use the model in terms of data requirements, both of which are considered essential in the industrial implementation of the models. The review revealed a further need for research on assessing remanufacturing initiation profitability, especially on economic assessment models designed to assist industries without previous remanufacturing knowledge in such an initiation.

Remanufacturing has been modelled extensively from an economic perspective. However, there are relatively few studies focusing on models that consider the implementation difficulties in industry, such as data availability and model transparency. This paper aims to identify how remanufacturing initiations can be economically assessed with models particularly suitable for industry. These models should contribute to disseminating the know-how about initiating remanufacturing to transit industries towards more circular product flows. To fulfil this aim, a systematic literature review was conducted. The search resulted in a total of 964 papers published till August 2021. The results show that assessment models could be categorised into a two-dimensional framework indicating the level of computer support needed to handle the models and the level of data requirements to use the models, both of which are considered essential in the industrial implementation of the models. The review revealed and structured a further need for research on assessing remanufacturing initiation profitability, especially on economic assessment models designed to assist industries without previous remanufacturing knowledge in such an initiation.

Comparative relations behind online reviews contain rich information concerning customers assessments of different products or services, thereby supporting upcoming consumers purchase decisions, as well as helping to identify enterprises market competitiveness. Instead of using the pattern recognition method, this paper proposes a hierarchical multi-attention network (HMAN) model to extract the comparative relations, in order to greatly reduce the requirements of artificial features and the manual annotation in the relation mining process. Such model outperforms both traditional classification models and text classification models in terms of accuracy, with its F1-score up to 81%. Besides, the proposed model has a good performance on extracting comparative relations from long texts where comparison information is relatively scattered. In this study, we visualise results of different experiments in order to demonstrate the interpretability of this model, and furthermore explore the mechanism of multi-attention method in comparative relations mining. This study applies the deep learning method instead of pattern recognition to automatically capture deep features of comparative relations, and therefore it redefines the identification process of comparative relations.

The business of two-sided platforms, such as those used for online ride-sharing, has expanded rapidly thanks to opportunities to efficiently match supply- and demand-side users. However, the development of these platforms faces the challenge of complying with corporate social responsibility (CSR) regulations, particularly on the supply side of two-sided platforms. How to improve CSR investment, in order to reduce CSR violations while ensuring profitability, is now an important question. In this paper, we develop a game-theoretic model for a two-sided platform and analyze the impacts of network externalities (including customer network externality and provider network externality) and risk aversion on CSR investment decision-making. The analytical results show that, contrary to our intuition, greater network externalities do not necessarily stimulate the platform to invest in CSR. When the strength of customer network externality is high, investment in CSR may have a "dilution effect", i.e., CSR investment may reduce the platforms number of users and profit. Conversely, risk aversion always has an "incentive effect" on CSR investment, thereby increasing the platforms willingness to invest in CSR. Second, both provider and customer network externalities will increase the platforms prices. Interestingly, when the strength of customer network externality is high, the platform attracts more customers, even at high prices. Finally, our analysis indicates that risk aversion may reduce customer surplus when the strength of customer network externality is high. This result contradicts the initial expectation that risk aversion inspires platforms to invest in CSR, thereby improving customer utility and customer surplus.& COPY; 2022 Elsevier B.V. All rights reserved.

An inventory stacking decision assigns positions to items which are stacked vertically, such as containers in container terminals and steel plates in steel plants. The performance of stacking decisions is greatly affected by the arrival and departure information on items. We study an inventory stacking problem with partial information based on industrial observation in a steel plant. On the inbound side, we investigate three levels of information on future arriving items and their effect on performance. On the outbound side, we study the impact of the retrieval sequence, which is often random. We develop models incorporating different availabilities of information and determine stacking strategies. The study shows that the stacking strategy and stacking performance depend highly on information quality and space utilisation. Especially, when the space utilisation is high, low-quality information deteriorates the performance and such information should be ignored. This contradicts the general belief that more information should bring better performance. The study further proposes a time window allocation approach to reduce the uncertainty in retrieval, and it is effective in improving stacking performance.

Maintenance aims to ensure the availability and reliability of equipment so that production processes keep operations, and products sustain with good qualities. However, maintenance decisions rely essentially on the distribution of product’s lifetime. For instance, professional users may use machine tools intensively, whereas as hobby users, the usage of same tools is much less frequent. This variability poses a challenge for companies when adopting product-service offerings, as the maintenance policies should differ to minimise the number of unexpected failures as well as the product life cycle usage costs. This study investigates the identification of customer usage behaviour groups in mixed Weibull distributed product failure datasets. The study proposes an algorithmic model using the Weibull moments to distinguish the underlying Weibull distribution in a mixed distribution. The developed knowledge defines whether customer usage data needs to be distinguished between groups.

Worldwide, energy systems are experiencing a transition to more sustainable systems. According to the Hydrogen Roadmap Europe (FCH EU, 2019), hydrogen will play an important role in future energy systems due to its ability to support sustainability goals and will account for approximately 13% of the total energy mix in the coming future. Correct hydrogen supply chain (HSC) planning is therefore vital to enable a sustainable transition, in particular when hydrogen is produced by water electrolysis using electricity from renewable sources (renewable hydrogen). However, due to the operational characteristics of the renewable HSC, its planning is complicated. Renewable hydrogen supply can be diverse: Hydrogen can be produced de-centrally with renew-ables, such as wind and solar energy, or centrally by using electricity generated from a hydro power plant with a large volume. Similarly, demand for hydrogen can also be diverse, with many new applications, such as fuels for fuel cell electrical vehicles and electricity generation, feedstocks in industrial processes, and heating for build-ings. The HSC consists of various stages (production, storage, distribution, and applications) in different forms, with strong interdependencies, which further increase HSC complexity. Finally, planning of an HSC depends on the status of hydrogen adoption and market development, and on how mature technologies are, and both factors are characterised by high uncertainties. Directly adapting the traditional approaches of supply chain (SC) planning for HSCs is insufficient. Therefore, in this study we develop a planning matrix with related planning tasks, leveraging a systematic literature review to cope with the characteristics of HSCs. We focus only on renewable hydrogen due to its relevance to the future low-carbon economy. Furthermore, we outline an agenda for future research, from the supply chain management perspective, in order to support renewable HSC devel-opment, considering the different phases of renewable HSCs adoption and market development.

PurposeThis study explores the impact of carbon neutrality policies on Chinese stock market from a supply chain perspective. Specifically, the carbon policy refers to the Action Plan for Carbon Dioxide Peaking Before 2030 (the Plan) in China.Design/methodology/approachThis paper is based on the resource dependence theory (RDT) and applies the event study methodology to explore the impact. It uses the cross-sectional regression model to reveal the moderating effect of supply chain characteristics on the stock market reaction with a data set of 354 listed companies in A-shares (excluding ChiNext and SME board).FindingsThe promulgation of the Plan shows a significant negative stock market reaction. Customer concentration, out-degree centrality and smart supply chains (SSCs) have a significant negative moderating effect. In-degree centrality and supplier concentration have a significant positive moderating effect. Furthermore, the conclusions concerning out-degree centrality, supplier concentration and SSCs are counterintuitive.Practical implicationsFor policymakers, the study results provide a reference for evaluating the carbon neutrality policy. For managers, this study provides theoretical support for strategically adjusting and designing supply chain structures in the context of advocating peak carbon dioxide emissions and carbon neutrality.Originality/valueThis paper is the first attempt that includes the supply chain structure factors into the impact of carbon neutrality policies on the stock market.

This paper studies the channel choice problem in an e-retailing market when a reseller and an agency seller are experimenting with a new format, i.e., a hybrid retailing strategy. Under this strategy, the reseller not only sells products to consumers directly, but also expands the market in collaboration with the agency seller who operates a platform. However, the motivation and effectiveness of this strategy are not clear. Therefore, we develop game-theoretic models to investigate retail and wholesale prices, and the equilibrium channel choice. First, we find that the hybrid retailing strategy results in a higher retail price for the reseller; in contrast, the agency seller prefers to reduce the retail price when the fraction of market demand through the hybrid retailing channel is large. Second, we find that the hybrid retailing strategy can benefit all stakeholders when the fraction of market demand through the hybrid retailing channel is small. Third, under a dual retailing channel with price competition, a reseller and an agency seller are still willing to collaborate through a hybrid retailing strategy, because the cost of market expansion caused by this strategy is partly transferred to the manufacturer. Our results can provide meaningful decision support and operational rules for stakeholders to make strategic retail decisions.

The advent of the era of the smart economy has made agricultural production more intelligent. An increasing number of companies have launched a series of investment activities aimed at smart agricultural production (SAP). However, whether smart agricultural production investment (SAPI) impacts the stock market has yet to be confirmed. Therefore, based on the sample data of 118 listed companies in China from 2010 to 2019, this study empirically examines the impact of SAPI announcements on shareholder value, as indicated by abnormal returns of stocks. Further, we tested the moderating effect of certain characteristic factors on abnormal stock returns. The research results illustrate a significant positive connection between SAPI announcements and shareholder value. Moreover, considering the announcement content and company factors, this study investigates the impacts of different investment targets and industries on the market reaction to SAPI announcements. We find that non-agricultural companies have a more positive market reaction to SAPI than agricultural companies; the higher the liability-asset ratio, the more positive will be the stock market reaction to SAPI.

We construct portfolio strategies consisting of different stocks from four main energy market sectors, including oil and gas, oil and gas related equipment and services, multiline utilities and renewable energy. To construct portfolio strategies, we first forecast assets returns by using multivariate copula models. These forecasting frameworks enable us to undertake both symmetric and asymmetric tail connectedness in simulating from the joint distribution. Second, we applied four major risk measures including volatility, mean absolute deviation, conditional value-at-risk and conditional drawdown-at-Risk. Our findings indicate that the consideration of homogeneity of oil and gas sector and oil and gas related equipment and services sector, together with the heterogeneity of multiline utilities sector and renewable energy sector should lead to information decoupling among these sectors, thereby providing portfolio diversification. The mixed copula model results in better out-of-sample economic performance, indicating the advantage obtained from modelling both symmetric and asymmetric tail dependence. Our analysis of the portfolio weights, among the energy market sectors, shows that for optimal portfolios, multiline utilities and renewable energy sectors constitute higher portion of the invested assets. The study results provide an encouraging guideline for developing renewable energy sector from the perspective of financial market.

The European Union expects that hydrogen will play a vital role in future energy systems. Fuel cell electric vehicles currently present a key development path for electrification of the transport sector, which requires infrastructure investments of hydrogen refueling stations, preferably powered by renewables such as solar and wind energy. The economic feasibility of refueling stations depends on geographical locations. This study introduces a model to identify the key cost components of renewable hydrogen for refueling stations, and simulates the performance using solar radiation, wind speed, and electricity price data in a selection of Swedish cities. The study demonstrates the importance of integrating the electricity grid in green hydrogen production. Wind speed is crucial in reducing the cost, whereas solar radiation has less influence. In addition, a combination of solar and wind brings better performance in an off-grid scenario. The most encouraging finding is the cost of 35-72 SEK/kg (3.5-7.2 V/kg), which is competitive with reported costs in other EUcountries, especially since this cost excludes any government support scheme. The study provides a reference for investors and policy makers foreseeing the industrial landscape for hydrogen energy development. (c) 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Remanufacturing has in recent decades become an alternative way for sustainable development to cope with the increasingly resource crisis and environmental pollution problems. The line balancing of remanufacturing is more complex than that of traditional manufacturing due to the uncertainty in the remanufacturing process, especially as the assembly time is uncertain. As a result, the line balancing of the remanufacturing assembly has become a critical issue. This paper evaluates the uncertain assembly time in each station based on an approach of Fuzzy Graphical Evaluation and Review Technology (FGERT) network. A remanufacturing multi-objective mixed-flow assembly model is established by optimizing the cycle time, assembly line smoothing coefficient and balance time loss rate. Then an adaptive bilayer genetic algorithm is proposed to solve the optimization problem. Finally, an example was given to demonstrate the effectiveness of the proposed method. Results show that the production rhythm balance of remanufacturing assembly is significantly improved, and the idle time in each assembly station has been reduced as well. The cycle time of the remanufacturing has reduced from 344s to 336s, with the smoothing coefficient and balance time loss rate of being 8.73 and 1.69% compared to that without assembly line balancing. The proposed method provides a useful tool for improving mixed-flow remanufacturing assembly lines in an electromechanics industry. Copyright (C) 2022 The Authors.

Worldwide, energy systems are experiencing a transition to more sustainable systems. According to the Hydrogen Roadmap Europe (FCH EU, 2019), hydrogen will play an important role in future energy systems due to its ability to support sustainability goals and will account for approximately 13% of the total energy mix in the coming future. Correct hydrogen supply chain (HSC) planning is therefore vital to enable a sustainable transition, in particular when hydrogen is produced by water electrolysis using electricity from renewable sources (renewable hydrogen). However, due to the operational characteristics of the renewable HSC, its planning is complicated. Renewable hydrogen supply can be diverse: Hydrogen can be produced de-centrally with renew-ables, such as wind and solar energy, or centrally by using electricity generated from a hydro power plant with a large volume. Similarly, demand for hydrogen can also be diverse, with many new applications, such as fuels for fuel cell electrical vehicles and electricity generation, feedstocks in industrial processes, and heating for build-ings. The HSC consists of various stages (production, storage, distribution, and applications) in different forms, with strong interdependencies, which further increase HSC complexity. Finally, planning of an HSC depends on the status of hydrogen adoption and market development, and on how mature technologies are, and both factors are characterised by high uncertainties. Directly adapting the traditional approaches of supply chain (SC) planning for HSCs is insufficient. Therefore, in this study we develop a planning matrix with related planning tasks, leveraging a systematic literature review to cope with the characteristics of HSCs. We focus only on renewable hydrogen due to its relevance to the future low-carbon economy. Furthermore, we outline an agenda for future research, from the supply chain management perspective, in order to support renewable HSC devel-opment, considering the different phases of renewable HSCs adoption and market development.

The rapid development of the supply chain of the Internet of Things (IoT) industry may trigger financial risk contagion among IoT manufacturers. This article collects data on listed IoT companies in the Chinese market from 2010 to 2019 and explores the development of the environment for the IoT industry. Two dynamic time wrapping (DTW) networks are created to analyze the topological structures of the IoT industry environment. Both the standard DTW and strongly connected DTW networks are revolutionary in terms of their interconnectedness in the IoT industry. We found that the level of clustering and transitivity of the network continued to decline between 2010 and 2019; i.e., the efficiency of financial risk contagion on IoT networks was significantly reduced. This article contributes to the literature in two aspects. First, it reveals that Chinas IoT industry is increasingly competitive; financial risks have become more difficult to transfer. The IoT industry has become more robust and exhibits a lower likelihood of financial risk contagion. Second, the article provides empirical evidence for the theory of coevolution, showing that risk contagion ability in an industry setting is decreasing with the development of individual firms.

In the aftermath of large-scale natural disasters, supply shortage and inequitable distribution cause various losses, hindering humanitarian supply chains? performance. The optimal decisions are difficult due to the complexity arising from the multi-period post-disaster consideration, uncertainty of supplies, hierarchal decision levels and conflicting objectives in sustainable humanitarian supply chains (SHSCs). This paper formulates the problem as a fuzzy tri-objective bi-level integer programming model to minimize the unmet demand rate, potential environmental risks, emergency costs on the upper level of decision hierarchy and maximize survivors? perceived satisfaction on the lower level of decision hierarchy. A hybrid global criterion method is devised to incorporate a primal-dual algorithm, expected value and branch-and-bound approach in solving the model. A case study using data from the Wenchuan earthquake is presented to evaluate the proposed model. Study results indicate that the hybrid global criterion method guides an optimal strategy for such a complex problem within a reasonable computational time. More attention should be attached to the environmental and economic sustainability aspects in SHSCs after golden rescue stage. The proposed bi-level optimization model has the advantages of reducing the total unmet demand rate, total potential environmental risks and total emergency costs. If the decision-agents with higher authorities act as the leaders with dominant power in SHSCs, the optimal decisions, respectively taking hierarchical and horizontal relationships into account would result in equal performance.

The multi-armed bandit (MAB) is a classical model for the exploration vs. exploitation trade-off. Among existing MAB models, the restless bandit model is of increasing interest because of its dynamic nature, which makes it highly applicable in practice. Like other MAB models, the traditional (risk-neutral) restless bandit model searches for the arm with the lowest mean cost and does not consider risk-aversion, which is critical in cases such as clinical trials and financial investment. This limitation thus hinders the application of the traditional restless bandit. Motivated by these concerns, we introduce a general risk measure that satisfies a mild restriction to formulate a risk-aware restless model; in particular, we set a risk measure as the criterion for the performance of each arm, instead of the expectation as in the traditional case. Compared with classical MAB models, we conclude that our model settings accommodate risk-aware researchers and decision makers. We present an index-based online algorithm for the problem, and derive an upper bound on the regret of this algorithm. Then, we conclude that our algorithm retains an instance-based regret of order O(log T/T), which is consistent with the classical MAB model. Further, some specific risk measures, namely, mean-deviation, shortfall and the discrete Kusuoka risk measure, are used to demonstrate the details of our framework. (C) 2020 Elsevier B.V. All rights reserved.

Short-term electricity price forecasting has received considerable attention in recent years. Despite this increased interest, the literature lacks a concrete consensus on the most suitable forecasting approach. This study reports an extensive empirical analysis that we conducted to evaluate the short-term price forecasting dynamics of different regions in the Swedish electricity market (SEM). We utilized several forecasting approaches ranging from standard conditional volatility models to wavelet-based forecasting. In addition, we performed out-of-sample forecasting and back-testing, and we evaluated the performance of these models. Our empirical analysis indicates that an ARMA-GARCH framework with the Student’s t-distribution significantly outperforms other frameworks. We only performed wavelet-based forecasting based on the MAPE. The results of the robust forecasting methods are capable of displaying the importance of proper forecasting process design, policy implications for market efficiency, and predictability in the SEM.

We introduce an original concept of the backroom effect for perishable products when the deterioration rate in a backroom is lower than that on retail shelves. With IoT-generated real-time information about the perishable products, this phenomenon has a significant impact on joint shelf-space and inventory decisions. We define the deterioration rate gap, formulate the perceived on-shelf product freshness, and describe the freshness-dependent demand distribution, with continuous backroom-shelf replenishment. Assuming that demand depends on both perceived freshness and shelf level, we develop a decision-making model that simultaneously determines the inventory replenishment policy and the shelf space allocation for multiple items. To facilitate the solution process, we propose a hybrid solution approach by combining genetic algorithm (GA) and variable neighbourhood search (VNS). The results provide a prioritised inventory policy for item selection that incorporates the deterioration improvement. The results of the performance analysis show that a policy considering the backroom effect achieves increased profit when the backroom/shelf deterioration gap increases. The optimal solutions for the problems with large backroom/shelf gap also show that the practitioner should increase the ordering quantity, which is contradictory to the outcome of traditional models.

Purpose Oil is the natural resource recognized as the most important source of revenue in oil-dependent countries and is most often referred to as being susceptible to corruption owing to its strategic importance. A major challenge in addressing and encountering the problems in complex social systems, such as corruption, is how to structure the problematic situation and how to capture mental models of the stakeholders involved in the situation, and also how to identify the systems behavior in response to various policy intervention attempts in the long run. This study aims to shed new lights on modeling and simulating corrupt system of the oil industry, as a complex social system needed to be structured according to social system theories principles. Design/methodology/approach Parsons theory is applied as a basic framework to capture the complexities of a corrupt system, dividing the system into political and structural, economic, legal and judicial and cultural and social sub-systems. Then soft system dynamics methodology, which is a combination of the two well-known methodologies, soft system methodology and system dynamics, is applied to model and simulate the complexities involved in the oil industry of Iran, which owns the second-largest oil reservoir in the world and its economy is much dependent on the oil revenue, struggles with corruption, and plans for a large amount of anti-corruption activities. Findings After simulating and calibrating the model, three groups of policies, namely, "reducing corruption opportunities," "reducing corruption demand," and "increasing anti-corruption capacity" are implemented in the model. As to the simulation results, due to the mutual inter-causality of opportunity and demand for corruption, individual application of each group of policies will not be helpful for long, rather a combination of policies will conduce to substantial improvements in declining corruption in the oil industry. Originality/value The developed model addresses the dynamics of the complex socio-economic system of corruption in the system of oil industry via modeling and simulation. The developed four-dimension system dynamics framework could be considered as a guidance for corruption modeling in general and as a basic model for corruption modeling of oil-dependent countries systems in particular.

In order to increase market share and enhance business competitiveness, comprehensive retail platforms (CRPs), such as Taobao.com and JD.com, are currently cooperating with social service platforms (SSPs), such as TikTok and Meiyou. Therefore, more research attention needs to be paid to such platform supply chains. To this end, this study develops stylized models to explore the impacts of the market power of an SSP and the precision marketing of a CRP on platform cooperation. Our major research findings include the following. First, we investigate the equilibrium strategy and find that if the CRPs commission rate is low (high), cooperation becomes the equilibrium strategy when the SSPs market power is low (high). Second, in most cases, market power will affect the equilibrium strategy with a change in the commission rate. However, in a certain range of commission rates, the equilibrium strategy remains unchanged. That is, market power has an "invalidation effect" on the equilibrium strategy. Finally, we find that as the commission rate increases, precision marketing reduces the willingness of supply chain members to implement platform cooperation. However, when the commission rate is low, precision marketing stimulates cooperation between platforms. The study results provide guidelines for improving the cooperation between CRPs and SSPs.

With more renewables on the Swedish electricity market, while decommissioning nuclear power plants, electricity supply increasingly fluctuates and electricity prices are more volatile. There is, hence, a need for securing the electricity supply before energy storage solutions become widespread. Electricity price fluctuations, moreover, affect operating income of nuclear power plants due to their inherent operational inflexibility. Since the anticipated new applications of hydrogen in fuel cell vehicles and steel production, producing hydrogen has become a potential source of income, particularly when there is a surplus supply of electricity at low prices. The feasibility of investing in hydrogen production was investigated in a nuclear power plant, applying Swedish energy policy as background. The analysis applies a system dynamics approach incorporating the stochastic feature of electricity supply and prices. The study revealed that hydrogen production brings alternative opportunities for large-scale electricity production facilities in Sweden. Factors such as hydrogen price will be influential and require in-depth investigation. This study provides guidelines for power sector policymakers and managers who plan to engage in hydrogen production for industrial applications. Although this study was focused upon nuclear power sources, it can be extended to hydrogen production from renewable energy sources such as wind and solar.

In order to eliminate the negative effects of customer strategic behaviour, retailers often adopt quick response or value-added services. While in a luxury market with conspicuous customers, retailers pricing decisions of these two strategies become more complicated. This paper studies a supply chain with a retailer serving a mixture of conspicuous and ordinary strategic customers. We develop three models so that the retailer provides (i) neither quick response nor value-added services; (ii) only quick response; (iii) only value-added services. Subsequently, we analyse the impacts of conspicuous customers on quick response and value-added services by pricing and strategy comparisons. The model further extends to the situation including both strategies. The results show that, firstly, when the proportion is less than a threshold, the retailer should adopt a low price strategy, and vice versa. Besides, the quick response could induce the retailer to adopt high price while value-added services inhibit it. Secondly, the customer conspicuous behaviour can motivate retailers to provide quick response and inhibit their value-added services. Finally, by observing the retailers decisions when they can adopt two strategies simultaneously, we find that the existence of quick response can amplify the benefits of value-added services.

In light of a circular economy, to encourage core returns, the remanufacturer charges a deposit and refund it to the customer based on quality inspection of cores. Generally, two types of classification errors exist and interact with each other during the inspection process: either low-quality cores are sorted as remanufacturable, or high-quality cores are sorted as non-remanufacturable. The remanufacturer needs to choose refund policies and determine a reasonable deposit value, considering customers potential responses. This paper firstly develops analytical solutions for these issues within a game theory framework. The effect of inspection information transparency is evaluated by comparing two settings: the information of inspection errors is available to customers or not. The study results show the advantage of inspection information transparency from the remanufacturers perspective. The analysis indicates the importance of avoiding overestimating customers payoff of products and the significance of inspection accuracy. The study also highlights that the salvage value of different cores significantly influences the remanufacturers profits, and the improvement of inspection accuracy does not necessarily reduce the customers return of low-quality cores.

Intelligent transformation of manufacturers requires smart logistics transformation collaboration, which improves competitiveness. In this study, we construct a Stackelberg game model based on the mutual influence and restriction in the relationship between a manufacturer and a logistics service provider (LSP) undergoing smart logistics transformation. We investigate whether cost-sharing (CS) or revenue-sharing (RS) contracts can coordinate the supply chain and suggest a hybrid CS-RS contract to improve performance. We find that, compared with decentralized options, CS and RS contracts achieve a higher level of smart logistics transformation. While the coordination and effectiveness of CS contracts are superior to those of RS contracts, neither can fully coordinate the supply chain. The proposed hybrid CS-RS contract allows the manufacturer to share the LSPs costs before the transformation and its partial revenue after transformation, so that the LSP can reduce its service charge, thereby achieving full supply chain coordination. (c) 2021 China Science Publishing & Media Ltd. Publishing Services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd.

As environmental issues attract more concern, shifting towards sustainable manufacturing that includes remanufacturing has become a strategic solution to enable a profitable business while improving environmental performance. The aim of this paper is to investigate the economic feasibility of remanufacturing at different supply chain locations for a robotic lawn mower manufacturer attempting to expand their business. Through a case study, five potential location categories were identified, of which two were deemed economically feasible: spare parts warehouse (OEM) and decentralized (dealers). The other three alternatives were deemed inferior in comparison, or only plausible, but identified as risky through a sensitivity analysis.

This paper investigates a multi-stage hybrid flow shop scheduling problem with challenging characteristics including lot sizing, calendar constraints and sequence-dependent setup times in a real-world printed circuit board (PCB) assembly shop. Besides, other characteristics such as unrelated parallel machines and stage skipping also complicate the problem. Such features make the scheduling problem very difficult to find an optimal or near optimal solution. To reduce the complexity of such a PCB scheduling problem, this study develops a hierarchical approach which decomposes the original problem into two highly coupled sub-problems including job sequencing and lot scheduling with lot sizing, and further proposes a two-stage ant colony algorithm with lot sizing to evolve best results in the makespan performance. Extensive computational experiments have been conducted to illustrate the superiority of the algorithm in terms of computational time and stability.

It is very common that retailers are storing and managing perishables of multiple types together. Due to chemical or biological reactions, the preservation period of some perishables (e.g., vegetables, fruits, fish, meats) either prolongs or shortens with the co-storage of other product types. Although this phenomenon is significant, it has not been mentioned in the perishable inventory literature. Therefore in this research, we first introduce the concept of cross-perishability. We then formulate an inventory model with a novel control variable of preservation effort that in turn affects the preservation period with cross-perishability when multiple product-types coexist. With an Internet of Things (IoT) sensor system as the background, this model takes the advantage of real time data, based on which the cross perishable effect, inventory characteristics and control policy can be analyzed. Our results indicate that an integrated decision making mechanism with consideration of the cross perishable effect should lead to an improved global mixed perishable inventory policy, in terms of reducing the deterioration cost, decreasing the inventory level, and improving the perishables quality. We prove the upper and lower bound conditions for the decision variables and utilize this result to facilitate the searching algorithm for a fast convergence to the feasible global optima for the non-linear problem with multiple product types and cross perishable effects. In conclusion, we offer managerial and policy implication for the perishable inventory system where the cross perishable effect should be seriously considered. (C) 2019 Elsevier B.V. All rights reserved.

Delivery time and delivery reliability are two top-level measures of delivery performance, and they both influence customers perception of service value. However, the classic queue-pricing literature emphasizes the former and ignores the latter. In order to bridge the gap between research and practice, this study addresses the interactive impact of price, delivery time, and delivery-reliability level on the equilibrium behaviour of rational customers and the optimal decisions of a revenue-maximizing service provider. We assume that the customers sensitivity to the delivery-reliability level is characterized by an increasing concave service value function. We model the operations of the service provider as an M/M/1 queue. Two cases are investigated: homogeneous customers and heterogeneous customers. For the homogeneous customers case, we analytically characterize the service providers optimal price, delivery time, and delivery reliability level decisions. We show how the service providers decisions on whether to provide faster or more reliable service are affected when different problem parameters are subject to variation. For instance, when customers become more sensitive to the delivery-reliability level, the service provider increases the delivery-reliability level at the expense of a longer delivery time. However, the optimal price may either increase or decrease depending on a benchmark value for the delivery-reliability level. For the heterogeneous customers case, our results suggest that when the potential arrival rate is sufficiently high, the service provider always benefits from markets with higher levels of customer heterogeneity. (C) 2018 Elsevier B.V. All rights reserved.

Purpose The purpose of this paper is to analyze the influencing factors of new logistics service product design (NLSPD) in China to establish a theoretical framework for the future development of the logistics industry. Design/methodology/approach The paper adopts the multi-case study method based on a sample of four Chinese logistics enterprises, in which the authors consider the logistics service maturity (LSM), a distinct characteristic of logistics enterprises. Findings NLSPD is directly related to the degree of supply-demand matching (SDM) and LSM. Customer demand, service capability and peer competition influence the performance of NLSPD through the SDM degree, whereas LSM moderates these influencing mechanisms. Moreover, the degree of SDM has a positive impact on LSM. Practical implications - The findings can help the managers of logistics enterprises and practitioners in the logistics industry understand the complexity of NLSPD. First, they should broaden and deepen their service offering to enhance the degree of LSM. Second, they should pay attention to the factors that affect SDM systematically. Finally, it is vital to balance the relationship between LSM and SDM. Originality/value NLSPD has become an important tool affecting the competitiveness and sustainability of logistics service enterprises. This is the first paper to propose a theoretical framework for NLSPD that considers the characteristic of the logistics industry. It clarifies the mechanisms of influencing factors, and contributes to the literature by filling the research gap.

In this study, we aim to explore the role of the involvement of suppliers while firms execute sustainable initiatives. We have based the entire study on a survey covering 101 Swedish manufacturers. The structural equation models of partial least squares are adopted to analyse their responses, examining the relationship among the constructs, stakeholders influence, sustainable practices, sustainable performance, and supplier involvement. We find that, in the firms, the effects of stakeholder influence on the sustainable practices is both significant and positive; the sustainable practices of sampled firms are to a great extent facilitating the sustainable performance. In addition, intensely participating in the initiatives related to environmental protection (e.g., cleaner production) by the suppliers, helps reinforce the relationship of sustainable practice and sustainable performance in the firms, however the moderating effects of suppliers involvement in economic and social activities is not significant. This has significant implications to firms decision regarding where to invest in sustainability. (C) 2019 Published by Elsevier Ltd.

Due to fierce competition in markets, recently, many airlines have faced the challenge of reducing channel distribution costs. However, channel distribution decisions are often made separately from inventory allocation decisions in practice. Thus, in this study, we propose a dynamic programming model to derive the optimal policy and investigate customer-shift behaviours in a problem setting with the above two issues combined. The numerical experiment results illustrate that introducing the channel distribution into the airline revenue system significantly improves the revenues and efficiently reduces the channel distribution costs. The improvement comes mainly from a better match between channels and fare classes and a subsequent risk reduction of revenue losses.

It is of importance for restaurants to identify their competitors to gain competitiveness. Meanwhile, opinion-rich resources like online reviews sites can be used to understand others opinion toward restaurant services. We thus propose a novel model to extract comparative relations from online reviews, and then construct three types of comparison relation networks, enabling competitiveness analysis for three tasks. The first network help restaurants analyze market structure for their positioning. The second network enables to identify top competitors using competitive index and dissimilarity index. The third network help restaurants identify strengths and weaknesses through aspects-comparison relation mining. Finally, the market environment is illustrated in a visual way according to the three types of networks. Experimental results reveal the effectiveness of the proposed competitiveness analysis using text analytics, which can identify top competitors and evaluate the market environment, as well as help the focal restaurant effectively develop a service improvement strategy.

In developing countries, coal power plants still play a major role in the power sector and they are considered as a major emission source of air pollution. Strict regulations have compelled the coal power plants to improve environmental performance by reducing carbon emissions and the emission of pollutants. However, due to cost disadvantages, the coal power plants often lack motivation to internalize environmental externalities through investing in green technology. This situation raises a question: is there any alternative to reduce pollutants in operations economically? With a focus on service supply as well as a consideration of government policies, this paper develops a model to investigate the opportunity of outsourcing a pollutant-reduction service to meet the environmental constraint. The service supply chain consists of a coal power plant (end user) and a pollutant-reduction service provider, with the former outsourcing the service to the latter. We study the policy for improving the profit of this service supply chain whereas the benefit allotment is adjusted through outsourcing price negotiation between the two partners. The results show that the green service outsourcing price is interrelated with the government incentive policy which defines the shares of the two partners. Our key contribution lies in integrating the complex factors affecting the supply chain collaboration such as green service, financial feasibility, environmental constraint, government policies, outsourcing price negotiation, and profit sharing. Our research findings have the following implications; considering environmental externalities, the government should motivate the collaboration between supply chain partners; the economic scale of output and sales price subsidy of electricity generation are the primary factors affecting the price of outsourcing green service and, consequently, the allotment of supply chain profits. The study results indicate the collaboration is potentially effective in improving environmental performance. (C) 2018 Elsevier Ltd. All rights reserved.

This paper studies a two-echelon logistics service supply chain (LSSC) composed of one logistics service integrator (LSI) and one functional logistics service provider (FLSP). We develop a two-period service capacity procurement model where market demand surges in the second period. The LSI, as the Stackelberg game leader, tends to be overconfident when market demand surges. The results show that when the demand surges in the second period, if the overconfident purchasing capacity of LSI cannot meet the market demand, the overconfidence behaviour will negatively affect LSI s optimal pricing. Besides, the overconfidence behaviour leads to the lowest service level of the FLSP in the second period under demand surge. However, such negative impacts can be reduced or even eliminated in certain conditions through the FLSP-led mechanism and the dynamic wholesale price mechanism. The numerical simulation and the case study from China are used to illustrate the model and draw some conclusions.

Energy policy has a vital impact on the investment in renewable energy capacities and on the decommissioning of traditional ones. Currently Sweden and Norway aim to expand the renewable electricity production by 26.4 TWh between 2012 and 2020, and subsequently to reduce CO2 emissions. To achieve this, the Swedish Energy Agency issues to renewable producers electricity certificates, which are sold on an open market to increase revenues. Meanwhile, the electricity is priced based on a marginal cost principle, and the price is highly reliant on the capacity profile and energy balance in the system, and consequently on the expanding and decommissioning decisions. The above price issues, together with the intermittent availability of renewable energy sources and the uncertainty of future fuel costs, will significantly affect the economic performance of the electricity producers. It is only after understanding the interaction of those factors that we can define companies business models for achieving a sustainable development in the electricity sector. This study applies a system dynamics approach and presents a model to integrate both strategic decisions such as capacity expansion/decommission, and operational features such as randomness and seasonal factors in electricity production. The model highlights the complex and nonlinear interaction of important factors in the electricity sector. The study results indicate that the energy policy should not be introduced in an isolated manner, but rather need to incorporate the incentives of renewables with other decisions such as nuclear decommission. Additionally, this study predicts an upcoming increase in electricity price, as well as a more volatile price after the capacity profile has been changed and dominated by hydro, biomass and wind. This study provides guidelines for policy makers and managers to make better-informed decisions for a healthy development of their businesses as well as of the entire electricity sector.

This paper studies the influence of the demand-supply environment on the capacity scheduling performance of the logistics service supply chain. According to the key characteristics of the demand-supply environment, the cases of five Chinese companies were introduced and cross-analysed, then research hypotheses were developed. After receiving 154 valid questionnaires and testing our hypotheses, some key conclusions were obtained. From the aspect of demand, there is a positive correlation between the customised levels of demand and the scheduling cost of logistics service integrators but a negative correlation between the customised levels of demand and the scheduling flexibility; From the aspect of supply, a higher self-support ratio of logistics source and a higher sourcing integrity of logistics service integrators will lead to a higher scheduling cost and a lower scheduling flexibility; a whole-process performance evaluation is a moderator, which will positively improve the impact of the whole process scheduling performance.

New technology is altering business strategies and innovation capabilities while increasing the possibilities of production and process innovation. Supply chain collaboration undertaken for the sake of sustainability is currently speeding up this process of change; a growing pool of research is exploring the links between sustainability collaboration and company performance on economic, environmental, and social metrics. It is a good time to review the literature to reveal what has been studied and what are the gaps in the current body of knowledge, and also to comment on what the future research agenda should include. For these purposes, the authors conducted a systematic literature review and a quantitative bibliometric analysis. Results indicate that research about supply chain collaboration for the purpose of sustainability is gaining growing attention in the business field; however, environmental and economic considerations still dominate the research, while there is a lack of consideration about social concerns such as child labor and personal development. In addition, the collaboration partners under investigation have mainly been the company and its customers and suppliers, whereas competitors and other horizontal collaboration partners have received little attention.

Negative impacts on environment such as carbon emissions and pollution resulting from the business activities of firms in a supply chain have attracted great attention worldwide. Hence, one of the crucial issues for supply chain management is the trade-off between economic objectives and environmental sustainability. This paper focuses on investigating the government policy incentive mechanism, with which supply chain members are motivated to work collaboratively to reduce carbon and pollutant emissions by investing in producing environmental-friendly products (EFP). Such a mechanism affects the transfer price through negotiation between the supply chain firms, and consequently it has an impact on the supply chains value transition and profit allocation. A collaborative supply chain decision-making framework is formulated with environmental constraints and carbon caps; its objective is to maximize the net present value of an integrated supply chain as well as satisfy the interests of its individual members. Our key contribution lies in exploring a decision-making mechanism for an environmentally sustainable supply chain that is jointly constrained by environmental carrying capacities and carbon caps, and also takes into account government policy incentives. The results show that collaboration between supply chain members plays a crucial role in improving their environmental performance, as the transfer price is determined through negotiations to share government subsidies to satisfy the individual interests of supply chain members while the level of pollutants and carbon emissions are in compliance with environmental standards.(C) 2016 Elsevier B.V. All rights reserved.

We study inventory rationing in a system with multiple demand classes and lost sales. It is assumed to have at most one outstanding order, resulting in two periods in an order cycle separated by the time of order release. We review the most related work by Melchiors (2001, PhD Thesis, University of Aarhus; 2003, International Journal of Production Economics 81-82, 461-468), and find that the existing approximated and optimal policies are not easy to obtain due to computational complexity. Also as the rationing issue before order release is not well addressed in literature, in this paper we have proved the static rationing being optimal. Furthermore in such a system with two distinct periods, the optimal rationing policy is a combination of a dynamic policy during the replenishment lead time and a static policy before order release. In order to make the rationing policies to be readily used in practice, we introduce two approximated methods for calculating the rationing levels in two periods, respectively. The results, in particular the combination of static and dynamic rationing, outperform the existing approximations in literature. In addition, the computation is obviously simplified due to the efficient algorithm of dynamic rationing and the explicit expressions of static rationing.

This study explored whether there are patterns linking sustainability practices and performance in the Swedish manufacturing industry. Meanwhile, the relationships between sustainability improvement practices and companies’ triple bottom line performance were investigated using survey data from Swedish manufacturing companies. Treating each sustainability practice and performance indicator as an individual item, factor analysis and cluster analysis were conducted to explore the potential patterns and relationships. The results indicated that the triple bottom line provides a valid outline for representing companies’ sustainability practices in the Swedish manufacturing industry. In terms of sustainability performance, the results showed that economic performance was often treated as a separate category in practice, whereas environmental sustainability and social sustainability were often combined. Process and product technology level was positively correlated with environmental performance and innovation performance. Economic, social, and environmental practices had positive correlations with performance in the respective area. Even though not all social and environmental practices directly improved companies’ economic performance, some social and environmental practices, such as education, individual development, and environmental health improvement, had an indirect effect and, thus, are deserving of specific attention. These selected practices often had a positive impact on product and process innovation, which could further improve companies’ economic performance.

The relationship between environmental management practices (EMPs) and company performance hasrecently been debated in literature and is of interest for both industrial managers and political decisionmakers.This paper investigates the relationship between EMPs and firm performance in manufacturingcompanies in Sweden, China and India. With the content analysis of Global Reporting Initiative (GRI)reports and financial reports of sample companies, the levels of EMPs and the companies’ financialperformances were coded. Further statistical assessment was conducted in order to identify patterns andcorrelations. The results indicate that only selected EMPs have been employed differently in threedifferent countries. Most EMPs clearly do not have a positive correlation with the financial performance;i.e. employing EMPs does not necessarily improve the economic consequence of companies. Nevertheless,a number of EMPs do have a strong correlation with improving innovation performance in variouscompanies. It is also interesting to note that a negative correlation exists between the Environmentalstandard for suppliers and Sales growth. This is possibly due to increasing operational costs and a delay inmarket acceptance. This research illustrates the possibility of using standard environmental data fromGRI reports as a resource for future studies of EMPs. In order to improve long-term financial performance,this study also suggests that innovation should gain a substantial amount of attention when EMPsare employed.

Core acquisition is essential for the success of remanufacturing business. To describe the current status of the quantitative research in Core Acquisition Management and to indicate possible future research directions, a literature review is conducted in this paper about the quantitative modeling in Core Acquisition Management research area. The activities included in Core Acquisition Management are categorized into topics such as acquisition control, forecasting return, return strategies, quality classification and reverse channel design. While most of the studies focus on acquisition control, studies on return strategies and return forecast are relatively limited. Furthermore, this paper analyzes the research papers according to the key assumptions such as, hybrid/non-hybrid remanufacturing systems, acquisition functions, quality classification methods and perfect/imperfect substitutions. In conclusion, studies based on the assumptions of non-hybrid remanufacturing systems and imperfect substitution should gain more attentions, since these situations frequently occur in practice but are less investigated in the existing literature. In addition, empirical validation of the various forms of the acquisition function (relations between acquisition incentives and acquisition volume) should be important for further investigations.

This study examines the moderating role of supplier involvement in the focal company’s sustainable initiatives. Survey methodology was used to collect data from 349 Swedish manufacturers. Partial least squares structural equation modeling was then applied to analyze the causal relationships and moderating effects. The results showed that there was a significant positive relationship between sustainable drivers and sustainable improvement practices within the focal company itself. The focal company’s sustainable improvement practices significantly contributed to its sustainable performance. Moreover, the high levels of supplier involvement in environment-related work significantly strengthened the relationship between the focal company’s sustainable practices and performance. This study contributes to the literature in the field of green supply chain management. The results indicate not only that a “win-win” opportunity exists for members of the Swedish manufacturing industry who implement sustainable practices, but also that organizational green capabilities can be strengthened by cooperating with suppliers through organizational learning.

Realizing the importance of remanufacturing for sustainable development due to the large scale of the economy and its increasing pressure on the environment, the Chinese government has been strongly promoting its remanufacturing industry since 2008. The objective of this paper is to identify the motives and barriers for remanufacturing in China. According to the survey conducted among remanufacturers in China, environmental and ethical responsibility, customer orientation and strategic advantage are the three most important motives, while customer recognition is the most serious barrier at present. This survey also shows that there are many differences between car part and machinery remanufacturers in China. For example, car part remanufacturers are more motivated by subsidies, at the same time, they are also more restricted by legislation, while lack of sales channels is a more serious barrier for the machinery remanufacturers. The differences exist partly due to the Chinese remanufacturing environment, for example the policies from different government departments that regulate the related industries. Suggestions for improving the remanufacturing industry, in particular from the policy makers’ perspective, are provided according to the survey results.

Acquisition of cores is important for the success of remanufacturing business, but evaluating the value of cores is difficult due to many uncertain issues in the remanufacturing system. In this paper, we examine the value of cores using the real option valuation (ROV) approach, which well captures the production flexibility and represents different operations options in remanufacturing. First, in a system where the demand of remanufactured products is low, we focus on the uncertainty of price. We compare the cases where disposing cores occurs only at the expiration time and before that. The model also identifies under which circumstances disposing core early brings in more benefit. Furthermore, we study a remanufacturing system where demand and return are both uncertain. In this case, a spread option is used for evaluating the marginal value of obtaining additional cores. This approach also brings the advantage of linking the correlation between demand and return, which in fact is often exhibited in remanufacturing. The numerical experiments indicate that this correlation has an impact on collecting policies. This study illustrates the possibility of using ROV for core pricing modelling, and the study results also provide some managerial insights in managing returned cores.

Cores are essential for the remanufacturing business. The lack of cores with proper quality is reported as a highly ranked factor that limits both third party and OEM (Original Equipment Manufacturer) remanufacturers. To encourage the return of quality cores, in practice it is common for OEMs to charge a certain amount of deposit, and refund it fully or partially depending on the quality of cores during the return process. Furthermore, the core quality varies and leads to different remanufacturing costs. The core refund policy should reflect such differences, in order to encourage the customers to return the cores with “correct” quality. In this paper, we propose three refund policies and develop profit maximization model for the remanufacturer. Under the assumption of quality following a uniform distribution, we develop analytical solutions for the refund policies and principles for quality partition. Numerical examples indicate that the customers׳ valuation of core is an important factor influencing the return rates and the economics performance of the system as well. Multiple refund policy with a small number of quality classes already brings major advantages, even with a market where the competition for collecting cores is relatively high. The study is also extended to the cases that core quality follows an adjusted normal distribution. Credit refund policies are also studied for comparison purpose.

Whether the corporate social performance affects the financial performance is still unclear in many manufacturing companies. We commonly expect, on one side, that profitable corporations have stronger incentives to reveal information on social performance in order to improve their publicity; on the other hand, companies may face the fear of rising costs due to Corporate Social Responsibility (CSR) activities. With increasing concerns of CSR, it is timely to investigate the relationship between the disclosure of corporate social performance and financial performance. In this paper with the above study objective, we use Global Reporting Initiative (GRI) reports of 75 sample companies, collect evidences by applying the method of structured content analysis of the cases and attempt to identify this relationship. The corporate social performance is measured by the indicators according to the GRI guidelines, i.e. within the categories of Labor practices and decent work, Human Rights, Society as well as Product responsibility. Financial performance is measured by return on equity, sales growth and cash flow/sales ratio. Using statistical evaluation methods, our results indicate that the categories of Human Rights, Society as well as Product responsibility display a significant and positive correlation with the return on equity. Same conclusion also holds for many CSR indicators. Nevertheless, when examining the CSR practices across different manufacturing sectors, we have not observed significant differences. The study results are important for understanding the development and implementation of CSR practices in the manufacturing industry.

This paper examines a periodic-reviewed lot sizing problem with random yields, disruptions and limited inventory capacity. To characterise the continuous production, an additive random yield model is considered rather than a multiplicative one. Disruptions cause breakdowns to production. Inventory capacity is included since the production has to be shut down when the inventory buffer is full. Both disruptions and shutdowns lead to a start-up cost and a stochastic lead time to recover the production. These compound factors of uncertainty are encountered in practical planning decisions in process industries. We review the existing random yield models, which are then compared with the additive model. With a linear production cost, the additive model has an order-up-to policy to be optimal. Disruptions deteriorate the expected actual production quantity and the fill-rate dramatically, even though the optimal order-up-to level increases compared with the cases of no disruption. Considering inventory capacity makes the problem to be a non-convex dynamic programming problem. Numerical analysis shows that the performance is dramatically deteriorated when the inventory capacity is rather tight, which indicates the importance of selecting a proper inventory capacity to reduce the negative impacts and avoid redundant investment on capacity. Moreover, the start-up cost plays an important role in determining the level of inventory capacity.

Managers and researchers are increasingly interested in the factor that logistics enterprise competitiveness(LEC) has significant effects on the development of Chinese logistics enterprises, especially in view of theenterprise life cycle. This paper investigates the contents and evolution of the composing factors of LEC inChina by a survey.With Statistical Product and Service Solutions (SPSS 15.0) software, the factor analysismethod is used to determine the effects of each factor on LEC. Furthermore, the comparative analysismethod is applied to compare the composing factors of LEC in different types of logistics enterprises andat different enterprise life cycle stages. The results show that factors of LEC according to their descendingimportance level are corporate capabilities, corporate resources, and dynamic mechanism. Three kindsof corporate capabilities (financial management capability, logistics risk control capability, and humanresource management capability) and two kinds of corporate resources (corporate human resources andcorporate culture) have the greatest influence on the development of LEC, but in reality have poor practicalperformance, and hence deserve more consideration from the enterprises.