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Throughout its history, Operational Research has evolved to include methods, models and algorithms that have been applied to a wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first summarises the up-to-date knowledge and provides an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion and used as a point of reference by a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order. The authors dedicate this paper to the 2023 Turkey/Syria earthquake victims. We sincerely hope that advances in OR will play a role towards minimising the pain and suffering caused by this and future catastrophes. [ABSTRACT FROM AUTHOR]

This paper explores the relevance to industry's needs of operations management (OM) teaching in higher education, by researching the content of OM modules delivered by UK academics and comparing the results of this research with the views of business practitioners having had first-hand experience of OM teaching on MBA programmes. To determine whether a gap exists in terms of the importance placed on key content areas, the views of OM academics and practitioners were empirically tested using an online survey instrument. The findings indicate that although there is a broad degree of cohesion among academics relating to module content there are gaps between academics and practitioners in terms of the relative importance of key content areas. Such differences are most evident with regard to supply chain management, capacity management, inventory control and lean production tools and techniques. In this regard, the results provide a backdrop for the development of this important subject discipline to ensure that what is taught in the lecture theatre is valued in the business environment. (Contains 9 tables and 2 figures.)

Background: This paper proposes a framework to cope with the lack of data at the time of a disaster by employing predictive models. The framework can be used for disaster human impact assessment based on the socio-economic characteristics of the affected countries. Methods: A panel data of 4252 natural onset disasters between 1980 to 2020 is processed through concept drift phenomenon and rule-based classifiers, namely the Moving Average (MA). Results: Predictive model for Estimating Data (PRED) is developed as a decision-making platform based on the Disaster Severity Analysis (DSA) Technique. Conclusions: comparison with the real data shows that the platform can predict the human impact of a disaster (fatality, injured, homeless) with up to 3% error; thus, it is able to inform the selection of disaster relief partners for various disaster scenarios. [ABSTRACT FROM AUTHOR]

The concepts of sustainable supply chains and Industry 4.0 are progressively getting attention in different domains. Companies have started developing and implementing these practices in their business models. However, several challenges influence the adoption of sustainability and Industry 4.0 (I4.0) in small and medium-sized enterprises (SMEs). This study aimed (i) to identify the adoption barriers of sustainability and I4.0 and (ii) to establish the interrelationship among these barriers for SMEs. An extensive literature search supported by interviews with supply chain practitioners from three SMEs identified 12 critical barriers to adoption. The barriers are then ranked using 'Interpretive Structural Modeling'. The results suggest that the 'lack of resources' and the 'lack of employee's competence/expertise' are the most influencing barriers. Changing government regulations on the allocation of capital and financial incentives for SMEs to encourage training and skills development programs could promote sustainable supply chains and practices. The study also reflects short-, medium- and long-term planning strategies for supply chain practitioners for adoption of sustainability and I4.0 in SMEs. [ABSTRACT FROM AUTHOR]

This research investigates the effect of political risk on the offshore service industry. The study empirically examines how an extended political risk definition, operationalised into a model consisting of 12 political risk variables, helps predict location decisions across offshoring entry modes and activity types. The research focuses on captive offshoring and offshore outsourcing entry modes, and Information Technology Outsourcing (ITO), Business Process Outsourcing (BPO) and Knowledge Process Outsourcing (KPO) activity types. The research indicated that political risk factors accounted for 38% of the variability in offshore outsourcing flows, implying that concerns about service disruptions and/or cost implications of external uncertainties feature as a key factor in supplier selection and location decisions. The findings further confirm a positive relationship between institutional and regulatory factors in host locations, and the flow of offshoring activities with a high knowledge content. The research contributes to enhancing the explanatory ability of Transaction Cost Economics by re-operationalising the concept of political risk in the context of both offshore outsourcing and captive offshoring. For practitioners, these findings provide a clear indication of the political risks that can affect service offshoring decisions; for policymakers, they highlight the importance of strengthening institutional and regulatory factors to attract investment. [ABSTRACT FROM AUTHOR]

The rush of the humanitarian suppliers into the disaster area proved to be counter-productive. To reduce this proliferation problem, the present research is designed to provide a technique for supplier ranking/selection in disaster response using the principles of utility theory. A resource allocation problem is solved using optimisation based on decision maker's preferences. Due to the lack of real-time data in the first 72 h after the disaster strike, a Decision Support System (DSS) framework called EDIS is introduced to employ secondary historical data from disaster response in four humanitarian clusters (WASH: Water, Sanitation and Hygiene, Nutrition, Health, and Shelter) to estimate the demand of the affected population. A methodology based on multi-attribute decision-making (MADM), Analytical Hierarchy processing (AHP) and Multi-attribute utility theory (MAUT) provides the following results. First a need estimation technique is put forward to estimate minimum standard requirements for disaster response. Second, a method for optimization of the humanitarian partners selection is provided based on the resources they have available during the response phase. Third, an estimate of resource allocation is provided based on the preferences of the decision makers. This method does not require real-time data from the aftermath of the disasters and provides the need estimation, partner selection and resource allocation based on historical data before the MIRA report is released. [ABSTRACT FROM AUTHOR]

Nowadays, postal services and third-party logistics services (3PL) have been pressured by the increasing demand for delivery services. Therefore, they need to improve their last-mile delivery strategies to meet customers' expectations. This paper aims to investigate how logistics service expectations affect the delivery process in urban areas using a multiple-criteria decision support system based on the Fuzzy Analytic Hierarchy Process (FAHP). We developed a decision-making model employing six criteria and five delivery methods indicated in the literature and collected information from 27 experts working in academia and local and multinational third-party logistics providers in Brazil to validate this model. The results indicate that cost (21.4%) and tracking and tracing (19.3%) are the most important two criteria in the decision model, and the best delivery methods are smart lockers (21.8%) followed by small trucks (21.3%). Our results suggest that service expectations regarding last-mile delivery are aligned with extensive use of road transport and the increase in e-commerce sales can raise greenhouse gas emissions and compromise the environment in urban areas. [ABSTRACT FROM AUTHOR]

The grocery sector has transitioned into an omnichannel operating mode, allowing consumers to buy online and have their order delivered to their chosen address. The last mile delivery service leads to avoidable inefficiencies such as low asset utilisation and repeated trips to nearby neighbourhoods, increasing vehicle emissions, traffic, and operational costs. Combining historical order and delivery data of an online grocery retailer with secondary data publicly available on other retailers, we employ Monte Carlo simulation to estimate grocery home delivery demand per 1-hour time windows. We use the simulation output as an input to daily vehicle routing problem instances under independent and collaborative last mile delivery operation to estimate the impact of collaboration. Our analyses show distance savings of around 17% and route reduction of around 22%. These results can support policies incentivising vehicle and infrastructure sharing settings and decoupling the last mile delivery from the core grocery retail services. [ABSTRACT FROM AUTHOR]

This special issue idea came to life with Prof. Ilker Topcu hosting the 25th International Conference on Multiple Criteria Decision Making in Istanbul from 16 to 21 June 2019 (https://mcdm2019.org/about/). International Society on Multiple Criteria Decision Making (MCDM) brings together academicians, professionals, researchers, students and policymakers at a bi-annual conference since 1975. [8] develop an integrated decision model which evaluates provider agents with respect to reliability, unreliability, and uncertainty and proposes the most trustworthy provider agent in e-commerce multi-agent environments utilising TOPSIS method. [Extracted from the article]

This paper presents a novel application of Data Envelopment Analysis (DEA) to analyze the impact of oil price changes on the efficiency of banks. Factors that affect the efficiency of banks have been of interest to researchers in various geographical regions. With a special focus on oil price changes, we investigate the determinants of bank efficiency in the Middle Eastern Oil-Exporting (MEOE) countries where macro-financial conditions are substantially affected by swings in oil prices. Our analysis consists of two stages: (i) measuring the efficiency scores of banks using the Semi-Oriented Radial Measure (SORM) DEA model, (ii) investigating the impact of alternative indicators of oil prices on the estimated efficiency scores after controlling for key bank-specific and country-specific variables. The analysis is based on an un-balanced panel data of banks operating in the Middle Eastern Oil-Exporting countries over the period of 2001–2011. Our findings reveal that oil price changes affect the efficiency of banks in the MEOE countries through both direct and indirect channels. In addition, we find that Islamic banks in the region are less responsive to oil price changes than commercial and investment banks. [ABSTRACT FROM AUTHOR]

This research investigates sustainability concepts, linking them with social, environmental, and operational activities in the food supply chain. Building on the literature treating social sustainability as an antecedent of environmental sustainability, we present the effects of environmental sustainability on operational performance using constructs that reflect flexibility, quality, and responsiveness. For this purpose, manufacturing companies in the Turkish food industry are surveyed and 101 responses are collected. A partial least squares structural equation model (PLS-SEM) is constructed to test the reliability and the validity of the measurement model and the structural model. The results show that social sustainability is positively associated with environmental sustainability. Moreover, environmental sustainability has a positive influence on operational performance measures: flexibility, quality, and responsiveness with effect sizes that range from medium to large. Organizations in the food supply chain should consider not only the economic, but also the social and the environmental aspects of sustainability. To do this, governments could inform manufacturers in the food sector about the importance of sustainability and encourage them with different incentives towards more sustainable operational practices. This work establishes that investing in social and environmental sustainability returns increased operational performance. The limitation of the research is the size of the sample. In the future, the questionnaire can be used to compare results from other countries and other sectors. [ABSTRACT FROM AUTHOR]

This paper examines the environmental impact of potential coordination on supply chains. A decentralized two-node supply chain is studied, in which one node is a buyer ordering from a second node, who is a supplier operating under the lot-for-lot policy. The supplier is allowed to use a quantity discount to manipulate the buyer’s decision reducing both his individual cost and system’s operational costs. This results in decreasing the frequency of deliveries. We demonstrate that environmentally friendly policies could be also cost saving. The crucial factor about the environmental benefits is the total distance travelled rather than the vehicle loads. We establish the magnitude of the environmental benefits using numerical examples under specific operational parameters. Complete and incomplete information cases are investigated, where the buyer and the supplier make their decisions to optimize their own business operations. [ABSTRACT FROM AUTHOR]

Food losses and waste have always been a significant global problem for mankind, and one which has become increasingly recognised as such by policy makers, food producers, processors, retailers, and consumers. It is, however, an emotive subject whereby the extent, accuracy and resolution of available data on postharvest loss and waste are questionable, such that key performance indicators on waste can be misinformed. The nature and extent of food waste differ among developed economies, economies in transition and developing countries. While most emphasis has been put on increasing future crop production, far less resource has been and is still channelled towards enabling both established and innovative food preservation technologies to reduce food waste while maintaining safety and quality. Reducing food loss and waste is a more tractable problem than increasing production in the short to medium term, as its solution is not directly limited, for instance, by available land and water resources. Here we argue the need for a paradigm shift of current funding strategies and research programmes that will encourage the development, implementation and translation of collective biological, engineering and management solutions to better preserve and utilise food. Such multidisciplinary thinking across global supply chains is an essential element in the pursuit of achieving sustainable food and nutritional security. The implementation of allied technological and management solutions is reliant on there being sufficient skilled human capital and resources. There is currently a lack of robust postharvest research networks outside of the developed world, and insufficient global funding mechanisms that can support such interdisciplinary collaborations. There is, thus, a collective need for schemes that encourage inter-supply chain research, knowledge exchange and capacity building to reduce food losses and waste. © 2017 Society of Chemical Industry [ABSTRACT FROM AUTHOR]

Multifaceted characteristics of urban travel have an impact on the passengers' overall satisfaction with the transport system. In this study, we investigate the interrelationships among traveler satisfaction, travel and traveler characteristics, and service performance in a multimodal network that comprises of a trunk line and its feeder lines. We analyze the factors influencing the choices of access to rail transit stations and the satisfaction of transit travelers with the rapid rail transit systems. We quantitatively study these relationships and demonstrate the complexity of evaluating transit service performance. Since the interrelationships among variables affecting this system are mainly stochastic, we analyze the satisfaction with transit system problem using a Bayesian Belief Network (BBN), which helps capture the causality among variables with inherent uncertainty. Using the case of Istanbul, we employ the BBN as a decision support tool for policy-makers to analyze the rapid rail transit services and determine policies for improving the quality and the level of service to increase the satisfaction with transit system. In the case study, satisfaction with accessibility and access mode variables are found to be more effective variables than total travel time for travel time satisfaction, confirming the significant role of access in multimodal travels. [ABSTRACT FROM AUTHOR]