Consumer Habits and Adoption of Multiple-Functions of Mobile Phones

Mobile phone applications are rapidly becoming an important channel of interaction between brands and consumers. Recent findings, however, suggest that only few brands succeed in attracting consumers to their mobile applications. Based on findings in the literature, we suggest that consumers with high use-variety, i.e., those who use their mobile phones for multiple functions, are likely to be more interested in mobile applications than others. There are, however, few insights regarding high use-variety consumers. This is the issue that we address in this research by developing and testing a theory, based on habits, that heavy users of the core functions of calling and texting will exhibit high use-variety. We empirically test the theory on two nationally representative samples of mobile phone users. Our results on both samples support the theory. We also discuss the managerial and future research implications of our findings

Why Consumers Talk: An Investigation of the Extrinsic Motivators of Electronic Word of Mouth

We investigate the relative effects of intrinsic and extrinsic motivators on online consumer word of mouth. Specifically, we examine how the influence of product satisfaction – an intrinsic motivator – compares to three extrinsic motivators, i.e., product life cycle stage, product attributes and expert opinions, in stimulating electronic word of mouth. We also examine the roles of different types of product attributes in generating electronic word of mouth. The context of our investigation is electronic word of mouth for automobiles. Our results suggest that while intrinsic motivators do play a strong role in generating electronic word of mouth, extrinsic motivators such as the product’s life cycle stage, its attributes and experts’ opinions play a stronger role. Specifically, new products are likely to generate more word of mouth than older ones. Following the product’s life cycle stage in importance are the product’s attributes and expert opinions, in that order, in their influence. We also provide implications for additional research on the role of extrinsic motivators in generating consumer word of mouth

A Multiplicative Fixed-Effects Model of Consumer Choice

The issue of consumer heterogeneity in discrete choice analysis has been attracting much attention recently. Research has suggested that heterogeneity can result in biased parameter estimates which, in turn, can lead to incorrect conclusions. Among the many methods proposed in the literature to handle heterogeneity, models seem to be the most attractive from a substantive point of view. However, in order to provide consistent estimates, these models typically require long purchase histories. This difficult constraint has prevented their widespread use. In this paper, we propose a new model which offers the benefits of fixed effects models without requiring long purchase histories. Our approach differs from the classic formulation in two ways. First, we calibrate the common and fixed-effects sequentially rather than simultaneously. This two-stage estimation permits us to obtain unbiased estimates of the common parameters even when the sample has households with very few observations. Second, we incorporate the fixed effects in a multiplicative rather than in an additive form. Our assumptions regarding the error term result in a probit model with heteroskedastic and temporally correlated random utilities. We develop a method of moments based estimator to calibrate parameters of models with this type of error structure. This procedure exploits the property that the method of moments yields estimates which are asymptotically as efficient as the maximum likelihood estimates given an appropriate starting point and a matrix of instruments. This is a very general procedure in that its mechanics are not tied to the proposed model. It can be readily applied to other problems where probit models are used to analyze data with serial correlation. This is a methodological contribution of the paper. The model and estimation procedure are illustrated on the A. C. Nielsen scanner data base for the liquid detergent category. Our results indicate that the proposed model can provide a better fit than random effects and loyalty based models and better predictive performance than random effects models. From a substantive perspective, our analysis provides the following findings. (a) —thus, most households have very similar price sensitivity in this category; (b) —suggesting that there are some households that are highly responsive to promotions while there are quite a few households that are less influenced by promotions; (c) —which is an indication that a reduction in preference for a brand is associated with an increase in price sensitivity and ; (d) —thus, as the preference for a brand increases, response to promotions by the brand also increases; and (e) —implying that, as households become more price sensitive, purchases may be driven more by price than by promotions; in other words, rather than responding to promotions such as displays and features as signals of a reduced price, price sensitive households actively evaluate prices in arriving at a choice. The proposed approach can be used by theoretical as well as applied researchers of brand choice behavior. Specifically, estimates of fixed-effects provided by the model can be used to cluster households into groups with similar parameters. Profiling the resulting groups in terms of demographics would provide interesting insights—from a theoretical perspective—regarding the household characteristics that are associated with different types of response behavior. It would also help managers to better target their brands. Using the proposed approach for cross-category analyses of fixed-effects would be an interesting area of future research. For instance, given a sample of households and their purchase histories in multiple categories, the proposed model can be used to explore the relationship between household behavior and category characteristics. In particular, issues such as the following can be investigated by comparing household-level estimates across categories: (a) are households that are highly price sensitive in one category also price sensitive in other categories? (b) what household characteristics are associated with high (low) price sensitivity or high (low) promotion response across categories? and (c) in what types of categories are households likely to exhibit high (low) price sensitivity or high (low) promotion response?brand choice, choice models, heterogeneity, fixed-effects, method of moments

A Probit Model of Choice Dynamics

There are many products which are repeatedly purchased by consumers. In such cases it is likely that choice history, that is the sequence of choices made in the past, as well as marketing variables affect subsequent choice decisions. Attempts to model the effects of choice history have been generally based on the inclusion of variables that represent brand loyalty and/or variety seeking behavior. In this paper we present a model of dynamic choice behavior which is more general and incorporates four characteristics. The first characteristic labeled preference reinforcement and preference reduction represents loyalty and variety seeking. The second is the short-term reluctance of a consumer to move from the current brand (inertia) or the willingness to move to another brand (mobility). The third characteristic captures the effect of repetitive consumption (the long term effect) on inertia and mobility. The fourth characteristic incorporates the similarity or dissimilarity of choice alternatives. This is important in a dynamic model because choice on the current purchase occasion can be affected by whether a similar or dissimilar alternative was chosen on the previous occasion. Similarities of alternatives are represented in terms of distances. The effect of price on choice behavior is also modeled. Individual-level purchase data from a consumer panel are used to estimate a covariance probit and an independent probit specification of the model. From a substantive perspective the model gives interesting insights into the dynamics of choice behavior. The model predicts switches better than a benchmark model which incorporates only loyalty. In addition, it is superior to three benchmark models in overall predictive ability.inertia/mobility, choice dynamics, covariance probit, similarity

Relative importance of online versus offline information for Internet purchases: Product category and Internet experience effects

Across three studies we examine the relative importance of online versus offline information for Internet purchases. Study 1 reveals that the relative importance of online information is higher for utilitarian products (computer hardware and software) than for hedonic products (books, music, and movies). Study 2 shows that, in the case of online purchases, the relative importance of online information decreases with increasing consumer Internet experience. Consequently, offline information becomes relatively more important for consumers with high levels of Internet experience. In addition, the relative importance of online information is higher for utilitarian products than for hedonic products, supporting Study 1 results. Study 3 suggests a possible mechanism for the effect of Internet experience on decreasing importance of online information, showing that consumers' trust of online search engine information decreases with increasing Internet experience. We conclude with implications of our results for firms that sell products on the Internet.Online purchases Online behavior Information importance Internet experience

Google or BizRate? How search engines and comparison sites affect unplanned choices of online retailers

Recent trends in online retailing suggest that "33% of buyers often or sometimes make unplanned purchases" [Annual Retail Consumer Survey Report. Jupiter Research 2003.]. Findings based on online retailing trends also suggest that both search engines and infomediaries are beginning to play a strong role in leading consumers to online retail sites. Additionally, some practitioner studies find that about half of online consumers use comparison shopping sites before choosing a retailer. Retailers therefore need to understand whether search engines or infomediaries play a stronger role in bringing unplanned consumers. This is the issue that we investigate in this research. Our results indicate that, retailer and consumer factors, category characteristics and the consumer's past relationship with the retailer do play a role in the store choice decisions of online consumers. Between search engines and infomediaries, however, search engines play a far stronger role than infomediaries. The effect is, in fact, more than twice that of infomediaries.Online retailing Unplanned purchases Search engines Comparison sites Household production Human capital

The Effect of Promotion on Consumption: Buying More and Consuming It Faster,”

Abstract This paper empirically demonstrates the existence of flexible consumption rates in packaged goods products, how this phenomenon can be modeled, and its importance in assessing the effectiveness of sales promotion. We specify an incidence, choice and quantity model, where category consumption varies with the level of household inventory. We use two different functions to relate consumption rates to household inventory, and estimate the models using scanner panel data from two product categories --yogurt and ketchup. Both provide a significantly better fit than a conventional model, which assumes a constant daily usage rate. They also have strong discriminant validity --yogurt consumption is found to be much more flexible with respect to inventory than ketchup consumption. We use a Monte Carlo simulation to decompose the long-term impact of promotion into brand switching and consumption effects, and conclude with the implications of our findings for researchers and managers