Li Zhang , Tingting Chen , Baozhen Yao , Bin Yu , Yunpeng Wang
{"title":"Routing and charging scheduling for the electric carsharing system with mobile charging vehicles","authors":"Li Zhang , Tingting Chen , Baozhen Yao , Bin Yu , Yunpeng Wang","doi":"10.1016/j.omega.2024.103211","DOIUrl":"10.1016/j.omega.2024.103211","url":null,"abstract":"<div><div>Electric carsharing systems are expected to be an optional alternative to private vehicles for decreasing the urban traffic congestion and emissions. However, the temporal and spatial imbalance of the charging demand of shared electric vehicles adds to the managerial complexity of electric carsharing systems. This paper integrates mobile charging vehicles into the electric carsharing system to address this imbalance. Mobile charging vehicles can dwell at stations to provide elastic charging capacity, and thereby decrease both the waiting time of shared electric vehicles at busy stations and the investments in fixed charging piles at suburban stations. In this paper, a mixed integer linear programming formulation is proposed based on a time-space network, in which the routes of shared electric vehicles, charging schedules of shared electric vehicles, and routes of mobile charging vehicles are optimized simultaneously. Then, an algorithm based on Lagrangian relaxation is proposed. Specifically, the proposed formulation is decomposed into three independent subproblems. We propose three exact algorithms for these subproblems, and a tailored multistep repair algorithm is designed to generate feasible solutions. A case study in Hefei, China demonstrates the performance of the proposed algorithm and the effects of the number of SEVs, the number of MCVs, the number of fixed charging piles, trip component, battery capacity, and revenue on the operation of the electric carsharing system.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"131 ","pages":"Article 103211"},"PeriodicalIF":6.7,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142552347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Accurate preference-based method to obtain the deterministically optimal and satisfactory fairness-efficiency trade-off","authors":"Liming Yao , Zerui Su , Hao-Chun Lu","doi":"10.1016/j.omega.2024.103214","DOIUrl":"10.1016/j.omega.2024.103214","url":null,"abstract":"<div><div>The resource allocation problem is a classic multi-objective challenge, particularly when balancing the fairness-efficiency trade-off. To achieve a deterministically optimal and satisfactory solution, researchers frequently employ preference-based methods, including selecting among Pareto solutions based on the decision-maker's a posteriori preference and using deterministic models incorporating a priori preferences. In this study, we address two main challenges—specifically, (1) the limitations in measuring the abstract concepts of fairness and efficiency and (2) finding a deterministically optimal and satisfactory balance between fairness and efficiency. We apply a Gini impurity index derived from the classification and regression tree to calculate fairness, ensuring the Gini index function's differentiability. Additionally, we unify the scales of fairness and efficiency to facilitate calculation. Using accurate preference information, we employ the extended interval goal programming method to solve the model and achieve a deterministically optimal and satisfactory solution. The comparative analysis results demonstrate that our model (1) efficiently addresses the real-world water resource allocation problem concerning the fairness-efficiency trade-off; and (2) generates fewer penalties, with an average improvement ratio of 8% in the case study, using more refined penalty functions that align closer to the decision-maker's real and nonlinear preferences.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"131 ","pages":"Article 103214"},"PeriodicalIF":6.7,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142533334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kaili Li , Song Yao , Yongjian Li , Fangcheng Tang , Zhongbin Wang
{"title":"Deliberate shortage in live-streaming commerce","authors":"Kaili Li , Song Yao , Yongjian Li , Fangcheng Tang , Zhongbin Wang","doi":"10.1016/j.omega.2024.103201","DOIUrl":"10.1016/j.omega.2024.103201","url":null,"abstract":"<div><div>Live-streaming commerce has gained significant traction in recent years as an additional channel employed by online retailers to engage consumers in real-time interactions. However, it is essential to highlight the growing prevalence of limited sales as a popular marketing strategy within these live-streaming channels, resulting in an inability to fulfill all consumer demands. Surprisingly, this phenomenon has gone largely unnoticed in previous literature. This paper aims to bridge this gap by delving into the impact of product shortages within the realm of live-streaming commerce. To accomplish this objective, we introduce a stylized model that captures the strategic interactions between online retailers and consumers within live-streaming channels featuring rationed product availability. Our findings reveal that the online retailer’s profit exhibits a unimodal trend concerning the quantity of products offered in the live-streaming channel when the product value falls within a non-extreme range. In simpler terms, deliberately limiting product availability in live-streaming commerce can lead to significantly higher profits, incentivizing retailers to implement rationing strategies. Moreover, contrary to conventional expectations that consumers anticipate a greater supply of products than the retailer intends to provide, we uncover that consumers expect a lower quantity when the potential product value is relatively small. Finally, our research highlights that while live-streaming channels attract consumers with high patience, encouraging their engagement, impatient consumers who favor traditional online channels may face long-term adverse effects due to the retailer’s strategic pricing response. We validate the robustness of our main findings by exploring various extensions, such as the influence of strategic waiting behavior, advertising effects and enhanced perceived product value.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"131 ","pages":"Article 103201"},"PeriodicalIF":6.7,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142533335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Miłosz Kadziński , Michał Wójcik , Mohammad Ghaderi
{"title":"From investigation of expressiveness and robustness to a comprehensive value-based framework for multiple criteria sorting problems","authors":"Miłosz Kadziński , Michał Wójcik , Mohammad Ghaderi","doi":"10.1016/j.omega.2024.103203","DOIUrl":"10.1016/j.omega.2024.103203","url":null,"abstract":"<div><div>We adopt an experiment-oriented perspective to investigate two essential characteristics – expressiveness and robustness – of multiple criteria sorting methods. We focus on the approaches from the family of UTADIS, learning the parameters of a value-driven threshold-based model from the Decision Maker’s assignment examples. Even if the considered properties are crucial for the methods’ reliability and usefulness in real-world scenarios, their verification through explicit numerical tests has been so far neglected. On the one hand, expressiveness captures the models’ flexibility to reproduce different preferences, including simple and complex ones, meaningfully and accurately. On the other hand, robustness reflects the ability to deliver valid recommendations and ensure proper conclusiveness given the multiplicity of compatible preference model instances. We consider different variants of UTADIS, from assuming monotonic and preferentially independent criteria to more advanced settings that relax the monotonicity constraints or represent interactions. The experimental results capture the trade-off between the considered quality dimensions, indicating that richer models are characterized by greater expressiveness and lesser robustness. We also formulate a comprehensive framework indicating when some variant should be used, given the nature of supplied preferences or problem characteristics. These findings aid decision analysts in making robust recommendations in different contexts and help refine preference modeling assumptions. The framework’s practical use is illustrated in a case study involving sorting mobile phone models into pre-defined preference-ordered classes.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"131 ","pages":"Article 103203"},"PeriodicalIF":6.7,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142533332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Brand extension strategy in the presence of carbon tax regulation policy and social influence","authors":"Pin Zhou , He Xu , Xu Liu , Dan Gao","doi":"10.1016/j.omega.2024.103210","DOIUrl":"10.1016/j.omega.2024.103210","url":null,"abstract":"<div><div>Brand extension is a common marketing strategy used to capture a competitive advantage in the fashion industry and often causes social influence between the parent and sub-brands. On the one hand, sub-brand consumers are more willing to buy products when the parent brand sells well. On the other hand, the parent brand consumers’ purchase intention decreases when the sub-brand product sells too much. The fashion industry also contributes considerably to global carbon emissions. To reach sustainable development goals, governments impose carbon taxes. This paper analyzes how social influence and carbon tax regulations can affect a monopolistic firm’s brand extension strategy. The analytical results show that the firm extends from the parent brand to the sub-brand when the magnitude of social influence is not strong in the absence of a carbon tax, as the market expansion effect dominates the cannibalization effect. When the regulator imposes a carbon emissions tax, the range is further narrowed of the social influence that allows the firm to benefit from brand extension strategy because of the cost effect. Counterintuitively, the brand extension strategy can force the regulator to lower the tax price. Moreover, our findings reveal that social influence exerts an inverse impact on the regulator’s tax pricing decisions, contingent upon the extent of the parent brand’s brand power advantage. Carbon tax regulation hurts the firm and consumer surplus, but benefits the environment and social welfare. Additionally, we reaffirm the robustness of our findings under conditions of asymmetry in the intensity of social influence and different pollution damage functions. Intriguingly, we find that the firm can mitigate the negative cannibalization effect by selling its sub-brand products through a downstream retailer.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"131 ","pages":"Article 103210"},"PeriodicalIF":6.7,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142441808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jie Gao, Chunguo Fan, Ting Liu, Xiuran Bai, Wenyong Li , Huimin Tan
{"title":"Embracing market dynamics in the post-COVID era: A data-driven analysis of investor sentiment and behavioral characteristics in stock index futures returns","authors":"Jie Gao, Chunguo Fan, Ting Liu, Xiuran Bai, Wenyong Li , Huimin Tan","doi":"10.1016/j.omega.2024.103193","DOIUrl":"10.1016/j.omega.2024.103193","url":null,"abstract":"<div><div>This paper aims to enhance the understanding and prediction of stock market behavior during unexpected events like the COVID-19 pandemic, with a specific focus on the role of market attention, social media sentiment indicators, and the development and evolution of unexpected events. We highlight that the common trading and technical indicators used in forecasting the stock index futures prices often overlook investor sentiment and pandemic-related data, which can be instrumental in predicting stock market behavior during significant emergencies. In response, we propose a multi-faceted approach that incorporates these overlooked factors. First, we enhance the predictive index system by integrating investor sentiment, derived from stock message board commentary, and investor behavior influenced by the development and evolution of the pandemic. This innovative approach refines our model's predictive capabilities and is validated through comparative analysis. Second, we introduce a hybrid framework for predicting stock index futures closing prices. By decomposing the closing price series into long-term trends, cyclical variations, and random fluctuations, we create a more nuanced forecast. Each component is predicted separately using appropriate time-series algorithms, improving the overall predictive accuracy and offering generalizability and scalability. Third, we devise a dynamic trading strategy that recognizes pandemic-related data, evolving over time, as a pivotal factor. This strategy is adaptable to evolving market conditions, and our experimental evidence demonstrates its effectiveness in yielding higher returns and reducing associated risks. Our findings underline the importance of incorporating investor sentiment and pandemic-related data into stock market predictions, thus offering a more comprehensive and accurate approach to market forecasting and risk management.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"131 ","pages":"Article 103193"},"PeriodicalIF":6.7,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142533333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Live streaming channel and product assortment with both national and store brand products","authors":"Qiuyan Chen , Xin Yan , Yiwen Bian , Xiaohua Han","doi":"10.1016/j.omega.2024.103212","DOIUrl":"10.1016/j.omega.2024.103212","url":null,"abstract":"<div><div>To counteract the fierce competition in the online retailing market, retailers are increasingly adopting live streaming selling model and introducing store brand product to enhance their competitiveness. In this context, we attempt to examine whether and when a retailer should launch a live streaming channel. If launched, we further investigate how the retailer should assort both national and store brand products across available channels. To delve into these questions, we consider a supply chain consisting of a manufacturer and an online retailer, where the retailer resells the manufacturer's national brand product and also sells a store brand product. We examine the retailer's optimal channel strategy and product assortment strategy by considering six scenarios, differentiated by whether introducing the live streaming channel and various product assortment tactics. Our findings indicate that as long as the fixed setup cost of the live channel is relatively low, the retailer will always introduce a live streaming channel. The retailer's optimal assortment of both products across channels highly depends on the consumers’ additional value derived from the live streaming channel and the perceived quality of the store brand product. We also find that, the retailer's optimal channel strategy and product assortment may not always benefit the manufacturer, but there exist conditions that can create win-win situations for both players. Our study further shows that if the retailer launches the live streaming channel at the start, it may not always be necessary to introduce the store brand product under certain conditions.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"131 ","pages":"Article 103212"},"PeriodicalIF":6.7,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142446031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Finding robustly fair solutions in resource allocation","authors":"Özlem Karsu, İzzet Egemen Elver, Tuna Arda Kınık","doi":"10.1016/j.omega.2024.103208","DOIUrl":"10.1016/j.omega.2024.103208","url":null,"abstract":"<div><div>In this study, we consider resource allocation settings where the decisions affect multiple beneficiaries and the decision maker aims to ensure that the effect is distributed to the beneficiaries in an equitable manner. We specifically consider stochastic environments where there is uncertainty in the system and propose a robust programming approach that aims at maximizing system efficiency while guaranteeing an equitable benefit allocation even under the worst scenario. Acknowledging the fact that the robust solution may lead to high efficiency loss and may be over-conservative, we adopt a parametric approach that allows controlling the level of conservatism and present the decision maker alternative solutions that reveal the trade-off between efficiency and the degree of conservatism when incorporating fairness. We obtain tractable formulations, leveraging the results we provide on the properties of highly unfair allocations. We demonstrate the usability of our approach on project selection and shelter allocation applications.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"131 ","pages":"Article 103208"},"PeriodicalIF":6.7,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142441807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yan Lu , Junyi Lin , Shupeng Huang , Jianghang Chen
{"title":"On the bullwhip behaviour of a hybrid manufacturing and remanufacturing system under autocorrelated demand and returns","authors":"Yan Lu , Junyi Lin , Shupeng Huang , Jianghang Chen","doi":"10.1016/j.omega.2024.103209","DOIUrl":"10.1016/j.omega.2024.103209","url":null,"abstract":"<div><div>This study explores the bullwhip behaviour of a hybrid manufacturing-remanufacturing system, replenished by the order-up-to policy, under auto-correlated autoregressive and integrated moving average (ARIMA) demand and corrected returns. The phenomena of demand auto-correlation are common in various industries such as automobile, beverage, and fruit and vegetables industries. However, only first-order vector autoregressive (VAR(1)) and independent and identically distributed (i.i.d.) process have been studied in the context of closed loop supply chains (CLSCs) system dynamics. Therefore, by using <span><math><mi>z</mi></math></span>-transform and discrete-time simulation, we explore bullwhip and inventory variance under i.i.d, AR (1), first-order moving average (MA(1)) and first-order autoregressive and moving average (ARMA(1,1)) demand processes. It is found that, for products that have autoregressive demand characteristics, bullwhip decreases with the autoregressive demand parameter, while autoregressive return parameter has a U-shaped impact on the bullwhip. For those with moving average demand patterns, bullwhip increases with the moving average demand parameter and decreases with the moving average return parameter. Also, system parameters including return rate, inventory proportional controller and forecasting smoothing not only directly impact on bullwhip and inventory variance, but also act as the <em>moderator</em> in influencing the relationship between demand processes and bullwhip/inventory variance. These findings imply important managerial implication to control the bullwhip costs associated with products characterised by both autoregressive and moving average demand processes.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"131 ","pages":"Article 103209"},"PeriodicalIF":6.7,"publicationDate":"2024-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142572356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Adjustable robust optimization approach for SVM under uncertainty","authors":"F. Hooshmand, F. Seilsepour, S.A. MirHassani","doi":"10.1016/j.omega.2024.103206","DOIUrl":"10.1016/j.omega.2024.103206","url":null,"abstract":"<div><div>The support vector machine (SVM) is one of the successful approaches to the classification problem. Since the values of features are typically affected by uncertainty, it is important to incorporate uncertainty into the SVM formulation. This paper focuses on developing a robust optimization (RO) model for SVM. A key distinction from existing literature lies in the timing of optimizing decision variables. To the best of our knowledge, in all existing RO models developed for SVM, a common assumption is that all decision variables are decided before the uncertainty realization, which leads to an overly conservative decision boundary. However, this paper adopts a different strategy by determining the variables that assess the misclassification error of data points or their fall within the margin post-realization, resulting in a less conservative model. The RO models where decisions are made in two stages (some before and the rest after the uncertainty resolution), are called adjustable RO models. This adjustment results in a three-level optimization model for which two decomposition-based algorithms are proposed. In these algorithms, after providing a bi-level reformulation, the model is divided into a master-problem (MP) and a sub-problem the interaction of which yields the optimal solution. Acceleration of algorithms via incorporating valid inequalities into MP is another novelty of this paper. Computational results over simulated and real-world datasets confirm the efficiency of the proposed model and algorithms.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"131 ","pages":"Article 103206"},"PeriodicalIF":6.7,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142438247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}