Reseach Talks Personal Mobility Management & Innovation

From Cars to Car Sharing, from Meat to Less Meat: How Mainstream Consumers Shift Practices toward Sustainability

Mainstream consumers often express interest in “doing something” for sustainability, yet many sustainable consumption practices remain confined to niche audiences that accept moralization, friction, and infrastructural inconvenience. This research asks how environmentally improved consumption can become mainstream without requiring consumers to adopt identity-transforming lifestyles. Drawing on an interpretive qualitative research design, combining life-course interviews and Reddit netnography, we examine two empirically distinct yet structurally analogous domains: shifts from private car ownership to car sharing and shifts from meat-centered eating to flexitarian eating. We show that mainstream consumers rarely frame these shifts as moral conversions. Instead, they pursue change through continuity. We theorize this mode of change as practice anchoring: consumers actively keep a sustainable practice variant as close as possible to the conventional practice it adapts. Practice anchoring is accomplished through three interlinked processes – meaning reframing, competence scaffolding, and material deployment – that jointly stabilize sustainable practices by preserving familiarity, predictability, and identity continuity. The findings advance practice-theoretical accounts of consumption change and explain how sustainability can be domesticated into ordinary life rather than remaining a niche project.

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Will new Driving Technologies Change the Value of Transportation Investments?

This paper analyzes how the adoption of self-driving vehicles (SDVs) reshapes commuter behavior and alters the economic returns to public transportation investments. Using detailed data from the Greater Boston area, we estimate consumer preferences over residential location and commuting modes, highlighting the trade-offs households face between private vehicle use and public transit. We find that by lowering the time and effort costs of driving, SDVs could increase vehicle miles traveled by approximately 40 percent, while reducing public transit ridership and fare revenues by about 10 percent. Investments in public transportation—such as faster rail service and lower transfer costs—continue to generate revenue gains, but their impact on overall travel behavior is modest relative to the disruptive effects of SDVs. These results have important implications for transportation agencies, urban planners, and private mobility providers, as they underscore how emerging autonomous technologies may fundamentally change demand patterns, revenue models, and investment priorities in urban mobility markets.

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The AR-Display Bias: How Augmented Reality Disproportionately Benefits Inferior Products

Brands increasingly enable consumers to virtually experience products in their personal space before purchase through Augmented Reality (AR). Compared to more traditional formats, such as static images or 360° displays, AR displays have shown favorable effects. Our research proposes a more nuanced perspective by considering the role of product quality. Specifically, our findings (NTotal = 7,857) demonstrate a novel phenomenon—the AR-display bias: Relative to other product displays, AR produces a larger increase in preferences for inferior products than for superior products. We theorize that AR’s unique ability to display products in consumers’ personal space induces psychological proximity, thereby increasing psychological ownership. The AR-display bias then results from disproportionate effects of AR-induced psychological ownership, depending on product quality. Specifically, increased psychological ownership in AR disproportionately benefits inferior products by influencing consumers to generate more positive thoughts early in consideration, thereby elevating product perceptions and preferences. Importantly, this AR-display bias attenuates when AR fails to foster psychological ownership, such as when products are displayed farther away (lower physical proximity) or are incongruent with the self (lower psychological proximity). These findings highlight that AR’s influence is not uniform, offering important theoretical and marketing implications. 

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The Proximity Effect in Augmented Reality (PEAR)

Brands such as IKEA and Amazon increasingly encourage consumers to explore products through Augmented Reality (AR) within their immediate physical environments. This article examines whether the use of AR consistently benefits these brands. Drawing on visual-scene processing and psychological distance theories, we develop a conceptual framework introducing the proximity effect in Augmented Reality (PEAR). PEAR suggests AR enhances consumer preference when the AR-displayed product is in relational consistency with its environment, making the product feel more psychologically proximate. However, when relational consistency is violated, AR use fails to deliver these benefits. Initial insights into PEAR are derived from 20 consumer interviews. Nine main experiments (NTotal = 5,737) and five replications (NTotal = 1,664), conducted online and in the field, test and validate the PEAR framework and examine its robust-ness. Our research contributes to the literature on visual-scene processing and advances theoretical understanding of psychological distance and relational violations of AR product displays. Managerially, our findings show that while AR can strengthen purchase intentions, its effectiveness depends on guiding consumers toward appropriate object placement, offering insights for AR interface design and online retail strategy.

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Scaling the Returns to Automation:\\ Algorithms, Robots and Organizational Learning

Digital automation technologies (DAT), including algorithmic optimization and advanced robotics, are increasingly adopted, yet evidence on how organizations scale their benefits remains limited. We study the operational and labor effects of DAT using unique data from a global logistics firm covering 13,000 management units in 60 countries. Alongside granular performance and operational data, we can follow 4,000 projects and deployment decisions of algorithmic optimization tools and robotic devices. Exploiting quasi-random delays in deployment timing and policy-induced variation in technology availability, we can identify the causal effects of DAT.
We find that DAT increases revenue and profit, as well as total labor demand by about 20 percent. These effects are driven by higher capital utilization and task expansion, alongside a reduction in operative managerial hours. We show that technological complementarity matters to surface these benefits. The largest gains arise when facilities deploy algorithmic tools and robotic devices jointly rather than in isolation. Crucially, we find that implementation experience is a key driver of scale. Organization-wide experience with the implementation of DAT explains between 20 and 40 percent of the observed increases in labor demand, revenue, and profit.
Together, these findings highlight the organizational challenge of scaling automation. The benefits of robots and algorithmic optimization do not emerge automatically, but increase with accumulated and well-managed implementation experience and the deliberate exploitation of complementarities. Organizations scale the returns to automation by learning how to deploy, adapt, and combine technologies across operations, rather than by expanding technology use alone.

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