In the constantly evolving transportation and mobility industry, objective and reliable decision‐support systems (DSS) are crucial for addressing complex issues such as transit planning, mode selection, and policy formulation. This paper presents multiactor multicriteria analysis plus agent‐based modeling (MAMCABM), a novel framework that combines multiactor multicriteria analysis (MAMCA) and agent‐based modeling (ABM) to provide a comprehensive DSS. MAMCA excels in facilitating stakeholder‐centric evaluations, while ABM, enhanced by data analytics, adeptly models intricate, interactive systems. The combination of MAMCA and ABM enhances adaptability and precision in decision making. This integration utilizes data analytics and optimization algorithms to provide solutions that consider multifaceted criteria and diverse stakeholder perspectives in dynamic and uncertain contexts. The study outlines the mathematical underpinnings of MAMCABM and offers a practical guide for its implementation. The framework's efficacy is demonstrated through an empirical investigation that addresses mobility challenges in the Brussels Capital Region of Belgium. Compared to the previous study, this approach leverages simulated quantitative data alongside qualitative judgments from stakeholders. The integration of a consensus‐reaching algorithm further enhances the robustness of outcomes and effectively addresses uncertainties.
{"title":"The MAMCABM framework for the evaluation of mobility decision‐making problems: theory and practice","authors":"He Huang, Shiqi Sun, Koen Mommens, Cathy Macharis","doi":"10.1111/itor.13544","DOIUrl":"https://doi.org/10.1111/itor.13544","url":null,"abstract":"In the constantly evolving transportation and mobility industry, objective and reliable decision‐support systems (DSS) are crucial for addressing complex issues such as transit planning, mode selection, and policy formulation. This paper presents multiactor multicriteria analysis plus agent‐based modeling (MAMCABM), a novel framework that combines multiactor multicriteria analysis (MAMCA) and agent‐based modeling (ABM) to provide a comprehensive DSS. MAMCA excels in facilitating stakeholder‐centric evaluations, while ABM, enhanced by data analytics, adeptly models intricate, interactive systems. The combination of MAMCA and ABM enhances adaptability and precision in decision making. This integration utilizes data analytics and optimization algorithms to provide solutions that consider multifaceted criteria and diverse stakeholder perspectives in dynamic and uncertain contexts. The study outlines the mathematical underpinnings of MAMCABM and offers a practical guide for its implementation. The framework's efficacy is demonstrated through an empirical investigation that addresses mobility challenges in the Brussels Capital Region of Belgium. Compared to the previous study, this approach leverages simulated quantitative data alongside qualitative judgments from stakeholders. The integration of a consensus‐reaching algorithm further enhances the robustness of outcomes and effectively addresses uncertainties.","PeriodicalId":49176,"journal":{"name":"International Transactions in Operational Research","volume":"3 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study examines how smart food‐sharing platforms (SFSP) can help reduce food waste and suggests a method for using smart contracts to share extra food among different partners effectively. For smart contracts to work automatically and prevent food wastage, artificial intelligence systems can recognize how smart clauses should be executed. This will involve analyzing several factors like the selling price, expiration dates, offers from other partners, transport costs, wholesale price, shelf life, donation rates, and demand rates. The findings indicate that adopting an SFSP is an efficient solution for preemptively adopting redistribution strategies and improving social outcomes through donations as well as achieving positive environmental outcomes through reduced waste. However, we also identify cases in which reducing food waste to achieve social sustainability may negatively impact economic performance.
{"title":"Smart food‐sharing platforms for social sustainability: a heuristic algorithm approach","authors":"Behzad Maleki Vishkaei, Pietro De Giovanni","doi":"10.1111/itor.13543","DOIUrl":"https://doi.org/10.1111/itor.13543","url":null,"abstract":"This study examines how smart food‐sharing platforms (SFSP) can help reduce food waste and suggests a method for using smart contracts to share extra food among different partners effectively. For smart contracts to work automatically and prevent food wastage, artificial intelligence systems can recognize how smart clauses should be executed. This will involve analyzing several factors like the selling price, expiration dates, offers from other partners, transport costs, wholesale price, shelf life, donation rates, and demand rates. The findings indicate that adopting an SFSP is an efficient solution for preemptively adopting redistribution strategies and improving social outcomes through donations as well as achieving positive environmental outcomes through reduced waste. However, we also identify cases in which reducing food waste to achieve social sustainability may negatively impact economic performance.","PeriodicalId":49176,"journal":{"name":"International Transactions in Operational Research","volume":"25 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
American options are one of the most traded instruments in the financial markets. However, pricing them is challenging because of the early exercise possibility. We propose a robust pricing method based on nonlinear regression over a representative set of “exact” pricing instances obtained via a binomial lattice. Our “power approximation” approach is inspired from the literature on the well‐known periodic review inventory system. Our objective is to develop a closed‐form approximation for pricing American options that performs well on accuracy, computational efficiency (speed), and simplicity. Our results include developing a large set of “exact” American option premiums and critical stock price (indicating when to exercise the option) over a carefully designed grid with parameter values, which are common in practice. In addition, we compile the literature for existing American option pricing approximations and identify suitable ones. These approximations serve two purposes: (i) providing a starting point for our approximations and (ii) developing a benchmark for our work. We develop two closed‐form approximations for the critical stock price, and premium of an American put option, which perform very well with a median error below 0.45% for both.
{"title":"Power approximation for pricing American options","authors":"Noura El Hassan, Bacel Maddah","doi":"10.1111/itor.13540","DOIUrl":"https://doi.org/10.1111/itor.13540","url":null,"abstract":"American options are one of the most traded instruments in the financial markets. However, pricing them is challenging because of the early exercise possibility. We propose a robust pricing method based on nonlinear regression over a representative set of “exact” pricing instances obtained via a binomial lattice. Our “power approximation” approach is inspired from the literature on the well‐known periodic review inventory system. Our objective is to develop a closed‐form approximation for pricing American options that performs well on accuracy, computational efficiency (speed), and simplicity. Our results include developing a large set of “exact” American option premiums and critical stock price (indicating when to exercise the option) over a carefully designed grid with parameter values, which are common in practice. In addition, we compile the literature for existing American option pricing approximations and identify suitable ones. These approximations serve two purposes: (i) providing a starting point for our approximations and (ii) developing a benchmark for our work. We develop two closed‐form approximations for the critical stock price, and premium of an American put option, which perform very well with a median error below 0.45% for both.","PeriodicalId":49176,"journal":{"name":"International Transactions in Operational Research","volume":"4 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study delves into the interaction between hybrid financing and asymmetric demand information within a dual‐channel supply chain. In this setup, the supplier directly sells to customers and also through a capital‐constrained retailer. We investigate a unique financing approach involving a blend of bank loans and supplier equity investment to support the retailer's operational (procurement and marketing) activities. Analyzing the equilibrium strategies under both symmetric and asymmetric information settings yields intriguing insights. In the case of symmetric information, we find that the retailer's equilibrium order quantity decreases with the potential market size under hybrid financing, contrary to traditional notions. When asymmetric information is present, a higher acceptance of supplier equity investment by the retailer tends to lead to order quantity distortion downward, increasing signaling costs. Furthermore, a greater proportion of supplier equity investment prompts the retailer to order more products, ultimately boosting profits for both the retailer and supplier. This suggests that supplier equity investment can enhance supply chain efficiency and alleviate the double marginalization effect.
{"title":"Hybrid financing in a dual‐channel supply chain with asymmetric demand information","authors":"Baofeng Zhang, Shuang Xiao","doi":"10.1111/itor.13541","DOIUrl":"https://doi.org/10.1111/itor.13541","url":null,"abstract":"This study delves into the interaction between hybrid financing and asymmetric demand information within a dual‐channel supply chain. In this setup, the supplier directly sells to customers and also through a capital‐constrained retailer. We investigate a unique financing approach involving a blend of bank loans and supplier equity investment to support the retailer's operational (procurement and marketing) activities. Analyzing the equilibrium strategies under both symmetric and asymmetric information settings yields intriguing insights. In the case of symmetric information, we find that the retailer's equilibrium order quantity decreases with the potential market size under hybrid financing, contrary to traditional notions. When asymmetric information is present, a higher acceptance of supplier equity investment by the retailer tends to lead to order quantity distortion downward, increasing signaling costs. Furthermore, a greater proportion of supplier equity investment prompts the retailer to order more products, ultimately boosting profits for both the retailer and supplier. This suggests that supplier equity investment can enhance supply chain efficiency and alleviate the double marginalization effect.","PeriodicalId":49176,"journal":{"name":"International Transactions in Operational Research","volume":"15 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Online review sites play a crucial role in shaping consumer purchasing decisions, making the analysis of customer feedback essential for businesses. Given the complexity of these reviews, often including both quantitative and qualitative data, advanced analytical frameworks are necessary. To this end, this paper introduces an integrated framework for customer feedback analysis, combining aspect‐based sentiment analysis, multicriteria decision‐making, and a fuzzy rule‐based approach. The proposed system effectively processes both textual and numerical data from online reviews, enabling the extraction of actionable insights. To demonstrate its practical utility, we apply it to a real‐world dataset from a major European airline. The results illustrate the framework's effectiveness in identifying key factors influencing customer satisfaction and pinpointing areas needing improvement. Additionally, data‐driven recommendations are provided to support business decision‐making and enable the customization of products and services to better meet customer expectations.
{"title":"Extracting knowledge from customer reviews: an integrated framework for digital platform analytics","authors":"Anastasios Kyriakidis, Stelios Tsafarakis","doi":"10.1111/itor.13537","DOIUrl":"https://doi.org/10.1111/itor.13537","url":null,"abstract":"Online review sites play a crucial role in shaping consumer purchasing decisions, making the analysis of customer feedback essential for businesses. Given the complexity of these reviews, often including both quantitative and qualitative data, advanced analytical frameworks are necessary. To this end, this paper introduces an integrated framework for customer feedback analysis, combining aspect‐based sentiment analysis, multicriteria decision‐making, and a fuzzy rule‐based approach. The proposed system effectively processes both textual and numerical data from online reviews, enabling the extraction of actionable insights. To demonstrate its practical utility, we apply it to a real‐world dataset from a major European airline. The results illustrate the framework's effectiveness in identifying key factors influencing customer satisfaction and pinpointing areas needing improvement. Additionally, data‐driven recommendations are provided to support business decision‐making and enable the customization of products and services to better meet customer expectations.","PeriodicalId":49176,"journal":{"name":"International Transactions in Operational Research","volume":"11 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We develop a method for modelling multi‐stage production using stochastic frontier analysis. This approach is suitable for the analysis of costs or output where intermediate outputs become inputs into a subsequent stage of the production process, either within an organisation or in the form of a supply chain. Our focus is on higher education institutions in England, and the purpose is to assess the performance of our novel methods using Markov Chain Monte Carlo methods. Without taking into full account of the complexity of the ‘network’, key decisions cannot be made regarding intake quality, student/staff ratios, per‐student spending or academic reputation (the last of which involves costly decisions in terms of academic openings and the profile of candidates desired for any given university).
{"title":"Multi‐stage stochastic frontier analysis for simple networks","authors":"Geraint Johnes, Mike Tsionas, Marwan Izzeldin","doi":"10.1111/itor.13538","DOIUrl":"https://doi.org/10.1111/itor.13538","url":null,"abstract":"We develop a method for modelling multi‐stage production using stochastic frontier analysis. This approach is suitable for the analysis of costs or output where intermediate outputs become inputs into a subsequent stage of the production process, either within an organisation or in the form of a supply chain. Our focus is on higher education institutions in England, and the purpose is to assess the performance of our novel methods using Markov Chain Monte Carlo methods. Without taking into full account of the complexity of the ‘network’, key decisions cannot be made regarding intake quality, student/staff ratios, per‐student spending or academic reputation (the last of which involves costly decisions in terms of academic openings and the profile of candidates desired for any given university).","PeriodicalId":49176,"journal":{"name":"International Transactions in Operational Research","volume":"20 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To address the high‐carbon emissions from port equipment, one of the most effective measures is to replace diesel‐powered rubber‐tyred gantry cranes (RTGs) with electric‐powered alternatives. However, the oil‐to‐electricity retrofitting for diesel‐driven RTGs may negatively impact port operation efficiency. Moreover, port enterprises typically do not initiate the retrofitting without the low‐carbon policies. Therefore, this study focuses on the retrofitting of RTGs in combination with their deployment under the carbon emissions trading (CET) and government subsidy policies. An integer programming model is developed to help port enterprises determine the multistage planning of RTGs' retrofitting and deployment. Based on the block‐diagonal structure of the proposed model, a column generation method employing Dantzig–Wolfe decomposition is developed. The optimal integer solution of the model is then further refined using a branch‐and‐price approach. The Shanghai Yangshan Deep Water Port is used for numerical experiments. Numerical results demonstrate that the implementation of CET and government subsidy policies can reduce approximately 17,630 tons of carbon emissions and $8,751,861 operating costs in container terminal yard. Meanwhile, increasing government subsidies and carbon trading prices, and reducing free carbon emission quotas can encourage port enterprises to reduce more emissions.
{"title":"Oil‐to‐electricity retrofitting and deployment of rubber‐tyred gantry cranes considering low‐carbon policies","authors":"Yi Ding, Deng Pan, Kaimin Chen, Yang Yang","doi":"10.1111/itor.13535","DOIUrl":"https://doi.org/10.1111/itor.13535","url":null,"abstract":"To address the high‐carbon emissions from port equipment, one of the most effective measures is to replace diesel‐powered rubber‐tyred gantry cranes (RTGs) with electric‐powered alternatives. However, the oil‐to‐electricity retrofitting for diesel‐driven RTGs may negatively impact port operation efficiency. Moreover, port enterprises typically do not initiate the retrofitting without the low‐carbon policies. Therefore, this study focuses on the retrofitting of RTGs in combination with their deployment under the carbon emissions trading (CET) and government subsidy policies. An integer programming model is developed to help port enterprises determine the multistage planning of RTGs' retrofitting and deployment. Based on the block‐diagonal structure of the proposed model, a column generation method employing Dantzig–Wolfe decomposition is developed. The optimal integer solution of the model is then further refined using a branch‐and‐price approach. The Shanghai Yangshan Deep Water Port is used for numerical experiments. Numerical results demonstrate that the implementation of CET and government subsidy policies can reduce approximately 17,630 tons of carbon emissions and $8,751,861 operating costs in container terminal yard. Meanwhile, increasing government subsidies and carbon trading prices, and reducing free carbon emission quotas can encourage port enterprises to reduce more emissions.","PeriodicalId":49176,"journal":{"name":"International Transactions in Operational Research","volume":"33 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Planning is an important part of the management of organizations, which deals with the setting of targets that guide the actions needed to improve performance. Decision making is at the essence of planning, as it involves the identification of alternative directions for improvement and the selection of a future course of action. Decision makers (DMs) appreciate information on different ways of improving performance toward best practices, so they can make a choice of the plan that is more closely aligned with management in an ex post evaluation of possibilities. This paper responds to the need of providing DMs with a few (manageable) alternatives when planning improvements. The proposed approach is developed within the framework of data envelopment analysis (DEA). Although DEA has been used for planning, there is a gap in the literature in the sense that we can find only a few papers that have the explicit aim of identifying alternatives. In order to deal with this issue, we explore the whole DEA strong efficient frontier through all of its maximal efficient faces, which allows us to handle targets determined by a broad range of reference sets, and then use location theory tools, namely a p‐median problem, for the selection of p representatives that define alternative directions for improvement. Eventually, DMs are provided with a decision‐support tool for planning improvements by learning from the best practices of others, without requiring prior information on preferences.
规划是组织管理的一个重要组成部分，它涉及设定目标，以指导提高绩效所需的行动。决策是规划的精髓所在，因为它涉及确定其他改进方向和选择未来的行动方案。决策制定者（DMs）需要了解有关提高绩效的最佳做法的各种方法的信息，以便在事后评估各种可能性时，选择与管理层更密切相关的计划。本文旨在满足管理者在制定改进计划时提供一些（可管理的）备选方案的需求。本文提出的方法是在数据包络分析（DEA）框架内开发的。尽管数据包络分析已被用于规划，但文献中仍存在空白，因为我们只能找到几篇明确以确定替代方案为目标的论文。为了解决这个问题，我们探索了整个 DEA 强有效边界的所有最大有效面，这使我们能够处理由广泛的参考集决定的目标，然后使用位置理论工具，即 p 中值问题，来选择 p 个代表，这些代表定义了可供选择的改进方向。最终，我们为管理者提供了一个决策支持工具，让他们通过学习他人的最佳实践来规划改进工作，而无需事先了解偏好信息。
{"title":"Planning in management: identifying alternative ways of improving performance toward best practices","authors":"Juan F. Monge, José L. Ruiz","doi":"10.1111/itor.13534","DOIUrl":"https://doi.org/10.1111/itor.13534","url":null,"abstract":"Planning is an important part of the management of organizations, which deals with the setting of targets that guide the actions needed to improve performance. Decision making is at the essence of planning, as it involves the identification of alternative directions for improvement and the selection of a future course of action. Decision makers (DMs) appreciate information on different ways of improving performance toward best practices, so they can make a choice of the plan that is more closely aligned with management in an ex post evaluation of possibilities. This paper responds to the need of providing DMs with a few (manageable) alternatives when planning improvements. The proposed approach is developed within the framework of data envelopment analysis (DEA). Although DEA has been used for planning, there is a gap in the literature in the sense that we can find only a few papers that have the explicit aim of identifying alternatives. In order to deal with this issue, we explore the whole DEA strong efficient frontier through all of its maximal efficient faces, which allows us to handle targets determined by a broad range of reference sets, and then use location theory tools, namely a <jats:italic>p</jats:italic>‐median problem, for the selection of <jats:italic>p</jats:italic> representatives that define alternative directions for improvement. Eventually, DMs are provided with a decision‐support tool for planning improvements by learning from the best practices of others, without requiring prior information on preferences.","PeriodicalId":49176,"journal":{"name":"International Transactions in Operational Research","volume":"74 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142217004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Decentralized energy systems can be an alternative to stabilizing the power system in a rapidly changing power market environment. In this regard, it is very important to level the significant gap between electricity loads and power generation, which is caused by expanding renewable energy resources. This study investigates an electricity control strategy to encourage forming a microgrid and to level the load profile that the microgrid optimizes based on its individual objective. To address the problems encountered by two players at different decision levels, this study introduces a bilevel optimization model that considers two players’ objectives. In the proposed model, the first player is called the grid system operator, and the decisions of the player are subsidy rates for distributed generators and an energy storage system. The second player is called the community microgrid, and the major decisions of the player are the configuration and operation of the microgrid. To solve the problem, an efficient algorithm is developed based on Karush–Kuhn–Tucker (KKT) conditions and a decomposition approach. Numerical experiments show that the peak load can be reduced by setting an adequate subsidy rate.
{"title":"A bilevel approach to reduce peak load of community microgrid with distributed generators","authors":"Young‐Bin Woo, Ilkyeong Moon","doi":"10.1111/itor.13539","DOIUrl":"https://doi.org/10.1111/itor.13539","url":null,"abstract":"Decentralized energy systems can be an alternative to stabilizing the power system in a rapidly changing power market environment. In this regard, it is very important to level the significant gap between electricity loads and power generation, which is caused by expanding renewable energy resources. This study investigates an electricity control strategy to encourage forming a microgrid and to level the load profile that the microgrid optimizes based on its individual objective. To address the problems encountered by two players at different decision levels, this study introduces a bilevel optimization model that considers two players’ objectives. In the proposed model, the first player is called the grid system operator, and the decisions of the player are subsidy rates for distributed generators and an energy storage system. The second player is called the community microgrid, and the major decisions of the player are the configuration and operation of the microgrid. To solve the problem, an efficient algorithm is developed based on Karush–Kuhn–Tucker (KKT) conditions and a decomposition approach. Numerical experiments show that the peak load can be reduced by setting an adequate subsidy rate.","PeriodicalId":49176,"journal":{"name":"International Transactions in Operational Research","volume":"25 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142217003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Marcelo Gonçalves de Medeiros, Rodrigo José Leite Cavalcante, Anderson Lucas Carneiro de Lima da Silva, Lucia Reis Peixoto Roselli
The logistics market represents a fundamental segment for the circulation of goods and greater economic activity. Logistics startups have been gaining great importance, being potential substitutes for traditional carriers. Given this context, there is a huge need for large carriers to develop digital and sustainable solutions, and especially to look at inorganic strategies such as mergers and acquisitions. However, the process by which carriers may acquire logistics startups is quite complex. This study sought to solve the problem of ranking logistics startups with the potential to be acquired by the carrier in a Brazilian company through a multi‐criteria approach. The Flexible and Interactive Tradeoff (FITradeoff) method was used to solve the case and a ranking of the startups was obtained. The whole process was quick and simple, so this study contributes to proposing a useful model for logistics problems, and demonstrates the practicality of how to solve them using FITradeoff.
{"title":"A multicriteria model for ranking logistics startups during the acquisition process in a transport company","authors":"Marcelo Gonçalves de Medeiros, Rodrigo José Leite Cavalcante, Anderson Lucas Carneiro de Lima da Silva, Lucia Reis Peixoto Roselli","doi":"10.1111/itor.13536","DOIUrl":"https://doi.org/10.1111/itor.13536","url":null,"abstract":"The logistics market represents a fundamental segment for the circulation of goods and greater economic activity. Logistics startups have been gaining great importance, being potential substitutes for traditional carriers. Given this context, there is a huge need for large carriers to develop digital and sustainable solutions, and especially to look at inorganic strategies such as mergers and acquisitions. However, the process by which carriers may acquire logistics startups is quite complex. This study sought to solve the problem of ranking logistics startups with the potential to be acquired by the carrier in a Brazilian company through a multi‐criteria approach. The Flexible and Interactive Tradeoff (FITradeoff) method was used to solve the case and a ranking of the startups was obtained. The whole process was quick and simple, so this study contributes to proposing a useful model for logistics problems, and demonstrates the practicality of how to solve them using FITradeoff.","PeriodicalId":49176,"journal":{"name":"International Transactions in Operational Research","volume":"16 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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