Probabilistic versus random-utility models of state dependence: an empirical comparison

In this paper we develop a general class of dynamic brand choice models, called Lightning Bolt (LB) models, which are consistent with the theory of random utility maximization of consumer choice behavior. The underlying random utility process is Markov, and the inter-temporal evolution of the (utility-maximizing) brand choice process is also Markov. The models permit parsimonious parameterizations of the random utility process in brand choices with the resulting switching probabilities being functionally related to explanatory variables. The model allows for structural state dependence (feedback), habit persistence (inertia), and unobserved heterogeneity. The theoretical development shows that several well known stochastic brand choice models can be deduced from random utility maximization theory. From a managerial perspective, the usefulness of the proposed model stems from its ability to separate out the effects of habits, state dependence and heterogeneity. Strong state dependence effects imply incentives for inducing trial of a brand (e.g., product sampling). In contrast with state dependence, a strong habit persistence effect may be indicative of buyer behavior where inducement of trial of a different brand may not be sufficient to maintain a (sustained) defection of the consumer from the habitually purchased brand to the trial brand. Failure to distinguish between these two effects has important implications. For example, a model that only accounts for state dependence effects would, in the presence of only habit persistence, incorrectly attribute it to state dependence. Based on this the manager could decide to embark on an expensive sampling program that might prove ineffective due to the absence of state dependence. It is also important to distinguish between the effects of unobserved heterogeneity and state dependence. In the absence of true state dependence, failing to account for unobservable variations across households (such as differences in price sensitivities), results in the temporally persistent unobservable elements showing up as state dependence in the model. Hence, a manager may incorrectly opt for sampling as the appropriate marketing action, whereas, a couponing or price promotion strategy should have been preferred. We estimate the model parameters using the AC Nielsen household scanner panel data set on catsup purchases. Further, we investigate empirical techniques for overcoming the “initial conditions” problem that affects many dynamic models of brand choice. Through simulation analysis using the estimated parameters, we show that the calculated profitability of a promotion must take into account the multi-period impact due to state dependence. Further, we demonstrate how ignoring heterogeneity can result in spurious state dependence, thereby making marketing tactics such as product sampling appear far more attractive than they actually are. Specifically, the model that accounts only for habit persistence and state dependence effects predicts a share increase of 2.4% points through sampling for one of the brands in the empirical analysis. Once the effects of unobserved heterogeneity are accounted for, however, this number drops precipitously to 0.3%. While even this low number might fulfill the objectives of the brand manager, it ensures that expectations are not eight times that number. It is important to note that this paper is a first attempt at analyzing the three fundamental dimensions of dynamic brand choice behavior. Our formulation represents a “reduced form” approach as opposed to a “structural” approach. Other limitations of the model include our focus on time-invariant choice sets. Extensions of the model to situations where choice sets vary over time are possible, but are difficult. Another limitation is the dependence on multivariate extreme value distributions. An alternative would be to use multivariate normal distributions, i.e., a probit-like structure which has certain useful properties. A comparison of the two approaches would be useful. Empirical extensions of the model to allow for higher-order processes and nested logit type model structures could also be fruitful. Explicitly incorporating variety-seeking behavior in the model would further enrich the theoretical framework proposed in this paper.

This study analyzes TV program content for viewers with respect to the following three properties: primary utility (intrinsic value by genre, cast, and so on), macro externality, such as the effect of others' past behavior (audience ratings), and state dependence, or the viewer's past actions that determine whether to watch the program. Focusing on the effects of macro externality and state-dependence on viewer behavior, the authors construct a hierarchical Bayesian model and derive an individual utility function. Applying their method to the choice of TV programs in Japan, they estimate the effects of macro externality and state dependence on an individual's viewing behavior, and illustrate the distribution of these effects. The authors find that macro externality has a strong overall effect on the total number of viewers and the state-dependence effect has a slightly positive effect. Moreover, comparing the attributes revealed that male viewers tend to show a lower effect of ratings and higher state dependence than females. They find that the older the viewers are, the higher the effect of state dependence. Further, using utility function data obtained by our estimation, they conduct a simulation to measure the dynamic effects of macro externality and state dependence.

Empirical research (as well as theoretical reasoning) has led to contradictory findings with regard to whether increases in brand advertising activities lead to increases or decreases in consumer price sensitivity. Lack of data to measure the exposure of individual households to advertisements and to capture competitive activities has been an important limitation to date. This study, using single source data for a midwestern US market, finds that increased advertising exposures are associated with increases in a household's brand choice price sensitivity for two frequently purchased consumer products. However, under high levels of advertising exposure, it is possible for a household's brand choice price sensitivity to decrease.

PurposeThis study evidences the influence that sales promotion has on brand choice behaviour. Establishments wish to influence consumers' buying behaviour, and thus they launch strong promotional campaigns or introduce changes in their price policies, among other actions. However, they are not always capable of achieving their goal, since, although they may reach their objective in the short term, when the longer term is considered there are undesirable consumer actions.Design/methodology/approachThe problem of consumer brand choice can be adequately described with logit models that allow the use of discrete dependent variables. The probability that the consumer chooses a brand depends directly on the capacity of satisfaction that the brand holds for him/her. In this case, the dependent variable is the brand, and the independent variables are price, reference price, losses and gains, and the different types or techniques of sales promotion. With the aim of obtaining the necessary information for the present study, a regional consumer panel was used.FindingsThe results show that it is necessary to consider the product's promotional state at the moment of purchase as an explanatory element of the process. Promotion is a tool that can help manufacturers and/or retailers in the achievement of their objectives (try the brand, help to decide what brand to buy, etc.). Immediate price reduction is the technique that exerts greatest influence on the brand choice process. It is possible that the consumer perceives a promotion, for example, coupons or rebates, but does not modify his or her behaviour. In this case, manufacturers and/or retailers will be investing their resources in promotional actions that do not have any effect on the consumer.Originality/valuePresents a regional consumer panel that has been elaborated and planned by the authors. Because of this, the information collected is just what was necessary for this study. On the other hand, the paper shows that is very important to know the consumer's preferences and the actions that influence his or her behaviour. Considering the results, it seems that promotions based on price have the greatest effectiveness.

Rats with cannulas implanted in the septal area were conditioned, tested, or both conditioned and tested shortly after intracerebral injection of local anesthetic via the cannulas. A 2 X 2 factorial design was used to determine whether the presumed state of temporary septal area dysfunction, previously shown to produce amnesia, has state-dependent properties. A state-dependent learning effect was observed in the rats both conditioned and tested in the dysfunctional stat remembered the aversive conditioning better than those conditioned in the dysfunctional state but tested in the normal state. Since rats conditioned in the normal state but tested during septal dysfunction did appear to exhibit conditioned fear when tested, the state-dependent effect was asymmetrical. Performance effects of the procaine injection were observed and accounted for in determining the state-dependent nature of temporary septal area dysfunction.

The impact of internal and external reference prices on brand choice: The moderating role of contextual variables

Tracking time-varying brand equity using household panel data

The Effect of Media Advertising on Brand Consideration and Choice

Since FY 2013, as a part of the Affordable Care Act (ACA) program, the Hospital Value-Based Purchasing (HVBP) program has adjusted Medicare’s payments to hospitals based on the total performance score of the hospital. First, the program reduces a portion of the hospital’s Medicare payments in a specific fiscal year, and then, by the end of the same fiscal year, the amount of the payment reductions will be awarded to the hospitals based on the total performance score; thus, the hospitals that do not receive the reward will lose the portion of money reduced by Medicare. In this research, we apply the theory of state dependence and use the dynamic random effect probit model to estimate this effect. The results show that the hospital payment adjustment dynamics have a very significant state dependence effect (0.341); this means that hospitals that received a reward in the previous year are 34.1% more likely to receive a reward this year than the ones that received a penalty in the previous year. Meanwhile, we also find that the state dependence effect varies significantly across hospitals with different ownership (proprietary/government owned/voluntary nonprofit), and the results show that voluntary nonprofit hospitals exhibit the largest effect of state dependence (0.370), while government-owned hospitals exhibit the lowest effect of state dependence (0.293), and proprietary hospitals are in the middle. Among the factors that influence the likelihood that a hospital receives a reward, we find that teaching hospitals with a large number of beds (>400) are less likely be rewarded; in terms of ownership, we find that voluntary nonprofit hospitals are more likely be rewarded; in terms of demographic factors, hospitals where the average household income are higher within the region are more likely be rewarded.

Objective: The study aims to analyze the brand choice process through consumer attitudes toward product attributes that are considered favorable or unfavorable when selecting brands. Theoretical Framework: The main theoretical line that underpins this work is the concept of attitude and its interrelated components: cognitive, affective, and conative, and how they are essential for brand choice. Method: This research methodology comprises a qualitative study of in-depth interviews using a script. Data were collected from 15 Brazilian women through individual interviews conducted in Miami. Results and Discussion: The results revealed that attitudes are crucial in brand choice. Considering the theoretical framework in the discussion section, these results are contextualized, highlighting the implications and relationships between attitude components and brands. The study's main limitations are the qualitative methods and sampling constraints. Research Implications: This research's practical and theoretical implications are discussed, providing insights into how the results can be applied to or influence consumer behavior practices. These implications may encompass the study of brand choice and loyalty and the practical application of content analysis methods. Originality/Value: This study contributes to the literature by reflecting on the importance of attitudes in understanding brand choice. The detailed demonstration of content analysis highlights the relevance and value of the research methods employed.

Brand choice processes and actual brand choices differ importantly across consumers of different age groups. This chapter presents selected findings and reviews the potential underlying mechanisms. Older consumers tend to prefer long-established brands. Their awareness set comprises typically fewer, older brands. This leads to smaller considerations sets and a shrinking purchase process. Not surprisingly, older consumers have a higher tendency to repeat purchase the previous brand. As a consequence, market shares depend on both consumer age and brand age (how long ago the brand was introduced). A variety of mechanisms may account for these results. They include well-known age-related factors: cognitive decline in memory and processing speed, biological aging and its impact on physical capabilities, increased aversion to change, declining innovativeness, increased socioemotional selectivity, stronger brand attachment and habits built over time, and nostalgia. Expertise may have opposite effects, depending on whether expertise acquired over a lifetime is still relevant for today’s market offering. Of course, it is difficult to delineate the effects of age, cohort, and period. We review questions for further research and consider the public policy issues. What can be done to protect older consumers while helping them realize benefits from both the new market opportunities and their own accumulated experience?

When retailers make product assortment changes by eliminating certain stockkeeping units (SKUs), how does this affect sales of individual brands? This is the main question the authors address in this article. Using data from an online retailer that implemented a permanent systemwide SKU reduction (SR) program, the authors investigate how the program affected various components of purchase behavior for individual brands. They find substantial variations in the SR effects across brands, categories, and consumers. They explore possible drivers for these differences and find that higher-market-share, higher-priced, and more frequently promoted brands tend to gain share and that reduction in the number of sizes, reduction in the number of SKUs, and change in SKU share in the category are important in affecting change in a brand's purchase share after the SR. They also find that SRs lead to an increase in category purchase incidence and quantity for highly state-dependent consumers and frequent buyers but a decrease in category purchase and quantity for mildly state-dependent consumers and infrequent buyers. In addition, SRs tend to cause more changes in brand choice probabilities among consumers of lower state dependence and higher price and promotion sensitivity. These findings are of importance both to retailers wanting to make product assortment changes and to manufacturers affected by them.

This empirical research is focusing on how consumers use their internal reference price when they make a brand choice. Past research in grocery store showed that consumers' price knowledge depends on in-store marketing activities like a special price. Author tried to build a price memory based brand choice model and compared with other brand choice models using scanner panel data. As a consequence, the fitness of the price memory based brand choice model is better than the other models. This is because this model considered consumers' price knowledge as a stochastic model and consumers' asymmetric response to price. This empirical research shows that consumers do not change their internal reference price if they buy the brand with normal price. But when they purchase the brand with a reduced price, they will replace their old internal reference price by a new reduced internal reference price. This finding will beuseful for managers when they try to plan price promotions or price settings.

A state dependence model of serial behavior suggests that each occurrence increases the subsequent likelihood of that behavior being repeated. A heterogeneity model, by contrast, suggests that the likelihood of a behavior occurring is predetermined, and uninfluenced by intervening occurrences. We have applied the random-effects probit model of Gibbons and Bock (1987) to examine the fit of the state dependence and heterogeneity models to longitudinal data on suicide attempts by 928 patients with affective disorder. Heterogeneity but not state dependence was required to model these data. The findings suggest that when considering patients with moderate to severe major affective disorder, the clinician should not interpret the absence of any recent suicide attempts to mean that the patient is at relatively low risk for attempting suicide in the future. An implication of the heterogeneity model is that suicide attempts made many years ago may have equal value to recent attempts when estimating an individual's "predisposition" to nonlethal attempts in the future.

Random utility models with binary tree decomposable rank orders satisfy Tversky's elimination-by-aspects model