Proceedings of the Fourteenth International Conference on Management Science and Engineering Management : Volume 1

著者名：Xu, Jiuping (EDT)/Duca, Gheorghe (EDT)/Ahmed, Syed Ejaz (EDT)/García Márquez, Fausto Pedro (EDT)/Hajiyev, Asaf (EDT)

Springer（2020/06/22発売）

• 言語：ENG
• ISBN：9783030498283
• eISBN：9783030498290

Description

This book gathers the proceedings of the 14th International Conference on Management Science and Engineering Management (ICMSEM 2020). Held at the Academy of Studies of Moldova from July 30 to August 2, 2020, the conference provided a platform for researchers and practitioners in the field to share their ideas and experiences.

Covering a wide range of topics, including hot management issues in engineering science, the book presents novel ideas and the latest research advances in the area of management science and engineering management. It includes both theoretical and practical studies of management science applied in computing methodology, highlighting advanced management concepts, and computing technologies for decision-making problems involving large, uncertain and unstructured data. The book also describes the changes and challenges relating to decision-making procedures at the dawn of the big data era, and discusses new technologies for analysis, capture, search, sharing, storage, transfer and visualization, and in the context of privacy violations, as well as advances in the integration of optimization, statistics and data mining. Given its scope, it will appeal to a wide readership, particularly those looking for new ideas and research directions. 

Table of Contents

Advancement of Statistical Analysis, Machine Learning and Decision Analysis Based on the Fourteenth ICMSEM Proceedings.- Factors Influencing Online Shopping Experience and Customer Satisfaction in Karachi.- Factors Affecting Furniture Purchase in Pakistan.- Impact of Ownership Structure and Credit Behavior on Performance of Rural Commercial Banks: Evidence from China.-Education Impact on Health Shocks: Evidence from C.H.N.S. Data.- Spatio-temporal Evolution and Regional Difference Analysis of China’s Agricultural Technology Progress under Two-way Output.