株式会社極東書店トップ商品一覧Data-Driven Strategic Management : Quantitative and Qualitative Analysis.

商品詳細

Data-Driven Strategic Management

Data-Driven Strategic Management : Quantitative and Qualitative Analysis.

・ISBN 978-1-032-93893-6 hard GB£ 171.99

¥54,486.- (税込) (※)価格はご注文時の参考価格となります。
納品価格につきましては書籍の入荷時点で確定となります。
版元の原価改定、外国為替の変動等により異なる場合がございますので、予めご了承下さい。

お気に入り

・ISBN 978-1-032-93891-2 paper GB£ 46.99

¥14,886.- (税込) (※)価格はご注文時の参考価格となります。
納品価格につきましては書籍の入荷時点で確定となります。
版元の原価改定、外国為替の変動等により異なる場合がございますので、予めご了承下さい。

お気に入り
電子版あり 大学・学術機関向け電子ブック(eBook)ISBN 9781003568100
著者・編者Agnihotri, Arpita / Bhattacharya, Saurabh,
出版社(Routledge, UK)
出版年月2026.09
ページ数256 pp.
言語ENG
ニュース番号<773-523>

解説

This text provides a comprehensive and integrated understanding of contemporary concepts and practical frameworks in Strategic Management.

Emphasizing data-driven decision-making, the book incorporates quantitative tools, analytical frameworks, case studies, and critical-thinking exercises tailored to volatile business environments. Data analysis is supported by IBM SPSS, alongside a dedicated chapter on digital business and AI-based strategy. Real-world examples from firms of varying sizes and industries, across both developed and emerging markets such as India and China, illustrate how strategic decisions are made, both successfully and unsuccessfully. Each chapter is structured with clear learning objectives, while "data challenge" exercises, drawing on qualitative and quantitative data, help students develop practical analytical skills. End-of-chapter questions further reinforce understanding and application.

Designed as core reading for advanced undergraduate and postgraduate students in Strategic Management, Business Strategy, and Business Analytics, this text equips learners to make data-informed decisions, formulate competitive strategies, evaluate market expansion opportunities, identify competitors, and leverage AI effectively.

Online resources accompanying the text include PowerPoint slides, a test bank, additional case studies, and data challenge materials.