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But secondary reinforcers also play a central role in the relationship of individual conduct to biological fitness via economic choice. o perant behavior is therefore economic behavior in that it is the allocation of a limited number of responses among competing alternatives. This has become enshrined in definitions of rewards found in biology and neuroeconomics, which cast them as “stimuli for which an organism will work” (e.g., Rolls, 2008, pp. 118–119). Classically conditioned behavior is not economic behavior in this sense; it does not require behavior at all on the part of the organism and therefore there arises no conception that the organism is expending responses in order to obtain a biologically or socially relevant outcome. Both matching analysis and behavioral economics are, therefore, theories of behavior in general interpreted in economic terms. They lead to the conclusion that all behavior is choice and can be analyzed in economic terms: operant behavior is economic behavior. To the extent that we embrace this conclusion, there is no need for a separate subdiscipline of behavioral economics; behavioral economics would be, rather, a technique or methodology that can be applied to all behavior analytic research.

Consumer behavior analysis has a more restricted sphere of application—human economic and social choices that involve social exchange—and, if we are to address what is commonly understood as economic behavior, we must delineate the subject matter with some care. it is the understanding of exchange that is crucial to the definition of economic behavior in this more restricted sense. The ultimate maximand of operant/economic behavior is inclusive fitness; genetic influences determine that this is met by the establishment of certain goals represented by primary reinforcers, and by association, secondary reinforcers are established that have similar effects. Genes therefore determine the goals of behavior—reinforcers, rather than particular behaviors; specific appropriate instrumental behaviors are selected environmentally through the contingent availability of primary and secondary reinforcers. The Behavioral Perspective Model At the heart of consumer behavior analysis is the BPM (Foxall, 1990, 2010), which adapts the idea of the contingencies of reinforcement and punishment to accommodate research into the nature of human consumers’ economic and social choices (Figure 1). Behavior Setting Scope Closed Open Accomplishment CC2 CC1 Fulfillment Status consumption Hedonism CC4 CC3 Inescapable entertainment Popular entertainment Accumulation CC6 CC5 Token-based consumption Saving and collecting Maintenance CC8 CC7 Mandatory consumption Routine purchasing Utilitarian Reinforcment Informational Reinforcement Utilitarian Punishment Informational Punishment Consumer Behavior Setting Learning History Consumer Situation Consumer Situation Behavior High utilitarian reinforcement Low utilitarian reinforcement High informational reinforcement AccomplishmentAccumulation Low informational reinforcement HedonismMaintenance Figure 1. Summative Behavioral Perspective Model.

FOXALL AND SIGURDSSON 233 The antecedent events that set the occasion for consumer behavior compose the consumer behavior setting. This consists of all the physical (including temporal) and social (including verbal) discriminative stimuli and motivating operations that signal and enhance the likely outcomes of behaving in a particular way. Behavior settings facilitate or inhibit consumer movement and choice and form a continuum from the most open (where numerous behavioral options are available to the consumer and positive reinforcement predominates) to the most closed (where few behaviors, perhaps only a single response, are available and negative reinforcement is prevalent). The consumer’s learning history is the cumulative effect of rewarding and punishing outcomes of past consumer choice. Consumer behavior is shaped by three broadly defined consequences. utilitarian reinforcement derives from the satisfaction produced by buying, owning, and consuming economic goods. i nformational reinforcement is provided by feedback on the consumer’s performance, especially the social status produced by conspicuous consumption. Finally, aversive consequences are the costs of consuming: relinquishing money, waiting in line, forgoing alternative products, and so forth. Four operant classes of consumer behavior are defined based on the pattern of high/low utilitarian and informational reinforcement that maintains them (Figure 2). Behavior Setting Scope Closed Open Accomplishment CC2 CC1 Fulfillment Status consumption Hedonism CC4 CC3 Inescapable entertainment Popular entertainment Accumulation CC6 CC5 Token-based consumption Saving and collecting Maintenance CC8 CC7 Mandatory consumption Routine purchasing Utilitarian Reinforcment Informational Reinforcement Utilitarian Punishment Informational Punishment Consumer Behavior Setting Learning History Consumer Situation Consumer SituationBehavior High utilitarian reinforcement Low utilitarian reinforcement High informational reinforcement AccomplishmentAccumulation Low informational reinforcement HedonismMaintenance Figure 2. Operant classes of consumer behavior. Maintenance consists of activities necessary for the consumer’s physical survival and welfare (e.g., food) and the fulfillment of the minimal obligations entailed in membership of a social system (e.g., paying taxes). Accumulation includes the consumer behaviors involved in certain kinds of saving, collecting, and installment buying. Pleasure includes such activities as the consumption of popular entertainment. Finally, accomplishment is consumer behavior reflecting social and economic achievement: acquisition and conspicuous consumption of status goods and displaying products and services that signal personal attainment. Both types of reinforcers figure in the maintenance of each of the four classes, though to differing extents. Adding in the scope of the current behavior setting leads to the eightfold classification depicted in Figure 3, which shows the variety of contingency categories that exclusively constitute a functional analysis of consumer behavior. Behavior Setting Scope Closed Open Accomplishment CC2 CC1 Fulfillment Status consumption Hedonism CC4 CC3 Inescapable entertainment Popular entertainment Accumulation CC6 CC5 Token-based consumption Saving and collecting Maintenance CC8 CC7 Mandatory consumption Routine purchasing Utilitarian Reinforcment Informational Reinforcement Utilitarian Punishment Informational Punishment Consumer Behavior Setting Learning History Consumer Situation Consumer SituationBehavior High utilitarian reinforcement Low utilitarian reinforcement High informational reinforcement AccomplishmentAccumulation Low informational reinforcement HedonismMaintenance Figure 3. The Behavioral Perspective Model contingency matrix. Note. CC = contingency category.

1. The Analysis of Product and Brand Preference The first four papers in the special issue are concerned with consumers’ selection of products and brands within an array of items available to them and are all concerned in varying degrees with the suitability of the BPM as a means of conceptualizing consumer INTRODUCTION 234 choice in operant terms. The first paper by Victoria K. Wells and Gordon R. Foxall, “Matching, demand, Maximization, and Consumer Choice,” embraces perennial concerns in the quantitative analysis of behavior with the implications of matching and maximization (Commons, hernstein, & Rachlin, 1982), but it does so in the naturally occurring environments of human consumer choice and with a rather different import.

To some behavioral economists, a division of labor is suggested by the fact that matching has generally been the province of psychologists rather than economists. But there is good reason to include matching analysis in behavioral economics. A theoretical treatment of the apparent compatibility of matching analyses and studies of consumer brand choice (Foxall, 1999a) concludes that matching is appropriate to the study of human choice as economic behavior through its capacity to represent patterns of mutual reinforcement by identifying not only what acts as a reinforcer but also how this reinforcer is valued by the participants in an exchange. Matching analysis depicts human exchange in terms of mutual reinforcement (between marketer and consumer) and, through the inclusion of informational reinforcement, can incorporate socially enforceable transfer of property rights as a consequence of transacting. More importantly, it provides measures of economic variables such as degrees of substitutability, complementarity, and independence, which provide means of defining brands, product categories, and product subcategories (Foxall, James, Chang, & oliveira- Castro, 2010; Foxall, James, o liveira- Castro, & Ribier, 2010). in the second paper in this section, “ individual differences in Consumer Buying Patterns: A Behavioral Economic Analysis,” Paulo R. Cavalcanti and colleagues identify several stable regularities in buying behavior and differences between individuals. They form an underlying framework for personalized marketing and segmentation and integrate this research literature into the BPM. Valdimar Sigurdsson and colleagues, in “An Econometric Examination of the Behavioral Perspective Model in the Context of Norwegian Retailing,” report evidence for the role of informational reinforcement in consumer choice. This variable emerges as the single most important influence on consumer preference, but the strongest predictor of consumer behavior is the combination of utilitarian and information reinforcement and price proposed by the model. These papers embody a methodological shift from the experimental analysis of behavior, which is particularly necessary in the realm of behavior analysis in natural settings: i t uses aggregate panel data or databanks from retailers. The last paper in this section employs the more usual experimental method albeit in the form of a field experiment in an online environment. Based on a recent study of consumer choice in an e- retailing environment, Sigurdsson and colleagues, in “A Test of the Behavioral Perspective Model in the Context of an E- mail Marketing Experiment,” report a distinction in the roles of utilitarian and informational reinforcement: Although the former is more closely related to buying behavior, the latter is more instrumental in effecting the opening of e- mails in the first place.

2. Contextual Influences on Consumer Behavior The papers in this section take consumer behavior analysis beyond the confines of product and brand choice simpliciter. in “Gambling in the Public Marketplace: Adaptations to Economic Context,” Charles A. lyons examines gambling behavior in light of the vicissitudes of economic and political turbulence. Consumer behavior can be conceptualized along a continuum from that which is maximally under the self- control of the individual (e.g., adhering to self- generated rules based on learning history) to that which is maximally impulsive (Foxall, 2010; Foxall & Sigurdsson, 2011). The range of behaviors stretches from everyday brand choice, much like those covered in the papers in the opening section of this issue, through credit sales and environmental despoliation to compulsive buying and extreme addiction, from buying small quantities that cover one’s FOXALL AND SIGURDSSON 235 immediate needs to wanting it all, and now! Asle Fagerstrøm and donald A. hantula, in “Buy it Now and Pay for it l ater: An Experimental Study of Consumer Credit use,” building on the hyperbolic discounted utility model, seek to expand the behavior analytical understanding of credit card use. h yperbolic discounting is the tendency for people to increasingly choose a smaller- sooner reward (showing an impulse) over a larger- later reward, as the delay occurs sooner rather than later in time. Fagerstrøm and hantula conducted a simulated shopping experiment, and the overall results revealed tendencies to show hyperbolic discounting as the participants were willing to pay a high interest charge (nearly 40%) rather than waiting to save money and purchase a phone interest- free. This paper shows the real and applied nature of consumer behavior analysis as researchers study a wide range of economic topics in which the main focus is the contingencies that influence the behavior of the economic agent. The BPM is often summarized as an elaboration of the three- term contingency applied to the context of economic behavior. in fact, it embraces multi- term contingencies and, in particular, the role of motivating operations in the enhancement of behavior– reinforcer relationships. The paper entitled “ on Motivating o perations at the Point of online Purchase Setting,” by Asle Fagerstrøm and Erik Arntzen, provides an overview of this work on the impact on motivating operations at the point of online purchase situation. The fourth paper in this section, by Rafael Barreiros Porto and Jorge M. oliveira- Castro, is titled “Say– do Correspondence in Brand Choice: interaction Effects of Past and Current Contingencies.” it handles the interaction effects between current and past contingencies. unlike the seemingly popular view that customers are nothing more than marionettes, where consumer behavior is prompted by the current environment, this paper reminds us that generally the relevant environment is yesterday’s. This article examines possible relations between what consumers say about the brands they bought last and they intend to buy, which is a way of measuring part of their learning history with brands, and their actual purchases, taking into account the programmed reinforcement contingencies (marketing strategies) at the point of sale. Results showed, in general, that current and past contingencies interact and have different impacts on say–do correspondence, which can be explained by the BPM. According to the authors, behavior prediction can be enhanced if the effects of brands that consumers “bring” to the shopping environment are combined to brand- related strategies present in the retailing environment. This research provides interesting findings to the consumer behavior analytical literature and an efficient methodology, taking into account past contingencies, when using in- store experiments to test the influences of behavioral contingencies predicted by the BPM.

The last paper, “Consumer Behavior Analysis of Fair Trade Coffee: Evidence From Field Research,” written by Jeanine P. Stratton and Matt J. Werner reveals the results from their in- store field study where they examined consumer purchase behavior of Fair Trade–labeled coffee in a coffee shop. This study continues the recent upsurge of in- store experimentation where researchers work on the functional relationships between factors within the marketing mix (e.g., promotions, placements, pricing) and consumer behavior at the point of purchase, or PoP, as it often called (Sigurdsson, Engilbertsson, & Foxall, 2010; Sigurdsson, Foxall, & Saevarsson, 2010; Sigurdsson, larsen, & Gunnarsson, 2011a, 2001b; Sigurdsson, Saevarsson, & Foxall, 2009). This research has dealt with applications to problematic consumer behaviors of social interest, as promoted by Baer, Wolf, and Risley (1968) in their influential paper. The current paper is no exception to this. The study assessed the impact of two experimental conditions, low- and high- information P oP label conditions promoting Fair Trade coffee availability, and the service time. The finding suggested consumer preference for Fair Trade over non– Fair Trade coffee types across all conditions. Coffee shops could use similar P oP advertisements to promote their sales, provided price is similar between Fair Trade and non–Fair Trade coffee selections.

INTRODUCTION 236 3. Beyond Consumer Choice: The Behavior of the Firm A major deficiency in economic psychology and marketing science is the lack of a common framework in which to discuss the behavior of consumers and the behavior of firms. The BPM suggests an obvious extension to the corporate field (Foxall, 1999b), which seeks to interpret business conduct as operant responses that are shaped by the known reactions of consumers. Marketing activity is thus understood in terms of the attempt to reduce the scope of the consumer behavior setting and to influence consumer choice through the judicious management of the pattern of reinforcement contingent upon purchase and consumption (Vella & Foxall, 2011). Kevin J. Vella and Gordon R.

Foxall, in “The Marketing Firm: operant interpretation of Corporate Behavior,” used data from the reports of the united Kingdom Competition Commission to examine this interpretation. The collective aim of the papers introduced is to enlarge the capacity of behavior analysis to elucidate human activity in natural settings, with the aim of demonstrating that a behaviorist understanding can be provided for human economic behavior, and furthermore that behavior analysis can be used to modify consumer behavior. We have therefore argued for consumer behavior analysis as an integral component of applied behavior analysis. The unifying framework for this research is the BPM, which has formed the basis of the exploration of behavioral economics in consumer behavior analysis. References BAER , d. M., Wol F, M. M., & Ri Sl Ey, T. R. (1968). Some current dimensions of applied behavior analysis. Journal of Applied Behavior Analysis, 1, 9 1 – 9 7. Co MM oNS , M. l ., hERRNSTE iN , R. J., & R AChli N, h . (Ed S.). (1982). Quantitative analyses of behavior: Vol 2. Matching and maximizing accounts. Cambridge, u K: Ballinger. FoxAll, G. R. (1990). Consumer psychology in behavioral perspective. l ondon, uK:

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New y ork, Ny: Routledge. Fox All, G. R., J AMES, V. K., Ch ANG, J., & o liVE iRA - C ASTR o, J. M. (2010). Substitutability and complementarity: Matching analyses of brands and products. Journal of Organizational Behavior Management, 30, 14 5 –16 0. FoxAll, G. R., J AMES, V. K., o liVE iRA - C ASTR o, J. M., & Ri BiER , S. (2010). Product substitutability and the matching law. The Psychological Record, 60, 185 –216. FoxAll, G. R., & Si Gu Rd SS oN, V. (2011). d rug use as consumer behavior. Behavioral and Brain Sciences, 35, 313 –314. RollS, E. T. (2008). Memory, attention, and decision- making. oxford, u K: oxford u niversity Press. Si Gu Rd SS oN, V., E NGilBERTSS oN, h ., & Fox All, G. (2010). The effects of a point- of- purchase display on relative sales: An in- store experimental evaluation. Journal of Organizational Behavior Management, 30, 222–233.

FOXALL AND SIGURDSSON 237 SiGu Rd SS oN, V., Fox All, G., & S AEVARSSoN, h . (2010). i n- store experimental approach to pricing and consumer behavior. Journal of Organizational Behavior Management, 30, 234 –246. SiGu Rd SS oN, V., lARSEN , N. M., & Gu NNARSSoN, d . (2011a). An in- store experimental analysis of consumers’ selection of fruits and vegetables. The Service Industries Journal, 31, 2587–2602. Si Gu Rd SS oN, V., lARSEN , N. M., & Gu NNARSSoN, d . (2011b). The behavioural economics of neutral and upward sloping demand curves in retailing. The Service Industries Journal, 31, 2543 –2558. Si Gu Rd SS oN, V., S AEVARSS oN, h ., & Fox All, G. (2009). Brand- placement and consumer choice: An in- store experiment. Journal of Applied Behavior Analysis, 42, 741–74 4 . STA ddo N, J. E. R. (1980). Limits to action, the allocation of individual behavior. New y ork, N y: Academic Press. V Ell A, K. J., & Fox All, G. R. (2011). The marketing firm: Economic psychology of corporate behaviour. Cheltenham, u K: Edward Elgar Publishing limited.

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