A review of operations management literature: a data-driven approach

Production and operations management has been a significant field of research for many years. However, other than an educated guess by researchers in the field or a perusal of textbook chapter titles, the major topics and their trends over time are not well established. This study provides a comprehensive review of production and operations management literature using a data-driven approach. We use Latent Semantic Analysis on 21,053 abstracts representing all publications in six leading operations management journals since their inception. 18 unique topic clusters were identified algorithmically. Just being aware of the history of research topics should be of great interest to all academics in the field, but to help future researchers we conducted three post hoc analyses: 1) analysis of methods used in all these studies, 2) citation rates by topic area over time, and 3) the growing prevalence of research covering multiple topics.     

On differences in how operations and supply chain managers approach quality management

In this research, we administered surveys to operations and supply chain managers from different companies to better understand how they approached quality management. The underlying research question was whether the increased emphasis in supply chain management in the workplace had implications for how quality management is practiced and how quality-related values are emphasised. We found that those who identified themselves as supply chain managers utilised and emphasised quality tools and values to a greater extent than those who identified themselves as operations managers. The tools emphasised by supply chain managers included benchmarking, complaint resolution, design for the environment, ERP, supplier development, focus groups, and supply chain management. The primary theoretical implication of this study is that there exists an emerging field that we can term ‘supply chain quality’. This study provides a preliminary outline of the domain of this field.     

National culture and operations management: a structured literature review

National culture has received a substantial amount of interest in the operations management literature. We present the first structured review of articles studying national culture in operations management. Our search returned 51 papers published in ten leading journals between 2000 and 2017. We sort and analyse the papers according to three focus areas of operations management (strategy, execution and improvement). We also analyse the papers according to whether they address the relevance of national culture, the impact of national culture or the actions managers can use to manage or mitigate the effects of national culture. We find that national culture appears as a relevant variable in all focus areas of operations management research but that the direction and strength of its impact remain undetermined. Only a handful of papers address how managers can actively deal with challenges related to national culture. We propose a research agenda and a guiding framework for future research.     

Application of genetic algorithms in production and operations management: a review

Over the last decade, there has been a rapid growth of the use of genetic algorithms in the various areas of production and operations management. This paper provides a review of genetic algorithms research published in twenty-one major production and operations management journals from 1990–2001. More specifically, it identifies research trends and publication outlets of genetic algorithms applications. Our findings show that there are only a handful of production and operations management areas to which genetic algorithms have been applied as the solution approach. Furthermore, we recognize and discuss potential research areas and outlets in which researchers may target their work as well as the need for top ranked POM journals to consider publishing genetic algorithms related papers.     

Trust in humanitarian operations: a content analytic approach for an Indian NGO

Trust between partners, a key element enabling coordination across supply chains, has recently started gaining attention in humanitarian operations literature. Yet, empirical examination of this concept is scant. Borrowing from extant literature on trust within organisational behaviour stream, this paper aims to empirically verify trust formation types: companion, competence and commitment, in a disaster relief supply chain using primary and secondary data from an Indian Humanitarian relief organisation (HRO). Further, we identify variations in trust formation during disaster relief activities and developmental programmes, and between upstream and downstream partners of a humanitarian relief organisation. Based on the results of our content analysis, we contend that while companion based trust is significantly more prevalent during developmental programmes, competence based trust is important during both disaster periods and otherwise. We also find that there are significant differences in the trust formation between upstream and downstream partners and the HRO. This study has significant theoretical and practical implications on identifying the role of trust in humanitarian operations.     

Information retrieval: United air lines operations system

The development of United Air Lines operational computer system is described. This is a medium-volume general-purpose on-line system with off-line capability, the need for such a system arose from the decentralized nature of airline operations coupled with the increasing need to automate many areas of company operations in addition to the traditional reservations and accounting functions. The computer utility is designed to handle all of the airline's message switching, flight planning and monitoring, and aircraft parts inventory control. Also under evaluation and implementation are applications involving airport terminals and air freight control.     

Evaluating reverse third-party logistics operations using a semi-fuzzy approach

The responsiveness and efficiency of distributed and multi-echelon supply chains are increasingly reliant upon reduced cycle times within forward and reverse logistics operations. Within the high-tech industry, Reverse Logistics (RL) in the form of end-of-life, stock balancing, defective/warranty, recycle, and re-use product returns, is particularly important owing to the complexity and dependency that exist throughout the extended supply chain in order to maintain brand loyalty and customer satisfaction (source, OEM vendors and end customers alike). RL is fast becoming a strategy to acquire an organisational competitive advantage, making the quest to exploit such a function a premeditated decision. The introduction of Third-Party Logistics (3PL) providers has become a necessity for those supply-chain operations where issues of cost and risk mitigation need to be balanced with agility and responsiveness. This paper develops a conceptual framework of the factors influencing Reverse 3PL based upon Information Systems (IS) and associated Resource Commitment (RC) factors. The framework is then tested using a mixed-method research based approach using a 3PL organisation based in Thailand. The research findings reveal that among the proposed factors, IS- and RC-based operating performance, resource cost-effectiveness and RC (at financial, managerial and technological levels in the firm) were deemed to have a stronger positive relationship and input into reverse 3PL operations for the firm in context. The model is validated using the techniques of System Dynamics and Fuzzy Cognitive Mapping.     

Machine-component cell formation in group technology: a neural network approach

This paper presents a neural network clustering method for the part-machine grouping problem in group technology. Among the several neural networks, a Carpenter-Grossberg network is selected due to the fact that this clustering method utilizes binary-valued inputs and it can be trained without supervision. It is shown that this adaptive leader algorithm offers the capability of handling large, industry-size data sets due to the computational efficiency. The algorithm was tested on three data sets from prior literature, and solutions obtained were found to result in block diagonal forms. Some solutions were also found to be identical to solutions presented by others. Experiments on larger data sets, involving 10000 parts by 100 machine types, revealed that the method results in the identification of clusters with fast execution times. If a block diagonal structure existed in the input data, it was identified to a good degree of perfection. It was also found to be efficient with some imperfections in the data     

Changes in Toyota Motors’ operations management

A key driver behind Toyota Motors’ rise to prominence has been the Toyota Production System (TPS). This pillar of the firm's competitive strength was developed over several decades. As of the late 1980s, various changes were introduced into the TPS. Some of these, such as line segmentation, the use of inter-segment buffers and high-tech automation, have been portrayed as breaks with TPS foundations. With virtually no exception published accounts on these changes stop with the situation in the mid-1990s. Based on general literature and three factory visits, this article aims to provide an update on the situation in April 2001.     

Information processing by biochemical networks: a dynamic approach

Understanding how information is encoded and transferred by biochemical networks is of fundamental importance in cellular and systems biology. This requires analysis of the relationships between the stochastic trajectories of the constituent molecular (or submolecular) species that comprise the network. We describe how to identify conditional independences between the trajectories or time courses of groups of species. These are robust network properties that provide important insight into how information is processed. An entire network can then be decomposed exactly into modules on informational grounds. In the context of signalling networks with multiple inputs, the approach identifies the routes and species involved in sequential information processing between input and output modules. An algorithm is developed which allows automated identification of decompositions for large networks and visualization using a tree that encodes the conditional independences. Only stoichiometric information is used and neither simulations nor knowledge of rate parameters are required. A bespoke version of the algorithm for signalling networks identifies the routes of sequential encoding between inputs and outputs, visualized as paths in the tree. Application to the toll-like receptor signalling network reveals that inputs can be informative in ways unanticipated by steady-state analyses, that the information processing structure is not well described as a bow tie, and that encoding for the interferon response is unusually sparse compared with other outputs of this innate immune system.     

Social capital,a theory for operations management: a systematic review of the evidence

As Pfeffer (1993 Pfeffer, J. 1993. Barriers to the advance of organizational science: paradigm development as a dependable variable. Academy of Management Review, 18(4): 599–620. [Crossref], [Web of Science ®] , [Google Scholar]) states that until agreement is reached on a subject, progress may be slow. This paper converges the discussions on social capital in the operations management literature by way of a systematic literature review of 3- and 4-star journals. Human resource management, voluntary work and entrepreneurship were identified as minor themes within the review and thus potentially underexplored areas. Quality management, project management and new product development show significant use of social capital and particularly the role of social capital in the intrafirm environment. Finally, supply chain management shows the most significant use of social capital, particularly in explaining the characteristics of buyer–supplier relationships and how these impact inter-firm performance. Areas of future research are presented that draw on all forms of social capital to explore how they may be affect by contextual factors. The paper concludes by proposing a conceptual model of social capital for use within operations management.     

Enterprise risk management: a DEA VaR approach in vendor selection

Enterprise risk management (ERM) has become an important topic in today's more complex, interrelated global business environment, replete with threats from natural, political, economic, and technical sources. The development and current status of ERM is presented, with a demonstration of how risk modelling can be applied in supply chain management. Within supply chain management, a major managerial decision is vendor selection. We start with discussion of the advanced ERM technology, i.e. value-at-risk (VaR) and develop DEA VaR model as a new tool to conduct risk management in enterprises. A vendor selection set of data is used to demonstrate how this model can be used to assess supply risks in ERM. Such models provide means to quantitatively improve decision making with respect to risk.     

Intelligent secondary control in smart microgrids: an on-line approach for islanded operations

Dealing with islanded microgrids (MGs), this paper aims at improving the secondary control process to restrict the fluctuations in both the voltage and frequency signals. With the aim of retrieving these parameters at the nominal values, an intelligent control scheme is devised to adjust the corresponding control parameters. To do so, an on-line self-optimizing control approach is embedded in the MG’s central controller. In the tuning process, evolutionary-based techniques such as genetic algorithms provide proper initial adjustment for the parameters. Subsequently, an artificial neural network (ANN) is triggered to provide accurate online modification of the control parameters. Specifically, the training capability of the ANN mechanism along with its extensibility feature avoids the dependency of the controller on the operating point conditions and accommodates different changes and uncertainty reflections. Detailed simulation studies are conducted to investigate the performance of the proposed approach, and the results are discussed in depth.     

A comprehensive assessment of measurement equivalence in operations management

This paper provides a comprehensive framework for treating equivalence both prior to data collection and during subsequent analyses, and assesses the extent to which equivalence is considered in survey research in six leading empirical Operations Management (OM) journals (Decision Sciences, International Journal of Operations & Production Management, International Journal of Production Research, Journal of Operations Management, Management Science and Production and Operations Management). Measurement equivalence of latent variables in survey data is an important condition that should be met in order to meaningfully pool and/or compare data stemming from apparently heterogeneous sub-groups. We assess 465 survey articles from a six-year period from 2006 to 2011 and document these articles in relation to the four main stages of our comprehensive framework: identifying sources of heterogeneity; maximising equivalence prior to data collection; testing measurement equivalence after data collection; and dealing with partial and non-equivalence. We conclude that pooling of data from heterogeneous sub-groups is common practice in OM, but that awareness and testing of equivalence remains limited. Given these findings, we further elaborate the best practices detected in those few OM studies that do address equivalence in some way. We conclude that to improve the quality of OM survey research, authors, editors and reviewers should pay greater attention to equivalence, and we provide a pragmatic checklist of measurement equivalence issues across the four stages.