The Experts below are selected from a list of 79587 Experts worldwide ranked by ideXlab platform
Judith A Scully - One of the best experts on this subject based on the ideXlab platform.
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top management team Demography and process the role of social integration and communication
Administrative Science Quarterly, 1994Co-Authors: Ken G Smith, Ken A Smith, Judy D Olian, Henry P Sims, Douglas P Obannon, Judith A ScullyAbstract:Examines the effect of team Demography on firm performance. Three models of team Demography, process, and firm performance are considered: direct Demography, process, and the intervening model. The Demography model, which holds that team Demography is the sole determinant of performance outcomes, is modeled in terms of heterogeneity, team tenure, and team size. The process model, which purports that Demography and process contribute separately to performance outcomes, measures Demography in the same terms as the Demography model and measures process in terms of social integration, informal communication, and communication frequency. The intervening model proposes that team Demography affects team process and in turn influences process. Data were collected from 53 U.S. high-technology firms, through interviews and surveys of the firm CEOs and their top management teams. The results show little support for the Demography model, while partial support is shown for the intervening model. Team process is shown to have a direct impact on performance while Demography is shown to have direct and indirect effects. These results indicate that keeping team size small enhances informal communication and social integration. It is evidence that the relationship between team Demography, process and performance is not straightforward. (SRD)
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top management team Demography and process the role of social integration and communication
Administrative Science Quarterly, 1994Co-Authors: Ken G Smith, Ken A Smith, Judy D Olian, Henry P Sims, Douglas P Obannon, Judith A ScullyAbstract:We thank Ed Locke, Martin Gannon, Marshall W. Meyer, Stefan Wally, and three anonymous reviewers for their helpful comments on earlier drafts of this paper, and the Dingman Center for Entrepreneurship at the University of Maryland for the-financial grant that made this research possible. This research used data from 53 high-technology firms to test three alternative models of the effects of the top management team's Demography and process on organizational performance: (1) a Demography model, in which team Demography accounts entirely for performance outcomes, and process has no impact; (2) a process model, in which process contributes incrementally and directly to performance outcomes, over and above the team's Demography; and (3) an intervening model, in which the effects of the top management team on performance outcomes are due entirely to the effects of its Demography on process. The study found the top management team's Demography indirectly related to performance through process and process directly related to performance, although direct effects of team Demography on performance were also found. These results suggest a fourth, more complex model of top management team behavior.'
David Welch - One of the best experts on this subject based on the ideXlab platform.
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overexploitation causes profound demographic changes to the protandrous hermaphrodite king threadfin polydactylus macrochir in queensland s gulf of carpentaria australia
Fisheries Research, 2017Co-Authors: Bradley R Moore, Jason Stapley, Ashley J Williams, David WelchAbstract:Fishing pressure is a significant driver of the Demography of exploited fish populations. Here, we examine temporal patterns in the Demography of king threadfin (Polydactylus macrochir), a large, protandrous teleost, in Queensland’s south-eastern Gulf of Carpentaria, Australia, between two periods: 1986–1990 (Period 1) and 2007–2009 (Period 2). Significant age truncation was evident from Period 1 (max age = 14 years, modal age = 5 years) to Period 2 (max age = 8 years, modal age = 3 years). Fish >5 years constituted 58% of the catch in Period 1, and less than 4% of the catch in Period 2. Length and age at sex change differed considerably between periods. In Period 1, the relationships between length and sex ratio and age and sex ratio were best described by a logistic model with 50% of the population changing sex to female at 889 mm fork length and at 6.3 years of age. In Period 2, there were substantially more females in small length and younger age classes with no obvious length or age at which sex change occurred. The predicted mean asymptotic length (L∞) from the best-fit models of growth was 361 mm greater in Period 1 than in Period 2, while the growth rate (K) was more than twice as high in Period 2 than in Period 1. Fishing mortality during Period 2 was estimated to be 2–3.5 times higher than that of natural mortality (M) and 2.6–5.4 times higher than that of Period 1, depending on the maximum age used to calculate M. No significant trends were evident in total annual rainfall or air temperature in the region over the study period, suggesting the observed changes in Demography were not related to contrasting patterns in rainfall or temperature between sampling periods. These results suggest that heavy fishing pressure has likely had a profound effect on the Demography of P. macrochir in the study region over a period of approximately 20 years, with the use of gillnets resulting in the selective removal of larger, older, female P. macrochir and subsequent reductions in age structures and sex change schedules. Accordingly, management intervention is urgently required to reduce fishing pressure and restore the natural Demography of the population.
Ken G Smith - One of the best experts on this subject based on the ideXlab platform.
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top management team Demography and process the role of social integration and communication
Administrative Science Quarterly, 1994Co-Authors: Ken G Smith, Ken A Smith, Judy D Olian, Henry P Sims, Douglas P Obannon, Judith A ScullyAbstract:Examines the effect of team Demography on firm performance. Three models of team Demography, process, and firm performance are considered: direct Demography, process, and the intervening model. The Demography model, which holds that team Demography is the sole determinant of performance outcomes, is modeled in terms of heterogeneity, team tenure, and team size. The process model, which purports that Demography and process contribute separately to performance outcomes, measures Demography in the same terms as the Demography model and measures process in terms of social integration, informal communication, and communication frequency. The intervening model proposes that team Demography affects team process and in turn influences process. Data were collected from 53 U.S. high-technology firms, through interviews and surveys of the firm CEOs and their top management teams. The results show little support for the Demography model, while partial support is shown for the intervening model. Team process is shown to have a direct impact on performance while Demography is shown to have direct and indirect effects. These results indicate that keeping team size small enhances informal communication and social integration. It is evidence that the relationship between team Demography, process and performance is not straightforward. (SRD)
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top management team Demography and process the role of social integration and communication
Administrative Science Quarterly, 1994Co-Authors: Ken G Smith, Ken A Smith, Judy D Olian, Henry P Sims, Douglas P Obannon, Judith A ScullyAbstract:We thank Ed Locke, Martin Gannon, Marshall W. Meyer, Stefan Wally, and three anonymous reviewers for their helpful comments on earlier drafts of this paper, and the Dingman Center for Entrepreneurship at the University of Maryland for the-financial grant that made this research possible. This research used data from 53 high-technology firms to test three alternative models of the effects of the top management team's Demography and process on organizational performance: (1) a Demography model, in which team Demography accounts entirely for performance outcomes, and process has no impact; (2) a process model, in which process contributes incrementally and directly to performance outcomes, over and above the team's Demography; and (3) an intervening model, in which the effects of the top management team on performance outcomes are due entirely to the effects of its Demography on process. The study found the top management team's Demography indirectly related to performance through process and process directly related to performance, although direct effects of team Demography on performance were also found. These results suggest a fourth, more complex model of top management team behavior.'
Bradley R Moore - One of the best experts on this subject based on the ideXlab platform.
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overexploitation causes profound demographic changes to the protandrous hermaphrodite king threadfin polydactylus macrochir in queensland s gulf of carpentaria australia
Fisheries Research, 2017Co-Authors: Bradley R Moore, Jason Stapley, Ashley J Williams, David WelchAbstract:Fishing pressure is a significant driver of the Demography of exploited fish populations. Here, we examine temporal patterns in the Demography of king threadfin (Polydactylus macrochir), a large, protandrous teleost, in Queensland’s south-eastern Gulf of Carpentaria, Australia, between two periods: 1986–1990 (Period 1) and 2007–2009 (Period 2). Significant age truncation was evident from Period 1 (max age = 14 years, modal age = 5 years) to Period 2 (max age = 8 years, modal age = 3 years). Fish >5 years constituted 58% of the catch in Period 1, and less than 4% of the catch in Period 2. Length and age at sex change differed considerably between periods. In Period 1, the relationships between length and sex ratio and age and sex ratio were best described by a logistic model with 50% of the population changing sex to female at 889 mm fork length and at 6.3 years of age. In Period 2, there were substantially more females in small length and younger age classes with no obvious length or age at which sex change occurred. The predicted mean asymptotic length (L∞) from the best-fit models of growth was 361 mm greater in Period 1 than in Period 2, while the growth rate (K) was more than twice as high in Period 2 than in Period 1. Fishing mortality during Period 2 was estimated to be 2–3.5 times higher than that of natural mortality (M) and 2.6–5.4 times higher than that of Period 1, depending on the maximum age used to calculate M. No significant trends were evident in total annual rainfall or air temperature in the region over the study period, suggesting the observed changes in Demography were not related to contrasting patterns in rainfall or temperature between sampling periods. These results suggest that heavy fishing pressure has likely had a profound effect on the Demography of P. macrochir in the study region over a period of approximately 20 years, with the use of gillnets resulting in the selective removal of larger, older, female P. macrochir and subsequent reductions in age structures and sex change schedules. Accordingly, management intervention is urgently required to reduce fishing pressure and restore the natural Demography of the population.
Quak Evert-jan - One of the best experts on this subject based on the ideXlab platform.
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COVID-19 Demography Evidence Summary No.3
'Korea Society for Computational Fluids Engineering', 2020Co-Authors: Quak Evert-janAbstract:This is the third of a weekly COVID-19 Demography Evidence Summary (DES) to signpost DFID and other UK government departments to the latest relevant evidence and discourse on COVID19 to inform and support their response. It is a result of 4 hours of work per week and is not intended to be a comprehensive summary of available evidence on COVID-19 but aims to make original documents easily accessible to decisionmakers which, if relevant to them, they could refer to before making decisions. This DES looks specifically to the demographic indicators that impact on transmission/spreading and mortality rate, and the emerging evidence and policy advice on tailoring such responses to account for demographic indicators.This summary covers publications on Academic journal articles and research papers; Policy briefs, statements, tools, guidelines; Webinars (recordings); Comments, Editorials, Opinions, Blogs, News; COVID-19 Data hubs relevant for Demography; and COVID-19 Resource hubs relevant for Demograph
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COVID-19 Demography Evidence Summary No.2
'Korea Society for Computational Fluids Engineering', 2020Co-Authors: Quak Evert-janAbstract:This is the first of a weekly COVID-19 Demography Evidence Summary (DES) to signpost DFID and other UK government departments to the latest relevant evidence and discourse on COVID19 to inform and support their response. It is a result of 4 hours of work per week and is not intended to be a comprehensive summary of available evidence on COVID-19 but aims to make original documents easily accessible to decision-makers which, if relevant to them, they could refer to before making decisions. This DES looks specifically to the demographic indicators that impact on transmission/spreading and mortality rate, and the emerging policy advice on tailoring such responses to account for demographic indicators. This summary covers publications on Academic journal articles and research papers; Policy briefs, statements, tools & guidelines; Webinars; Comments, Editorials, Opinions, Blogs & News; COVID-19 Data hubs relevant for Demography; and Covid-19 Resource Hubs relevant for Demograph
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COVID-19 Demography Evidence Summary No.1
'Korea Society for Computational Fluids Engineering', 2020Co-Authors: Quak Evert-janAbstract:This is the first of a weekly COVID-19 Demography Evidence Summary (DES) to signpost DFID and other UK government departments to the latest relevant evidence and discourse on COVID19 to inform and support their response. It is a result of 4 hours of work per week and is not intended to be a comprehensive summary of available evidence on COVID-19 but aims to make original documents easily accessible to decision-makers which, if relevant to them, they could refer to before making decisions. This DES looks specifically to the demographic indicators that impact on transmission/spreading and mortality rate, and the emerging policy advice on tailoring such responses to account for demographic indicators. This summary covers publications on Academic journal articles and research papers; Policy briefs, statements, tools & guidelines; Comments, Editorials, Opinions, Blogs & News; and Covid-19 Resource Hubs relevant for Demograph
