Understanding Entrepreneurial Team Decisions: Measuring Team Members’ Influences With The Metricized Limit Conjoint Analysis
Contextualizing research on entrepreneurial team decisions (ETDs) is closely related to elaborating the influence of several team members (TMs) on group decisions. Therefore, this study shows how the metricized limit conjoint analysis (MLCA) provides a method to more accurately determine TMs’ influe...
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2018-05-01
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doaj-92c7b1a7917641e78b6b6aa83189ef3e2020-11-25T04:10:41ZengSAGE PublishingSAGE Open2158-24402018-05-01810.1177/2158244018779106Understanding Entrepreneurial Team Decisions: Measuring Team Members’ Influences With The Metricized Limit Conjoint AnalysisRonny Baierl0Dresden University of Applied Sciences, GermanyContextualizing research on entrepreneurial team decisions (ETDs) is closely related to elaborating the influence of several team members (TMs) on group decisions. Therefore, this study shows how the metricized limit conjoint analysis (MLCA) provides a method to more accurately determine TMs’ influences. For doing so, this study introduces a new approach as a suitable alternative to directly ask for TMs’ influences by utilizing a detailed step-by-step instruction for further research. Moreover, this study theoretically underlines the usability and preferableness of this new approach and validates it with a simulation of 45,000 assessments nested within 5,000 artificial respondents. The results indicate a diverse application potential for researching ETDs in several contexts. In addition, an illustrative example shows how this conjoint approach can be of value in subsequent research projects. Therefore, the MLCA is of increased interest for both researchers and practitioners when focusing on ETDs in several contexts.https://doi.org/10.1177/2158244018779106 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ronny Baierl |
spellingShingle |
Ronny Baierl Understanding Entrepreneurial Team Decisions: Measuring Team Members’ Influences With The Metricized Limit Conjoint Analysis SAGE Open |
author_facet |
Ronny Baierl |
author_sort |
Ronny Baierl |
title |
Understanding Entrepreneurial Team Decisions: Measuring Team Members’ Influences With The Metricized Limit Conjoint Analysis |
title_short |
Understanding Entrepreneurial Team Decisions: Measuring Team Members’ Influences With The Metricized Limit Conjoint Analysis |
title_full |
Understanding Entrepreneurial Team Decisions: Measuring Team Members’ Influences With The Metricized Limit Conjoint Analysis |
title_fullStr |
Understanding Entrepreneurial Team Decisions: Measuring Team Members’ Influences With The Metricized Limit Conjoint Analysis |
title_full_unstemmed |
Understanding Entrepreneurial Team Decisions: Measuring Team Members’ Influences With The Metricized Limit Conjoint Analysis |
title_sort |
understanding entrepreneurial team decisions: measuring team members’ influences with the metricized limit conjoint analysis |
publisher |
SAGE Publishing |
series |
SAGE Open |
issn |
2158-2440 |
publishDate |
2018-05-01 |
description |
Contextualizing research on entrepreneurial team decisions (ETDs) is closely related to elaborating the influence of several team members (TMs) on group decisions. Therefore, this study shows how the metricized limit conjoint analysis (MLCA) provides a method to more accurately determine TMs’ influences. For doing so, this study introduces a new approach as a suitable alternative to directly ask for TMs’ influences by utilizing a detailed step-by-step instruction for further research. Moreover, this study theoretically underlines the usability and preferableness of this new approach and validates it with a simulation of 45,000 assessments nested within 5,000 artificial respondents. The results indicate a diverse application potential for researching ETDs in several contexts. In addition, an illustrative example shows how this conjoint approach can be of value in subsequent research projects. Therefore, the MLCA is of increased interest for both researchers and practitioners when focusing on ETDs in several contexts. |
url |
https://doi.org/10.1177/2158244018779106 |
work_keys_str_mv |
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