University of Central Florida

Orlando, FL

Marketing

Extracting Quantitative Information

2007

Ph D

Universidad De Navarra

Pamplona, Spain

Economics

1997

BA

Empirical Generalizations From Brand Extension Research: How Sure Are We?

253-261

Echambadi, Raj
Arroniz, Inigo
Reinartz, Werner
Lee, Junsoo

2006

International Journal of Research in Marketing

Yes

The 12 Different Ways for Companies to Innovate

75-81

Sawhney, Mohanbir
Wolcott, Robert
Arroniz, Inigo

2006

MIT Sloan Management Review

Yes

Entry Timing and Firm Survival: The Moderating Effects of Firm and Industry Factors.

This study examines the relationship between entry timing and firm survival. While extant literature has extolled the benefits of early entry, we draw on multiple theoretical perspectives to propose that windows of opportunity and therefore survival advantages exist for entrants both early and late in an industry’s life cycle. Thus, we suggest that the relationship between entry timing and survival is best modeled as a curvilinear relationship, moderated by both firm level and marketplace factors. Using a panel data of 3,431 firms from 33 industries over the period 1908-1991, our findings support our general premise. Moreover, due to different underlying competitive processes, early entry is more beneficial for large firms whereas small firms are better able to take advantage of late entry opportunities. Early mover advantage is also enhanced in industries that undergo a rapid pace of technological change. Implications of these results for order of entry studies are discussed.

On-Going

Scholarly

Forecasting Movie Success Using Text-Based Information

Despite the widespread availability and importance of non-numeric data, marketers do not have the tools to extract information from these non-numeric data sources. This dissertation attempts to fill this void: I develop a scalable methodology that is capable of extracting information from huge volumes of non-numeric data. The proposed methodology integrates concepts from information retrieval and content analysis to analyze textual information. This approach avoids a pervasive difficulty of traditional content analysis, namely the classification of terms into predetermined categories, by creating a linear composite of all terms in the document and then, weighting the terms according to their inferred meaning. In the proposed approach, meaning is inferred by the collocation of the term across all the texts in the corpus. It is assumed that there is an underlying lower dimensional space of concepts that underlies word usage. The semantics of each word are inferred by identifying its various contexts in a document. After the semantic similarity space is inferred from the corpus, the words in each document are weighted to obtain their representation on the lower dimensional semantic similarity space, effectively creating a score that measures the concept of interest. I provide an empirical application of the proposed methodology. For this empirical illustration, I revisit an important marketing problem, the effect of movie critics on the performance of the movies. Unlike extant literature, wherein researchers have utilized an overall numerical rating of the review to capture the content of the movie reviews and hence lose valuable information present in the textual materials, I use the proposed methodology to extract valuable information from the non-numeric text of over 9000 movie reviews. This setting is particularly attractive because it allows for a simple validation of the text-derived metrics from the new methodology by comparing it the numeric ratings provided by the reviewers. Results indicate that the metrics directly obtained from the text using the proposed method are good predictors of the numeric ratings provided by reviewers, thereby suggesting good predictive validity. Results also indicate that, even after controlling for the numeric ratings provided by reviewers, information extracted from textual materials adds significant explanatory power as determinants of movie performance. This incremental effect is robust across alternative measures of the movie performance. Specifically, as we move from sales (i.e. box office) to financial return measures (i.e. gross profits and ROI), the relative importance of the content of the review, and therefore the critic’s role, in predicting movie performance increases.

On-Going

Scholarly

GARCH models in SEM

On-Going

Scholarly

Masters of Value and Possibility: Optimizing the Marketing and Research & Development Relationship

We contend that Development (i.e, R&D) and Marketing must become intimate partners if a company hopes to optimize its innovation performance. Unfortunately, too often the Development and Marketing relationship is ill-defined and challenging. In many cases, one function dominates and de-emphasizes the voice of the other. It stands to reason that companies that enhance the working relationship between these two fundamental functions should manage to improve overall performance. To explore this critical arena, we investigated the quality of the working relationship between Development and Marketing in a wide range of companies. We interviewed marketers, R&D personnel, engineers and product managers. Exhibit 1 summarizes our interview queries. Our interviews produced a number of insights and recommendations regarding how to enhance the working relationship between Development and Marketing with this objective of increasing a company’s innovation success rate.

On-Going

Non-Scholarly

Strategic allocation of innovation effort: A contingent approach

On-Going

Scholarly

A 360 Degree View of Innovation

Product Development Management Association Cincinnati Chapter

LyondellBasell Industries

2008