Production Management Research Research Articles

A systematic literature review exploring and linking circular economy and sustainable development goals in the past three decades (1991–2022)

Amid the escalating environmental crises and economic disparities, Circular Economy (CE) has garnered recognition as a pragmatic mechanism for achieving Sustainable Development Goals (SDGs). In response, several supply chain organisations are integrating CE strategies into their business operations and production processes. Despite these developments and since the introduction of Business Charter for Sustainable Development by the International Chamber of Commerce in 1991, the academic corpus comprehensively connecting CE research themes, catalysts, deterrents, practices with the SDGs has remained limited. To bridge this gap, we present a systematic literature review (SLR) of CE research in operations, supply chain and production management encompassing a time span of 31 years (January 1991 – June 2022), by sourcing, screening, and analysing articles obtained from multiple research databases. Our thematic coding analysis generated ten research themes, and subsequently linking them with relevant SDGs. Additionally, we interweaved CE catalysts and deterrents, establishing a connection with the SDGs. This is further enriched with CE strategies aimed at equipping business practitioners to enhance sustainable business performance and contributing to specific SDGs. Lastly, we delineate CE knowledge data management and priority actions frameworks to aid organisations to enhance employee capability and actively leverage digital technologies for implementing CE strategies.

Assessing the impact of human–robot collaborative order picking systems on warehouse workers

Robotisation is increasing in warehouse operations, but human employment continues to be relevant. Traditionally manual activities, such as order picking, are being re-designed into collaborative human–robot tasks. This trend exemplifies the transition towards a human-centric Industry 5.0, focusing on synergy instead of seeking human replacement. However, human workers are increasingly hard to recruit and retain. We contribute to the underrepresented literature on human factors within the domain of operations and production management research and investigate the deployment of robotic technologies alongside human workers in a sustainable way. With a unique real-effort experiment, we investigate how the manipulation of picker’s experienced levels of autonomy affects their job satisfaction and core self-evaluations, two key behavioural outcomes that determine employee turnover intentions. We establish that the introduction of human–robot collaboration positively affects job satisfaction for the contrasting collaboration dynamics of (i) gaining control (the human leading the robot) and (ii) ceding control (the human following the robot). This positive effect is larger when the human is following the robot. We additionally find that following the robot positively affects pickers’ self-esteem and that self-efficacy related to human–robot interaction benefits from the introduction of collaborative robotics, regardless of the setup dynamics.

Commodity supply risk assessment of China's copper industrial chain: The perspective of trade network

With the rapid development of China's new energy industry, the consumption demand for copper resources is increasing. As a key raw material, copper resources are becoming increasingly important. Taking the demand for copper commodities in China's new energy development as the research background and the international trade environment and pattern of copper supply as the research perspective, this paper makes an overall assessment of the commodity supply risk of China's copper industrial chain from 2010 to 2021 using the complex network and the newly established three-dimensional risk assessment model and finally reaches the following conclusions. The supply risk of commodities in China's copper industrial chain has been rising continuously since 2019 after experiencing fluctuating development in the early stage and a continuous decline in recent years, and there may be a trend of continuing to rise. The supply risk of China's copper industrial chain was gradually reduced from upstream to midstream and downstream, and the supply risk of copper smelting was more severe. The disruption potential risk of China's copper industrial chain was relatively low, and the international import market structure of copper commodities was relatively reasonable. The supply risk characteristics of each link in China's copper industrial chain were different. Due to the influence of import dependence, the copper mining industry had a high risk of trade exposure. However, the smelting and copper processing industries had certain limitations in production management, operation management and technology research and development, and their ability to withstand risks was weak. In addition, the impact of the domestic COVID-19 epidemic ha caused a high industrial chain vulnerability risk.

The method of reducing energy consumption in large blast furnace smelting by increasing top pressure

Based on the fundamental processes and principles of ironmaking in a BF, an analysis was conducted on the production technical data from 18 large-scale 3200 m3 BFs in China in 2020. The study systematically investigated the influence of top pressure on reduction, air injection, furnace top, energy consumption, and pig iron composition within the BF. Practical operations in a newly No. 1 3200 m3 BF in a Chinese company demonstrated that increasing the top pressure not only effectively improved the smelting process, operational stability, and reduced furnace fluctuations but also led to a decrease in dust emissions, increased pig iron yield and quality, and significantly reduced fuel consumption and process energy consumption. Against the backdrop of dual carbon objectives, gaining a scientific understanding of the dynamic operation principles of the BF smelting process and continuously exploring low-carbon ironmaking methods have become the focus for professionals and researchers in the fields of BF ironmaking, production management, technology, and scientific research.

Permeation of the term “analytics” in production and operations management research

This is an exploratory study to analyze the permeation of the term/word “analytics” in the operations management domain by reviewing 2175 papers published in the Production and Operations Management journal (POMJ) since its inception in the winter 1992 until the summer of 2022. We identify the words that commonly precede the term “analytics” in these papers. We also identify the most common words that appear in the research papers in which the term “analytics” has appeared. This analysis allows us to reflect on the contexts in which analytics studies have focused and the influence they might exert in future studies. Results show that the usage of the term “analytics” has increased from less than 2% of articles published in POMJ during the period (2007–2016) to about 1 out of every 10 articles published from 2020 to the summer of 2022.

Research in Production Systems and Management: “How to” and Lessons

This paper has multiple objectives. The first motivation comes from the fact that research in production systems and management is challenging, and it is even harder to teach a beginning researcher or graduate student how to embark on good research. In this regard of research pedagogy, we outline salient research principles behind conducting research in the design of manufacturing systems. Arguably, these are more widely applicable to research in other domains; nevertheless, our interest and illustrative examples are closely drawn from the manufacturing systems context. The second purpose is to pay tribute to my academic advisers, Profs. Jean-Marie Proth and George Harhalakis, for all that they taught me and so I can use my personal example to illustrate these research principles. Finally, we include a specific research area of supply chain/network design to illustrate modeling and algorithmic developments under various production situations.

Prescriptive block replacement policy for production degrading systems

Most of the current research in production management is related to the question of integrating data analytics in optimization models. This leads to some very nice models, especially for maintenance planning. Nevertheless, from our point of view, the question of integrating such data-based maintenance optimization models in production planning context remains challenging. The objective of this work is to investigate first insights into prescriptive maintenance within production management context. In this paper, we propose to elaborate a maintenance decision model for a degrading production system. The model allows to optimize both the expected capacity for production planning without maintenance interruption and a condition preventive replacement setting out of the production time. The maintenance decision is also extended to ensure the production objectives with a new prescriptive decision: the acceleration or deceleration production rate which also impacts the degradation speed.

Established Digital Model of Fruit Body Growth of Agrocybe cylindracea Based on Network Programming

Agricultural information technology is an emerging technology based on the cross-fertilization of information technology and agricultural science, which has caused the rapid development of digital agriculture and smart agriculture. Crop growth models, as one of their core components, can dynamically simulate the crop growth and development process and its relationship with climate factors, soil properties, and management techniques, thus effectively overcoming the strong spatial and temporal limitations in traditional agricultural production management research and providing quantitative tools for early warning and effect assessment of crop productivity prediction under different conditions. This study focuses on the general technical approach, the latest research progress, and future development thinking developed by the authors in the construction and application of the tea mushroom growth model. Based on the fitting method of the data model curve of the Internet laboratory, this study is proposed to use network programming technology to digitally fit the growth curve of cap diameter and stalk diameter of the fruiting body in the process of Agrocybe cylindracea growth. The fitting system adopted the development mode of PHP + MYSQL and took the MYSQL database as the core, which made the curve fitting of the final experimental data fast, convenient, and more intelligent. This study laid a preliminary foundation for the effective establishment and improvement of laboratory Agrocybe cylindracea, fruiting body growth data statistics and analysis, and graphical output network sharing.

Application of integrated recurrent neural network with multivariate adaptive regression splines on SPC-EPC process

The integration of statistical process control and engineering process control has been reported as an effective way to monitor and control the autocorrelated process. However, because engineering process control compensates for the effects of underlying disturbances, the disturbance patterns become very hard to recognize, especially when various abnormal control chart patterns are mixed and co-existed in the engineering process. In this study, a new control chart pattern recognition model which integrates multivariate adaptive regression splines and recurrent neural network is proposed to not only address the problem of feature selection (i.e., lagged process measurements) but also improve the pattern recognition accuracy. The performance of the proposed method is evaluated by comparing the recognition results of multivariate adaptive regression splines and recurrent neural network with the results of four competing approaches (multivariate adaptive regression splines-extreme learning machine, multivariate adaptive regression splines-random forest, single recurrent neural network, and single random forest) on the simulated individual process data. The experimental study shows that the proposed multivariate adaptive regression splines and recurrent neural network approach can not only solve the problem of variable selection but also outperform other competing models. Moreover, according to the lagged process measurements selected by the proposed approach, lagged observations that exerted significant impact on the construction of the control chart pattern recognition model can be identified successfully. This study has significant implications for research and practice in production management and provides a valuable reference for manufacturing process managers to better understand and develop strategies for control chart pattern recognition.

Interplay between Competing Policy Regimen in Supply Networks

Competing policy regimen may arise owing to the incompatibility of incentives between either a local state and a federal government, or between two different government jurisdictions across which supply networks operate. Traditional studies of supply chain dynamics typically explore the impact of policies as standalone instruments. This research explores how simultaneous implementation of competing policy regimen, and their interplay, can impact the supply dynamics between agricultural producers and customers. Our work is motivated by the federal/state dissonance in the case of agriculture supply chains in India. In this case alternative and simultaneous policy interventions, ostensibly aimed at transforming production and distribution, lead to shifts in the bargaining power of producers, intermediaries and customers, with counter-intuitive and competing outcomes. We conclude this paper by pointing to the implications of competing policy regimen, and their interplay, for the field of production and supply chain management research.

Formulating and clarifying the research topic: insights and a guide for the production management research community

Paper aims To provide guidance on formulating and clarifying research questions from abstract and broad ideas. Originality Reports of empirical research invariably offer limited insights on the opaque process of developing research questions, aims and objectives. Moreover, we are not aware of a similar discussion within this journal, as well as other management journals. Research method This is a theoretical paper. Main findings Among other factors, our discussion highlights the role of theory and self-reflection in the process of research topic refinement. We consider the nature and types of theoretical contribution a research project can make, highlighting some common reasons why journal submissions are often rejected due to failure to provide a theoretical contribution. Implications for theory and practice Greater reflexivity in this process should ultimately lead to clearer theoretical contributions and more manageable research topics, with greater practical and societal relevance.

Industry 4.0: coherent definition framework with technological and organizational interdependencies

PurposeThe purpose of this paper is to introduce coherent Industry 4.0 definition via a rigorous analysis framework, and provide a holistic view of technological, organizational and other key aspects (variables) of Industry 4.0 along with the identification of interdependencies that co-occur between them.Design/methodology/approachThe study conducts a systematic literature review using Preferred Reporting Items for Systematic Review and Meta-Analysis methodology, and includes 675 papers analyzed both quantitatively and qualitatively. The former utilizes TIBCO Statistica. Furthermore, to define Industry 4.0, the authors reviewed 52 publications.FindingsIndustry 4.0 is a multidimensional system of value creation that includes 42 groups of terms in management, organizational and business-related variables, 30 technological and manufacturing-related variables – classified into seven categories – and several interdependencies that co-occur between them.Practical implicationsThe analyses’ outcomes are of high importance both for academia and industry practitioners, as the findings elucidate the meaning of Industry 4.0 and may be used as the basis of future research in management, production management, industrial organizations and other Industry 4.0-related disciplines. Regarding industrial companies, the publication serves as a compendium, and should support industrial businesses in the transition from traditional manufacturing into the Industry 4.0 era.Originality/valueThis work’s novelty and value is threefold: first, the paper introduces an Industry 4.0 definition framework based on the most popular publications in the field. Second, the paper identifies and presents Industry 4.0’s common technologies and organizational variables via a systematic and current literature review. Finally, the paper extends the ongoing discourse on Industry 4.0. For the first time in this discipline, interdependences between identified Industry 4.0 variables are presented and discussed.

Research in Production and Operations Management: A University-Based Bibliometric Analysis

Universities across the world are contributing greatly to production and operations management (POM) research and playing significant roles in social and economic development. This article analyzes the performance of universities in POM research and development between 1990 and 2014. The Web of Science core collection database is used to collect all the necessary data. The results show a wide diversity among the countries of origin of the top universities, with some of them being in Asia, Europe, and North America. These results are quite different from many other management areas where English-speaking countries, especially the USA, tend to be dominant. Hong Kong Polytechnic University is the most productive university, while Michigan State University is the most influential one. Time-based evolution reveals that the USA previously had a more dominant position, while now there is more distribution of top universities around the world. The analysis of selected journals indicates that many journals tend to be more influenced by their respective countries of origin. However, other journals show a more general profile by publishing papers from most of the countries around the world.

How Research in Production and Operations Management May Evolve in the Era of Big Data

We are living in an era in which data is generated in huge volume with high velocity and variety. Big Data and technology are reshaping our life and business. Our research inevitably needs to catch up with these changes. In this short essay, we focus on two aspects of supply chain management, namely, demand management and manufacturing. We feel that, while rapidly growing research on these two areas is contributed by scholars in computer science and engineering, the developments made by production and operations management society have been insufficient. We believe that our field has the expertise and talent to push for advancements in the theory and practice of demand management and manufacturing (of course, among many other areas) along unique dimensions. We summarize some relevant concepts emerged with Big Data and present several prototype models to demonstrate how these concepts can lead to rethinking of our research. Our intention is to generate interests and guide directions for new research in production and operations management in the era of Big Data.

A Review of Production and Operations Management Research on Outsourcing in Supply Chains: Implications for the Theory of the Firm

This paper reviews the state of the art in Productions and Operations Management (POM) academic research regarding outsourcing in supply chain contexts. We first acknowledge the “Theory of the Firm” (ToF), the venerable and vast body of thought regarding where the firm draws the boundary between what it performs in‐house and what it outsources. Despite the clear linkage between outsourcing and POM, the ToF literature is most closely associated with the fields of strategy and economics. This disconnect might in part be due to a difference in theoretical lenses and terminology, which we address for the POM audience by providing a ToF tutorial. Our review of publications by the POM community from 2000 to 2016 includes a framework that organizes the in‐scope papers and a structured summary of each work. We partition the research into empirical/conceptual and analytical sub‐literatures, each of which gets its own critical assessment and discussion of open opportunities. Along the way, we articulate the features of the POM lens that distinctively position POM researchers to contribute further to the ToF, a convergence which we hope to encourage through this study. A deeper conversation among strategy, economics, and POM would enrichen the rigor and the relevance of each field.

China-related POM research: Literature review and suggestions for future research

This study investigates trends in China-related production and operations management (POM) research over the past 10 years (2006–2015). Descriptive statistics analyses are used to identify trends in topics, data, and contributions. We also identify representative examples from the literature to illustrate topics and contributions. Due to China's economic success, there has been a remarkable growth of China-related POM research in the past 10 years. Supply chain management, performance measurement and productivity, regulatory and environmental issues in operations, and purchasing/sourcing systems are the four most prominent research areas, which is a different pattern from the publications on other emerging economies. The number of articles adopting novel frameworks and approaches has increased, while the number of descriptive articles has decreased. This literature review offers an overview of previous China-related POM articles and provides several areas for future research. It also provides a better understanding of how China-related POM research has evolved and of new research topics that are emerging, which will help researchers to identify key POM issues in China.

How Research in Production and Operations Management May Evolve in the Era of Big Data

We are living in an era in which data is generated in huge volume with high velocity and variety. Big Data and technology are reshaping our life and business. Our research inevitably needs to catch up with these changes. In this short essay, we focus on two aspects of supply chain management, namely, demand management and manufacturing. We feel that, while rapidly growing research on these two areas is contributed by scholars in computer science and engineering, the developments made by production and operations management society have been insufficient. We believe that our field has the expertise and talent to push for advancements in the theory and practice of demand management and manufacturing (of course, among many other areas) along unique dimensions. We summarize some relevant concepts emerged with Big Data and present several prototype models to demonstrate how these concepts can lead to rethinking of our research. Our intention is to generate interests and guide directions for new research in production and operations management in the era of Big Data.

Economic costs of recorded reasons for cow mortality and culling in a pasture-based dairy industry

The objective of this study was to determine the economic costs associated with different reasons for cow culling or on-farm mortality in a pasture-based seasonal system. A bioeconomic model was developed to quantify costs associated with the different farmer-recorded reasons and timing of cow wastage. The model accounted for the parity and stage of lactation at which the cows were removed as well as the consequent effect on the replacement rate and average age structure of the herd. The costs and benefits associated with the change were quantified, including animal replacement cost, cull salvage value, milk production loss, and the profitability of altered genetic merit based on industry genetic trends for each parity. The total cost of cow wastage was estimated to be NZ$23,628/100 cows per year (NZ$1 = US$0.69) in a pasture-based system. Of this total cost, NZ$14,300/100 cows worth of removals were for nonpregnancy and unknown reasons, and another NZ$3,631/100 cows was attributed to low milk production, mastitis, and udder problems. The total cost for cow removals due to farmer-recorded biological reasons (excluding unknown, production, and management-related causes) was estimated to be NZ$13,632/100 cows per year. Of this cost, an estimated NZ$10,286/100 cows was attributed to nonpregnancy, mastitis, udder problems, calving trouble, and injury or accident. There is a strong economic case for the pasture-based dairy industries to invest in genetic, herd health, and production management research focused on reducing animal wastage due to reproductive failure, mastitis, udder problems, injuries or accidents, and calving difficulties.

Применение функционально-стоимостного анализа в управлении персоналом организации

Many users think that functional cost analysis (FCA) is quite diffi cult to understand. Perhaps this is due to the fact that there is too little information explaining what it actually is. The aim of this work is the essence of functional-cost analysis, ease-of-use. FCA is a method for a systematic study of functions, the functionality of various objects and their costs. Advantage of FSA is the presence of a fairly simple computational and graphical methods to give a dual quantitative assessment of the identifi ed causal relationships. This advantage puts the FSA in a number of the most eff ective methods of the analysis which are not only technical, but also socio-economic systems, structures, methods of organizing and planning production management and scientific research. However, the work of the FSA is carried out in isolation from the economic calculations of the enterprises and unions. Therefore, the economic standards of existing production are not covered by the functional approach, based on substantive economic analysis, planning from the achieved level. Value analysis management system allows to perform the following activities: definition and implementation total cost analysis of business processes at the enterprise (marketing, production of goods and provision of services, marketing, quality management, warranty maintenance, etc.); functional analysis associated with the establishment and justification carried out by structural subdivisions of an enterprise functions in order to ensure production of high quality products and services; definition and analysis of basic, additional and unnecessary cost functional; comparative analysis of options for reducing costs in production, marketing and management by streamlining the functions of the structural divisions of the enterprise; analysis of integrated improved results of the company.

Environmental sustainability and production: taking the road less travelled

The research on production and operations management and its linkage to environmental sustainability has seen growth in recent years. The International Journal of Production Research (IJPR) community of scholars has contributed to the advancement of this field. This paper provides an overview of how the research in IJPR has evolved alongside the social-environmental evolution. An overview of the literature of the past 55 years, especially more recent works, is provided. Future predictions of research topics and influences are introduced. Overall, this review found that the call for incorporating environmental sustainability into production research goes back for decades to the early years of IJPR publications. Recent work shows a broader perspective on production research expanding to inter-organisational, supply chain, research. This expanded focus is especially evident in environmental sustainability research. There is still a need and call for expanding the horizon of production and operations management research and environmental sustainability. Travelling the road less travelled is more difficult and complex, but the rewards at the end of this road are a healthy society and environment.