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Methods to improve our field /

"Research Methodology in Strategy and Management advances understanding of the methods used to study organizations - including managers, strategies, and how firms succeed. Offering innovative ideas that explore how strategy and management methodology can be developed, the chapter authors in Vol...

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Bibliographic Details
Group Author: Hill, Aaron D. (Editor); McKenny, Aaron F. (Editor); O'Kane, Paula (Editor); Paroutis, Sotirios (Editor)
Published: Emerald Publishing,
Publisher Address: Bingley :
Publication Dates: 2023.
Literature type: Book
Language: English
Edition: First edition.
Series: Research methodology in strategy and management, volume 14
Subjects:
Management > Research > Methodology.
Business planning > Methodology.
Management > Methodology. > Methodology.
Summary: "Research Methodology in Strategy and Management advances understanding of the methods used to study organizations - including managers, strategies, and how firms succeed. Offering innovative ideas that explore how strategy and management methodology can be developed, the chapter authors in Volume 14, Methods to Improve Our Field, consider approaches that range from the re-imagining of secondary data in the digital age and Interpretive phenomenological Analysis (IPA) to Machine Learning and Artificial Intelligence. Methods to Improve Our Field is a necessity for both academics and researchers interested in the progression and cutting-edge studies of management, strategy, international business, entrepreneurship, and organization theory"--Back cover.
Carrier Form: xii, 174 pages : illustrations ; 24 cm.
Bibliography: Includes bibliographical references.
ISBN: 9781804553657
1804553654
Index Number: HD30
CLC: C93-03
Call Number: C93-03/M592
Contents: Introduction to methods to improve our field /
Reimagining secondary data in a digital age /
Insights from the application of interpretative phenomenological analysis in management research /
Synthesizing best practices for conducting dictionary-based computerized text analysis research /
Using mixed-effect growth models to examine time as a predictor of interest and between-firm differences over time /
Garbage in, garbage out: a theory-driven approach to improve data handling in supervised machine learning /
Artificial intelligence and the operationalization of psychological constructs: the case of emotions and emotional authenticity of entrepreneurs during pitch presentations /
PechaKucha-based participatory video for organizational research /

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