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To cope with the complexity of modern retail stores and personal time constraints, shoppers must be selective in processing information. During a typical shopping trip, they visit only a fraction of a store’s departments and categories, examine a small subset of the available products, and often make selections in just a few seconds. New research techniques can help marketers understand how customers allocate their attention and assess the impact of in-store factors on shopper behavior. This chapter summarizes studies using observational research, virtual reality simulations, and eye tracking to identify the drivers of shopper attention, product engagement, and purchase conversion. These include shopper goals; product assortment, package appearance, price, and merchandising; shelf space allocation, organization, and adjacencies; and salesperson interaction. The research reveals that small changes in a product’s appearance and presentation can have a powerful impact on consideration and choice.

Although organizational citizenship behavior (OCB) is widely known to have a positive ethical impact in work organizations, the causal antecedents that influence the likelihood of such behaviors among employees is understudied. We addressed this gap by examining the influence of visual images of people on relevant work-related behavior in a work-like setting using the theoretical frame of the social identity perspective. We found that students in a university setting, who were exposed to religious-themed student images, exhibited slower helping behaviors toward the organization than those who were exposed to organizational-themed student images. The results of the current study provide the first-known experimental confirmation of organizational identity as a causal antecedent of OCB.

This study explores how balanced scorecard format and reputation from environmental performances interact to influence performance evaluations.

Two general options exist for inserting environmental measures into a scorecard: embedded among the four traditional perspectives or grouped in a fifth perspective. Prior balanced scorecard research also assumes negative past environmental performances. In such settings, and when low management communication levels exist on the importance of environmental strategic objectives (a common practitioner scenario), environmental measures receive less decision weight when they are grouped in a fifth scorecard perspective. However, a positive environmental reputation would generate loss aversion concerns with reputation, leading to more decision weight given to environmental measures. Participants (N=138) evaluated performances with scorecards in an experimental design that manipulates scorecard format (four, five-perspectives) and past environmental performance operationalizing reputation (positive, negative).

The environmental reputation valence’s impact is more (less) pronounced when environmental measures are grouped (embedded) in a fifth perspective (among the four traditional perspectives), when the environmental feature of the measures is more (less) salient.

Findings provide the literature with original empirical results that support the popular, but often anecdotal, position of advocating a fifth perspective for environmental measures to help emphasize and promote environmental stewardship within an entity when common low management communication levels exist. Specifically, when positive past environmental performances exist, entities may choose to group environmental performance measures together in a fifth scorecard perspective without risking those measures receiving the discounted decision weight indicated in prior studies.

The growth of social media and the sharing economy is generating abundant unstructured image and video data. Computer vision techniques can derive rich insights from unstructured data and can inform recommendations for increasing profits and consumer utility – if only the model outputs are interpretable enough to earn the trust of consumers and buy-in from companies. To build a foundation for understanding the importance of model interpretation in image analytics, the first section of this article reviews the existing work along three dimensions: the data type (image data vs. video data), model structure (feature-level vs. pixel-level), and primary application (to increase company profits vs. to maximize consumer utility). The second section discusses how the “black box” of pixel-level models leads to legal and ethical problems, but interpretability can be improved with eXplainable Artificial Intelligence (XAI) methods. We classify and review XAI methods based on transparency, the scope of interpretability (global vs. local), and model specificity (model-specific vs. model-agnostic); in marketing research, transparent, local, and model-agnostic methods are most common. The third section proposes three promising future research directions related to model interpretability: the economic value of augmented reality in 3D product tracking and visualization, field experiments to compare human judgments with the outputs of machine vision systems, and XAI methods to test strategies for mitigating algorithmic bias.

Based on a synthesis of findings from psychology, neuroscience, and machine learning, we propose a unified theory of curiosity as a form of motivated cognition. Curiosity, we propose, is comprised of a family of mechanisms that range in complexity from simple heuristics based on novelty, salience, or surprise, to drives based on reward and uncertainty reduction and finally, to self-directed metacognitive processes. These mechanisms, we propose, have evolved to allow agents to discover useful regularities in the world – steering them toward niches of maximal learning progress and away from both random and highly familiar tasks. We emphasize that curiosity arises organically in conjunction with cognition and motivation, being generated by cognitive processes and in turn, motivating them. We hope that this view will spur the systematic study of curiosity as an integral aspect of cognition and decision making during development and adulthood.