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The purpose of this paper is to introduce altmetric indicators and combine with traditional citation indicators to comprehensively evaluate the impact of academic journals from the perspective of multidimensional and multi-indicator fusion.

The authors take international multidisciplinary journals as an example, combining 14 traditional citation indicators of academic journals and introducing 14 altmetric indicators to build a comprehensive evaluation model of the impact of academic journals (academic impact and societal impact). At the same time, the authors systematically construct a journal evaluation indicator system from three dimensions. Then, the indicators data of three dimensions are evaluated by normalized processing, correlation analysis, reliability and validity analysis, PCA and factor analysis.

Two-dimensional and three-dimensional analyses can exactly provide some useful information for academic journals’ location in the respective coordinate systems. There are strong positive correlations among the measured indicators in the three dimensions, and each indicator has a significant consistency between whole and internal. The correlation coefficient between FD1 and FD2 is 0.888 with a strong positive correlation. It shows that the traditional citation indicators provided by WoS and Scopus database are highly consistent, and they are comparable and alternative in evaluating the academic impact of journals. The correlation coefficients of FD1, FD2 with FD3 are 0.831 and 0.798. There are strong positive correlations among them, which indicate that the evaluation of journals’ societal impact based on altmetrics indicator can be considered as a potential supplement to academic impact evaluation based on citation and to reflect the multidimensional nature of journals impact in an immediate way.

Multidimensional and multi-indicator perspective evaluation can provide references for the selection of impact evaluation indicators and model optimization of academic journals, and also provide new ideas for improving the status of the impact evaluation of academic journals.

The purpose of this paper is to enhance conceptual understanding of reporting boundaries in corporate annual reports by developing a conceptual framework of the rules and principles, referred to here as dimensions, underlying boundaries. A total of nine contemporary regulations/guidelines are compared in terms of the boundary dimensions identified to illustrate similarities and differences in boundary concepts.

To develop a conceptual framework of reporting boundary dimensions, academic and industry literature were analysed to identify boundary dimensions. Thereafter, nine contemporary regulations/guidelines were compared in terms of these dimensions. A qualitative approach was taken including document analysis and content analysis.

A total of 10 key boundary dimensions were identified through analysis of academic and industry literature. Each dimension represents a continuum along which regulations/guidelines can position themselves. Taken together, the 10 dimensions provide a comprehensive description of the chosen boundary concept.

The paper contributes to accounting theory by providing a holistic conceptual framework of dimensions relating to reporting boundaries, thus answering calls for more conceptual development of the boundary construct. The conceptual framework and comparison of contemporary regulations/guidelines adds to scarce literature considering financial and non-financial boundaries simultaneously, which is relevant for annual reports. From a practical perspective, the paper brings renewed visibility to boundaries with implications for preparers, users, standard setters and auditors of annual reports.

Several frameworks have been developed to map and document scientific societal interaction and impact, each reflecting the specific forms of impact and interaction that characterize different academic fields. The ReAct taxonomy was developed to register data about “productive interactions” and provide an overview of research activities within the social sciences and humanities (SSH). The purpose of the present research is to examine whether the SSH-oriented taxonomy is relevant to the science, technology, engineering and mathematics (STEM) disciplines when clarifying societal interactions and impact, and whether the taxonomy adds value to the traditional STEM impact indicators such as citation scores and H-index.

The research question was investigated through qualitative interviews with nine STEM researchers. During the interviews, the ReAct taxonomy and visual research profiles based on the ReAct categories were used to encourage and ensure in-depth discussions. The visual research profiles were based on publicly available material on the research activities of the interviewees.

The study provided an insight into how STEM researchers assessed the importance of mapping societal interactions as a background for describing research impact, including which indicators are useful for expressing societal relevance and impact. With regard to the differences between STEM and SSH, the study identified a high degree of cohesion and uniformity in the importance of indicators. Differences were more closely related to the purpose of mapping and impact assessment than between scientific fields. The importance of amalgamation and synergy between academic and societal activities was also emphasised and clarified.

The findings highlight the importance of mapping societal activities and impact, and that societal indicators should be seen as inspiring guidelines depending on purpose and use. A significant contribution is the identification of both uniformity and diversity between the main fields of SSH and STEM, as well as the connection between the choice of indicators and the purpose of mapping, e.g. for impact measurement, profiling, or career development.

The work sheds light on STEM researchers' views on research mapping, visualisation and impact assessment, including similarities and differences between STEM and SSH research.

The purpose of this study is to examine scholarly impact which is critical to universities in their aspiration to create, disseminate and apply knowledge. However, scholarly impact is an elusive concept. First, the authors present a conceptual model to clarify different dimensions of scholarly impact (i.e. theory and research, education, organizations and society) and four key stakeholders (i.e. other researchers, students, practitioners and policy makers). Second, the authors provide actionable recommendations for university administrators, researchers and educators on how to enhance impact. The scholarly impact model is flexible, expandable, scalable and adaptable to universities in different regions of the world and with different strategic priorities.

The authors conducted a general review of the literature and offered a multidimensional and multistakeholder model of scholarly impact to guide future actions aimed at enhancing scholarly impact.

The authors describe the multidimensional and multistakeholder nature of the critical and yet elusive concept of scholarly impact. The authors delineate multiple dimensions of impact, different stakeholders involved and recommendations for enhancing scholarly impact in the future.

The authors offer practical and actionable recommendations on how to enhance scholarly impact. For university administrators, the authors recommend aligning scholarly impact goals with actions and resource-allocation decisions; ensuring that performance management and reward systems are consistent with impact goals; being strategic in selecting a journal list; developing a strong doctoral program; and promoting practical knowledge and applications. For researchers and educators, the authors recommend developing a personal scholarly impact plan; becoming an academic decathlete; finding ways to affect multiple impact dimensions simultaneously; and leveraging social media to broaden impact on external stakeholders. Implementing these recommendations will benefit other researchers, students, practitioners (e.g. managers, consultants) and policy makers.

The authors provide an innovative way of conceptualizing scholarly impact. In turn, the conceptual analysis results in actionable recommendations for university administrators, researchers and educators to enhance impact.

This article aims to analyze a set of features in the managerial implications of the most-cited business-to-business (B2B) marketing articles which are related to their managerial relevance. The purpose is to further identify which are the most recurrent features of managerial implications, as well as the connections between such features. Finally, the articles aim to verify if these features of managerial implications vary depending on the scientific impact of the article.

The 60 most-cited articles were selected from both generalist and specialized academic journals and a content analysis was conducted. Then the article assesses the formal features (e.g. dedicated space), the language (e.g. consulting or normative), the translation of scientific results (e.g. message efficacy) and such other features as time orientation, specificity and abstraction of the managerial implications in these high-impact articles. The article also analyses patterns and associations between the aforementioned dimensions across the 60 articles, also depending on their level of scientific impact (i.e. their number of citations).

The results point that six out of nine features contributing to managerial relevance are the most frequently present in the implications (dedicated section easy to find, balance between academic and consulting language, partly scientific approach, overlap with scientific findings, message neither too complicated nor too simplistic, and long-term orientation). However, three other features reducing managerial relevance afflict nearly half of the articles: non-normative, generic and abstract implications. The ten articles lacking completely managerial implications are slightly more frequent among highest impact ones, which also often include overly complicated implications; while speculative and overly simplistic implications typically appear more among lowest impact articles which, however, also stand for very specific messages. There seems not to be any statistical correlation between the features contributing to managerial relevance and the scientific impact (number of citations) of an article. Instead, several of these features are correlated among each other, meaning that when one is missing, it is likely that the others also are. Finally, when implications are included in a dedicated section of the article, they tend to be specific and consequently also tend to have the other features favoring relevance.

The article provides an empirically grounded assessment of features that influence the managerial relevance of scientific research in the areas of B2B marketing. Our results are, in fact, grounded in a detailed examination of the managerial implications of 60 high-impact articles in this disciplinary domain.

The purpose of this paper is to provide a decision support model for optimizing the composition of portfolios of market-driven academic programs, primarily in schools offering market-driven academic programs. This model seeks to maximize financial performance during a desired planning time period while also achieving targets for other non-financial dimensions of the portfolio (e.g. mission alignment, student demographics and faculty characteristics) by deciding the types of programs to be added, redesigned and/or removed for each year of the planning period.

This paper introduces an integer linear program (i.e. mathematical optimization) to describe the portfolio optimization problem. Integer linear programs are widely used for optimizing portfolios of financial and non-financial products and services in non-educational settings. Additionally, in order to use an integer linear program for the model, qualitative data must be incorporated into the quantitative model. To do so, this paper first discusses two methods of quantifying qualitative information related to market-driven program dimensions in the following section.

The paper provides empirical insights related to the impact of this model through an illustrative case from a school offering market-driven academic programs at a prestigious private university in the USA. The results of the case highlight the potential positive impact of utilizing a similar model for planning purposes. Financially, the model results in almost double financial surplus than without the model while also achieving higher scores for all non-financial dimensions measured for the portfolio analyzed.

This paper provides a unique and impactful model for decision support in strategic planning for market-driven academic programs, an area of intense discussion and focus in higher education today.

Citations have been used as a common basis to measure the academic accomplishments of scientific books. However, traditional citation analysis ignored content mining and without consideration of citation equivalence, which may lead to the decline of evaluation reliability. Hence, this paper aims to integrate multi-level citation information to conduct multi-dimensional analysis.

In this paper, books’ academic impacts were measured by integrating multi-level citation resources, including books’ citation frequencies and citation-related contents. Specifically, firstly, books’ citation frequencies were counted as the frequency-level metric. Secondly, content-level metrics were detected from multi-dimensional citation contents based on finer-grained mining, including topic extraction on the metadata and citation classification on the citation contexts. Finally, differential metric weighting methods were compared with integrate the multi-level metrics and computing books’ academic impacts.

The experimental results indicate that the integration of multiple citation resources is necessary, as it can significantly improve the comprehensiveness of the evaluation results. Meanwhile, compared with the type differences of books, disciplinary differences need more attention when evaluating the academic impacts of books.

Academic impact assessment of books via integrating multi-level citation information can provide more detailed evaluation information and cover shortcomings of methods based on single citation data. Moreover, the method proposed in this paper is publication independent, which can be used to measure other publications besides books.

University–industry (UI) collaboration is essential for knowledge and technology exchange between higher education institutions and industries, enabling enterprises to accelerate innovation. However, few studies have investigated the collaborative innovation mechanism through which UI collaboration can enhance the accumulation of firms' intellectual capital (IC) and how this, in turn, affects their innovation-driven development.

Drawing from the knowledge management and collaborative innovation theory, this research proposes a theoretical framework of the inter-organization relationship between enterprises and universities to investigate the influence mechanism of UI collaboration, including academic engagement and commercialization, on corporate performance as well as the mediating role of IC by employing survey that covers 177 UI collaborations.

Empirical results show that human capital and relational capital fully mediate the relationship between academic engagement UI collaboration and corporate economic performance, while human capital partially mediates the relationship between commercialization UI collaboration and corporate economic performance. Additionally, structural capital and relational capital partially mediate the relationship between academic engagement and corporate innovation performance, while structural capital fully mediates the relationship between commercialization and corporate innovation performance.

This study empirically investigates how academic engagement and commercialization impact corporate performance (i.e. innovation dimension or economic dimension). It uncovers this relationship's underlying mechanism by documenting the IC's mediating impact.

This paper aims to conduct a comprehensive analysis to evaluate the current situation of journals, examine the factors that influence their development, and establish an evaluation index system and model. The objective is to enhance the theory and methodologies used for journal evaluation and provide guidance for their positive development.

This study uses empirical data from economics journals to analyse their evaluation dimensions, methods, index system and evaluation framework. This study then assigns weights to journal data using single and combined evaluations in three dimensions: influence, communication and novelty. It calculates several evaluation metrics, including the explanation rate, information entropy value, difference coefficient and novelty degree. Finally, this study applies the concept of fuzzy mathematics to measure the final results.

The use of affiliation degree and fuzzy Borda number can synthesize ranking and score differences among evaluation methods. It combines internal objective information and improves model accuracy. The novelty of journal topics positively correlates with both the journal impact factor and social media mentions. In addition, journal communication power indicators compensate for the shortcomings of traditional citation analysis. Finally, the three-dimensional representative evaluation index serves as a reminder to academic journals to avoid the vortex of the Matthew effect.

This paper proposes a journal evaluation model comprising academic influence, communication power and novelty dimensions. It uses fuzzy Borda evaluation to address issues related to the weighing of single evaluation methods. This study also analyses the relationship of the three dimensions and offers insights for journal development in the new media era.

Conducting relevant research is a cornerstone of good academic practice. However, considering academics and practitioners’ divergent paradigms and social systems, it is challenging to undertake impactful research. Indeed, the research–practice gap remains an essential issue in human resource management research. There have been several calls for translating research for dissemination, making it more societally relevant, and beginning conversations and activities that move beyond the confines of the academic context. In fact, research on talent management (TM) has been accused of lagging in offering organizations vision and direction. Understanding the perceived causes and potential solutions for relevant problems is a real need to successfully narrow the TM research–practice gap. Thus, the purpose of this chapter is to offer an in-depth discussion on the research–practice gap in TM. To do so, we first identify the critical dimensions of research relevance that will help us to ground our discussion regarding the applicability of current academic TM research. By doing this, we seek to understand better what is happening with TM research, which should then help provide insights into how its practical impact can be improved.