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This paper aims to propose a new metric, called the Research Productivity Index (RPI), which can be used to measure universities’ research productivity and benchmark them accordingly at both national and global levels.

The paper used a partial-factor productivity measurement as the basis to develop RPI, which considers the ratio of total weighted publications (outputs) to the used input (affiliated researchers). To demonstrate the applicability of the RPI, data were collected from Scopus to assess the research productivity of a university in the UAE, as an example. The methodological steps (algorithm) were demonstrated using mathematical and query functions to extract the required data from the Scopus data set and then compute the RPI value.

A new effective and objective metric was developed for measuring universities’ research productivity.

This paper suggests that Scopus could use RPI as a metric for measuring the research productivity of each university. RPI can be used by university administrators and government decision-makers to evaluate and rank/benchmark institutions’ research productivity. They can consequently make more effective decisions with regard to the efficient allocation of research budgets and funding.

This paper distinguishes between measuring research impact and research productivity. It proposes RPI for measuring the latter, whereas most existing metrics measure the former. RPI is an objective measurement, as it is calculated based on a constant period of time, three years, and takes into consideration the university size (i.e. affiliated researchers) in addition to the quality and quantity (total) of research outcomes.

Academic rankings are facing various issues, including the use of data sources that are not publicly verifiable, subjective parameters, a narrow focus on research productivity and regional biases and so forth. This research work is intended to enhance creditability of the ranking process by using the objective indicators based on publicly verifiable data sources.

The proposed ranking methodology – OpenRank – drives the objective indicators from two well-known publicly verifiable data repositories: the ArnetMiner and DBpedia.

The resultant academic ranking reflects common tendencies of the international academic rankings published by the Shanghai Ranking Consultancy (SRC), Quacquarelli Symonds (QS) and Times Higher Education (THE). Evaluation of the proposed methodology advocates its effectiveness and quick reproducibility with low cost of data collection.

Implementation of the OpenRank methodology faced the issue of availability of the quality data. In future, accuracy of the academic rankings can be improved further by employing more relevant public data sources like the Microsoft Academic Graph, millions of graduate's profiles available in the LinkedIn repositories and the bibliographic data maintained by Association for Computing Machinery and Scopus and so forth.

The suggested use of open data sources would offer new dimensions to evaluate academic performance of the higher education institutions (HEIs) and having comprehensive understanding of the catalyst factors in the higher education.

The research work highlighted the need of a purposely built, publicly verifiable electronic data source for performance evaluation of the global HEIs. Availability of such a global database would help in better academic planning, monitoring and analysis. Definitely, more transparent, reliable and less controversial academic rankings can be generated by employing the aspired data source.

We suggested a satisfying solution for improvement of the HEIs' ranking process by making the following contributions: (1) enhancing creditability of the ranking results by merely employing the objective performance indicators extracted from the publicly verifiable data sources, (2) developing an academic ranking methodology based on the objective indicators using two well-known data repositories, the DBpedia and ArnetMiner and (3) demonstrating effectiveness of the proposed ranking methodology on the real data sources.

The purpose of this paper is to investigate the activities of the Asian Productivity Organisation (APO). The study identifies the various roles and activities of the APO and evaluates how well it performs in these roles. The study also investigates the impacts of the APO on the productivity initiatives of National Productivity Organisations (NPOs) in 16 Asian countries. These productivity initiatives are important in enhancing productivity performance and national competitiveness in the countries of interest.

The study collects data from stakeholders in the NPOs in 16 countries. A Likert-scale questionnaire was used to collect data from two types of respondents – NPO CEOs and NPO professional/technical staff. Data were analysed by comparing the responses across the participating countries.

The result shows that there was general satisfaction with the mission, vision and strategic direction of the APO. With respect to the operational performance of the organisation, the study showed that there were some differences in perception of the performance of the APO although the overall perception was positive.

The study provides insights into the top management of the APO with regards to deciding on the future direction of the organisation and, in particular, the ways in which it understands and supports the varied requirements of the different NPOs.

Organisations such as the APO dedicate significant resources into supporting NPOs, and by extension productivity-related commercial operations, in several countries. It is important to understand how these services are perceived and experienced in these countries, and a definitive study to examine this has not previously been carried out.

The overall aim of this research is to propose a research incentive framework for academic staff members at the South African universities of technology (UoTs).

An exploratory case study methodology was applied, while a questionnaire was used to (1) identify the factors that stimulated staff members' research activities; (2) assess what was considered an appropriate way of measuring research productivity and (3) identify appropriate research awards, recognition and rewards. Working from the self-determination theory (SDT), the results of the data analysis were used to develop a framework for ensuring crowding-in of research incentives into intrinsic motivation. This framework is anchored on the three main components (competence, autonomy and social relatedness) of the cognitive evaluation theory (CET) that provides guidelines for the design of a research incentive system.

Intrinsically motivated researchers tend to conduct research for their inherent satisfaction because it meets their basic individual psychological need for competence. Existing research incentives and productivity systems fail to provide intrinsic motivation for researchers. Recommendation for a framework for designing research incentive systems is centred on the researchers themselves. This approach contributes to a research environment that provides space for autonomy, creativity, flexibility and innovation and consequently a successful research output that is hinged on the ability to keep researchers intrinsically motivated.

A conceptual framework is proposed specifically for technically focused UoT suggesting that crowding-in the motivation of researcher incentives results in improved intrinsic-based motivation. The autonomy of researchers in particular is regarded as the most important driver of such motivation, with the availability of resources, collegiality and research skills and development ranking as the most important aspects specifically driving intrinsic motivation. The framework not only provides a tool for institutions of higher education focused on developing the technical skills, but also offers management at any type of university challenged with low research outputs and a poor research ethos with an alternative method to improve both the quantity and quality of research outputs.

The perceived prestige of the doctoral degree granting institution traditionally has had a major effect on job opportunities available to a new accounting Ph.D. However, given recent shortages of accounting academics, the role of program prestige may have changed. It is possible that individual factors also may now play a role in the initial placement decision. This study examines the effects of both doctoral program prestige and individual factors on the initial placement decision.

While our results indicate that doctoral program prestige still largely dictates the initial placement decision, several other factors are found to be important. New graduates initially placed at higher level institutions report faculty involvement during the application process as well as significant research support by the hiring institution. New faculty placing lower than expected report the mix of teaching and research as well as the quality of life as being significant factors in their employment decision.

This paper seeks to present a scientometric analysis of the Proceedings of the McMaster World Congress on the Management of Intellectual Capital and Innovation for the 1996‐2008 period in order to better understand the evolution and identity of the discipline.

Qualitative and quantitative data analysis techniques were applied to determine author distribution, country, individual and institutional‐level productivity rankings, and employed methodologies.

It was found that an average manuscript was written by 1.73 authors. The USA, Canada and the UK were the three most productive countries, which is consistent with prior KM/IC productivity research. Most productive institutions were the University of Calgary (Canada), Polytechnic University of Catalonia (Spain) and Universidad de Oviedo (Spain). The most productive individuals were James Falconer, Jose Maria Viedma Marti and Scott Erickson. Lotka's α, which represents the degree of conference delegate retention rate, was established as 2.7. Case studies were the most frequent method of inquiry, followed by framework development and literature reviews. Surveys and usage of secondary data were the leading empirical methodologies. Interviews, laboratory experiments, and field studies were under‐represented.

The findings offer valuable insights into the state and development of the KM/IC discipline and shed some light on its identity.

Scientometric analyses are of primary interest for academic researchers and therefore the practical implications of this study are limited.

The research reported is among the first to investigate the issue of the KM/IC discipline identity from a descriptive perspective.

This article aims to explore how self‐efficacy is related to academic research activities and how intra‐culturally relevant factors may play a role in self‐efficacy in the context of higher education in Beijing. In particular, relationships of self‐efficacy for research with research productivity and idiocentrism‐allocentrism are to be examined.

A survey was administered to academics in ten randomly selected universities in Beijing and generated 296 valid questionnaires. Data were analysed using factor analysis and multiple regression.

Gender and discipline are identified as predictors of self‐efficacy. Specifically, female academics reported lower levels of self‐efficacy for research than males. Academics in the social sciences reported lower levels of self‐efficacy for research than those in the natural sciences. Moreover, relationships are also found between self‐efficacy for research and idiocentrism‐allocentrism.

The study makes an extensive investigation of self‐efficacy theory, originally developed in Western contexts, in an Eastern culture and provides evidence that intra‐cultural and demographic factors play substantial roles in research self‐efficacy.

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.

To examine the relationship between monochronic work behavior (behavior that minimizes interruptions on the job) and Type A behavior, 147 faculty members of a midsized private university responded to a set of questionnaires which measured monochronic work behaviors, Type A behavior, job‐induced stress, research productivity, and number of working projects. Type A behavior was significantly and positively correlated with monochronic behaviors – in other words, Type As were more likely to use behavioral strategies that reduced polychronic thought. Type A and monochronic behaviors were also significantly correlated with job‐induced stress and number of publications. Contrary to the hypothesis, Type A and monochronic behaviors were also positively and significantly correlated with number of working projects.

The purpose of this paper is to review studies on ranking in finance journals, which have grown substantially in recent decades.

This paper depicts the trend and development of ranking studies in finance area, describes the regional work and lists the studies which focus on specific journal. This paper discusses some important and possible issues of ranking studies in finance in the future and makes some conclusions.

First, the authors find that the assessing method has changed from counting number to citation-based method. Second, the authors sort the ranking studies which focus on the research and publication quality based on regional area. Finally, in specific journal ranking studies, the authors can find how a journal reputation has changed, better or worse.

This paper reviews the ranking studies in finance area and particularly focusses on three parts. Because of the importance of ranking studies in research quality assessing, a series of issues are raised to improve the assessing objectiveness of journal ranking.