Research productivity in management schools of India during 1968-2015: A directional benefit-of-doubt model analysis

Sahoo, Biresh K.; Singh, Ramadhar; Mishra, Bineet; Sankaran, Krithiga

doi:10.1016/j.omega.2016.02.004

Cited by 61 publications

(39 citation statements)

References 86 publications

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“…Numerous metrics and models that built on existing approaches were also reported 118. For example, some developed composite metrics that included a publication’s JIF alongside an author contribution measure119 or other existing metrics 120. However, each of these approaches reported limitations, in addition to their strengths or improvements on other methods.…”

Section: Resultsmentioning

confidence: 99%

Comprehensive Researcher Achievement Model (CRAM): a framework for measuring researcher achievement, impact and influence derived from a systematic literature review of metrics and models

et al. 2019

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ObjectivesEffective researcher assessment is key to decisions about funding allocations, promotion and tenure. We aimed to identify what is known about methods for assessing researcher achievements, leading to a new composite assessment model.DesignWe systematically reviewed the literature via the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols framework.Data sourcesAll Web of Science databases (including Core Collection, MEDLINE and BIOSIS Citation Index) to the end of 2017.Eligibility criteria(1) English language, (2) published in the last 10 years (2007–2017), (3) full text was available and (4) the article discussed an approach to the assessment of an individual researcher’s achievements.Data extraction and synthesisArticles were allocated among four pairs of reviewers for screening, with each pair randomly assigned 5% of their allocation to review concurrently against inclusion criteria. Inter-rater reliability was assessed using Cohen’s Kappa (ĸ). The ĸ statistic showed agreement ranging from moderate to almost perfect (0.4848–0.9039). Following screening, selected articles underwent full-text review and bias was assessed.ResultsFour hundred and seventy-eight articles were included in the final review. Established approaches developed prior to our inclusion period (eg, citations and outputs, h-index and journal impact factor) remained dominant in the literature and in practice. New bibliometric methods and models emerged in the last 10 years including: measures based on PageRank algorithms or ‘altmetric’ data, methods to apply peer judgement and techniques to assign values to publication quantity and quality. Each assessment method tended to prioritise certain aspects of achievement over others.ConclusionsAll metrics and models focus on an element or elements at the expense of others. A new composite design, the Comprehensive Researcher Achievement Model (CRAM), is presented, which supersedes past anachronistic models. The CRAM is modifiable to a range of applications.

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Section: Resultsmentioning

confidence: 99%

Comprehensive Researcher Achievement Model (CRAM): a framework for measuring researcher achievement, impact and influence derived from a systematic literature review of metrics and models

et al. 2019

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“…Nevertheless, a few recent papers have worked with a directional-benefit-of-doubt model. These are, for example, Fusco (2015), where a principal component analysis is applied to choose the directional vector, and Sahoo et al (2017), who developed a composite indicator of research productivity of Indian management schools. However, neither of these papers focus on adapting the corresponding model to deal with bad outputs and the presence of zeros, as we do.…”

Section: Measuring Csp-our Proposalmentioning

confidence: 99%

Enhancing the Measurement of Composite Indicators of Corporate Social Performance

Aparicio

Kapelko

2019

Soc Indic Res

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The aggregation of multiple metrics of corporate social performance (CSP) poses one of the major problems in CSP research. In this paper we propose a new method to compute a composite indicator of CSP from an efficiency perspective using data envelopment analysis. The new approach makes it possible to appropriately account for both positive and negative aspects of CSP, and also to measure CSP for firms for which some of the metrics are exhibiting zero values. Within the new method, we propose measuring global (metafrontier) CSP inefficiency with regard to all firms in the sample and decomposing it into within-industry CSP inefficiency measured with regard to own industry group and industry gap CSP inefficiency. In this way, we measure inefficiencies due to shortcomings in managerial practices and due to the differences between industries in relation to CSP. Using a sample of United States firms in a variety of economic sectors from 2004 to 2015, as covered by the Kinder, Lydenberg and Domini database, we find considerable potential for improvement in CSP practices, with the most CSP-efficient firms representing mining and manufacturing sectors, and the most inefficient belonging to the construction sector. We also find that CSP inefficiency dropped in the period related to the recent financial crisis.

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“…Moreover, they found that research experience is a significant determinant of research productivity. On the source of educational attainment, Sahoo et al (2016) found that Indian business faculty members who attain their doctoral degrees from outside India and/or had worked abroad for a few years are more research productive than their counterparts who had such degrees or experience solely from India.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Quimbo and Sulabo (2014), for example, investigated the impact of research policy, research funding, research benefits and incentives on research productivity and found that only research benefits and incentives load significantly on research productivity. Sahoo et al (2016) asserted the institutional importance documenting that business faculty staff at the Indian Institutes of Technology are more research productive than those at Indian Institutes of Management. Other factors suggested by (Bland, Ruffin 1992;Pratt et al 1999;Rix et al 2004;MacGregor et al 2006;Dhillon et al 2015;Lamm 2015;Gregory et al 2016), are: (1) Research management structure transparency and effectiveness, (2) The linkage between research and workloads, (3) New researchers' nutrition, (4) Facilities provided by faculty research management, 5 On the country level, other factors emerge.…”

Section: Literature Reviewmentioning

confidence: 99%

Factors Affecting Research Environment at Syrian Business Faculties: A Student-Perceived Model

Khalifa

Abdulraouf

Mouselli

2016

Business, Management and Education

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This study aims at investigating the factors that affect the research environment of business postgraduate students, particularly master students, from the perspective of these students. From the same perspective, it also aims at assessing these factors together with the quality of research environment. A questionnaire survey method was employed. The questionnaire was developed by academics from five business faculties based on relevant studies and was distributed to graduate students enrolled in all of the research business programs at the Faculty of Economics, Damascus University, ending up with 88 valid responses. To explore the factors that may affect research environment, exploratory factor analysis was employed. In addition, multiple regression analysis and t-test were applied to respond to the study purposes. Facilities and industry linkage come to be significant factors in the research environment. However, the results show insignificant impact for each of the research courses, networking, and research skills in the overall research environment. Variations in regard to the availability of these factors were identified with low level of availability for the facilities and industry linkage. The study is one of a kind that investigates factors affecting research environment of postgraduate students and particularly master students. Further and to the best of our knowledge, it is the first study that examines such factors in war conditions, which enables us to understand what students perceive as critical factors influencing their research performance in these conditions. Recommendations to policy makers are presented to develop strategies that respond to students’ concerns for a better research environment.

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Research productivity in management schools of India during 1968-2015: A directional benefit-of-doubt model analysis

Cited by 61 publications

References 86 publications

Comprehensive Researcher Achievement Model (CRAM): a framework for measuring researcher achievement, impact and influence derived from a systematic literature review of metrics and models

Comprehensive Researcher Achievement Model (CRAM): a framework for measuring researcher achievement, impact and influence derived from a systematic literature review of metrics and models

Enhancing the Measurement of Composite Indicators of Corporate Social Performance

Factors Affecting Research Environment at Syrian Business Faculties: A Student-Perceived Model

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