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How to Make your Doctoral Research Relevant

Insights and Strategies for the Modern Research Environment

Edited by Friederike Welter and David Urbano

Everyone wants their research to be read and to be relevant. This exciting new guide presents a broad range of ideas for enhancing research impact and relevance. Bringing together researchers from all stages of academic life, it offers a far-reaching discussion of strategies to optimise relevancy in the modern research environment.
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Edited by Friederike Welter and David Urbano

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Edited by Keith Townsend, Mark N.K. Saunders, Rebecca Loudoun and Emily A. Morrison

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How to Keep your Doctorate on Track

Insights from Students’ and Supervisors’ Experiences

Edited by Keith Townsend, Mark N.K. Saunders, Rebecca Loudoun and Emily A. Morrison

The path of a doctoral student can feel challenging and isolating. This guide provides doctoral students with key ideas and support to kick-start a doctoral journey, inspire progress and complete their thesis or dissertation. Featuring observations from experienced supervisors, as well as the reflections of current and recent postgraduate researchers, this intimate and entertaining book offers vital insights into the critical moments in any doctoral experience.
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Paulo Albuquerque and Bart J. Bronnenberg

We present an illustration of how marketing and structural models can be applied in a public policy context. We describe the demand model in Albuquerque and Bronnenberg (2012) to evaluate the impact of the 2009 federal policy measure known as the “Car Allowance Rebate System” program (or “Cash for Clunkers”) on prices and demand in the auto sector.

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Rebecca Kirk Fair and Laura O’Laughlin

Despite the wide scope for survey evidence used in litigation, the relevance and usefulness of expert-submitted surveys in any legal context is dependent on how they are designed and implemented. The avoidance of bias in survey evidence is central to a survey’s admissibility and the probative weight accorded to the survey expert’s testimony. This chapter discusses possible sources of bias and describes methods and techniques that a survey expert can use to minimize this bias.

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Greg M. Allenby and Peter E. Rossi

Bayesian econometric methods are particularly well suited for analysis of marketing data. Bayes theorem provides exact, small-sample inference within a flexible framework for assessing particular parameters and functions of parameters. We first review the basics of Bayesian analysis and examine three areas where Bayesian methods have contributed to marketing analytics – models of choice, heterogeneity, and decision theory. We conclude with a discussion of limitations and common errors in the application of Bayes theorem to marketing analytics.

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Asim Ansari and Yang Li

The field of “Big Data” is vast and rapidly evolving. In this chapter, strict attention is paid to challenges that are associated with making statistical inferences from big data. We characterize big data by the four Vs (volume, velocity, variety and veracity) and discuss the computational challenges in marketing applications using big data. We review stochastic approximation, variational Bayes, and the methods for wide data models.

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Peter E. Rossi

This chapter summarizes the major methods of causal inference and comments on the applicability of these methods to marketing problems.

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Olivier Toubia

This chapter offers an overview of Conjoint Analysis, with an eye toward implementation and practical issues. After reviewing the basic assumptions of Conjoint Analysis, I discuss issues related to implementation; data analysis and interpretation; and issues related to ecological validity. In particular, I discuss recent evidence regarding consumers’ attention in Conjoint Analysis surveys, how it may be increased and modeled, and whether responses in Conjoint Analysis surveys are predictive of real-life behavior. Each section concludes with practical recommendations.