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This study aims to investigate the manufacturing reshoring decision-making content from an Eclectic Paradigm perspective.

Data were collected through a six-step systematic literature review on factors influencing manufacturing reshoring decision-making. The review is based on 100 peer-reviewed journal papers discussing reshoring decision-making contents published from 2009 to 2022.

In total, 80 decision factors were extracted and then categorized into resource-seeking (8%), market-seeking (11%), efficiency-seeking (41%) and strategic asset-seeking (16%) advantages. Additionally, 24% of these were identified as hybrid, which means that they were classified into multiple categories. Some decision factors were further identified as reshoring influencing factors (i.e. drivers, enablers and barriers).

Scholars need to consider what other theories can be used or developed to identify and evaluate the decision factors (determinants) of manufacturing reshoring as well as how currently adopted theory can be further advanced to create clearer and comprehensive theoretical frameworks.

This research underscores the importance of developing clearer and more comprehensive theoretical frameworks. For practitioners, understanding the multifaceted nature of decision factors could enhance strategic decision-making regarding reshoring initiatives.

To the best of the authors’ knowledge, this is the first study to investigate the value and practicality of the Eclectic Paradigm in categorizing factors in manufacturing reshoring decision-making content and presents in-depth theoretical classifications. In addition, it bridges the gap between decision factors and influencing factors in the decision-making content research realm.

The purpose of this paper is to provide scholars with a robust, easy-to-follow structural model for crafting compelling academic publications. Recognizing the diversity of research methodologies and genres, the paper proposes the symmetry of specificity framework as a guide to maintaining coherence, depth and relevance across different sections of an academic paper.

This paper presents a theoretical framework – “symmetry of specificity” – through an iterative approach inspired by supervision and examination of theses, writing and reviewing research papers and editorial work. The framework builds upon the established IMRAD model and uses the concept of symmetry to explain the structural elements of academic publications. Its unique contribution lies in elucidating the two-dimensional funneling process that takes place within academic writing, and providing a nuanced understanding of how to maintain balance between different sections.

The symmetry of specificity framework introduces a novel perspective on academic writing, emphasizing the concept of “symmetry in specificity”. It shows how maintaining a balance in detail and focus across different sections of a research paper can significantly enhance its coherence and relevance. By elucidating the interaction between theory and data in research writing, it provides valuable insights into the nuances of crafting a compelling academic paper.

While the proposed symmetry of specificity framework may not be universally applicable across all types of research, it provides a solid foundation for the development of alternate structures tailored to specific research paradigms. There is ample opportunity for future research to explore adaptations of this model for various types of academic writing, offering a fresh perspective on structuring academic publications and potentially sparking new discussions and innovations in this realm.

This framework can aid both novice and experienced scholars in structuring their research papers effectively. By offering a conceptual roadmap, it guides the writer through the complex process of academic writing, from crafting the methodology and analysis sections to articulating compelling conclusions. Thus, it serves as a useful tool in enhancing the quality and impact of research communication.

This paper presents a unique approach to structuring academic publications that goes beyond the conventional IMRAD model. By offering a theory-based structural model, it contributes to an underexplored area in academic writing and opens up new avenues for pedagogy and practice in research communication.

Given the importance of the growing segmentation of ageing consumers and their increasing interaction with the Internet, digital marketing scholars are becoming more interested in this market. Prior research needs to pay more attention to this market in many contexts of digital marketing. This study aims to provide insights into ageing consumers’ content usage, content typology choices, and online brand advocacy (OBA).

Semi-structured interviews were applied, and 16 consumers from Southern Europe aged 55+ were included. The interviews were transcribed and examined following the principles of content analysis.

According to the research, older consumers display their usage and concerns regarding online content. They have different decision-making processes depending on whether they are purchasing products or services. Likewise, their choices of content typology vary based on the utilitarian or hedonic product category.

This study contributes to the literature by providing insights into this growing segmentation and proposing an OBA framework for older consumers related to content marketing. Finally, the study suggests that older consumers are passive online and active offline brand advocates.

The purpose of this study is to compare violent and non-violent extremists in terms of their age when they first perpetrate an extremist act, and to understand how this relates to other factors underlying extremist behaviours. While the end goal of many extremists may be functionally similar, the pathways into extremism vary, and the literature has demonstrated that a “one-size-fits-all” explanation does not exist. Motivational drivers are complex and dynamic; therefore, attempting to identify a terrorist “profile” has limited applied efficacy.

This study applied a temporal approach (“crime script analysis” or CSA) to identify, map and compare the sequential stages (or “scenes”) in the life histories of violent and non-violent extremists who have committed acts of extremism across different age groups. Crime scripts comprising mainly qualitative data for 40 male extremists (20 violent, 20 non-violent “cases”) were developed, and CSA was conducted according to the age at which they committed their first extremist offence.

Results demonstrated key temporal, developmental differences between the pathways of extremists who commit their first offence at different ages. One key difference was that for both the violent and non-violent extremists, those under 30 used the internet as a main means of joining networks and spreading information, whereas the over 30s made more personal, community links.

This research can aid identification of potential environmental triggers and potential increased susceptibility to triggers across certain age groups.

The purpose of this study is shed light on the underlying forces behind entrepreneurship within a regional innovation system (RIS) in a remote rural region. The authors examine the following questions: Which are the main underlying forces behind the entrepreneurial process in a rural RIS characterized by traditionally low-tech, small-scale businesses? How can the development of a low-tech regional innovation system be conceptualized?

The design of the study is based on entrepreneurship theory. Data analysis followed practices used in phenomenography, a research approach used to analyse and identify commonalities and variations in populations' perceptions of a certain phenomenon. Data are composed using semi-structured interviews and a database composed of company information of all firms in the population.

A proactive mobilization of regional stakeholders and resources can be an important driving force behind the entrepreneurial process and generation of a rural RIS. Innovation can be generated within low-tech industries turning the rural context into an asset. An RIS in a remote rural context can be initiated and orchestrated by regional authorities, but knowledge brokering and orchestration can also be managed by networks of small-scale businesses brought together by mutual benefit and common interests.

Regional innovation systems theory is most often used to study high-tech industries. But by combining regional innovation systems with rural entrepreneurship and entrepreneurship context theory is a fruitful avenue to understand the role of rural entrepreneurship in regional development, even in remote and peripheral regions. Innovation does not need to entail high-tech international environments; it can appear as the result of efforts in low-tech industries in rural and remote environments. The authors’ findings need to be scrutinized; therefore, the authors call for more research on regional innovation systems in rural environments.

It is possible for regional authorities to orchestrate a development process through the actions of a strong regional agent but also by supporting the creation of networks of small businesses that are built on trust and common interests.

This study contributes to the literature with a new perspective to the study of entrepreneurship and of regional innovation systems. Entrepreneurship research with focus on rural contexts most often highlight limits to entrepreneurship and see entrepreneurship as “just running a business”. A perspective that starts from innovation and innovative behaviour, despite the rural context and embedded resources, helps to generate new knowledge that can enrich the understanding of entrepreneurship and also be the foundation for more precise business development policies in rural settings.

This study employs the Social Identity Theory to examine the differential effects of personal and social dimensions of fear of missing out (FOMO) on sustainable food consumption (SFC) practices.

An online survey-based empirical study was conducted with 395 respondents. The data were analysed using structural equation modelling and Hayes process Macro in SPSS.

SFC was found to be positively influenced by personal FOMO. Contrary to expectations, social FOMO had a negative correlation with SFC. Social influence and social identity were shown to be positively correlated, whilst the social influence-SFC relationship was favourable. This approach was aided by social identity.

The study supports personal FOMO as an SFC-influencing factor. It evaluates the differential effects of FOMO’s personal and social dimensions on SFC. It also demonstrates that social FOMO negatively affects SFC, contrary to expectations.

The study advises sustainable food firms to reduce personal FOMO via advertising and messaging.

This research is amongst the first to segregate the differential effects of social and personal FOMO regarding SFC behaviour. Research has examined FOMO as a higher-order construct involving social and personal aspects. Second, FOMO is often associated with negative behaviours including social media addiction and substance abuse. This FOMO-related research analyses a desired behaviour.

Accounting information systems are mainly rule-based, and data are usually available and well-structured. However, many accounting systems are yet to catch up with current technological developments. Thus, artificial intelligence (AI) in financial accounting is often applied only in pilot projects. Using AI-based forecasts in accounting enables proactive management and detailed analysis. However, thus far, there is little knowledge about which prediction models have already been evaluated for accounting problems. Given this lack of research, our study aims to summarize existing findings on how AI is used for forecasting purposes in financial accounting. Therefore, the authors aim to provide a comprehensive overview and agenda for future researchers to gain more generalizable knowledge.

The authors identify existing research on AI-based forecasting in financial accounting by conducting a systematic literature review. For this purpose, the authors used Scopus and Web of Science as scientific databases. The data collection resulted in a final sample size of 47 studies. These studies were analyzed regarding their forecasting purpose, sample size, period and applied machine learning algorithms.

The authors identified three application areas and presented details regarding the accuracy and AI methods used. Our findings show that sociotechnical and generalizable knowledge is still missing. Therefore, the authors also develop an open research agenda that future researchers can address to enable the more frequent and efficient use of AI-based forecasts in financial accounting.

Owing to the rapid development of AI algorithms, our results can only provide an overview of the current state of research. Therefore, it is likely that new AI algorithms will be applied, which have not yet been covered in existing research. However, interested researchers can use our findings and future research agenda to develop this field further.

Given the high relevance of AI in financial accounting, our results have several implications and potential benefits for practitioners. First, the authors provide an overview of AI algorithms used in different accounting use cases. Based on this overview, companies can evaluate the AI algorithms that are most suitable for their practical needs. Second, practitioners can use our results as a benchmark of what prediction accuracy is achievable and should strive for. Finally, our study identified several blind spots in the research, such as ensuring employee acceptance of machine learning algorithms in companies. However, companies should consider this to implement AI in financial accounting successfully.

To the best of our knowledge, no study has yet been conducted that provided a comprehensive overview of AI-based forecasting in financial accounting. Given the high potential of AI in accounting, the authors aimed to bridge this research gap. Moreover, our cross-application view provides general insights into the superiority of specific algorithms.

The goal of this narrative review was to look at the link between the Mediterranean diet (MD) and the telomere length. Furthermore, this study aims to understand the impact of the MD on obesity-related telomere length.

Relevant literature was reviewed to explore the potential influence of the MD on telomere length and its association with obesity.

The MD is one of the healthiest diets of all known dietary patterns, and it is also linked to the telomere length. Except for fruits and vegetables, the main findings for other MD components are inconsistent. In terms of antioxidant and antiinflammatory properties, using the MD as a weight loss approach is a good method. For predicting changes in obesity characteristics, the initial telomere length is critical. However, there are not many studies in the field that have looked at the MD as a weight loss approach and its link to the telomere length. As a result, more research is needed to understand these connections in various groups.

This study is unique since it examines the MD, telomere length and obesity-related consequences. This study examines the MD, telomere length and obesity to determine if the MD can help lose weight while maintaining telomere length. As there are few studies on MD weight loss and telomere length, the work emphasizes the need for greater research in this area. This study fills a research gap and improves the understanding of nutrition, telomere biology and obesity-related outcomes.

In this paper, a systematic review of 284 articles published between 2015 and 2022 and a full-text thematic analysis of 70 selected articles was conducted to catalog and synthesize factors in a framework. Thematic analysis subsequently revealed 18 selective codes under three groups of drivers, barriers, and outcomes. These three groups were explained by four key aspects including organization, stakeholders, infrastructure, and business environment that set a framework for the digitalization of construction. The study finally concluded digitalization strategies with a focus on support mechanisms, government incentives, regulations, the transition from manual labor to technicians, organizational technology culture, methodology development, and innovation processes. Such strategies provide insight into prioritizing resources towards smooth digital transformation in construction businesses.

A two-stage methodology is adopted by undertaking a systematic literature review followed by thematic content analysis. This work concludes with an analysis of remaining research gaps and suggestions for potential future research.

In this paper, a systematic review of 284 articles published between 2015 and 2022 and a full-text thematic analysis of 70 selected articles was conducted to catalog and synthesize variables in a framework. Thematic analysis subsequently revealed a set of variables and factors describing construction digitalization under three groups of success factors, barriers, and outcomes. A critical content analysis of the representative studies was conducted to identify five future research trends as well as associated research gaps and directions on the topic.

This study contributes to practice by providing directions concerning the key strategies and priorities associated with the digitalization of construction businesses.

This ground-breaking research brings to light a classified set of factors that are important for the digitalization of construction businesses. The elicited framework contributes to the current body of knowledge by offering a unique conceptualization of both driving and adverse aspects for the seamless digital transformation of construction.

This study aims to examine the challenges facing the construction industry practitioners toward adopting digital construction technologies in the Jordanian construction industry.

Quantitative methods were used by reviewing the related literature to include 16 challenges that face the Jordanian construction industry in adopting digital construction. A questionnaire was used to achieve the desired study objectives for 373 respondents from various institutions and companies. The questionnaire was analyzed with SPSS using statistical tests such as mean score, Kruskal–Wallis H test and factor analysis.

After collecting the quantitative data, the study showed that the most challenges facing construction industry practitioners toward adopting digital construction techniques are lack of qualified workers, high requirement for computing equipment’s, high initial cost of bringing these technologies to the market and construction firms low investment in research and development. These challenges faced by respondents were divided into three main factors, namely, construction’s nature, financial constraints and poor management support.

This study provides information and statistics on the challenges that face individuals or companies toward adopting digital construction techniques in Jordan. It proposes recommendations and proper practical implantation strategies to overcome the challenges.