As brands increasingly engage in socially and environmentally responsible practices, understanding how consumers respond to these distinct forms of corporate responsibility becomes critically important. While prior research has examined the effects of social responsibility or environmental responsibility in isolation, little is known about whether and why consumers respond to them differently. The current research aims to fill this gap by comparing brands’ social initiatives focused on fair-trade practices to environmental initiatives focused on minimizing packaging waste. Three studies demonstrate that consumers respond more favorably to brands engaging in those socially (vs. environmentally) responsible actions and that perceived brand power is one meaningful driver of this effect via mediation and moderation. These findings add to the limited research investigating how brands’ social and environmental responsibility distinctively influences consumers’ brand evaluations, provide valuable managerial insights, and open avenues for future research.
From decadent desserts to sensual imagery, brands often generate visually indulgent content in the hope of motivating consumers to share (or repost) it on social media, thereby enhancing brand visibility. But is this strategy truly effective? An analysis of 98,081 social media images, complemented by controlled experiments, reveals that the impact of visual indulgence on sharing intention depends on brand luxury. For low-end mainstream brands, greater visual indulgence reduces sharing intention, primarily because consumers anticipate reputational costs (e.g., signaling undesirable personal traits) when sharing such content. However, as brand luxury increases, these reputational concerns diminish. For high-end luxury brands, visual indulgence increases sharing intention primarily by eliciting emotional arousal without triggering reputational concerns. Together, these findings contribute to research on indulgence, social media sharing, and luxury brand strategy.
The everyday lives of prominent CEOs have become increasingly visible through social and online media, yet little is known about how CEOs’ mundane consumption choices shape consumer brand evaluations. Addressing this gap, we draw on self-brand connection perspective to argue that CEOs’ everyday consumption behaviors function as symbolic cues that influence how perceived closeness consumers feel to the firm. We predict that consumption choices signaling equal treatment—where CEOs engage in the same consumption contexts as ordinary consumers—increase the self-brand closeness and, in turn, enhance brand attitudes. Two preregistered experiments provide consistent support for this framework across consumption contexts and product categories. This research contributes to the literature on CEO symbolic influence by identifying a complementary, value-neutral pathway through which routine CEO behaviors shape brand evaluations, and by clarifying how egalitarian cues affect consumer responses.
Given the widespread application of lexicon-based computer-aided text analysis (CATA), we present several overlooked issues in current research practice. We examine the implications of arbitrary lexicon selection and the improper use of difference scores (positive minus negative) to measure overall sentiment. We provide detailed guidelines to help researchers avoid empirical bias that can lead to inconsistent results in lexicon-based CATA. Specifically, we recommend assessing each lexicon’s ability to capture sentiment by comparing coverage rates and outline when the use of difference sentiment score is appropriate. We also show how lexicons serve as contextual anchors in the use of generative AI (GenAI) through few-shot prompting. Using consumer review data, we replicate prior research on perceived review usefulness across widely adopted lexicons to demonstrate our guidelines. Our findings highlight that arbitrary use of lexicons may produce biased and inconsistent results across lexicons, limiting generalizability, and support complementary use of GenAI and lexicons.
This paper examines three foundational modeling frameworks in marketing science (market response models, individual level choice models, and innovation diffusion models) and their role in empirical market research. Drawing on a retrospective synthesis of work originating from Frank Bass, we show that these frameworks continue to organize three core research issues: measurement of marketing effectiveness, stochastic modeling of individual choice, and new product adoption over time. Recent advances in artificial intelligence and machine learning, and expanded data availability and computational power, offer new modeling insights and opportunities. The paper discusses how the three structural marketing models remain relevant in this digital environment, evolving alongside modern computational tools while retaining their interpretability and decision-making power.
