Titlebook: Handbook of Market Research; Christian Homburg,Martin Klarmann,Arnd Vomberg Living reference work 20200th edition Data Analytics.Market R

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书目名称Handbook of Market Research影响因子(影响力)




书目名称Handbook of Market Research影响因子(影响力)学科排名




书目名称Handbook of Market Research网络公开度




书目名称Handbook of Market Research网络公开度学科排名




书目名称Handbook of Market Research被引频次




书目名称Handbook of Market Research被引频次学科排名




书目名称Handbook of Market Research年度引用




书目名称Handbook of Market Research年度引用学科排名




书目名称Handbook of Market Research读者反馈




书目名称Handbook of Market Research读者反馈学科排名

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Field Experiments,cus on causal inference and internal and external validity. We conclude the chapter with a practical case study as well as a brief literature review on recent published articles employing field experiments as a data collection method, providing the reader with a list of examples to consider and to r

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Crafting Survey Research: A Systematic Process for Conducting Survey Research,n, we offer a systematic approach for crafting surveys. We discuss key steps and decisions in the survey design process, with a particular focus on standardized questionnaires, and we emphasize how those choices can help alleviate potential biases. Finally, we discuss how investigators can address p

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Challenges in Conducting International Market Research,laborative and iterative translation and statistical methods for testing equivalence. This chapter provides researchers with the methods and tools necessary to derive meaningful and sound conclusions from research designed to guide international marketing activities.

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Dealing with Endogeneity: A Nontechnical Guide for Marketing Researchers,s of good quality is challenging. We discuss good practice in finding IVs, and we examine common IV estimation approaches, such as the two-stage least squares approach and the control function approach. Furthermore, we consider other implementation challenges, such as dealing with endogeneity when t

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Fusion Modeling,res including mismatched groups of customers, data at different levels of aggregation, and more general missing data problems that commonly arise in marketing. This chapter provides readers with a step-by-step guide to developing Bayesian data fusion applications, including an example fully worked o

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Modeling Marketing Dynamics Using Vector Autoregressive (VAR) Models,emic researchers pay attention to whether a performance change is temporary (short-term) or lasting (long-term). Establishing the distinction between short-term and long-term marketing effectiveness is central to the understanding of marketing strategy and its implications, which this chapter aims t

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