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Essentials of Marketing Research takes an applied approach to the fundamentals of marketing research by providing examples from the business world of marketing research and showing students how to apply marketing research results. This text focuses on understanding and interpreting marketing research studies. Focusing on the 'how-to' and 'so what' of marketing research helps students understand the value of marketing research and how they can put marketing research into practice. There is a strong emphasis on how to use marketing research to make better management decisions. The unique feature set integrates data analysis, interpretation, application, and decision-making throughout the entire text. The text opens with a discussion of the role of marketing research, along with a breakdown of the marketing research process. The text then moves into a section discussing types of marketing research, including secondary resources, qualitative research, observation research, and survey research. Newer methods (e.g. using blogs or Twitter feeds as secondary resources and using online focus groups) are discussed as extensions of traditional methods such. The third section discusses sampling procedures, measurement methods, marketing scales, and questionnaires. Finally, a section on analyzing and reporting marketing research focuses on the fundamental data analysis skills that students will use in their marketing careers. Features of this text include: - Chapter Openers describe the results of a research study that apply to the topics being presented in that chapter. These are taken from a variety of industries, with a greater emphasis on social media and the Internet. - A Global Concerns section appears in each chapter, helping prepare students to conduct market research on an international scale.This text emphasizes the presentation of research results and uses graphs, tables, and figures extensively. - A Statistics Review section emphasizes the practical interpretation and application of statistical principles being reviewed in each chapter. - Dealing with Data sections in each chapter provide students with opportunities to practice interpreting data and applying results to marketing decisions. Multiple SPSS data sets and step-by-step instructions are available on the companion site to use with this feature. - Each Chapter Summary is tied to the chapter-opening Learning Objectives. - A Continuing Case Study follows a group of students through the research process. It shows potential trade-offs, difficulties and flaws that often occur during the implementation of research project. Accompanying case questions can be used for class discussion, in-class group work, or individual assignments. - End-of-Chapter Critical Thinking Exercises are applied in nature and emphasize key chapter concepts. These can be used as assignments to test students' understanding of marketing research results and how results can be applied to decision-making. - End-of-chapter Your Research Project provides more challenging opportunities for students to apply chapter knowledge on an in-depth basis, and thus olearn by doing.
This book is a platform to publish new progress in the field of materials and technologies that can offer significant developments with the possibility of changing the future. These emerging developments will change the way we live now at an unprecedented pace across our society. It is important to note that such modern developments are no longer restricted to a single discipline, but are the outcome of a multidisciplinary approach, which combines many different engineering disciplines. This book explores the new technology landscape that will have the direct impact on production-related sectors, individually and in combination with different disciplines. A major driver for this actual research is the efficiency, many times connected with a focus on environmental sustainability.
This is the authoritative reference work in the field. An interdisciplinary set, it investigates the extensive history, design and methods of case study research.
China's banking sector has witnessed significant inbound M&A traffic by developed market banks in recent years. At the same time, Chinese banks have risen to become some of the world's biggest banks. Along with these massive market values and financing capabilities have come global ambitions culminating in first outbound M&A moves. This study exploratively researches the relationship between developed market banks' inbound M&A into China and Chinese banks' outbound M&A. Based on a conceptual discussion, case studies and expert interviews an explanation model is developed outlining the drivers and barriers of Chinese banks' outbound M&A and the factors in the inbound-outbound relationship. This model enables developed market banks to analyse potential M&A reactions by incumbents. Finally, dynamic M&A market entry strategies are derived, which explicitly account for future incumbent outbound M&A moves.
A new era of innovation is enabled by the integration of social sciences and information systems research. In this context, the adoption of Big Data and analytics technology brings new insight to the social sciences. It also delivers new, flexible responses to crucial social problems and challenges. We are proud to deliver this edited volume on the social impact of big data research. It is one of the first initiatives worldwide analyzing of the impact of this kind of research on individuals and social issues. The organization of the relevant debate is arranged around three pillars: Section A: Big Data Research for Social Impact: • Big Data and Their Social Impact; • (Smart) Citizens from Data Providers to Decision-Makers; • Towards Sustainable Development of Online Communities; • Sentiment from Online Social Networks; • Big Data for Innovation. Section B. Techniques and Methods for Big Data driven research for Social Sciences and Social Impact: • Opinion Mining on Social Media; • Sentiment Analysis of User Preferences; • Sustainable Urban Communities; • Gender Based Check-In Behavior by Using Social Media Big Data; • Web Data-Mining Techniques; • Semantic Network Analysis of Legacy News Media Perception. Section C. Big Data Research Strategies: • Skill Needs for Early Career Researchers—A Text Mining Approach; • Pattern Recognition through Bibliometric Analysis; • Assessing an Organization’s Readiness to Adopt Big Data; • Machine Learning for Predicting Performance; • Analyzing Online Reviews Using Text Mining; • Context–Problem Network and Quantitative Method of Patent Analysis. Complementary social and technological factors including: • Big Social Networks on Sustainable Economic Development; Business Intelligence.