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AbstractBy using scenarios based on moral dilemmas, Gill (2020) found that when consumers are riding in an autonomous vehicle (AV), they are more willing to harm a pedestrian than when they, themselves, are driving a regular car. By taking a first-person perspective, in contrast to most prior research that has taken a third-person perspective, the problem is framed in a personal way that allows identification of a mechanism of responsibility attribution. In this commentary, a generalized framework is developed in which we can locate the work of Gill (2020), as well as prior research that uses moral dilemmas, to understand how consumers believe that AVs should respond when faced with competing life-and-death alternatives. The framework shows the distinct positions that research to date has adopted, points out gaps in research, and suggests a family of four research agendas that can be pursued going forward, driven in large part by the perspective taken to the moral dilemma. Research employing these different perspectives, including the unresearched problem of taking the perspective of the object, holds promise for using moral dilemmas for enabling our understanding of consumer experience and consumer–object relationships with AVs.

Abstract
Up to now, IoT device adoption is happening mainly in the niche segments of technologically sophisticated upscale consumers and technology-focused DIYers. To reach a broader range of users, marketers must do a better job of understanding and offering the inherent value of smart products. Current marketing approaches are fragmented and tend to focus on individual products and single use cases. They may actually be underselling the consumer IoT. The mass-market consumer is not buying a platform or devices controlled by an algorithm, they are buying an experience. We need to ask, in what ways consumers and devices will interact with each other to create the experience they actually seek. Therefore, the main challenge is to implement a bottom-up approach that encourages users to experiment with their devices and their interactions and to integrate their individual experiences into everyday routines.

AbstractThe consumer Internet of Things (IoT) has the potential to revolutionize consumer experience. Because consumers can actively interact with smart objects, the traditional, human-centric conceptualization of consumer experience as consumers' internal subjective responses to branded objects may not be sufficient to conceptualize consumer experience in the IoT. Smart objects possess their own unique capacities and their own kinds of experiences in interaction with the consumer and each other. A conceptual framework based on assemblage theory and object-oriented ontology details how consumer experience and object experience emerge in the IoT. This conceptualization is anchored in the context of consumer-object assemblages, and defines consumer experience by its emergent properties, capacities, and agentic and communal roles expressed in interaction. Four specific consumer experience assemblages emerge: enabling experiences, comprising agentic self-extension and communal self-expansion, and constraining experiences, comprising agentic self-restriction and communal self-reduction. A parallel conceptualization of the construct of object experience argues that it can be accessed by consumers through object-oriented anthropomorphism, a nonhuman-centric approach to evaluating the expressive roles objects play in interaction. Directions for future research are derived, and consumer researchers are invited to join a dialogue about the important themes underlying our framework.

Abstract
We examine consumers' interactions with smart objects using a novel mixed-method approach, guided by assemblage theory, to discover the emergence of automation practices. We use a unique text data set from the web service IFTTT, ("If This Then That"), representing hundreds of thousands of applets that represent "if–then" connections between pairs of Internet services. Consumers use these applets to automate events in their daily lives. We quantitatively identify and qualitatively interpret automation assemblages that emerge bottom-up as different consumers create similar applets within unique social contexts. Our data discovery approach combines word embeddings, density-based clustering, and nonlinear dimensionality reduction with an inductive approach to the thematic analysis. We uncover 127 nested automation assemblages that correspond to automation practices. Practices are interpreted in terms of four higher-order categories: social expression, social connectedness, extended mind, and relational AI. To investigate the future trajectories of automation practices, we use the concept of the possibility space, a fundamental theoretical idea from assemblage theory. Using our empirical approach, we translate this theoretical possibility space of automation assemblages into a data visualization to predict how existing practices can grow and new practices can emerge. Our new approach makes conceptual, methodological, and empirical contributions with implications for consumer research and marketing strategy.

Much of Alzheimer disease (AD) research has been traditionally based on the use of animals, which have been extensively applied in an effort to both improve our understanding of the pathophysiological mechanisms of the disease and to test novel therapeutic approaches. However, decades of such research have not effectively translated into substantial therapeutic success for human patients. Here we critically discuss these issues in order to determine how existing human-based methods can be applied to study AD pathology and develop novel therapeutics. These methods, which include patient-derived cells, computational analysis and models, together with large-scale epidemiological studies represent novel and exciting tools to enhance and forward AD research. In particular, these methods are helping advance AD research by contributing multifactorial and multidimensional perspectives, especially considering the crucial role played by lifestyle risk factors in the determination of AD risk. In addition to research techniques, we also consider related pitfalls and flaws in the current research funding system. Conversely, we identify encouraging new trends in research and government policy. In light of these new research directions, we provide recommendations regarding prioritization of research funding. The goal of this document is to stimulate scientific and public discussion on the need to explore new avenues in AD research, considering outcome and ethics as core principles to reliably judge traditional research efforts and eventually undertake new research strategies.