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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 informat...

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.

Background Mutations in the XPR1 gene are associated with primary familial brain calcifications (PFBC). All reported mutations are missense and inherited as an autosomal dominant trait. PFBC patients exhibited movement disorders, neuropsychiatric symptoms, and other associated symptoms with diverse severity, even within the same family. Materials and methods We identified and enrolled a patient with PFBC. Clinical data were comprehensively collected, including the age of onset, seizure types and frequency, trigger factors of paroxysmal dyskinesia, response to drugs, and general and neurological examination results. Whole-exome sequencing (WES) was performed to detect pathogenic variants. We further systematically reviewed the phenotypic and genetic features of patients with XPR1 mutations. Results The patient showed bilateral calcification involving basal ganglia and cerebellar dentate. Clinically, he presented as paroxysmal kinesigenic dyskinesia with infantile convulsions (PKD/IC) with favorable outcome. We identified a compound heterozygous XPR1 mutation (c.786_789delTAGA/p.D262Efs*6, c.1342C>T/p.R448W), which were inherited from unaffected parents respectively. Further literature review shows a wide range of clinical manifestations of patients with XPR1 mutations, with movement disorders being the most common. Conclusions This is the first report of biallelic mutations in XPR1. The findings suggest for the first time a possible link between PKD/IC and XPR1 mutations.

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 het erogeneity 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/). Funding Agencies|Familjen Kamprads Stiftelse [20200103]

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.

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 supplier's involvement in economic and social activities is not significant. This has significant implications to firms' decision regarding where to invest in sustainability.

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.

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 provider’s optimal price, delivery time, and delivery-reliability level decisions. We show how the service provider’s 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.

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.

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. We conduct an extensive empirical analysis 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.

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. Funding Agencies|National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [71904021]; Social Science Planning Project of Chongqing [2019QNGL27]; Chunhui Plan of the Ministry of Education of the Peoples Republic of China [CQ2019001]; Natural Science Foundation of Chongqing, ChinaNatural Science Foundation of Chongqing [cstc2020jcyj-msxmX0164]; Project of Science and Technology Research Program of Chongqing Municipal Education Commission of China [KJQN201900830]; Key Project of Special Research regarding Response to Major Public Health Emergency of Chongqing Technology and Business University [ctbuyqzx01]; China Scholarship CouncilChina Scholarship Council [202008500051]; Scientific Research Startup Foundation for Introduction of Advanced Talents of Chongqing Technology and Business University [1955011]; Research Project of Chongqing Technology and Business University [1951025]; MOE Layout Foundation of Humanities and Social Sciences [20YJA630079]; International Science and Technology Innovation Cooperation Project of Sichuan Provice [20GJHZ0039]

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.