Operations Management Perspective Research Articles

Framework for a sustainable supply chain to overcome risks in transition to a circular economy through Industry 4.0

Transition from a linear to a circular economy (CE) is a challenging process for a sustainable supply chain, and innovative process approaches and technologies are needed to deal with the risks involved. Industry 4.0 principles have great potential to achieve optimal sustainable supply chain solutions and are expected to add value to sustainable supply chain operations by increasing efficiency and resource utilisation. Therefore, Industry 4.0 supports companies transitioning to a CE through improving the efficiency and sustainability of their supply chain management. Thus, the purpose of this paper is to investigate the potential risks of the transition from a linear to a CE, with proposed Industry 4.0-based responses from an operations management perspective within the sustainable supply chain. Implementation of the study was conducted in a logistics company in Turkey. An integrated MCDM (Multi-criteria Decision Making) approach was based on Fuzzy AHP, and TODIM was used to analyse the association between risks and responses. According to the findings, the most important Industry 4.0-based responses are the integrated business processes for cross-functional collaboration, modular processes for simplification and standardisation, and continuous monitoring of the cost and performance throughout the supply chain by big data and analytics. This study may assist managers in managing risks in supply chain operations during the transition from a linear to a CE through Industry 4.0 based responses. The main contribution of this study is a greater understanding of the risks related to the transition from a linear to a circular economy, and proposals for Industry 4.0-based responses as a means of overcoming these risks in a sustainable supply chain context.

Hydrological System Complexity Induces a Drought Frequency Paradox

Droughts occur as a result of a lack of water compared with normal conditions. Whilst this appears trivial, the exact drought definition of drought is not. Especially as different drought types are present, resulting from the different variables in a hydrological system, each with unique characteristics. We use a common drought definition, the percentile score, and apply the same definition across all drought types, to study whether the actual occurrence of droughts matches the definition. We focus on the data-rich Dutch province of Gelderland, to study droughts from observations across five major components of the terrestrial hydrological cycle. When a percentile threshold of 20% is used as drought definition, corresponding to a mild drought, droughts anywhere in the system occur at least three times more frequently (73% of the time). On the other hand, the situation where drought occurs across all components of the terrestrial hydrological cycle is more than four times less likely than the drought threshold of 20% (namely 5% of the time). This can be attributed by both (1) the different responses across the hydrological system, and (2) the spatial variability present within each component of the hydrological system. With this study, we show the existence of the drought frequently paradox: although droughts are seen and defined as rare from a scientific perspective, when viewed from a societal or operational water management perspective in typical hydrological systems subject to spatial variability and other system complexity, droughts become common, rather than rare. This paradox is a consequence of an inconsistent use of the percentile score drought definition between research and operational water management, and better communication between the two domains is needed in search for a universally accepted drought definition.

Collaborative robotics: a literature overview from the perspective of production management

Purpose: This paper aims to understand the specificities inherent to collaborative robotics from the perspective of production and operations management, as well as to identify opportunities for future research on the topic.
 Methodology/Approach: A systematic literature review was carried out through Scopus and Web of Science databases. This procedure covered 84 articles published between 1997 and 2018.
 Findings: The study revealed the issues most addressed in the research on Collaborative robots (Cobots), the most cited works, and the research approaches adopted.
 Research Limitation/implication: The sample was extracted from only two international databases excluding publications in the form of books and articles from other databases.
 Originality/Value of paper: The study reveals some specificities regarding the application and development of COBOTs, as well as their advantages and drawbacks in the scope of production management.

Extended Producer Responsibility: A Systematic Review and Innovative Proposals for Improving Sustainability

Extended producer responsibility (EPR) is an environmental policy introduced in Europe, back in the 1990s. Under EPR, a producer's responsibility for its products is extended beyond the consumption stage, and the producer has to meet the targets of collection and recycling rates imposed by the EPR legislation. Motivated by the importance of this topic, in this paper, we conduct a systematic review on EPR from an operations management perspective. To be specific, we categorize the EPR literature, for both e-wastes and non-e-wastes, by research methodologies (qualitative case studies, quantitative empirical research, and analytical modeling studies) and discuss the respective findings. In addition to systematically exploring the state-of-the-art research within the context of EPR, we investigate pertinent issues, such as the implementation of EPR, EPR management systems, supply chain management under EPR, and EPR-related operations (such as end-of-life product management and design for recyclability). We highlight some EPR-related innovative measures and proposals in five areas, namely policy, product, process, supply chain, and technology. Finally, we discuss future research and propose a concluding picture of how EPR can help establish innovative operational measures to improve sustainability.

A Conceptual Framework to Analyze Food Loss and Waste within Food Supply Chains: An Operations Management Perspective

Alongside the development of the circular economy and sustainable food supply chains (FSCs), research on food loss and waste (FLW) reduction and prevention has drawn much attention from academia, practitioners, and governments. The significance of FLW has been highlighted in the literature due to its impact on society, economy, and the environment. We propose a conceptual framework to systematically examine FLW issues within FSCs in the field of operations management (OM). We discuss various types and distribution modes of FSCs where FLW occurs, definitions of FLW, the impacts of FLW, and measures to reduce FLW in the OM field. We further introduce the methodologies that have been applied in existing FLW studies. The contribution of this paper is threefold. First, it proposes a conceptual framework to identify FLW problems within FSCs. Second, it helps to comprehensively understand FLW occurrence and thus stimulate research focusing on FLW from different perspectives. Third, it motivates researchers to discuss FLW issues by applying different methodologies.

Resource Requirements in Business Process Modelling from an Operations Management Perspective

Operations management entails the design and control of business operations with the goal of providing goods and services as efficiently as possible. Usually various resources are required to conduct operations and the required resources are usually limited in numbers and availability. Business process models supporting operations management should aid in effectively using available resources, identifying process inefficiencies, and enabling appropriate action if resources are unavailable or cannot operate as required. In this contribution we show how typical resource requirements found in operations management can be included in business process models and propose BPMN 2.0 compatible modelling patterns for describing resource requirements based on the concepts of requests and releases. We discuss various modelling requirements from an operations management perspective and discuss how request-release modelling patterns can be used for different application cases.

Book Review (Descriptive): Bernard D., Andrew L., Peter A. Ioannis S. (2018). Food and Beverage Management; Fourth Edition

Book Review (Descriptive): Bernard D., Andrew L., Peter A. Ioannis S. (2018). Food and Beverage Management; Fourth Edition

Improving peer-to-peer accommodation service based on text analytics

PurposeThis paper aims to identify key service attributes in peer-to-peer (P2P) accommodation from online reviews and formulate service improvement strategies based on the unsatisfactory service encounters mined from the reviews.Design/methodology/approachThe methodology involves topic modelling using latent Dirichlet allocation, sentiment analysis and process analysis based on process chain network (PCN).FindingsThe text analytics results showed that negative P2P accommodation experiences are caused by the lack of hot water for shower, poor sleep quality and unpleasant check-in.Research limitations/implicationsThe PCN analysis shows that the surrogate interactions of the P2P accommodation platform with both the guest and the host impact consumer experiences. This highlights that the key to managing consumer experiences lies in the non-human resources such as information, rather than direct interactions between process entities.Practical implicationsThe information on the P2P accommodation platform should be in a more interactive format such as video and 360 degrees camera. Hosts should ensure a good condition of the physical products such as water heaters and beds before guests' arrival. Professional videography and handyperson services should be provided by the platform to help hosts deliver a preferred consumer experience. Flexible and strict check-in polices should also be introduced to smoothen the check-in process.Originality/valueThis study is built on multi-attribute utility theory. It is also one of the first to study P2P accommodation services from an operations management perspective. It demonstrates how text analytics serves as an additional supplement for service improvement.

The roles of crowdfunding: financing, point provision and ex-post production

ABSTRACT While most researches focus on the financing role of crowdfunding, the functions of ex-post production and point provision have not been deeply investigated yet. In this paper, we reveal the three roles of crowdfunding from the perspective of operations management, wherein the ex-post production role can ensure the on-demand production, and the point provision mechanism can alleviate the risk of demand uncertainty. We construct mathematical models to derive the maximised performance of crowdfunding with the three roles in a holistic framework. Our results show that the synthetic of three roles can achieve maximisation performance, and crowdfunding also can improve consumer welfare by lowering the price or raising product quality. To prevent moral hazard, we further illustrate the existence of separate equilibrium by introducing partial pre-payment contract in the asymmetrical information situation. However, the separation cost is high when the initial capital is limited. Our research can shed light on crowdfunding operations.

A real-time decision support framework to mitigate degradation in perishable supply chains

Perishable products are highly susceptible to degradations in quality due to unstable environmental conditions. From an operations management perspective, retailers may be left with spoiled products with no salvage value. To mitigate these challenges, we develop a step-by-step analytical framework that enables managers to make dynamic tactical decisions for perishable products, to preserve their quality as they move through a supply chain network. First, by identifying key quality indicators and environmental factors, a data-driven quality degradation prediction model under a stochastic environment is established. The combined impact of volatile environmental factors on various quality indices are studied. Next, we utilize this degradation model as an input to a preliminary planning model, which determines a vehicle routing schedule and inventory quality targets throughout the network at least cost, subject to retailer service levels. Lastly, using the optimized supply chain network design, we dynamically optimize the environmental controls throughout the transportation process to ensure product quality. By applying this framework to a fresh apple supply chain case, we obtain valuable insights on product quality degradation along the supply chain, which aids practitioners in developing targeted solutions that enhance quality levels economically. With extended analyses, we observed the reaction of different quality indices to environmental variations, and the benefits brought by establishing initial environment conditions in delivery vehicles.

Hospital Admission and Social Distancing Intervention in COVID-19 Pandemic: An Operations Management Perspective

COVID-19 is a highly contagious disease and has been spread to most countries of the world with unprecedented transmission speed. Medical resources and treatments provided by the healthcare system are most critical to reduce the mortality rate of COVID-19 and to contain the spread of COVID-19 by isolating infectious individuals. We introduce a modified SEIR model with consideration of individuals’ access to limited medical resources to characterize the vital role of critical medical resources during the pandemic. We discuss how the three different hospital admission policies (hierarchy, mixed, and Fangcang sheltered healthcare system) affect the spread of the disease and the number of deaths and infections. We find that Fangcang shelter system results in the least number of infections, deaths as well as occupied beds among all three systems. In addition, when the hospital capacity is relatively high or transmission rate of the mildly infected patient is not ignorable, a mixed system can result in a lower number of infections and deaths but higher occupied beds than a hierarchy system because it prevents the disease transmission to a great extent. Public policies of social distancing play an important role in moderating the spreads overtime. We investigate the performance of the three healthcare systems under a static social distancing policy. We find that, under a static social distancing policy, a Fangcang shelter system results in the largest reduction in infections and deaths. Moreover, we conduct simulations on two types of dynamic lockdown policies and find that an effective dynamic lockdown policy should smooth the burden of a healthcare system and keeping minimum disruption of economic activities. That is, a lockdown that occurs either too early or two late could result in more deaths and infections.

Air taxi service for urban mobility: A critical review of recent developments, future challenges, and opportunities

Expected to operate in the imminent future, air taxi service (ATS) is an aerial on-demand transport for a single passenger or a small group of riders, which seeks to transform the method of everyday commute. This uncharted territory in the emerging transportation world is anticipated to enable consumers bypass traffic congestion in urban road networks. By adopting an electric vertical takeoff and landing concept (eVTOL), air taxis could be operational from skyports retrofitted on building rooftops, thus gaining advantage from an implementation standpoint. Motivated by the potential impact of ATS, this study provides a review of air taxi systems and associated operations. We first discuss the current developments in the ATS (demand prediction, air taxi network design, and vehicle configuration). Next, we anticipate potential future challenges of ATS from an operations management perspective, and review the existing literature that could be leveraged to tackle these problems (ride-matching, pricing strategies, vehicle maintenance scheduling, and pilot training and recruitment). Finally, we detail future research opportunities in the air taxi domain.

Optimizing the robotic surgery team: an operations management perspective.

To assess the critical threshold to optimize operating room (OR) time for each surgical team member in robotically assisted sacrocolpopexy (RASCP) and to evaluate the most efficient team compositions. All women who underwent RASCP for pelvic organ prolapse (POP) were prospectively entered in a database. Patients having unrelated concomitant surgery were excluded. Our primary outcome measure was total OR time. We utilized factor analysis, regression analysis, and analysis of variance, OR time mapping, and stochastic optimization to identify 'optimal' surgical team configuration. The database included 359 consecutive RASCPs, all performed for stage III-IV POP: 156 (43%) were with total and 44 (12%) supracervical hysterectomies and 159 (44%) post-hysterectomy. Mean age was 58.6 ± 9.3years. Mean parity was 2.8 ± 1.4, and mean body mass index was 28 ± 4.7kg/m2. A total of 4 surgeons, 34 first assistants, 20 circulating nurses, 15 surgical technologists, and 59 anesthesiologist/nurse anesthetists were involved. Optimal experience levels for each team member were achieved at the following number of robotic procedures: surgeon 44; first assistant 13; surgical technologist 66; circulating nurse 56; anesthesia provider 46. Our analysis revealed that the surgical technologist and first assistant played the most significant roles within the team. The surgeon was ranked third followed by the circulating nurse and anesthesia provider, respectively. Operating time in robotic surgery is multifactorial. Experience of each member of a robotic surgery team is critical. An optimal team can be composed of a variety of combinations of experience levels among the robotic team members.

A Framework for Managing Innovation

Innovation is critical in all types of organizations. Yet, it remains one of the most challenging efforts to perform and manage. This paper attempts to provide three insights on the challenge to innovate: first, a conceptual framework that breaks the complexity of innovation efforts down into three key phases, namely ideation, selection and execution. We then review the extant literature that has emerged over the last 20 years on the management of innovation, highlighting studies that offer specific insights for each of the three phases of our framework. While admittedly we adopt an operations research/ operations management (OR/OM) perspective on the literature, we showcase the breadth, depth and relevance of this growing body of literature. Finally, we identify that there is no one standard recipe that enables innovation. Instead the activities, structures and rules to perform innovation depend on the type of innovation outcomes, incremental or radical, pursued by an organization.

Analysis of firm CSR strategies

Corporate social responsibility (CSR) has become increasingly important. From the perspective of operations management, traditional non-CSR-compliant operations are less costly than CSR compliant operations but may be subject to the risk of being exposed to the public by third-party organizations such as Non-Governmental Organizations (NGOs) through external scrutiny. This exposure can negatively affect firms’ market share when customers are concerned about firms’ CSR compliance. This paper studies firms’ endogenous CSR compliance strategies, i.e., the incentive to adopt CSR compliant operations. We first consider a single firm's CSR compliance strategies, and then, we extend the analysis to the case of competition. We analyze how exogenous parameters, including the risk of exposure and cost premium, determine equilibrium CSR compliance strategies. We find that CSR compliant operations will be implemented either when the exposure risk is sufficiently high or when the cost premium is sufficiently low. We also discuss how competition affects firms’ CSR compliance strategies and whether firms perform better with CSR compliant operations in equilibrium. Our results show that, by adopting CSR compliant operations, firms will engage in a win-win equilibrium if the external risk is high or if the cost premium is low. Besides, we also conduct the analysis under Bertrand (price) competition. Based on these results, we provide managerial insights into when CSR compliant operations should be adopted in practice and how such adoption affects firms’ performance. Our results also imply that the practice of sustainability requires firms to consider both the external risk of exposure and cost premium.

Low carbon building performance in the construction industry: a multi-method approach of system dynamics and building performance modelling

The construction industry contributes significantly to energy consumption and carbon emissions. Moreover, people spend more time inside buildings, so their health is increasingly influenced by indoor environmental conditions. When considered through these lenses, the concept of total building performance can span energy consumption, the associated CO2 emissions, and indoor environmental quality (IEQ). At the individual project level, building underperformance with respect to energy and IEQ is frequent, and the ex post performance gap is partially attributed to the construction project management and operations phase of the building lifecycle. This underperformance motivates the research of this paper into the construction process outcomes in terms of energy performance and IEQ, and ways to reduce the performance gap. The paper develops a multi-methodology framework to analyse the effect of building development project process on energy performance and IEQ from an operations management perspective. The framework couples system dynamics modelling of construction project management to building performance modelling. The paper details the way they are coupled, the application steps and data requirements, so that they can be applied on a case by case basis. The aim is to combine operations management to building performance disciplines and deliver insights for industry practitioners and policy makers.

Cloud Computing Value Chains: Research from the Operations Management Perspective

Cloud computing has been recognized as a critical driver of Information-Technology (IT) enabled innovations. In this paper, we review recent cloud computing research from an Operations Management (OM) perspective, by focusing on major operations challenges faced by a cloud provider in three problem domains: (1) pricing strategies for the cloud computing marketplaces, (2) deployment and scheduling of cloud computing resources, and (3) capacity planning and supply chain management. We describe relevant business practices, followed by a discussion of current research in OM and related areas in each domain, and point out opportunities for future research. We argue that, although cloud computing operations share many features with classic OM problems (revenue management, scheduling theory, and inventory management), they also bring significant new challenges that are intellectually engaging. Thus, we believe that the cloud computing industry can stimulate much innovative OM research and deserves the attention of our community, which, in turn, has the potential to provide vital insights into cloud management practices.

How to increase access to kidney transplantation: the analysis of a Brazilian public hospital through operations management

End-stage renal disease is one of the most costly chronic diseases for the Brazilian public health system. Dialysis is still the most commonly used procedure, even though transplantation is one of the most recommended treatments. Considering the perspective of operations management as an approach for organisational interventions, the objective of this paper was to propose a new operation model for a transplantation unit in Rio de Janeiro State focused on reducing the patients waiting times in queues. The first step was to conduct a systematic literature review. Then, the kidney transplantation process was modelled using ARIS/IDS notation, which oriented the description and analysis of the operation model of the transplantation unit. A new model was proposed, along with a list of strategic, structural and political decisions to mitigate organisational, network design and budget pass-through logic inconsistences.

Process Institutionalization Crowds Out Innovativeness An Empirical Analysis on the Relationships Between ISO 9000 Adoption and R&D Expenditure

Much research from an organisational perspective suggests that process certifications such as ISO 9000 constrain firms' explorative capability, crowding out research and development (R&D) activities. Yet, from an operations management (OM) perspective, process certifications like ISO 9000 should provide a well-established system, strengthening firms' capabilities for both exploration and exploitation. In this research, we examine the impact of ISO 9000 certifications on R&D expenditure of firms and investigate how such an impact is moderated by different operating environments. We find that firms actually increase their R&D expenditure after ISO 9000 certifications. Our results further indicate that ISO 9000-certified firms are more responsive to the changing operating environments for their R&D investments. ISO 9000 certifications reduce R&D expenses more swiftly under turbulence but expand more significantly with operational slack. Our research indicates that ISO 9000-certified firms seem to be more responsive to external environments in controlling their R&D expenditure.

Reliability evaluation and big data analytics architecture for a stochastic flow network with time attribute

A network with multi-state (stochastic) elements (arcs or nodes) is commonly called a stochastic flow network. It is important to measure the system reliability of a stochastic flow network from the perspective of operations management. In the real world, the system reliability of a stochastic flow network can vary over time. Hence, a critical issue emerges—characterizing the time attribute in a stochastic flow network. To solve this issue, this study bridges (classical) reliability theory and the reliability of a stochastic flow network. This study utilizes Weibull distribution as a possible reliability function to quantify the time attribute in a stochastic flow network. For more general cases, the proposed model and algorithm can apply any reliability function and is not limited to Weibull distribution. First, the reliability of every single component is modeled by Weibull distribution to consider the time attribute, where such components comprise a multi-state element. Once the time constraint is given, the capacity probability distribution of elements can be derived. Second, an algorithm to generate minimal component vectors for given demand is provided. Finally, the system reliability can be calculated in terms of the derived capacity probability distribution and the generated minimal component vectors. In addition, a big data architecture is proposed for the model to collect and estimate the parameters of the reliability function. For future research in which very large volumes of data may be collected, the proposed model and architecture can be applied to time-dependent monitoring.