A dimensional versus attribute approach for disaggregate choice models

A fundamental issue facing choice modelers is to make a decision on what kind of independent variables to include in a choice model. With survey data, the two immediate options are: actual product attributes or underlying latent dimensions (factor scores). Using behavioral logic we argue that heterogeneity of consumer perceptions of variables and their saliences should be the key items moderating such a decision. We present empirical evidence to support our theory that dimensional (factor score) based models do better in terms of predictions than attribute based models in more heterogeneous populations. Empirical analysis shows that in segments (where consumer heterogeneity is lower) the predictive performance of attribute based models improves relative to the factor score model and may actually have a better predictive fit when the respondents are relatively homogeneous with respect to attribute ratings and saliences.     

How do firms make money selling digital goods online?

We review research on revenue models used by online firms who offer digital goods. Such goods are non-rival, have near zero marginal cost of production and distribution, low marginal cost of consumer search, and low transaction costs. Additionally, firms can easily observe and measure consumer behavior. We start by asking what consumers can offer in exchange for digital goods. We suggest that consumers can offer their money, personal information, or time. Firms, in turn, can generate revenue by selling digital content, brokering consumer information, or showing advertising. We discuss the firm’s trade-off in choosing between the different revenue streams, such as offering paid content or free content while relying on advertising revenues. We then turn to specific challenges firms face when choosing a revenue model based on either content, information, or advertising. Additionally, we discuss nascent revenue models that combine different revenue streams such as crowdfunding (content and information) or blogs (information and advertising). We conclude with a discussion of opportunities for future research including implications for firms’ revenue models from the increasing importance of the mobile Internet.     

Online Market Entry: The Motivations for Imitation across Retailer Types

This study examines the motivations for imitation in retailers' online channel entry. Extant literature suggests that legitimacy and efficiency are the primary motivators for firms to imitate. We develop hypotheses that center on the belief that not all firm types would use the same motivator for deciding to imitate and enter the online market; legitimacy would be the driving force for some retailer types whereas efficiency would be the motivator for others. We test our hypotheses on unique data collected from multiple sources. Our findings confirm that the motivators for imitation vary across retailer types. Copyright © 2014 John Wiley & Sons, Ltd.     

Role of monetary policy in a New Keynesian economy: a note from a laboratory experiment

This paper discusses an experimental study on the role of monetary policy within a New Keynesian macroeconomic framework. The novelty of this article is that each subject was asked to forecast both the inflation rate and output gap at the same time one period ahead, which is an improvement over the existing literature. We find that if both the expected inflation rate and expected output gap is incorporated in the monetary policy rule then inflation can be anchored and stabilized more efficiently.     

Forecast information and traditional retailer performance in a dual-channel competitive market

Independent firms in a dual-channel competitive market are expected to have their own information about the nature of the market. In this research, we develop a game-theoretic model to examine the value of forecast information about consumers' willingness to pay. The model is based on a simultaneously played Bertrand game. Our results indicate that the profits of online as well as traditional retailers always increase with forecast accuracy, and that forecast accuracy has a greater effect on the performance of the traditional retailer than on that of the online retailer. Our results also show that the difference in profit between that of the traditional retailer and the online retailer increases with forecast accuracy. In addition we find that forecast accuracy is much more valuable to the traditional retailer when there is an increasing volatility in the market, an increasing level of consumer valuation of the product, and an increasing intensity in market competition. Based on our results, we derive optimal market strategies and identify directions of future research.