ObjectiveThis study aims to explore the perceived dependence on Generative Artificial Intelligence (GenAI) tools among young adults and examine the relative reinforcing value of AI chatbots use compared to monetary rewards, applying a behavioral economics approach.Participants/methodsA total of 420 university students from Bogotá, Colombia, participated in an online survey. The study employed a Multiple Choice Procedure (MCP) to assess the relative reinforcement between different durations of GenAI use (1, 2, and 4 weeks) and monetary rewards, which varied in amount and delay. Additionally, an adapted AI Dependence Scale evaluated levels of dependence on AI tools. Data analysis included repeated measures ANOVA to examine the effects of reward magnitude and delay on choices, and correlations to assess the relationship between perceived dependence and reinforcement values.ResultsParticipants reported low average dependence on AI tools (mean AI Dependence Scale score = 65.6), with no significant gender differences. MCP findings indicated significant differences in crossover points across varying durations or delays for AI chatbots use, suggesting a higher relative value of use for the option to use AI chatbots immediately. The average reinforcement value for AI use versus monetary rewards did significantly vary with reward magnitude. On the other hand, significant differences were found in the levels of perceived dependence on AI, according to the average daily time of AI tool use.ConclusionThe results suggest that young adults exhibit low perceived dependence on GenAI tools but show differential reinforcement values based on usage duration or delay conditions. This behavioral economics approach provides novel insights into decision-making patterns related to AI chatbots use, emphasizing the need for further research to understand the psychological and social factors influencing dependence on AI technologies.

Understanding consumer heterogeneity is crucial for analysing attitude formation and its role in innovation diffusion. Traditional top-down models struggle to reflect the nuanced characteristics and activities of the consumer population, while bottom-up approaches like agent-based modelling (ABM) offer the ability to simulate individual decision-making in social networks. However, current ABM applications often lack a strong theoretical foundation. This study introduces a novel, theory-driven ABM framework to examine the heterogeneity of consumer attitude formation, focusing on electric vehicle (EV) adoption across consumer segments. The model incorporates non-linear decision-making rules grounded in established consumer theories, incorporating Rogers’s Diffusion of Innovations, Social Influence Theory, and Theory of Planned Behaviour. The consumer agents are characterised using UK empirical data, and are segmented into early adopters, early majority, late majority, and laggards. Social interactions and attitude formation are simulated, micro-validated, and optimised using supervised machine learning (SML) approaches. The results reveal that early adopters and early majority are highly responsive to social influences, environmental beliefs, and external events such as the pandemic and the war conflict in performing pro-EV attitudes. In contrast, late majority and laggards show more stable or delayed responses. These findings provide actionable insights for targeting segments to enhance EV adoption strategies.

Accepted by: Prof. Aris SyntetosUnderstanding consumer attitudes towards electric vehicle (EV) purchasing is essential for addressing the slow adoption rate. Traditional aggregated models of EV adoption employ a top-down approach, yet often fail to capture individual-level attitudes. In contrast, agent-based modelling (ABM) enables a bottom-up approach that reflects the heterogeneity in consumer decision-making and simulates social interactions. This study introduces an integrated model to analyze consumer attitudes towards EV adoption, incorporating empirical data and synthesized social interactions through ABM. The model undergoes micro-validation and optimization through parameter variation experiments and supervised machine learning (SML) methods. Results indicate that consumer attitudes towards EV purchasing are positively influenced by early adopters and environmental factors. These attitudes are further shaped by observing EVs in residential areas and receiving positive feedback from social circles. Perceptions of EVs as an environmentally friendly alternative also significantly enhance these attitudes. These findings suggest that marketers should develop targeted strategies for specific consumer segments, and policymakers should prioritize environmental awareness campaigns to drive positive public EV attitudes in the UK. This study emphasizes the importance of incorporating consumer heterogeneity and social interactions in attitude formation, which offers insights into EV promotion within Rogers's Diffusion of Innovations Theory.

Purpose - Consumer perception of corporate brand equity has primarily focused on product brand dimensions, neglecting considerations at the firm analysis level. Assessing corporate brands requires different criteria relevant to the competitiveness of companies, such as their prominence, management and meeting society's demands. In this sense, this study aims to develop and validate a scale of corporate brand equity founded on consumer perceptions, transcending industry boundaries and comparing its relationship with companies' market share. Design/methodology/approach - The authors used an integrative approach to clarify the construct's domain, building on previous measures. They took several steps to select appropriate items, refine the measure, validate it through reliability tests and convergent and discriminant analyses, test the validity of the second-order formative structure of corporate brand equity and assess associations between first-order factors, the second-order factor and market share. Findings - The model identifies three first-order dimensions of corporate brands (presence, outstanding management and responsible) that shape the second-order factor (corporate brand equity). They are directly related, but not proportionally, to market share, contributing to the general and joint assessment of the company's competitive performance considering the consumer. Originality/value - To the best of the authors' knowledge, this study is the first attempt to develop a comprehensive measurement model of corporate brand equity that considers the firm level of analysis, combines metrics from previous research on corporate brand evaluation criteria and includes consumer perceptions of the company's competitiveness, unifying branding theory with the theory of the marketing firm.

Human consumption is multi- faceted and so requires inter- disciplinary exploration in order to explain a spectrum of experiences that is at once particular and allpervading. Consumer choice is a microcosm of human activity which transcends the purview of the archetypal marketing or consumer psychology textbook. Its perspective is that of social science itself. This book understands the study of consumer choice as a paradigm of human socio- economic activity and seeks further understanding of its socio- economic and philosophical bases. The Continuum of Consumer Choice provides a novel view of consumer choice based on the temporal horizon of the consumer, giving rise to a spectrum of consumption styles from the everyday to the extreme. The focus is on explaining this continuum in behavioral, cognitive, and neurophysiological terms, affording the reader a unique perspective on the intellectual basis of consumer psychology and marketing. The reader gains insight into a critical combination of economic psychology, neurophysiology, and philosophy, which contributes to establishing marketing and consumer research as scholarly academic pursuits. The book's particular focus is the proper place and form of an intentional (cognitive and perceptual) explanation of consumer choice. This is an essential monograph for advanced students in consumer psychology and marketing as well as for researchers in these areas. It is particularly relevant to marketing and consumer theory, providing appreciation of their scholarly foundations. It also appeals to students, lecturers, and researchers in social science generally who are alert to the intellectual potential of consumer psychology and marketing as contributors to a full understanding of human behavior and experience.

Investigating consumer attitudes towards electric vehicle (EV) purchasing is crucial for understanding their slow adoption rate. Traditional aggregated models evaluate EV market penetration with a top-down approach but fail to reflect individual attitudes. Agent-based modelling (ABM) captures consumer heterogeneous decision-making and simulates social interactions in a bottom-up approach. Our work represents a novel integrated model to study consumers’ attitudes towards EV adoption, using empirical data and synthesised social interactions with ABM. The developed model was micro-validated and optimised using parameter variation experiments and supervised machine learning (SML) methods. The results show that consumers’ attitudes towards EV purchasing are influenced by early adopters and environmental factors. This work concludes that capturing consumers’ heterogeneity plays an important role in investigating their attitude formation under social interactions, providing new insights into EV promotion as an application of Rogers’s Diffusion of Innovations Theory at an early stage.

The neuropsychology of food consumption is a vast subject. This chapter concentrates on how value is established at the neurophysiological level and how it is related to behaviour. This is especially pertinent to the analysis of consumer choice, which refers here to being faced with two or more options, each of which has its own set of short and long term consequences that are in conflict with one another. Situations of choice arise principally when the expected outcomes of purchasing one commodity are relatively immediate, while those of a competing purchase are delayed, e.g., the taste reward of consuming a hyper-palatable food now as opposed to a healthier life enjoyed in the longer term.

Cognitive explanations raise epistemological problems not faced by accounts confined to observable variables. Many explanatory components of cognitive models are unobservable: beliefs, attitudes, and intentions, for instance, must be made empirically available to the researcher in the form of measures of observable behavior from which the latent variables are inferred. The explanatory variables are abstract and theoretical and rely, if they are to enter investigations and explanations, on reasoned agreement on how they can be captured by proxy variables derived from what people say and how they behave. Psychometrics must be founded upon a firm, intersubjective agreement among researchers and users of research on the relationship of behavioral measures to the intentional constructs to which they point and the latent variables they seek to operationalize. Only if these considerations are adequately addressed can we arrive at consistent interpretations of the data. This problem provides the substance of the intentional behaviorist research programme which seeks to provide a rationale for the cognitive explanation. Within this programme, two versions of the Behavioral Perspective Model (BPM), an extensional portrayal of socioeconomic behavior and a corresponding intentional approach, address the task of identifying where intentional explanation becomes necessary and the form it should take. This study explores a third version, based on neurophysiological substrates of consumer choice as a contributor to this task. The nature of "value" is closely related to the rationale for a neurophysiological model of consumer choice. The variables involved are operationally specified and measured with high intersubjective agreement. The intentional model (BPM-I), depicting consumer action in terms of mental processes such as perception, deliberation, and choice, extends the purview of the BPM to new situations and areas of explanation.

Objective This study provides a first approach to the use of the Multiple-Choice Procedure in social media networks use, as well as empirical evidence for the application of the Behavioral Perspective Model to digital consumption behavior in young users in conjunction with a methodology based on behavioral economics. Participants/methods The participants were part of a large university in Bogotá, Colombia, and they received an academic credit once they completed the online questionnaire. A total of 311 participants completed the experiment. Of the participants, 49% were men with a mean age of 20.6 years (SD = 3.10, Range = 15–30); 51% were women with a mean age of 20.2 years (SD = 2.84, Range = 15–29). Results Among the total participants, 40% reported that they used social networks between 1 and 2 h a day, 38% between 2 and 3 h, 16% for 4 h or more, and the remaining 9% used them for 1 h or less per day. The factorial analysis of variance (ANOVA) allowed us to identify a statistically significant effect of the delay of the alternative reinforcer, that is, the average crossover points were higher when the monetary reinforcer was delayed 1 week, compared to the immediate delivery of the monetary reinforcer. There was no statistically significant effect of the interaction between the magnitude of the reinforcer and the delay time of the alternative reinforcer. Conclusions This study supports the relative reinforcing value of an informational reinforcement consequence such as social media use, which is sensitive to both the magnitude of reinforcement and the delay in delivery as individual factors. The findings on reinforcer magnitude and delay effects are consistent with previous research that have applied behavioral economics to the study of non-substance-related addictions.