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This study aims to establish a reliable index to identify interdisciplinary breakthrough innovation effectively. We constructed a new index, the D_Div index, for this purpose.

The D_Div index incorporates the degree of interdisciplinarity in the breakthrough index. To validate the index, a data set combining the publication records and citations of Nobel Prize laureates was divided into experimental and control groups. The validation methods included sensitivity analysis, correlation analysis and effectiveness analysis.

The sensitivity analysis demonstrated the D_Div index’s ability to differentiate interdisciplinary breakthrough papers from various categories of papers. This index not only retains the strengths of the existing index in identifying breakthrough innovation but also captures interdisciplinary characteristics. The correlation analysis revealed a significant correlation (correlation coefficient = 0.555) between the interdisciplinary attributes of scientific research and the occurrence of breakthrough innovation. The effectiveness analysis showed that the D_Div index reached the highest prediction accuracy of 0.8. Furthermore, the D_Div index outperforms the traditional DI index in terms of accuracy when it comes to identifying interdisciplinary breakthrough innovation.

This study proposed a practical and effective index that combines interdisciplinary and disruptive dimensions for detecting interdisciplinary breakthrough innovation. The identification and measurement of interdisciplinary breakthrough innovation play a crucial role in facilitating the integration of multidisciplinary knowledge, thereby accelerating the scientific breakthrough process.

The purpose of this essay is to explore the opportunities and challenges that early-career researchers (ECRs) face when they seek to contribute to academic knowledge production through research activities “other than” those directly focused on making progress with their own, to-be-published, research papers in a context associated with the “publish or perish” (PoP) mentality.

Drawing broadly on the notion of technologies of humility (Jasanoff, 2003), this reflective essay develops upon the experiences of the authors in organizing and participating in a series of nine workshops undertaken between June 2013 and April 2021, as well as the arduous process of writing this paper itself. Retrospective accounts, workshop materials, email exchanges and surveys of workshop participants provide the key data sources for the analysis presented in the paper.

The paper shows how the organization of the workshops is intertwined with the building of a small community of ECRs and exploration of how to address the perceived limitations of a “gap-spotting” approach to developing research ideas and questions. The analysis foregrounds how the workshops provide a seemingly valuable research experience that is not without contradictions. Workshop participation reveals tensions between engagement in activities “other than” working on papers for publication and institutionalized pressures to produce publication outputs, between the (weak) perceived status of ECRs in the field and the aspiration to make a scholarly contribution, and between the desire to develop a personally satisfying intellectual journey and the pressure to respond to requirements that allow access to a wider community of scholars.

Our analysis contributes to debates about the ways in which seemingly valuable outputs are produced in academia despite a pervasive “publish or perish” mentality. The analysis also shows how reflexive writing can help to better understand the opportunities and challenges of pursuing activities that might be considered “unproductive” because they are not directly related to to-be-published papers.

In the era of artificial intelligence (AI), algorithms have gained unprecedented importance. Scientific studies have shown that algorithms are frequently mentioned in papers, making mention frequency a classical indicator of their popularity and influence. However, contemporary methods for evaluating influence tend to focus solely on individual algorithms, disregarding the collective impact resulting from the interconnectedness of these algorithms, which can provide a new way to reveal their roles and importance within algorithm clusters. This paper aims to build the co-occurrence network of algorithms in the natural language processing field based on the full-text content of academic papers and analyze the academic influence of algorithms in the group based on the features of the network.

We use deep learning models to extract algorithm entities from articles and construct the whole, cumulative and annual co-occurrence networks. We first analyze the characteristics of algorithm networks and then use various centrality metrics to obtain the score and ranking of group influence for each algorithm in the whole domain and each year. Finally, we analyze the influence evolution of different representative algorithms.

The results indicate that algorithm networks also have the characteristics of complex networks, with tight connections between nodes developing over approximately four decades. For different algorithms, algorithms that are classic, high-performing and appear at the junctions of different eras can possess high popularity, control, central position and balanced influence in the network. As an algorithm gradually diminishes its sway within the group, it typically loses its core position first, followed by a dwindling association with other algorithms.

To the best of the authors’ knowledge, this paper is the first large-scale analysis of algorithm networks. The extensive temporal coverage, spanning over four decades of academic publications, ensures the depth and integrity of the network. Our results serve as a cornerstone for constructing multifaceted networks interlinking algorithms, scholars and tasks, facilitating future exploration of their scientific roles and semantic relations.

This paper aims to review and summarize the findings of research dedicated to studying the process of building sustainable business models (BM) triggered by development of COVID-19 pandemic.

Bibliometric analysis is performed to identify the papers most relevant to the topic. The authors review the findings of more than 50 papers from Scopus database published between 2020 and 2022 dedicated to studying BM during COVID-19 pandemic, as well as papers dedicated to sustainability phenomenon and most cited BM research.

The paper identifies the gap in defining BM sustainability and contributes to better understanding of this phenomenon by demarcating it from traditional environment-based United Nations agenda. It also describes why network-based approach to BM helps to better address sustainability aspects. The paper demonstrates how representation of a networked BM by three levels of analysis (namely, structure of a BM, interaction mechanism between BM actors and results of their interaction) is organically connected to the key milestones of the value creation process (value definition, value creation, value distribution and value capture) and shows how these three levels can be used to analyze and structure the practical changes proposed in COVID-19-oriented BM. Finally, the paper summarizes key findings of the studies dedicated to BM during the pandemic and structures key insights in relation to building sustainable BM.

The results of the paper contribute to developing theory around BM sustainability as well as provide insights for business practitioners on how to adjust BM during the crisis. At the same time, many insights shown in the paper are industry specific, which limits their generalizability, as well as consequences of the pandemic are still not fully clear. Therefore, the authors argue that future research should be primarily focused on developing generalizable measurement frameworks to evaluate the antecedents, process and results of BM adaptation.

The paper strengthens theoretical foundations for the research focused on BM sustainability and helps businesses to better manage the adaptation in the fast-changing environment.

Differences in annual publication counts may reflect the dynamic of scientific progress. Declining annual numbers of publications may be interpreted as missing progress in field-specific knowledge.

In this paper, we present empirical results on dynamics of progress in economic fields (defined by Journal of Economic Literature (JEL), codes) based on a methodological approach introduced by Bornmann and Haunschild (2022). We focused on publications that have been published between 2012 and 2021 and identified those fields in economics with the highest dynamics (largest rates of change in paper counts).

We found that the field with the largest paper output across the years is “Economic Development”. The results reveal that the field-specific rates of changes are mostly similar. However, the two fields “Production and Organizations” and “Health” show point estimators which are clearly higher than the estimators for the other fields. We investigated the publications in “Production and Organizations” and “Health” in more detail.

Understanding how a discipline evolves over time is interesting both from a historical and a recent perspective. This study presents results on the dynamics in economic fields using a new methodological approach.

The purpose of this paper is to examine the recent economic boom in Tennessee and the role of work-based learning WBL opportunities in contributing to this growth. The paper will analyze data from the U.S. Bureau of Labor Statistics to provide an overview of the changes in the labor force and employment in the state over the past ten years. Additionally, the paper will delve into the various WBL programs offered in Tennessee, such as K-12 Career and Technical Education (CTE), Tennessee Chamber Work-based Learning, and more, that are designed to provide individuals of all ages and stages with the skills and knowledge needed to succeed in the workforce. The paper will also discuss how the growth in WBL opportunities has led to an increasing need for new hires and how it could lead to the development of new industry in Tennessee. The paper aims to provide a detailed examination of the economic boom in Tennessee, and the impact of WBL opportunities on the development of local workforce and industry.

The design of this paper is to analyze the recent economic boom in Tennessee and the role of work-based learning WBL opportunities in contributing to this growth. The methodology used in this paper is primarily a review of data from the U.S. Bureau of Labor Statistics to provide an overview of the changes in the labor force and employment in the state over the past ten years. Additionally, the paper will review the various WBL programs offered in Tennessee and their standards, to understand how they are designed to provide individuals of all ages and stages with the skills and knowledge needed to succeed in the workforce. The approach taken in this paper is an analytical one, where the data is analyzed to understand the trends and patterns in the labor market and the impact of WBL opportunities on the workforce. The paper also includes insights from relevant research studies and experts in the field to provide a comprehensive understanding of the subject.

The findings of this paper indicate that there has been a significant economic boom in Tennessee over the past decade, as evidenced by data from the U.S. Bureau of Labor Statistics. The data shows a consistent increase in the labor force and employment in the state, with a corresponding decrease in the unemployment rate. The paper also found that the growth in work-based learning WBL opportunities in Tennessee has played a significant role in contributing to this economic boom. The paper reviewed various WBL programs offered in Tennessee and found that they are designed to provide individuals of all ages and stages with the skills and knowledge needed to succeed in the workforce.

This paper brings an original perspective on the recent economic boom in Tennessee and the role of work-based learning WBL opportunities in contributing to this growth. By analyzing data from the U.S. Bureau of Labor Statistics, the paper provides an overview of the changes in the labor force and employment in the state over the past ten years, which has not been thoroughly examined in previous studies. Additionally, the paper delves into the various WBL programs offered in Tennessee, and how they are designed to provide individuals of all ages and stages with the skills and knowledge needed to succeed in the workforce, which is an original aspect of this paper. The paper also presents the original finding that the growth in WBL opportunities has led to an increasing need for new hires and could lead to the development of new industry in Tennessee. This paper provides an original and comprehensive examination of the economic boom in Tennessee and the impact of WBL opportunities on the development of local workforce and industry.

The study responds to the common concerns of authors, reviewers, and editors on writing and publishing high-quality literature review (LR) studies. First, we evolved the background and decision elements on the five parameters of a quality LR paper: Planning, Operationalizing, Writing, Embedding, and Reflecting (POWER), from the editorials and guiding literature. Statistical procedure and refinement of 256 responses from writers, reviewers, and editors revealed 37 decision elements. Finally, a multicriteria-decision-making approach was applied to the detailed responses from the lead editors of ABDC, Scopus, ABS, and WoS journals, and 31 decision elements were found strong enough to represent these five parameters on the quality of LR studies. All five parameters are found important to be considered. However, a high priority is suggested for embedding (the results coming out of the review) and operationalizing (the process of conducting the review), whereas reflection, writing, and planning of LR papers still remain important. The purpose of the POWER framework is to overcome the challenges and decision dilemmas faced by writers and decision-makers. The POWER framework acts as a guiding tool to conduct LR studies in general and business management scholars in specific ways. In addition, this study provides a checklist (Table 6) and template (Appendix A1) of a quality LR study to its stakeholders.

Systematic literature review (SLR) papers have gained significant importance during the last years as many reputed journals have asked for literature review submissions from the authors. However, at the same time, authors are experiencing a high number of desk rejections because of a lack of quality and its contribution to the existing body of knowledge. Therefore, the purpose of this paper is to offer guidance to researchers who intend to communicate SLR papers in top-rated journals. We attempt to offer a guide to buddy researchers who plan to write SLR papers. This purpose is achieved by clearly stating how the traditional review method is different from SLR, when and how can each type of literature review method be used, writing effective motivation of a review paper and finally how to synthesize the available literature. We have also presented a few suggestions for writing an impactful SLR in the last. Overall, this chapter serves as a guide to various aspirants of SLR paper to understand the prerequisites of an SLR paper and offers deep insights to bring in more clarity before writing an SLR paper, thereby reducing the chances of desk rejection.