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The public distribution system (PDS) is an Indian food security system established to manage the distribution of food grains at affordable prices. As a result of the population explosion, the long-established PDS system finds it challenging to maintain operational efficiency, quality, trust and transparency. This paper explores the possibility of leveraging blockchain technology to overcome these operational hurdles.

Through a literature review and expert interactions, the present research identifies critical success factors in terms of enablers and barriers that influence the adoption of blockchain technology in PDS. Furthermore, we propose two independent interpretive structural models (ISM) and MICMAC to characterize these attributes.

The research identifies 15 distinct enablers and ten barriers that influence the diffusion of the latest technology in the sector at focus. The analyses disclose the interrelationships/dependencies among these enablers and between barriers, along with their individual driving power and dependence power.

The research showcases the importance of automating the system and illustrates how the features of blockchain technology can assist in augmenting stakeholder satisfaction levels. However, poor or nonexistent government regulations and patronage are found to be the major impediments to adoption. The research also delineates the cost implications of this barrier through its interrelationships with other barriers.

Interesting inferences are drawn from the models that offer actionable insights for the industry, government and technologists for improving PDS performance. Such interventions will ensure national food security through enhanced trust and transparency, which can further improve efficiency and effectiveness.

This study aims to provide a bibliometric analysis and systematic literature review of Industry 4.0 (I4.0) research in the supply chain (SC) area and to understand related contemporary research trends. I4.0 has the potential to change the way goods are manufactured, distributed and made available to customers through the digitalisation of SC. Although I4.0 originated in 2011 in Germany, its application in managing the SC has only recently started gaining momentum. Therefore, it is essential to understand the research progress and identify the current trends of I4.0 application in the SC field.

A bibliometric analysis was conducted to empirically analyse the literature related to I4.0 implementation in the SC. This study retrieved papers from the Scopus database, reviewing 1,155 articles from the period 2016 to 2023 (November) for bibliometric analysis. Bibliometrix, using R software, was used for the bibliometric analysis, and VOSviewer was used for network analysis.

The findings provide an overview of the most relevant journals, most productive scholars, top academic institutions and top countries contributing to I4.0 research in the SC context. The results show that the most recent research contributions are related to the topics of SC performance, sustainability, digitalisation and digital transformation. Furthermore, a detailed review of articles published in the three and above-rated journals in the Chartered Association of Business Schools list is presented.

The novelty of this study lies in identifying the current research trends and themes of I4.0 research in the SC area. This research benefits researchers by identifying potential research areas for I4.0 implementation in the SC and providing directions for future research.

The digital warehouse management system is an emergence that forms a critical part of the transformation of economic structure in Industry 4.0. In the present business scenario, the warehouse management system encounters a messy layout, poor damage control, unsatisfactory order management, lack of visibility and lack of technological interventions. Digital twin (DT) based warehouse system shows the ontology and knowledge graphs for competitive advantage by consolidating and transferring goods directly from an inbound supplier to an outbound customer on short notice and with no or limited storage. There remains a lack of clarity on how the DT can be implemented successfully in warehouse management.

The current literature remains largely unstructured and scattered due to a lack of a systematic approach to integrating the research implications and analysis. This paper probes the conceptualization of the DT with the help of theoretical analysis using the systematic literature analysis method.

The study explores essential concepts such as interoperability and integrability in implementing DT. Further, it analyzes the role of a supply chain control tower (SCCT) in modern supply chain management. A research framework is proposed for practitioners and academicians by incorporating the opportunities and challenges associated with DT implementation. The research findings are mainly threefold: Conceptualization of DT, Featuring SCCT and Exploration of cross-computer platform interfaces, scalability and maintenance strategies.

This study is among the first to analyze and review DT applications in warehouse management. Moreover, the study proposes a theoretical toolbox for the practitioners to successfully implement the DT in warehouse DT-based warehouse management system: A theoretical toolbox for future research and applications.

Untimely responses to emergency situations in urban areas contribute to a rising mortality rate and impact society's primary capital. The efficient dispatch and relocation of ambulances pose operational and momentary challenges, necessitating an optimal policy based on the system's real-time status. While previous studies have addressed these concerns, limited attention has been given to the optimal allocation of technicians to respond to emergency situation and minimize overall system costs.

In this paper, a bi-objective mathematical model is proposed to maximize system coverage and enable flexible movement across bases for location, dispatch and relocation of ambulances. Ambulances relocation involves two key decisions: (1) allocating ambulances to bases after completing services and (2) deciding to change the current ambulance location among existing bases to potentially improve response times to future emergencies. The model also considers the varying capabilities of technicians for proper allocation in emergency situations.

The Augmented Epsilon-Constrained (AEC) method is employed to solve the proposed model for small-sized problem. Due to the NP-Hardness of the model, the NSGA-II and MOPSO metaheuristic algorithms are utilized to obtain efficient solutions for large-sized problems. The findings demonstrate the superiority of the MOPSO algorithm.

This study can be useful for emergency medical centers and healthcare companies in providing more effective responses to emergency situations by sending technicians and ambulances.

In this study, a two-objective mathematical model is developed for ambulance location and dispatch and solved by using the AEC method as well as the NSGA-II and MOPSO metaheuristic algorithms. The mathematical model encompasses three primary types of decision-making: (1) Allocating ambulances to bases after completing their service, (2) deciding to relocate the current ambulance among existing bases to potentially enhance response times to future emergencies and (3) considering the diverse abilities of technicians for accurate allocation to emergency situations.

With the emergence of the different Industry 4.0 technologies and the interconnectedness between the physical and cyber components within manufacturing systems, the manufacturing environment is becoming more susceptible to unexpected disruptions, and manufacturing systems need to be even more resilient than before. Hence, the purpose of this work is to explore how does incorporating Industry 4.0 into current manufacturing systems affects (positively or negatively) its resiliency.

A Systematic Literature Review (SLR) was performed with a focus on studying the manufacturing system’s resilience when applying Industry 4.0 technologies. The SLR is composed of four phases, which are (1) questions formulation, (2) determining an adequate search strategy, (3) publications filtering and (4) analysis and interpretation.

From the SLR results’ analysis, four potential research opportunities are proposed related to conducting additional research within the research themes in this field, considering less studied Industry 4.0 technologies or more than one technology, investigating the impact of some technologies on manufacturing system’s resilience, exploring more avenues to incorporate resiliency to preserve the state of the system, and suggesting metrics to quantify the resilience of manufacturing systems.

Although there are a number of publications discussing the resiliency of manufacturing systems, none fully investigated this topic when different Industry 4.0 technologies have been considered. In addition to determining the current research state-of-art in this relatively new research area and identifying potential future research opportunities, the main value of this work is in providing insights about this research area across three different perspectives/streams: (1) Industry 4.0 technologies, (2) resiliency and (3) manufacturing systems and their intersections.

This study aims to describe the fundamentals of teaching risk management in a classroom setting, with an emphasis on the learning interface between higher education and the workplace environment for business management students.

The study reviews literature that uses spreadsheets to visualize and model risk and uncertainty. Using six distinct case-based activities (CBAs), the study illustrates the practical applications of software like Palisade @RISK in risk management education. It helps to close the gap between theory and practice. The software assists in estimating the likelihood of a risk event and the impact or repercussions it will have if it occurs. This technique of risk analysis makes it possible to identify the risks that need the most active control.

@RISK can be used to create models that produce results to demonstrate every potential scenario outcome. When faced with a choice or analysis that involves uncertainty, @RISK can be utilized to enhance the perspective of what the future might contain.

The insights from this study can be used to develop critical thinking, independent thinking, problem-solving and other important skills in learners. Further, educators can apply Bloom’s taxonomy and the problem-solving taxonomy to help students make informed decisions in risky situations.

The lack of conceptual approaches for organizing and expressing capabilities, usage and impact of intelligent machines (IMs) in work settings is an obstacle to moving beyond isolated case examples, domain-specific studies, 2 × 2 frameworks and expert opinion in discussions of IMs and work. This paper's purpose is to illuminate many issues that often are not addressed directly in research, practice or punditry related to IMs. It pursues that purpose by presenting an integrated approach for identifying and organizing important aspects of analysis and evaluation related to IMs in work settings. 

This paper integrates previously published ideas related to work systems (WSs), smart devices and systems, facets of work, roles and responsibilities of information systems, interactions between people and machines and a range of criteria for evaluating system performance.

Eight principles outline a straightforward and flexible approach for analyzing and evaluating IMs and the WSs that use them. Those principles are based on the above ideas.

This paper provides a novel approach for identifying design choices for situated use of IMs. The breadth, depth and integration of this approach address a gap in existing literature, which rarely aspires to this paper’s thoroughness in combining ideas that support the description, analysis, design and evaluation of situated uses of IMs.

The authors propose the concept of “Autonomic Cycle for innovation processes,” which defines a set of tasks of data analysis, whose objective is to improve the innovation process in micro-, small and medium-sized enterprises (MSMEs).

The authors design autonomic cycles where each data analysis task interacts with each other and has different roles: some of them must observe the innovation process, others must analyze and interpret what happens in it, and finally, others make decisions in order to improve the innovation process.

In this article, the authors identify three innovation sub-processes which can be applied to autonomic cycles, which allow interoperating the actors of innovation processes (data, people, things and services). These autonomic cycles define an innovation problem, specify innovation requirements, and finally, evaluate the results of the innovation process, respectively. Finally, the authors instance/apply the autonomic cycle of data analysis tasks to determine the innovation problem in the textile industry.

It is necessary to implement all autonomous cycles of data analysis tasks (ACODATs) in a real scenario to verify their functionalities. Also, it is important to determine the most important knowledge models required in the ACODAT for the definition of the innovation problem. Once determined this, it is necessary to define the relevant everything mining techniques required for their implementations, such as service and process mining tasks.

ACODAT for the definition of the innovation problem is essential in a process innovation because it allows the organization to identify opportunities for improvement.

The main contributions of this work are: For an innovation process is specified its ACODATs in order to manage it. A multidimensional data model for the management of an innovation process is defined, which stores the required information of the organization and of the context. The ACODAT for the definition of the innovation problem is detailed and instanced in the textile industry. The Artificial Intelligence (AI) techniques required for the ACODAT for the innovation problem definition are specified, in order to obtain the knowledge models (prediction and diagnosis) for the management of the innovation process for MSMEs of the textile industry.

The purpose of this article is to conduct a bibliometric analysis of the cellular manufacturing system (CMS) literature published from 1982–2021 to identify key issues and trends for the future.

A six-stage methodology is used to conduct a literature review, which includes: (1) article collection; (2) inclusion/exclusion criteria; (3) reviewing the articles; (4) analyzing the articles; (5) framework development; and (6) future research directions. A total of 936 CMS-specific articles are reviewed. This paper made use of three software tools: the R package, VOSviewer and SciMAT.

According to the findings, the majority of CM researchers focused on cell formation and design. The USA, Iran and India are the top three leading publishers. Additionally, the gap and future direction of CM are discussed.

To the best of the authors' knowledge, the current study is the first attempt to investigate CMS evaluation through bibliometric and thematic analysis and provides a decisional framework as well as steps for CMS adoption. For individuals who are interested in understanding more about CMS and its evolution, this paper offers a starting point.

This paper explores how adaptive organizations, companies capable of continuously adapting their organizational model, dynamically solve the universal problems of organizing.

The authors applied grounded theory to data acquired from six interpretative case studies, collected in two rounds of interviews (15 in total), then completing and validating the study’s evidence through triangulation with several secondary data sources.

In adaptive organizations, polyarchies and intrapreneurial employees are essential to shape the division of labour, leading to high levels of autonomy and empowering individuals and teams, while reducing bureaucracy and hierarchy. In terms of the integration of effort, digital solutions are preferred to social proof in the provision of information, while the authors note that incentives are always geared towards developing strong higher-order dynamic capabilities.

This paper has some limitations that could be addressed in future research, including longitudinal studies to analyse the link between the universal problems of organizing and a company's dynamic capabilities.

Adaptive organizations go beyond tech firms in responding to the universal problems of organizing work by making specific use of digital technologies.

The paper studies how companies should organize themselves so that they continuously adapt to an ever-changing competitive environment.