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dc.contributor.authorMooi, Erik
dc.contributor.authorSarstedt, Marko
dc.contributor.authorMooi-Reci, Irma
dc.date.accessioned2020-06-11T07:36:44Z
dc.date.available2020-06-11T07:36:44Z
dc.date.issued2018
dc.identifier.isbn978-981-10-5218-7
dc.identifier.urihttp://ir.mksu.ac.ke/handle/123456780/6347
dc.description.abstractIn the digital economy, data have become a valuable commodity, much in the way that oil is in the rest of the economy (Wedel and Kannan 2016). Data enable market researchers to obtain valuable and novel insights. There are many new sources of data, such as web traffic, social networks, online surveys, and sensors that track suppliers, customers, and shipments. A Forbes (2015a) survey of senior executives reveals that 96% of the respondents consider data-driven marketing crucial to success. Not surprisingly, data are valuable to companies who spend over $44 billion a year on obtaining insights (Statista.com 2017). So valuable are these insights that companies go to great lengths to conceal the findings. Apple, for example, is known to carefully hide that it conducts a great deal of research, as the insights from this enable the company to gain a competitive advantage (Heisler 2012). This book is about being able to supply such insights. It is a valuable skill for which there are abundant jobs. Forbes (2015b) shows that IBM, Cisco, and Oracle alone have more than 25,000 unfilled data analysis positions. Davenport and Patil (2012) label data scientist as the sexiest job of the twenty-first century. This book introduces market research, using commonly used quantitative techniques such as regression analysis, factor analysis, and cluster analysis. These statistical methods have generated findings that have significantly shaped the way we see the world today. Unlike most market research books, which use SPSS (we’ve been there!), this book uses Stata. Stata is a very popular statistical software package and has many advanced options that are otherwise difficult to access. It allows users to run statistical analyses by means of menus and directly typed commands called syntax. This syntax is very useful if you want to repeat analyses or find that you have made a mistake. Stata has matured into a user-friendly environment for statistical analysis, offering a wide range of features. If you search for market(ing) research books on Google or Amazon, you will find that there is no shortage of such books. However, this book differs in many important ways:en_US
dc.language.isoen_USen_US
dc.publisherSpringeren_US
dc.titleMarket Researchen_US
dc.title.alternativeThe Process, Data, and Methods Using Stataen_US
dc.typeBooken_US


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