The Experts below are selected from a list of 24984 Experts worldwide ranked by ideXlab platform
Mario Coccia - One of the best experts on this subject based on the ideXlab platform.
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competition between basic and applied research in the Organizational Behaviour of public research labs
Social Science Research Network, 2018Co-Authors: Mario CocciaAbstract:The purpose of this paper is to investigate the competition between basic and applied research within public research organizations. International publications are considered here a proxy of basic research, whereas self-financing deriving from technology transfer activities is an indicator of applied research. Results suggest, within one of the largest European research organizations an increasing competition between basic and applied research, both in human and natural sciences, due to shrinking of public research lab budgets. In particular, institutes and scientists pay more attention to applied research activities, which are capable of attracting market funds for economic survival of public research labs but this Organizational Behaviour reduces basic research activity in the long run. Managerial and Organizational Behaviour of public research organizations are also discussed.
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competition between basic and applied research in the Organizational Behaviour of public research labs
Journal of Economics Library, 2018Co-Authors: Mario CocciaAbstract:Abstract. The purpose of this paper is to investigate the competition between basic and applied research within public research organizations. International publications are considered here a proxy of basic research, whereas self-financing deriving from technology transfer activities is an indicator of applied research. Results suggest, within one of the largest European research organizations an increasing competition between basic and applied research, both in human and natural sciences, due to shrinking of public research lab budgets. In particular, institutes and scientists pay more attention to applied research activities, which are capable of attracting market funds for economic survival of public research labs but this Organizational Behaviour reduces basic research activity in the long run. Managerial and Organizational Behaviour of public research organizations are also discussed. Keywords. Applied r esearch, Basic research, Public research organization, Public lab, Science policy, Organizational Behaviour, Public management. JEL. B50, B59, I23, L20, L29, O33.
Oyvind Lund Martinsen - One of the best experts on this subject based on the ideXlab platform.
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semantic algorithms can detect how media language shapes survey responses in Organizational Behaviour
PLOS ONE, 2018Co-Authors: Jan Ketil Arnulf, Kai R Larsen, Oyvind Lund MartinsenAbstract:Research on sensemaking in organisations and on linguistic relativity suggests that speakers of the same language may use this language in different ways to construct social realities at work. We apply a semantic theory of survey response (STSR) to explore such differences in quantitative survey research. Using text analysis algorithms, we have studied how language from three media domains–the business press, PR Newswire and general newspapers–has differential explanatory value for analysing survey responses in leadership research. We projected well-known surveys measuring leadership, motivation and outcomes into large text samples from these three media domains significantly different impacts on survey responses. Business press language was best in explaining leadership-related items, PR language best at explaining Organizational results and “ordinary” newspaper language seemed to explain the relationship among motivation items. These findings shed light on how different public arenas construct Organizational realities in different ways, and how these differences have consequences on methodology in research on leadership.
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Predicting Survey Responses: How and Why Semantics Shape Survey Statistics on Organizational Behaviour
PloS one, 2014Co-Authors: Jan Ketil Arnulf, Kai R Larsen, Oyvind Lund Martinsen, Chih How BongAbstract:Some disciplines in the social sciences rely heavily on collecting survey responses to detect empirical relationships among variables. We explored whether these relationships were a priori predictable from the semantic properties of the survey items, using language processing algorithms which are now available as new research methods. Language processing algorithms were used to calculate the semantic similarity among all items in state-of-the-art surveys from Organisational Behaviour research. These surveys covered areas such as transformational leadership, work motivation and work outcomes. This information was used to explain and predict the response patterns from real subjects. Semantic algorithms explained 60–86% of the variance in the response patterns and allowed remarkably precise prediction of survey responses from humans, except in a personality test. Even the relationships between independent and their purported dependent variables were accurately predicted. This raises concern about the empirical nature of data collected through some surveys if results are already given a priori through the way subjects are being asked. Survey response patterns seem heavily determined by semantics. Language algorithms may suggest these prior to administering a survey. This study suggests that semantic algorithms are becoming new tools for the social sciences, opening perspectives on survey responses that prevalent psychometric theory cannot explain.
Jan Ketil Arnulf - One of the best experts on this subject based on the ideXlab platform.
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semantic algorithms can detect how media language shapes survey responses in Organizational Behaviour
PLOS ONE, 2018Co-Authors: Jan Ketil Arnulf, Kai R Larsen, Oyvind Lund MartinsenAbstract:Research on sensemaking in organisations and on linguistic relativity suggests that speakers of the same language may use this language in different ways to construct social realities at work. We apply a semantic theory of survey response (STSR) to explore such differences in quantitative survey research. Using text analysis algorithms, we have studied how language from three media domains–the business press, PR Newswire and general newspapers–has differential explanatory value for analysing survey responses in leadership research. We projected well-known surveys measuring leadership, motivation and outcomes into large text samples from these three media domains significantly different impacts on survey responses. Business press language was best in explaining leadership-related items, PR language best at explaining Organizational results and “ordinary” newspaper language seemed to explain the relationship among motivation items. These findings shed light on how different public arenas construct Organizational realities in different ways, and how these differences have consequences on methodology in research on leadership.
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Predicting Survey Responses: How and Why Semantics Shape Survey Statistics on Organizational Behaviour
PloS one, 2014Co-Authors: Jan Ketil Arnulf, Kai R Larsen, Oyvind Lund Martinsen, Chih How BongAbstract:Some disciplines in the social sciences rely heavily on collecting survey responses to detect empirical relationships among variables. We explored whether these relationships were a priori predictable from the semantic properties of the survey items, using language processing algorithms which are now available as new research methods. Language processing algorithms were used to calculate the semantic similarity among all items in state-of-the-art surveys from Organisational Behaviour research. These surveys covered areas such as transformational leadership, work motivation and work outcomes. This information was used to explain and predict the response patterns from real subjects. Semantic algorithms explained 60–86% of the variance in the response patterns and allowed remarkably precise prediction of survey responses from humans, except in a personality test. Even the relationships between independent and their purported dependent variables were accurately predicted. This raises concern about the empirical nature of data collected through some surveys if results are already given a priori through the way subjects are being asked. Survey response patterns seem heavily determined by semantics. Language algorithms may suggest these prior to administering a survey. This study suggests that semantic algorithms are becoming new tools for the social sciences, opening perspectives on survey responses that prevalent psychometric theory cannot explain.
Chih How Bong - One of the best experts on this subject based on the ideXlab platform.
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Predicting Survey Responses: How and Why Semantics Shape Survey Statistics on Organizational Behaviour
PloS one, 2014Co-Authors: Jan Ketil Arnulf, Kai R Larsen, Oyvind Lund Martinsen, Chih How BongAbstract:Some disciplines in the social sciences rely heavily on collecting survey responses to detect empirical relationships among variables. We explored whether these relationships were a priori predictable from the semantic properties of the survey items, using language processing algorithms which are now available as new research methods. Language processing algorithms were used to calculate the semantic similarity among all items in state-of-the-art surveys from Organisational Behaviour research. These surveys covered areas such as transformational leadership, work motivation and work outcomes. This information was used to explain and predict the response patterns from real subjects. Semantic algorithms explained 60–86% of the variance in the response patterns and allowed remarkably precise prediction of survey responses from humans, except in a personality test. Even the relationships between independent and their purported dependent variables were accurately predicted. This raises concern about the empirical nature of data collected through some surveys if results are already given a priori through the way subjects are being asked. Survey response patterns seem heavily determined by semantics. Language algorithms may suggest these prior to administering a survey. This study suggests that semantic algorithms are becoming new tools for the social sciences, opening perspectives on survey responses that prevalent psychometric theory cannot explain.
Margaret Deery - One of the best experts on this subject based on the ideXlab platform.
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research in hospitality human resource management and Organizational Behaviour
International Journal of Hospitality Management, 1998Co-Authors: Yvonne Guerrier, Margaret DeeryAbstract:Abstract This paper surveys 156 books and articles on Organizational Behaviour and human resource management in the hospitality industry in order to assess the current state of research in this area. The paper looks at what research has been conducted within the following topic areas: labour market trends, employee attitudes, organization structure and culture, hospitality managers and management work and human resource practices. A picture emerges of a rich research area producing a very diverse range of work which is increasingly published in mainstream human resource management and Organizational Behaviour journals as well as in the hospitality journals; but where researchers are primarily engaged in applying mainstream ideas to the hospitality industry rather than influencing mainstream research. The paper identifies several gaps in current research.
