the participants in the Tuck Marketing Seminar Series for their valuable comments and helpful suggestions. The Impact of Brand Equity on Customer Acquisition, Retention, and Profit Margin ABSTRACTThis paper examines the relationship between brand equity and customer acquisition, retention, and profit margin, the key components of customer lifetime value (CLV). We examine a unique database from the U.S. automobile market that combines 10 years of acquisition rate, retention rate, and customer profitability data with measures of brand equity from Young & Rubicam's Brand Asset Valuator (BAV) over the same time period. We hypothesize and find that BAV brand equity is significantly associated with the components of CLV in expected and meaningful ways. For example, customer Knowledge of a brand has an especially strong positive relationship with all three components of CLV. Interestingly, however, Differentiation is a double-edged sword. While it is associated with higher customer profitability, it is also associated with lower acquisition and retention rates. We also find that marketing efforts exert indirect impacts on CLV through brand equity. Simulations show that changes in marketing, or exogenous changes in brand equity, can exert important effects on CLV. Overall, the findings suggest the "soft" and "hard" sides of marketing need to be managed in a coordinated fashion.We discuss these and other implications for researchers and practitioners.

Firms are increasingly seeking to harness the potential of social networks for marketing purposes. therefore, marketers are interested in understanding the antecedents and consequences of relationship formation within networks and in predicting interactivity among users. the authors develop an integrated statistical framework for simultaneously modeling the connectivity structure of multiple relationships of different types on a common set of actors. their modeling approach incorporates several distinct facets to capture both the determinants of relationships and the structural characteristics of multiplex and sequential networks. they develop hierarchical bayesian methods for estimation and illustrate their model with two applications: the first application uses a sequential network of communications among managers involved in new product development activities, and the second uses an online collaborative social network of musicians. the authors' applications demonstrate the benefits of modeling multiple relations jointly for both substantive and predictive purposes. they also illustrate how information in one relationship can be leveraged to predict connectivity in another relation.

Abstract. Currently, multiple data vendors utilize the cloud-computing paradigm for trading raw data, associated analytical services, and analytic results as a commodity good. We observe that these vendors often move the functionality of data warehouses to cloud-based platforms. On such platforms, vendors provide services for integrating and analyzing data from public and commercial data sources. We present insights from interviews with seven established vendors about their key challenges with regard to pricing strategies in different market situations and derive associated research problems for the business intelligence community.

Trading data as a commodity has become increasingly popular in recent years, and data marketplaces have emerged as a new business model where data from a variety of sources can be collected, aggregated, processed, enriched, bought, and sold. They are effectively changing the way data are distributed and managed on the Internet. To get a better understanding of the emergence of data marketplaces, we have conducted several surveys in recent years to systematically gather and evaluate their characteristics. This paper takes a broader perspective and relates data marketplaces as currently discussed in computer science to the neoclassical notions of market and marketplace from economics. Specifically, we provide a typology of electronic marketplaces and discuss their approaches to the distribution of data. Finally, we provide a distinct definition of data marketplaces, leading to a classification framework that can provide structure for the emerging field of data marketplace research.