Paul R. Kleindorfer, Kalyan Singhal, Luk N. VanWassenhove
Operations management researchers and practitioners face new challenges in integrating issues of sustainability with their traditional areas of interest. During the past 20 years, there has been growing pressure on businesses to pay more attention to the environmental and resource consequences of the products and services they offer and the processes they deploy. One symptom of this pressure is the movement towards triple bottom line reporting (3BL) concerning the relationship of profit, people, and the planet. The resulting challenges include integrating environmental, health, and safety concerns with green‐product design, lean and green operations, and closed‐loop supply chains. We review these and other “sustainability” themes covered in the first 50 issues of Production and Operations Management and conclude with some thoughts on future research challenges in sustainable operations management.
Abstract As the world’s population increases, demand for poultry products will continue to increase. To meet this demand, one candidate mechanism to increase production is to increase housing and manage more birds. However, this practice, along with labour shortages and increasing biosecurity practices will make it increasingly difficult for producers to monitor the production, health, and welfare status of all their birds. Employing smart poultry management systems is necessary to increase production while minimizing costs and the use of resources. Smart poultry management systems include precision livestock farming (PLF) technologies such as smart sensors, automation of farm processes, and data driven decision making platforms. Many new technologies will have great implications for poultry production in the areas of the poultry house environment, bird welfare, precision feeding, and rapid detection of infectious disease. As smart sensors collect data in real-time on a variety of parameters from poultry operations, large amounts of data will be generated. To make best use of this data, big data analytical tools must be employed to produce data driven decisions. Additionally, the devices that will be incorporated into smart poultry management systems will be connected to the Internet allowing for the formation of Internet of things (IoT) farm networks. IoT technologies allow for communication between farm sensors, devices, and equipment, and will lead to the automation of multiple farm procedures. The following review discusses the areas of impact that new smart sensor technologies will have on poultry operations and describes how sensor technology is related to big data analytics and IoT systems, and how these technologies can enhance production in the poultry industry. Additionally, challenges to the described systems and technologies will also be highlighted and discussed.
S. Gawusu, Xiaobing Zhang, Seidu Abdulai Jamatutu
et al.
This study provides an overview of green supply chain management (GSCM) in the context of renewable energy sources. Thus, it establishes a green management standard with GSCM that companies can adopt. The environmental, economic, and social components determine the concept of GSCM. However, the development and commercialization of renewable energy and sustainable manufacturing practices play a fundamental role in shaping the traditional supply chain management (SCM) and business models. GSCM means that firms and organizations must balance economic and environmental performance to stay competitive, and conform with regulatory and community pressures. This has forced enterprises to design and implement strategies such as eco‐efficiency, greener production, and cleaner environmental practices, for green management practices, which aim at reducing the environmental impacts of their operations. This study further highlights insights needed to significantly improve performance and overcome barriers to the development of renewable energy green supply chain management (REGSCM). It also presents useful techniques by outlining better control chain costs to make renewable energy more affordable and efficient, and a new conceptual model that is mainly grounded within the network of distributed energy systems in the context of GSCM. This concept allows renewable energy producers to sell their surplus electricity based on a peer‐to‐peer (P2P) network or sell directly via the general market. Specifically, this model brings to bear the linkages to the creation of value by firms.
Abstract Southeast Asian countries have become the production hub of lean textile and apparel supply chain. Textile supply chain consumes huge amount of natural resources and emits polluting effluents and gases creating serious environmental and human health concerns. Green design, green procurement, green operations and green transportation are the major areas of green supply chain management. This paper attempts to analyze the important barriers of green textile and apparel supply chain management in Southeast Asian countries. Twelve important barriers have been identified through literature review and questionnaire survey. Interpretive structural modeling (ISM) has been used to decipher the contextual relationships among the barriers. Complexity of green process and system design was found to be the most elementary barrier having the maximum driving power. Lack of consumer support and encouragement, lack of guidance and support from regulatory authorities and high implementation and maintenance cost are the other elementary barriers of green textile supply chain. Lack of green suppliers is the most dependent barrier which is influenced by all other barriers considered in this research. Elimination of root causes or driving barriers are paramount to save the environment. Concerted efforts in terms of green technological innovation, consumers’ awareness and support of the regulatory bodies are needed for effective implementation of green supply practices in textile and apparel supply chains.
Mathias Sæterbø, Wei Deng Solvang, Pourya Pourhejazy
Companies are increasingly turning to additive manufacturing as the demand for one-off 3D-printed metal parts rises. The differences in available additive manufacturing technologies necessitate considering both cost and externalities to select the most suitable alternative. This study compares some of the most prevalent metal additive manufacturing technologies through a shop floor-level operational analysis. A steel robotic gripper is considered as a case study, based on which of the complex, interconnected operational factors that influence costs over time are analyzed. The developed cost model facilitates the estimation of costs, identification of cost drivers, and analysis of the impact of various operations management decisions on overall costs. We found that cost performance across Powder-Bed Fusion (PBF), Wire Arc Additive Manufacturing (WAAM), and CNC machining is determined by part design, quantity, and machine utilization. Although producing parts with complex internal features favors additive manufacturing, CNC outperforms in terms of economy of scale. While PBF offers excellent design freedom and parallel production, it incurs high fixed costs per build in under-utilized situations. A rough but fast method, such as Directed-Energy Deposition (DED)-based additive manufacturing, is believed to be more cost-efficient for large, simple shapes, but is not suitable when fine details are required. Laser-based DED approaches address this limitation of WAAM.
Entrepreneurship literature has identified several factors influencing entrepreneurial intentions, including psychological, social, environmental and demographic. Considering the importance of youth entrepreneurship, examining how these factors affect students’ entrepreneurial inclinations is essential. Thus, the purpose of the study is to investigate the impact of age and race on the entrepreneurial inclinations of South African university students. Researchers collected data from 197 undergraduate entrepreneurship students at two public universities in Durban. Quantitative data was gathered using a self-administered structured questionnaire and analyzed using SPSS. The research found that students’ entrepreneurial intentions are not significantly influenced by age and race. This indicates that students' aspirations to initiate and manage business enterprises are unaffected by age or race. The study recommends that students should be exposed to equal entrepreneurship opportunities including education and training, support, funding and mentorship regardless of their age and race. Thus, students should be introduced to an entrepreneurial environment and ecosystem from primary school to instill in them an entrepreneurial mindset. Furthermore, entrepreneurship policies and regulatory frameworks should be developed and implemented regardless of age and race. Future research should consider the intersection between demographic factors and their influence on entrepreneurial intentions. Also, future studies can look at how demographic characteristics affect various entrepreneurship traits besides intention.
Business, Production management. Operations management
Blockchain-based decentralised lending is a rapidly growing and evolving alternative to traditional lending, but it poses new risks. To mitigate these risks, lending protocols have integrated automated risk management tools into their smart contracts. However, the effectiveness of the latest risk management features introduced in the most recent versions of these lending protocols is understudied. To close this gap, we use a panel regression fixed effects model to empirically analyse the cross-version (v2 and v3) and cross-chain (L1 and L2) effectiveness of liquidation mechanisms, measured through TVL and total revenue as proxies for performance of the two most popular lending protocols, Aave and Compound, during the period Jan 2021 to Dec 2024. Our analysis reveals that liquidation events in v3 of both protocols lead to an increase in total value locked and total revenue, with stronger impact on the L2 blockchain compared to L1. In contrast, liquidations in v2 have an insignificant impact, which indicates that the most recent v3 protocols have better risk management than the earlier v2 protocols. We also show that L1 blockchains are the preferred choice among large investors for their robust liquidity and ecosystem depth, while L2 blockchains are more popular among retail investors for their lower fees and faster execution.
Purpose – The paper proposes a framework for the successful deployment of Industry 4.0 (I4.0) principles in the aerospace industry, based on identified success factors. The paper challenges the perception of I4.0 being aligned with de-skilling and personnel reduction and instead promotes a route to successful deployment centred on upskilling and retaining personnel for future role requirements. Design/methodology/approach – The research methodology involved a literature review and industrial data collection via questionnaires to develop and validate the framework. The questionnaire was sent to a purposive sample of 50 respondents working in operations, and a response rate of 90% was achieved. Content analysis was used to identify patterns, themes, or biases, and the data were tabulated based on specific common attributes. The proposed framework consists of a series of gates and criteria that must be met before progressing to the next gate. Findings – The proposed framework provides a feedback mechanism to review minimum standards for successful deployment, aligned with new developments in capability and technology, and ensures quality assessment at each gate. The paper highlights the potential benefits of I4.0 implementation in the aerospace industry, including reducing operational costs and improving competitiveness by eliminating variation in manufacturing processes. The identified success factors were used to define the framework, and the identified failure points were used to form mitigation actions or controls for inclusion in the framework. Originality/value – The paper provides a framework for the successful deployment of I4.0 principles in the aerospace industry, based on identified success factors. The framework challenges the perception of I4.0 as being aligned with de-skilling and personnel reduction and instead promotes a route to successful deployment centred on upskilling and retaining personnel for future role requirements. The framework can be used as a guideline for organizations to deploy I4.0 principles successfully and improve competitiveness.
Industrial engineering. Management engineering, Production management. Operations management
This article examines the significant impact of ERP (Enterprise Resource Planning) on management control in modern organizations, based on the Marroy case study. Exploring the deep integration between ERP and critical management control functions, this essay offers an in-depth analysis of key benefits such as task automation, business process optimization, and improved decision-making. The study highlights the challenges associated with ERP implementation, and proposes effective solutions for maximizing the benefits of this technology in the context of today's digital transformation. By offering an essential perspective on the evolution of management control practices thanks to the technological innovations of ERP, this article contributes to the understanding of modern strategic and operational strategies in organizations.
Business, Production management. Operations management
Fernando Acebes, José Manuel González-Varona, Adolfo López-Paredes
et al.
The project managers who deal with risk management are often faced with the difficult task of determining the relative importance of the various sources of risk that affect the project. This prioritisation is crucial to direct management efforts to ensure higher project profitability. Risk matrices are widely recognised tools by academics and practitioners in various sectors to assess and rank risks according to their likelihood of occurrence and impact on project objectives. However, the existing literature highlights several limitations to use the risk matrix. In response to the weaknesses of its use, this paper proposes a novel approach for prioritising project risks. Monte Carlo Simulation (MCS) is used to perform a quantitative prioritisation of risks with the simulation software MCSimulRisk. Together with the definition of project activities, the simulation includes the identified risks by modelling their probability and impact on cost and duration. With this novel methodology, a quantitative assessment of the impact of each risk is provided, as measured by the effect that it would have on project duration and its total cost. This allows the differentiation of critical risks according to their impact on project duration, which may differ if cost is taken as a priority objective. This proposal is interesting for project managers because they will, on the one hand, know the absolute impact of each risk on their project duration and cost objectives and, on the other hand, be able to discriminate the impacts of each risk independently on the duration objective and the cost objective.
In portfolio optimization, decision makers face difficulties from uncertainties inherent in real-world scenarios. These uncertainties significantly influence portfolio outcomes in both classical and multi-objective Markowitz models. To address these challenges, our research explores the power of robust multi-objective optimization. Since portfolio managers frequently measure their solutions against benchmarks, we enhance the multi-objective min-regret robustness concept by incorporating these benchmark comparisons. This approach bridges the gap between theoretical models and real-world investment scenarios, offering portfolio managers more reliable and adaptable strategies for navigating market uncertainties. Our framework provides a more nuanced and practical approach to portfolio optimization under real-world conditions.
Given the continuous global degradation of the Earth's ecosystem due to unsustainable human activity, it is increasingly important for enterprises to evaluate the effects they have on the environment. Consequently, assessing the impact of business processes on sustainability is becoming an important consideration in the discipline of Business Process Management (BPM). However, existing practical approaches that aim at a sustainability-oriented analysis of business processes provide only a limited perspective on the environmental impact caused. Further, they provide no clear and practically applicable mechanism for sustainability-driven process analysis and re-design. Following a design science methodology, we here propose and study SOPA, a framework for sustainability-oriented process analysis and re-design. SOPA extends the BPM life cycle by use of Life Cycle Assessment (LCA) for sustainability analysis in combination with Activity-based Costing (ABC). We evaluate SOPA and its usefulness with a case study, by means of an implementation to support the approach, thereby also illustrating the practical applicability of this work.
Purpose The purpose of this paper is to investigate the effects of Blockchain on the customer order management process and operations. There is limited understanding of the use and benefits of Blockchain on supply chains, and less so at processes level. To date, there is no research on the effects of Blockchain in the customer order management process. Design/methodology/approach A twofold method is followed. First, a Blockchain is programmed and implemented in a large international firm. Second, a series of simulations are built based on three scenarios: current with no-Blockchain, 1-year and 5-year Blockchain use. Findings Blockchain improves the efficiency of the process: it reduces the number of operations, reduces the average time of orders in the system, reduces workload, shows traceability of orders and improves visibility to various supply chain participants. Research limitations/implications The research is based on a single in-depth case that has the scope to be tested in other contexts in future. Practical implications This is the first study that demonstrates with real data from an industrial firm the effects of Blockchain on the efficiency gains, reduction on the number of operations and human-processing savings. A detailed description of the Blockchain implementation is provided. Furthermore, this research shows a list of the resources and capabilities needed for building and maintaining a Blockchain in the context of supply chains. Originality/value This is the first study that demonstrates with real data from an industrial firm the effects of Blockchain on the efficiency gains, the reduction in the number of operations and human-processing savings. A detailed description of the Blockchain implementation is provided. This paper contributes to the resource-based view of the firm, by demonstrating two new competitive valuable capabilities and a new dynamic capability that organisations develop when implementing and using Blockchain in a supply–demand process. It also contributes to the information processing theory by highlighting the analytics capabilities required to sustain Blockchain-related operations.
N. Nikolakis, K. Alexopoulos, Evangelos Xanthakis
et al.
ABSTRACT Production systems empowered by digital simulation tools can be improved in a time and cost-effective approach. The enrichment of digital simulations with sensor data, can enhance their realism and improve the accuracy of their results. Hence, this study proposes an implementation of the digital twin approach as part of a wider cyber-physical system (CPS) to enable the optimisation of the planning and commissioning of human-based production processes using simulation-based approaches. This is achieved through a) sensor data fusion and motion recognition of human activities in a factory floor and b) knowledge management mechanism for capturing the implicit knowledge of the task execution. A case study from the intra-factory logistics operations in the white goods industry, demonstrates the feasibility of the proposed approach, by enriching the simulation of manual assembly operations with the operator’s knowledge in the form of spatiotemporal constraints.
Mariana Trujillo‐Gallego, William Sarache, M. Sellitto
Abstract In order to face the different pressures associated with the environmental damage generated by production processes, the Green Supply Chain Management (GSCM) approach is an alternative for manufacturing companies, as it allows them to have more sustainable operations, especially, in relation to other players, through environmental collaboration. The aim of the present article is to identify which practices facilitate environmental collaboration, as well as to establish the influence of said collaboration on sustainable production practices. A survey with 43 items, drawn from the literature, was applied to a convenience sample of Colombian manufacturing companies. The hypotheses, relating to environmentally sustainable practices and environmental collaboration data, were tested using Partial Least Squares Structural Equation Modeling (PLS-SEM). The main results show that internal environmental management, eco-design, and green marketing have direct and positive effect on environmental collaboration. However, no relationship was found between green human resources, green information and systems technology, and reverse logistics and environmental collaboration. In addition, the positive effect of environmental collaboration on sustainable production practices, such as green purchasing, green manufacturing, and green distribution, was reflected. The paper expands knowledge of the way in which environmentally practices are related to environmental collaboration and their implications for more sustainable production and consumption.