1st Edition

Entrepreneurial Complexity Methods and Applications

194 Pages
by CRC Press

194 Pages 21 B/W Illustrations
by CRC Press

194 Pages 21 B/W Illustrations
by CRC Press

Entrepreneurial Complexity: Methods and Applications deals with theoretical and practical results of Entrepreneurial Sciences and Management (ESM), emphasising qualitative and quantitative methods. ESM has been a modern and exciting research field in which methods from various disciplines have been applied. However, the existing body of literature lacks the proper use of mathematical and formal... Read more

Contents



Preface ix



Editors xi



Contributors xiii



1 Entrepreneurs for Renewables: Emergence of Innovation and



Entrepreneurship in Complex Social Systems 1



Diana Süsser, Barbara Weig, Martin Döring and



Beate M.W. Ratter



2 Entrepreneurial Network Effects: Empirical Observations of



Entrepreneurial Networks in a World of Complexity 49



John T. Scott



3 Entrepreneurial Process: The Overbearing Role of Complex Social



Network 61



Adekiya Adewale and Ahmed Musbah Aboyssir



4 Sustainable Entrepreneurial Activity within Complex Economic Systems 89



Panagiotis E. Petrakis and Kyriaki I. Kafka



5 Integration Opportunities of Stability-Oriented Processes for Real Estate



Transaction Entities 109



Linda Kauškale and Ineta Geipele



6 Entrepreneurial Dispositions Personality Inventory: Development and



Validation 117



Konrad Janowski, Marcin Waldemar Staniewski and



Katarzyna Awruk



7 Mapping the Entrepreneurship from a Gender Perspective 141



Magdalena Suárez-Ortega, María del Rocío



Gálvez-García and María Fe Sánchez-García



Index 171

Biography

Matthias Dehmer is a professor at the University of Applied Sciences Upper Austria, Steyr School of Management and UMIT – The Health and Life Sciences University in Austria. He also holds a guest professorship at Nankai University, College of Artificial Intelligence in China. His research interests are in graph theory, complex networks, complexity, data science, machine learning, big data analytics, and information theory. In particular, he is also working on machine learningbased methods to design new data analysis methods for solving problems in manufacturing and production.



Frank Emmert-Streib is a professor at Tampere University, Finland, heading the Predictive Society and Data Analytics Lab. His research interests are in the field of data science, machine learning and network science in the development and application of methods from statistics and machine learning for the analysis of big data from genomics, finance, social media and business.



Herbert Jodlbauer is a professor at the University of Applied Sciences Upper Austria, Steyr School of Management and also acts as a director of studies of the bachelor study program Production and Management and the master study program Operations Management. Furthermore, he leads the trans-faculty institute of Smart Production. His research is primarily concerned with production planning, time continuous production models, financial valuation of production related decisionmaking as well as digitalization.