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This study aims to provide an overall framework that connects and explains a macro-perspective of the findings from the five studies of this special issue. Through this, we aim to answer two main questions: How can Lean and Industry 4.0 be integrated, and what are the outcomes for workers from such integration?

The special issue received 64 papers that were evaluated in multiple stages until this final sample of five papers that describe different facets of the integration between Lean and Industry 4.0 and their relationship with worker activities. In this introduction, we review the main findings of these five studies and propose an integrative view and associated propositions. A discussion provides directions to advance the field further.

The framework shows that when Lean and Industry 4.0 are integrated, companies will face two types of tensions, dialectical and paradoxical, which require different managerial approaches. By managing such tensions, the Lean-Industry 4.0 integration can help improve social performance, as well as develop systematic problem-solving and cumulative learning capabilities. Five important themes for this field of research are outlined: the importance of work routines, legitimation, competence, sense and mental flexibility.

This study brings a new theoretical perspective to the integration of Lean with Industry 4.0-related digital technologies. The results go beyond the usual view of improving operational performance and dig into the effects on workers. It also shows that the integration process relies on and can enhance human capabilities such as learning and problem-solving.

The purpose of this study is to examine the welfare effects of product standards (which fall under Non-Tariff Barriers (NTBs)) on an exporting country when the country by its own choice prefers to follow the null standard for the domestic market, which is not possible due to high set up cost at two different standards. The model has used a theoretical framework to analyze the effects and has derived some important results. If the standard is not linked with a true negative externality, the exporting country, given the assumptions of the model will always prefer to be discriminated by “tariff” and the importing country will prefer to protect its market by “tariff” rather than going for NTB. The typical assumptions taken here resemble the trade between developed and developing countries when the developed country imposes some minimum standard on a product but becomes relatively “costly” for the developing country to comply with. As the importing country is not free to set tariffs, it will use NTB as a minimum standard (as it is welfare-improving than free trade). However, the minimum standard also affects the exporting country's local producers and consumers. So NTB leads to a worse situation for both countries and definitely worst for the exporting country. Using a game theoretic framework, the study shows that the imposition of standards which does not address any real externality can be an optimum response for an importing country leading to a loss in the global welfare compared to a free trade situation.

The study aimed to address how recruits perceive their roles and develop professional identities during in-classroom and in-field training.

This study explored the professional identity formation process by analysing asynchronous surveys with recruits from 13 municipal police departments in British Columbia, Canada. The participants were surveyed twice: after classroom-based training following Block I at the British Columbia Police Academy (BCPA) and after their departmental field training following Block II.

The analysis revealed that police recruits lacking public safety experience transformed their occupation and lifestyle. The training at the police academy helped develop recruits' muscle memory as they applied their knowledge to the situation through hands-on practice. Moreover, teamwork at the police academy and during field training allowed recruits to form their police identity. The study was conducted between 2020 and 2021 during the COVID-19 pandemic, thus revealing how the recruits learnt effectively whilst facing continuous challenges and adjusting.

This study relied solely on the respondents' language in text-based answers; therefore, it was not possible to ask follow-up questions or seek clarification. Consequently, several inputs were excluded from the analysis. This would not have been the case if a quantitative method, where answers can be selected accurately, had been used.

This study demonstrates that police recruits acquire diverse competencies and skill sets through rigorous formal requirements, nuanced informal aspects and comprehensive training at the BCPA and during field training, all of which pivotal in shaping their professional identities.

This project set out to explore information scholars’ perceptions of the influence of their keyword selections and the implications of their linguistic choices on possibilities for and perceptions of the field of Information Science. We trialed a narrative methodological approach to investigate the multiple stories told with specific keywords, how they relate to larger discourses within the field and the impact they have on the lives of information researchers.

This paper draws on Arthur Frank’s narrative analysis to consider keywords as stories, which shape one’s sense of professional identity and belonging. The analysis, which is informed by insights from multi-disciplinary scholars of keywords, employs data from a keywords-oriented workshop with Information School faculty and students, as well as an online questionnaire sent to heads of Information Schools.

We did not find a singular definitive story of information science scholars’ experiences with keywords. Rather we identify tensions surrounding common and contested understandings of discipline, canon and information, engaging the complexity of interdisciplinary, international, intellectual and moral claims of the field. This research offers insight into the experiential factors that shape scholars’ engagement with keywords and the tensions they can create.

A wealth of bibliometric analyses of keywords focuses on finding the “right” words to describe the scholarship you seek or the work you want others to discover. However, this study offers information researchers a novel approach, creating space to acknowledge the generative tensions of keywords, beyond the extractive logic of search and retrieval.

The purpose of this paper is to examine the digitalization of operational processes and activities in lean manufacturing firms and explore the associated learning implications through the lens of cumulative capability theory.

Adopting a multiple-case design, we examine four cases of digitalization initiatives within lean manufacturing firms. We collected data through semi-structured interviews and direct observations during site visits.

The study uncovers the development of learning capabilities as a result of integrating lean and digitalization. We find that digitalization in lean manufacturing firms contributes to the development of both routinized and evolutionary learning capabilities in a cumulative fashion.

The study adds nuance to the limited theoretical understanding of the integration of lean and digitalization by showing how it cumulatively develops the learning capabilities of lean manufacturing firms. As such, the study supports the robustness of cumulative capability theory. We further contribute to research by offering empirical support for the cumulative nature of learning.

This paper aims to present a systematic literature review and bibliometric analysis of research papers published on chat generative pre-trained transformer (ChatGPT), an OpenAI-developed large-scale generative language model. The study’s objective is to provide a comprehensive assessment of the present status of research on ChatGPT and identify current trends and themes in the literature.

A total of 328 research article data was extracted from Scopus for bibliometric analysis, to investigate publishing trends, productive countries and keyword analysis around the topic and 34 relevant research publications were selected for an in-depth systematic literature review.

The findings indicate that ChatGPT research is still in its early stages, with the current emphasis on applications such as natural language processing and understanding, dialogue systems, speech processing and recognition, learning systems, chatbots and response generation. The USA is at the forefront of publishing on this topic and new keywords, e.g. “patient care”, “medical”, “higher education” and so on are emerging themes around the topic.

These findings underscore the importance of ongoing research and development to address these limitations and ensure that ChatGPT is used responsibly and ethically. While systematic review research on ChatGPT heralds exciting opportunities, it also demands a careful understanding of its nuances to harness its potential effectively.

Overall, this study provides a valuable resource for researchers and practitioners interested in ChatGPT at this early stage and helps to identify the grey areas around this topic.

Simulations exist for the prediction of the behaviour of building structural systems under fire, including two-way coupled fire-structure interaction. However, these simulations do not include detailed models of the connections, whereas these connections may impact the overall behaviour of the structure. Therefore, this paper proposes a two-scale method to include screw connections.

The two-scale method consists of (a) a global-scale model that models the overall structural system and (b) a small-scale model to describe a screw connection. Components in the global-scale model are connected by a spring element instead of a modelled screw, and the stiffness of this spring element is predicted by the small-scale model, updated at each load step. For computational efficiency, the small-scale model uses a proprietary technique to model the behaviour of the threads, verified by simulations that model the complete thread geometry, and validated by existing pull-out experiments. For four screw failure modes, load-deformation behaviour and failure predictions of the two-scale method are verified by a detailed system model. Additionally, the two-scale method is validated for a combined load case by existing experiments, and demonstrated for different temperatures. Finally, the two-scale method is illustrated as part of a two-way coupled fire-structure simulation.

It was shown that proprietary ”threaded connection interaction” can predict thread relevant failure modes, i.e. thread failure, shank tension failure, and pull-out. For bearing, shear, tension, and pull-out failure, load-deformation behaviour and failure predictions of the two-scale method correspond with the detailed system model and Eurocode predictions. Related to combined load cases, for a variety of experiments a good correlation has been found between experimental and simulation results, however, pull-out simulations were shown to be inconsistent.

More research is needed before the two-scale method can be used under all conditions. This relates to the failure criteria for pull-out, combined load cases, and temperature loads.

The two-scale method bridges the existing very detailed small-scale screw models with present global-scale structural models, that in the best case only use springs. It shows to be insightful, for it contains a functional separation of scales, revealing their relationships, and it is computationally efficient as it allows for distributed computing. Furthermore, local small-scale non-convergence (e.g. a screw failing) can be handled without convergence problems in the global-scale structural model.

Considering the direct impact of retailers' performance on the economy, this paper aimed to propose a comprehensive framework to evaluate the performance of different branches of a retailer.

Through a case study, the weights of indicators were calculated by the best-worst method (BWM) and the branches' performance was appraised using data envelopment analysis (DEA).

The branches were ranked in terms of performance, and sensitivity analysis and statistical tests were conducted to realize the weaknesses and strengths of the branches. Then, some strategies were proposed using strengths, weaknesses, opportunities and threats (SWOT) analysis to improve the performance of the weak branches.

This paper contributes to previous studies on the evaluation of retailers' performance by proposing a triple framework based on resilience, sustainability and sales-marketing indicators. This paper focused on branches' operations and branches' optimization by improving performance in terms of these three indicators. This paper also offers a qualitative and quantitative analysis of retailers' performance, which has received less attention in previous studies.

The main aim of the current paper is to find a numerical plan for hydraulic fracturing problem with application in extracting natural gases and oil.

First, time discretization is accomplished via Crank-Nicolson and semi-implicit techniques. At the second step, a high-order finite element method using quadratic triangular elements is proposed to derive the spatial discretization. The efficiency and time consuming of both obtained schemes will be investigated. In addition to the popular uniform mesh refinement strategy, an adaptive mesh refinement strategy will be employed to reduce computational costs.

Numerical results show a good agreement between the two schemes as well as the efficiency of the employed techniques to capture acceptable patterns of the model. In central single-crack mode, the experimental results demonstrate that maximal values of displacements in x- and y- directions are 0.1 and 0.08, respectively. They occur around both ends of the line and sides directly next to the line where pressure takes impact. Moreover, the pressure of injected fluid almost gained its initial value, i.e. 3,000 inside and close to the notch. Further, the results for non-central single-crack mode and bifurcated crack mode are depicted. In central single-crack mode and square computational area with a uniform mesh, computational times corresponding to the numerical schemes based on the high order finite element method for spatial discretization and Crank-Nicolson as well as semi-implicit techniques for temporal discretizations are 207.19s and 97.47s, respectively, with 2,048 elements, final time T = 0.2 and time step size τ = 0.01. Also, the simulations effectively illustrate a further decrease in computational time when the method is equipped with an adaptive mesh refinement strategy. The computational cost is reduced to 4.23s when the governed model is solved with the numerical scheme based on the adaptive high order finite element method and semi-implicit technique for spatial and temporal discretizations, respectively. Similarly, in other samples, the reduction of computational cost has been shown.

This is the first time that the high-order finite element method is employed to solve the model investigated in the current paper.