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Seeks to explore the characteristics of organisational performance management with a view to speculating on the way the development of this emerging academic sub‐discipline might evolve. Identifies just what the nature of a research contribution to the field of performance management might be by briefly reviewing the nature of management as a discipline and how performance management might be located within this context. Performance management is located within two main dimensions: cognitive, and those relating to social organisation as proposed by Becher and Gibbons et al. The methodology compares the field of performance management with analysis that has already been undertaken in an attempt to analyse management as discipline. Analysis shows that research in the performance management field, unlike other more mainstream management research, is likely to be “hard” and “applied” (on the main cognitive dimensions – Becher) and convergent and urban (on the main dimensions in relation to its social organisation – Gibbons). Conclusions are discussed in detail.

Each of the four objectives can be applied within the military training environment. Military training often requires that soldiers achieve specific levels of performance or proficiency in each phase of training. For example, training courses impose entrance and graduation criteria, and awards are given for excellence in military performance. Frequently, training devices, training media, and training evaluators or observers also directly support the need to diagnose performance strengths and weaknesses. Training measures may be used as indices of performance, and to indicate the need for additional or remedial training.

Proper topic selection is an essential prerequisite for the success of research. To study this, this article proposes an important concerned factor of topic selection-topic popularity, to examine the relationship between topic selection and team performance.

The authors adopt extracted entities on the type of gene/protein, which are used as proxies as topics, to keep track of the development of topic popularity. The decision tree model is used to classify the ascending phase and descending phase of entity popularity based on the temporal trend of entity occurrence frequency. Through comparing various dimensions of team performance – academic performance, research funding, relationship between performance and funding and corresponding author's influence at different phases of topic popularity – the relationship between the selected phase of topic popularity and academic performance of research teams can be explored.

First, topic popularity can impact team performance in the academic productivity and their research work's academic influence. Second, topic popularity can affect the quantity and amount of research funding received by teams. Third, topic popularity can impact the promotion effect of funding on team performance. Fourth, topic popularity can impact the influence of the corresponding author on team performance.

This is a new attempt to conduct team-oriented analysis on the relationship between topic selection and academic performance. Through understanding relationships amongst topic popularity, team performance and research funding, the study would be valuable for researchers and policy makers to conduct reasonable decision making on topic selection.

The purpose of this paper is to identify, through an exploratory meta-analysis, which process- and outcome-related antecedents have the strongest relationship to overall team performance. The secondary objective is to create an understanding of the extent to which relative research interest in each construct to date has aligned with its reported effects.

This study uses a random-effects meta-analysis on studies that have measured the relationship between at least one process or outcome factor and overall team performance. The number of studies, effect size and between-study variances are captured and analyzed for each process/outcome factor. Prior literature has explored relationships between various process/outcome factors and overall team performance. This study expands on previous literature by examining a comprehensive set of process/outcome factors and their relative impact on overall team performance.

A meta-analysis of 190 effect sizes extracted from 52 empirical studies over the past two decades (1999–2020) showed the specific process and outcome factors that most strongly contributed to overall team performance were efficiency, schedule and innovation. In addition, only a weak correlation was found between process and outcome factors’ relationships with overall team performance and how often they are studied in the research community.

This study contributes to the body of knowledge on team performance by examining prior research to identify the relevant impact of various process and outcome factors on overall team performance. In addition, this study also assesses the extent to which research interest in these factors has appeared to match their relative impact. Analyzing the relative impact of various process and outcome factors allows researchers and practitioners to better identify methods to create improvement in overall team performance. Based on the findings, prioritizing efficiency, schedule and innovation may promote overall team performance.

The purpose of this paper is to present findings related to an instrument for the self‐appraisal of scientists' research performance, and highlight the suitability of self‐appraisal instruments for members of the scientific community.

An examination of the literature on self‐appraisal and the measurement of scientific research is presented. The initial development of the instrument employed qualitative methods through interview and discussions with PhD‐qualified scientific researchers (n=13). A quantitative investigation of the usefulness of the instrument was then conducted on a sample of biological and chemical research scientists (n=270). Results were compared with an existing performance measure and examined for representative reliability.

Results suggest that the instrument may be a reliable measure of research performance when used in a non‐critical context.

While the instrument shows promise, further research is needed to examine aspects of inter‐rater reliability. Additional research is also needed to further examine relationships between it and other measures of research performance at the same level of analysis. While the usefulness and validity of this instrument at the “international level” has been examined, further research is needed to examine the relative validity and reliability of the instrument at the “institutional” and “national” levels.

The instrument provides a useful and cost‐effective tool for use in the performance appraisal process of research scientists, and for use in focusing discussion on performance for developmental purposes. It is also useful as a research tool for the timely and cost‐effective measurement of research performance at an institutional, national and international level.

The paper presents an original paper and pencil instrument for the appraisal of scientific research performance at an institutional, national, and international level.

The purpose of this paper is to analyze the determinants of the performance of regional industrial technology development programs among the regional strategic industrial development program that the central government and Daegu metropolitan city jointly promoted between 2004 and 2012. Specifically, in this research, the authors are trying to identify the effects of R&D capabilities and technical development tasks on technological and managerial performance.

The dependent variables of this study are technical and economic performance. Technical performance, product and process innovation, economic performance, sales and export increases were measured using five-point Likert scales. The authors added the contribution of sales through technology development to economic performance. The independent variable is the company’s R&D capability, measured by the number of R&D staff compared to the average total number of employees from 2004 to 2012. The characteristics of the technology development tasks were measured by technical characteristics, market characteristics and collaborative research types. The technological characteristics were measured by seven factors, including technological change, technical difficulty, potential in commercialization, competition between domestic and foreign competitors, difficulty in introducing overseas technology and the technological gap. Market characteristics were largely divided into complexity, dynamics and competitiveness. The types of collaborative research were divided into whether or not there were collaborative research with the participation of large corporations. The control variables are firm size (number of employees) and firm age. Regression analysis was used to analyze the determinants of performance, and a difference analysis was conducted to determine the effect of collaborative research on performance.

The main determinants of the regional industrial technology development program performance are the characteristics of the technology development task rather than the internal R&D capability; moreover, the technical characteristics, complexity of the developed product market and participation of large corporations had significant effects on R&D capability. The R&D capacity of firms in internal R&D capacity had a significant effect only on the improvement of technology development ability. Therefore, R&D capacity, which is the main determinant of technology innovation, did not have a significant effect on the performance of short-term technology development tasks. Technological change, technological difficulty, competition between domestic and foreign competitors and the technological gap had positive effects on performance, excluding sales contributions. In addition, the complexity of the developed product market such as the diversification of demand, competitive product and sales distribution channels had positive influences on the performance of technology development programs, unlike dynamics and competitiveness. In this study, the authors cannot confirm the effect of collaborative research on the performance of the technology development programs, but they confirmed that collaborative research involving large corporations had a positive influence on performance.

The results of the analysis of the determinants of regional industrial technology development programs suggest some implications in the future evaluation of these regional industrial technology development programs. It is necessary to review the application qualification and merit, advance review of the business plans and confirmation, an examination of the research results and performance of the applicants and a review of the technology and market situation of the project. For this, the authors suggest that the written review from the relevant technical experts be submitted to the evaluation committees. Also, when establishing regional industrial development programs, they should be evaluated thoroughly, including detailed information and contents about the technical and market characteristics of the local industry.

This research is one of the first to investigate the achievements of R&D support programs among regional industrial development programs in Korea. The results of this study can substantially contribute to the development and implementation of the R&D support policies of the central and local governments. Furthermore, the findings suggest guidelines for improving the performance of R&D support programs in the future. A theoretical model for enhancing the efficiency of government R&D support programs may be established, and an empirical analysis may be conducted to provide practical and academic implications for further research.

The purpose of this paper is to explore the nature of the relationship between a scholar’s research performance (using weighted journal-impact factor average) and their degree centrality; the impact of author-homophily (in terms of gender, institutional sector, academic age, academic ranks, province and city) on this relationship is investigated as well.

Using scientific publishing data and journal-impact factors from Thomson Reuters’ ISI Web of Science (SCI) and Journal Citation Reports, respectively, the domestic co-authorship network of chemistry researchers in Pakistan during 2002-2009 was constructed then modeled via ordinary least squares regression.

Results show that the personal characteristics of a researcher do not necessarily lead to high degree centrality, i.e. attributes may not be causal to co-author relationships. Instead, high degree centrality is more so a function of the forerunning research performance of the researcher: those whom publish more in terms of impact factor, attract more co-authors (high degree centrality). Moreover, the relationship between research performance and degree centrality is positively moderated by age and province homophily and negatively moderated by city homophily.

Data are sourced wholly from the Pakistani chemistry research community; results many not be generalizable to other sub-populations or the wider research community.

The findings provide insights to performance-seeking authors: knowing that their research performance enhances their centrality, which in-turn may lead to increased research performance and various other desirable professional outcomes. In addition, researchers can look toward establishing similar (homophilous) or dissimilar (heterophilous) ties knowing that the relationship between research performance and centrality will likely be stronger when similarity or dissimilarity exists.

This study supports the idea that high research performance attracts more potential co-authors, which in-turn may lead to ever greater research performance, which suggests that the research community will be fragmented between high- and low-performing researchers. Also researcher will have similar or dissimilar ties in terms of various characteristics which in turn moderate the research performance centrality relationship.

This paper counteracts the empirical belief that researchers are attractive as potential co-authors according to their personal and professional characteristics. It is actually their research performance and homophily or heterophily of their ties which matters.

Current literature recognised big data as a digital revolution affecting all organisational processes. To obtain a competitive advantage from the use of big data, an efficient integration in a performance measurement system (PMS) is needed, but it is still a “great challenge” in performance measurement research. This paper aims to review the big data and performance measurement studies to identify the publications’ trends and future research opportunities.

The authors reviewed 873 documents on big data and performance carrying out an extensive bibliometric analysis using two main techniques, i.e. performance analysis and science mapping.

Results point to a significant increase in the number of publications on big data and performance, highlighting a shortage of studies on business, management and accounting areas, and on how big data can improve performance measurement. Future research opportunities are identified. They regard the development of further research to explain how performance measurement field can effectively integrate big data into a PMS and describe the main themes related to big data in performance measurement literature.

This paper gives a holistic view of big data and performance measurement research through the inclusion of numerous contributions on different research streams. It also encourages further study for developing concrete tools.

The purpose of this paper is to shed light on the use of bibliometric indicators as a people analytics tool for examining research performance outcome differences in faculty mobility and turnover.

Employing bibliometric information from research databases, the publication, citations, h-index and newly developed individual annualized h-index (hIa-index) for a sample of university faculty is examined (N = 684). Information relating to turnover decisions from a human resource (HR) information system and bibliometric data from a research database are combined to explore research performance differences across cohorts of retained, resigned or terminated faculty over a five-year period in a single university.

Analysis of variance (ANOVA) results indicate traditional bibliometric indicators of h-index, publication count and citation count which are limited in their ability to identify performance differences between employment status cohorts. Results do show some promise for the newly developed hIa-index, as it is found to be significantly lower for terminated faculty (p < 0.001), as compared to both retained and resigned faculty. Multinomial logistic regression analysis also confirms the hIa metric as a predictor of terminated employment status.

First, the results imply that the hIa-index, which controls for career length and elements of coauthorship is a superior bibliometric indicator for comparison of research performance.

Results suggest that the hIa metric may serve as a useful tool for the examination of employment decisions for universities. It also highlights the potential usefulness of bibliometric indicators for people analytics and the examination of employment decisions, performance management and faculty turnover in research-intensive higher education contexts.

This empirical paper is entirely unique. No research has previously examined the issue of turnover in a university setting using the bibliometric measures employed here. This is a first example of the potential use of hIa bibliometric index as an HR analytics tool for the examination of HR decisions such as employee turnover in the university context.

The linkage between strategy and performance is central to strategic management. Empirical studies have nevertheless produced mixed results on the nature of this relationship, and in recent decades, very little advancement has been made in research aimed at elucidating this relationship. Accordingly, the purpose of this paper is to identify the approaches to the strategy-performance linkage in previous studies and defines five principles that should characterize future research on this relationship. The paper develops a novel research design that follows these principles and tests the usefulness of this research design in practice.

This paper is exploratory in nature and its empirical methods include content analysis, multidimensional scaling, and cluster analysis. The primary difference between this paper and studies in the mainstream literature on the linkage between strategy and performance relates to the application of an endogenous strategy typology instead of predefined strategy categories.

The analysis shows that the adopted research design based on five principles is applicable to research on the linkage between strategy and performance and that such a research design produces meaningful results. The results support the findings of earlier studies regarding the potential of “hybrid” strategies for achieving superior firm performance.

This paper challenges the dominance of generic strategies in research on the strategy-performance linkage and provides statistical data that lay the foundation for more detailed investigation on this relationship. The paper argues for a contextually bound view of strategic management.

This paper invigorates the discussion on the linkage between strategy and performance, which has long been diminishing as a research topic in the literature because of contradictory results and the lack of fresh research opportunities. This paper further introduces a methodology that has been underutilized in the study of strategic management.