Behavioural loyalty towards store brands

This paper applies a consumer brand choice model to measure store brand (SB) loyalty. The aim of this paper is to examine whether SB loyalty is different across categories, and we focus on risk perception as an explanatory variable. The model is estimated using ACNielsen Spanish household scanner panel data on two laundry detergent categories over a 2-year period for more than 1107 households. Loyalty, price, socio-demographics and shopping behaviour variables are included. The discrete-choice model formulation is the logit model.     

Consumer adoption of No Junk Mail stickers: An extended planned behavior model assessing the respective role of store flyer attachment and perceived intrusiveness

Although store flyers play a crucial role in retailer communication, their environmental burden has raised a public debate, fostering No Junk Mail sticker adoption by a growing number of households. This study proposes and tests a planned behavior model of consumer intentions towards adopting a sticker that extends to the sticker adoption alternative (i.e., receiving store flyers) by introducing store flyer attachment and perceived intrusiveness as two potential intent determinants. While confirming the relevance of the extended model, the findings support a typology of store flyer consumers that enlighten retailers on possible shifts in their audience.     

A nested logit model of brand choice incorporating variety-seeking and marketing-mix variables

We model the effects of variety-seeking and marketing-mix variables on consumers' purchases of coffee using a nested logit model. We premise that on any given purchase occasion, the utilities of brands other than the one purchased on the previous occasion may be correlated due to the consumer's tendency to seek variety or to avoid variety. This results in a two-level hierarchical model where choice on any purchase occasion is conditioned on the brand purchased on the immediately preceding occasion. Such a structure accounts for variety seeking and inertia tendencies of consumers and is consistent with a hierarchical decision process, where consumers first decide whether or not to make a repeat purchase and then decide which brand size to purchase. The assumed hierarchical structure is shown to be consistent with observed coffee purchase behavior, and the model is shown to outperform a nonhierarchical logit model in predicting consumers' brand choices.     

Overcoming data limitations for store choice modelling.: Exploiting retail chain choice data by means of aggregate logit models

This paper reports on research aimed at exploiting certain data sources for store choice modelling purposes. Many databases, such as some consumer panels, only record the firm chosen by consumers and not the specific store at which they shop. Four alternative approaches are proposed in order to use this raw information for studying patronage determinants at store level: (a) an ordinary logit model in which chain utility is averaged across stores within; (b) an ordinary logit model in which the choice set is assumed to be composed of the nearest store for each chain; (c) a straightforward application of an aggregate logit model; and (d) the application of an aggregate logit model with choice sets spatially bounded by a distance threshold representing the maximum distance that consumers are willing to travel for shopping. The models are empirically tested in the context of spatial choice behaviour. Goodness of fit indicators reveal that only models (b), (c) and (d) acceptably represent competitive interaction dynamics. As performance of (b) is slightly better than that of (c), it seems that a priori the ‘nearest store assumption’ is a better approach than the modelling of aggregate choice structures. However, when the latter approach is applied with more reliable choice sets, as suggested in model (d), the best performance is achieved. The results thus lead us to think that the aggregate logit model is a promising methodology for solving the problem at issue, but subject to an appropriate definition of the consumers’ choice sets. In fact, such an approach provides a more suitable modelling solution to the extent that the saturation and the intra-firm store heterogeneity become more intense, because these situations presumably imply that consideration sets include several stores from the same chain.     

Dynamic assortment in the presence of brand heterogeneity

In this paper, we study the dynamic assortment planning problem in the presence of heterogeneous brands. Over a limited selling season, the retailer sells heterogeneous products from one store brand and one national brand. We use the nested multinomial logit (NMNL) framework to model consumer choice process, in which consumers choose first which brand to buy and then a product within that brand. We formulate this problem using the finite-horizon dynamic programming approach. Using available sales transaction data, we estimate the consumer choice behavior and empirically demonstrate existence of brand heterogeneity. Further, our results suggest that ignoring brand heterogeneity will make the retailer’s expected revenues significantly overestimated, and the potential revenue overestimation depends on initial inventories and prices of products of two brands. We finally show that the retailer will benefit from dynamic assortment optimization with the estimated consumer choice model.     

The effects of in-store themed events on consumer store choice decisions

Retailers are increasingly using in-store events to provide shoppers with unique experiences that will enhance shopping value and help differentiate their stores from competitors. However, relatively little is known about how consumers respond to experiential retail events in terms of their store choice decisions. The purpose of this research was to find out how in-store retail events affect consumers in terms of their store choice decisions. The paper presents findings from a discrete choice experiment that manipulated the presence of different types of in-store themed events in a do-it-yourself (DIY) category. Participants were 312 randomly recruited residents of Melbourne, Australia, who had recently shopped at a hardware store. The experiment was implemented as a mail-back survey. Using logit models the authors assess the effects of the in-store events along with those of various traditional store attributes, including store appearance, price image and distance, on consumer store choice decisions.     

Ethical consumption behaviours in supermarket shoppers: determinants and marketing implications

Understanding how consumers make ethical purchases has numerous benefits for firms and other stakeholders. Although several ethical decision-making frameworks seek to explain such purchasing behaviour, they typically focus on the content of such decisions, rather than considering how such decisions unfold in a given context. Yet, the complexities of consumer choice suggest that greater insight into how consumers make ethical purchases in store can enhance understanding. We report our findings from a survey of a geographically disperse sample of 688 UK shoppers and argue that a naturalistic theory of decision making, image theory, enhances our ability to explain consumer behaviour in this setting. As well as contributing to theoretical understanding of consumer choice, this has implications for the merchandising of ethical products, such as Fair Trade and ‘green’ goods.     

The covariates of regularity in purchase timing

An examination of the timing of consumers' purchases for coffee reveals that consumers vary a great deal in terms of the regularity of their purchasing behavior. Some consumers make purchases at seemingly random time intervals, while others purchase at highly regular intervals. The measurement of regularity in purchase timing, as well as the identification of its covariates, is important in many contexts such as modeling purchase incidence and sales forecasting. We measure the degree of regularity among a sample of coffee purchasers and identify several consumer characteristics that vary with the degree of regularity in purchase timing. Results show that regularity in purchase timing is related to brand loyalty, store loyalty and deal proneness, as well as to certain pattern of routinization by the households, and that regularity may be used, along with other aspects of purchase behavior, to provide a basis for market segmentation.The authors wish to acknowledge the support of Information Resources Inc. for providing the data, and are grateful to Professor Jane T. Landwehr, University of Delaware, for her help.     

Understanding Supermarket Competition Using Choice Maps

In this paper we propose a model which combines the spatial interaction models with the latest developments in internal market structure analysis and allows us to infer supermarket competition from revealed preference data. Using a nested logit formulation we model consumers' store choice decisions to be a two stage process in which consumers choose first the suburb and then the store from which to buy groceries. Hence, our method allows retail managers not only to understand the advantage (or disadvantage) of having their store chain in a particular area but also assess the competition within that area. Comparisons to Factor Analytic Choice Map is made.     

On consumer choice patterns and the net impact of feature promotions

Even in the digital age, feature promotions continue to receive significant investments from CPG manufacturers and retailers. Whether this is money well spent depends on consumers' (heterogeneous) tendency to switch brands or stores in response to features. This study proposes a ‘Mixed-pattern Random-effects Nested Logit’ (MRNL) model to analyse the effect of feature promotions in a multi-retailer multi-brand setting. Across 16 different CPG categories, our results reveal that in all cases a mixture of choice patterns prevails: about half of households exhibit a brand focus (i.e. rather substitute between stores offering that brand), the remaining half show evidence of a store focus (i.e. rather substitute brand offers within a visited store). We find that the size of the promotion lift and its underlying sources differ substantially between patterns. Brand-focused consumers are generally more responsive to feature ads than store-focused consumers – especially in low-concentration categories; while they imply much stronger cannibalization for the manufacturer, and much weaker cannibalization for the retailer. It follows that retailers reap much higher benefits in the brand-focused segment, while manufacturers may not prefer that segment in terms of net gains and must be wary of subsidizing those consumers. We identify household and category characteristics that underlie the choice patterns and offer opportunities for targeting.     

Re-thinking the relationship between store brand attitude and store brand loyalty: a simultaneous approach

Academic attention to the relationship between store brand attitude and store brand loyalty is insufficient. Our paper fills this research gap by proposing and testing a theoretical model that demonstrates a reciprocal and mutually-reinforcing relationship between store brand attitude and store brand loyalty. The literature review identifies independent variables as potential predictors of both characteristics. We apply a two stages least squares model to data that come from a survey of Spanish households. The findings corroborate some of the propositions of the conceptual model: the reciprocal relationship between the two dependent variables; the influence of risk, deal proneness, price and value consciousness and extrinsic and intrinsic cues on store brand attitude; and the influence of exploration, deal proneness, store loyalty, store brand trust and store brand affective commitment on store brand loyalty.     

Directing store flyers to the appropriate audience

Grocery shoppers were questioned about the frequency of purchasing items that were featured in the store's flyers. This measure was used as the dependent variable in a multinomial logit model with the independent variables being various aspects of shopping behaviour, usage of store flyers, age and employment status. Since only one threshold parameter was significant, the four-level dependent variable was then collapsed and a binary model was estimated. This study evidenced that less than half of the respondents looked forward to receiving unsolicited flyers. Most shoppers read the flyers only to be informed of price specials that the store has to offer. The odds ratio of responding to store flyer deals among those who look forward to sales flyers is more than double the odds ratio of those who do not await the flyers, across every category of shopping frequency. Retailers could employ direct marketing to target specific audiences who look forward to receiving store flyers.     

A simultaneous model of multiple-discrete choices of variety and quantity

In many categories, consumers purchase discrete quantities of multiple varieties. For example, when doing grocery shopping for cereals, consumers may purchase in each category three units of brand A, four of brand B, and one of brand C. These decisions are often influenced by nonlinear pricing strategies such as quantity discounts. Modeling such multiple-discrete choices is challenging, as they violate assumptions of standard choice models. In this research, the author introduces a computationally attractive choice model that simultaneously captures 1) variety, 2) discrete quantity, and 3) nonlinear pricing strategies, such as quantity discounts. The model assumes that consumers maximize variety of the choice outcome, while taking into account constraints on utilities of alternatives. Application of the proposed model to two datasets demonstrates the superior fit compared to several rival models. Counterfactual analyses demonstrate that the model is a valuable tool for assortment and pricing decisions.     

What Drives Household Choice of Organic Products in Grocery Stores?

This paper studies how households choose organic products on a given store visit. We develop a three-stage purchase incidence/brand choice/purchase quantity model for organic products. Shared random effects parameters link the three stages of the model. We empirically quantify the effects of category variables, marketing mix, and demographic variables on the purchase of organic products using a unique household panel dataset that includes actual organic purchase data from two markets, by over 4,500 households in 25 stores for the period between January 2004 and June 2009. First, we find that the purchase of organic products is greater among the high income, college educated, and older families as well as among consumers holding high-level occupations. Second, households tend not to purchase organic products when buying in concentrated categories. Third, on average, households tend to buy organic store brands more than the organic national brands. Promotions of organic brands (feature ad and display) are less likely to drive households to buy organic brands and so does the organic brand's distribution breadth. Finally, price has an inverted U-shaped effect. We discuss the implications of these results for retailers, manufacturers and researchers.     

INFLUENCE OF DEMOGRAPHIC FACTORS ON CONSUMER PURCHASING PATTERNS AND PREFERENCES FOR GROUND BEEF

A study of 198 household units in the Fort Collins, CO area was made to ascertain the importance of such factors as consumer age, income, education and marital status on the purchasing patterns for ground beef. Compared to younger consumers, older consumers tended to: (1) make more frequent purchases of ground beef; (2) buy less ground beef per purchase; and (3) select leaner ground beef. Households with gross incomes in excess of $25,000 tended to buy larger quantities of ground beef per purchase and bought leaner ground beef compared to households with less than $15,000 gross income. In making purchasing decisions, participants in the study considered leanness, visual appearance and price as the most important factors, while packaging and brand name were considered the least important factors.     

The Impact of Price Disclosure on Dynamic Shopping Decisions

A potentially powerful way to assist consumers in making dynamic shopping decisions is to disclose price information to them before they shop, for example by posting prices on the Internet. This paper addresses the differential impact of disclosing either only current, or both current and future prices, on consumer shopping decisions in multi-period tasks involving multiple product purchases. In the context of an Internet-based experiment, we find that consumer expenditure deviates more strongly from that of a normative model when both current and future prices are disclosed than if only current prices are disclosed. We investigate the behavioral effects underlying this finding by estimating a model that allows for variations in consumer discounting, strength of store price format preferences, as well as choice consistency between different price disclosure conditions.     

Going Online for Groceries: Drivers of Category-Level Share of Wallet Expansion

Some grocery product categories may be more successful than others in terms of stimulating consumers to increase their share of wallet (SoW) when they start buying through the online channel of a grocery chain. This study explores the circumstances in which online and multichannel marketing mix instruments determine the extent of category-level SoW expansion. To do so, the authors use U.K. household scanner panel data, covering online and offline purchases by 3,311 households in 59 categories of four multichannel retail chains. The results indicate that the effectiveness of online and multichannel marketing mix instruments for stimulating expansion is moderated by category characteristics, such that a selective approach to making decisions about the online price, online assortment breadth, online/offline assortment integration, and online national brand proliferation, tuned to account for category differences, can increase category-level SoW for the online-visited chain.     

Profiling the flyer-prone consumer

The purpose of this paper is to predict the differences between highly prone and less prone consumers to store flyers in terms of their sensitivity to economic, shopping-related and demographic variables. The empirical findings show that the flyer-prone consumer׳s profile somehow differs from the characteristics of consumers more prone to other types of promotion and to deals in general. The managerial implications underline that including a price-discount support is not essential if manufacturers and retailers wish to increase the probability of store flyers being consulted by a consumer. Nevertheless, the credibility of flyers depends on consumers’ perception of potential savings being maintained.     

Purchase frequency,sample selection,and price sensitivity: The heavy-user bias

We study the relationship between purchase frequency and volume and choice behavior as summarized by brand preferences and price sensitivity. Our most striking finding is that consumers with high purchase frequency or high purchase volume are much more price sensitive and have more sharply defined preferences for national brands than consumers with low frequency or low volume of purchase. In much of the choice literature, analysis is confined to households that have on average a larger number of purchases than is representative of the ERIM panel. Our findings suggest that some caution should be exercised in interpreting studies that employ purchase-frequency or purchase-number sample inclusion rules. Our findings also support an information theoretic point of view in which households become more price sensitive via costly acquisition of information about the distribution of prices.We acknowledge helpful comments from Greg Allenby and Bob Blattberg. Support from the Micro-Marketing Project at the Graduate School of Business at the University of Chicago is gratefully acknowledged. Byung-Do Kim is the corresponding author.