6 research outputs found

    Algorithmic Management: Its Implications for Information Systems Research

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    In recent years, the topic of algorithmic management has received increasing attention in information systems (IS) research and beyond. As both emerging platform businesses and established companies rely on artificial intelligence and sophisticated software to automate tasks previously done by managers, important organizational, social, and ethical questions emerge. However, a cross-disciplinary approach to algorithmic management that brings together IS perspectives with other (sub-)disciplines such as macro- and micro-organizational behavior, business ethics, and digital sociology is missing, despite its usefulness for IS research. This article engages in cross-disciplinary agenda setting through an in-depth report of a professional development workshop (PDW) entitled “Algorithmic Management: Toward a Cross-Disciplinary Research Agenda” delivered at the 2021 Academy of Management Annual Meeting. Three leading experts (Mareike Möhlmann, Lindsey Cameron, and Laura Lamers) on the topic provide their insights on the current status of algorithmic management research, how their work contributes to this area, where the field is heading in the future, and what important questions should be answered going forward. These accounts are followed up by insights from the breakout group discussions at the PDW that provided further input. Overall, the experts and workshop participants highlighted that future research should examine both the desirable and undesirable outcomes of algorithmic management and should not shy away from posing ethical and normative questions

    Public Acceptance and Adoption of Shared-Ride Services in the Ride-Hailing Industry

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    On-demand ride-hailing companies like Uber and Lyft, often referred to as transportation network companies (TNCs), now provide shared-ride services, such as UberPool or Lyft Shared. Shared-ride services match riders with similar origins and destinations together. Passengers benefit from these services by paying reduced fares for the additional time spent picking up and dropping off additional passengers. This study seeks to provide a deeper understanding of the social and behavioral considerations associated with travelers’ acceptance of shared-rides and how those considerations factor into individuals’ willingness to pay (WTP) for shared-ride services. We conducted a survey of TNC users through Qualtrics in February of 2020, which had 1609 respondents from ten major metropolitan areas across the United States. In addition to the survey, we also conducted one focus group in Detroit, Michigan which supplements our survey results with the narratives of actual TNC users. We found that (a) the average WTP is significantly less for a shared-ride than a solo-ride and that this average decreases at a decreasing rate with each additional passenger; (b) the average WTP for a commuter ride is less than a leisure ride, which could be due to feelings that ridesharing is unreliable and inconvenient in regard to fixed work schedules; (c) the average WTP for a leisure ride is higher than a commute ride, which could be due to the value that individuals place on not having to drink and drive and to avoid parking hassles, and; (d) the presence of an option that allows riders to be matched based on social preferences of “happy to chat”, “quiet preferred”, or “no preference” results in a decrease in WTP. This study revealed that although most interventions are viewed as positive additions to TNC services and that social and behavioral motivation for using shared-ride services are relevant, they matter less when compared to traditional factors, such as time and cost.Master of ScienceSchool for Environment and SustainabilityUniversity of Michiganhttps://deepblue.lib.umich.edu/bitstream/2027.42/154994/1/Public Acceptance and adoption of shared ride services.pd

    Meaning Matters: Cognitive Crafting as a Sensemaking Mechanism and Motivational Process to Enhance Gig Driver Well-being

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    As the gig work sector of the workforce continues to grow, organizational psychologists must actively contribute to raising the bar for gig drivers (e.g., ride-hailing, food delivery) so that they are not merely surviving but also thriving through their work. In my dissertation, I tested cognitive crafting as a positive meaning-making process that helps gig drivers make sense of their interactions with customers, generates positive, motivating states such as work engagement, and promotes positive outcomes such as work-related well-being and job satisfaction. My dissertation employed a mixed-methods design. The daily diary built on qualitative data results that identified interesting - and perhaps even counterintuitive - themes about gig drivers\u27 experiences and perceptions of their work. The daily diary results demonstrated that daily positive customer interactions were positively related to daily cognitive crafting and work engagement, and daily negative customer interactions had a negative relationship with daily cognitive crafting. These relationships were moderated by psychological capital. The serial mediation effects and the moderated serial mediation effects were not supported. This study provided insight into the customer interactions – cognitive crafting relationship at the daily level. Additionally, the results supported that individual differences in psychological capital explained which gig drivers cognitively crafted in light of customer interactions. As a whole, this dissertation provides important contributions to the literature by examining cognitive crafting and well-being in the unique context of gig driving with a positive organizational scholarship lens

    Rural and Urban Mobility: Studying Digital Technology Use and Interaction

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    Accessible Autonomy: Exploring Inclusive Autonomous Vehicle Design and Interaction for People who are Blind and Visually Impaired

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    Autonomous vehicles are poised to revolutionize independent travel for millions of people experiencing transportation-limiting visual impairments worldwide. However, the current trajectory of automotive technology is rife with roadblocks to accessible interaction and inclusion for this demographic. Inaccessible (visually dependent) interfaces and lack of information access throughout the trip are surmountable, yet nevertheless critical barriers to this potentially lifechanging technology. To address these challenges, the programmatic dissertation research presented here includes ten studies, three published papers, and three submitted papers in high impact outlets that together address accessibility across the complete trip of transportation. The first paper began with a thorough review of the fully autonomous vehicle (FAV) and blind and visually impaired (BVI) literature, as well as the underlying policy landscape. Results guided prejourney ridesharing needs among BVI users, which were addressed in paper two via a survey with (n=90) transit service drivers, interviews with (n=12) BVI users, and prototype design evaluations with (n=6) users, all contributing to the Autonomous Vehicle Assistant: an award-winning and accessible ridesharing app. A subsequent study with (n=12) users, presented in paper three, focused on prejourney mapping to provide critical information access in future FAVs. Accessible in-vehicle interactions were explored in the fourth paper through a survey with (n=187) BVI users. Results prioritized nonvisual information about the trip and indicated the importance of situational awareness. This effort informed the design and evaluation of an ultrasonic haptic HMI intended to promote situational awareness with (n=14) participants (paper five), leading to a novel gestural-audio interface with (n=23) users (paper six). Strong support from users across these studies suggested positive outcomes in pursuit of actionable situational awareness and control. Cumulative results from this dissertation research program represent, to our knowledge, the single most comprehensive approach to FAV BVI accessibility to date. By considering both pre-journey and in-vehicle accessibility, results pave the way for autonomous driving experiences that enable meaningful interaction for BVI users across the complete trip of transportation. This new mode of accessible travel is predicted to transform independent travel for millions of people with visual impairment, leading to increased independence, mobility, and quality of life

    The Rise of Algorithmic Work: Implications for Organizational Control and Worker Autonomy

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    In less than a decade the on-demand economy, a labor market characterized by short-term contracts where work is coordinated through algorithms, has radically reshaped organizations, employment relationships, workers’ lives, and consumer behaviors. Despite optimistic and pessimistic predictions, few studies have examined how algorithms affect work and workers in practice. This dissertation focuses on understanding the impact of algorithms on workers in an environment where the entire human resource cycle is coordinated by algorithms. Existing organizational theories suggest that algorithmic systems will tighten the iron cage by providing more comprehensive and invasive methods of control. This dissertation, however, reveals the myriad ways that workers find autonomy in an algorithmic work environment. To theorize this central finding, I draw upon field work collected from the ride hailing industry, the largest sector in the on-demand economy. I begin with an overview of some of the changes in the contemporary workplace highlighting how they may challenge and extend mainstream organizational theories. I follow with a review of the on-demand economy, including its predecessors of production and service work, and how it affects workers, consumers, and communities. Next, I describe how algorithm-based control systems differ from prior systems and conceptualize algorithmic work—a set of job-related activities that are structured by algorithms—drawing on a synthesis of literature across six social science disciplines. I conclude this chapter with unexplored questions at the nexus of work, workers, and algorithms. In the two empirical papers, I draw on participant observation (including three years as a driver and a rider), longitudinal interviews, online archival data and focus groups. In the first study, I examine how workers interpret the insecure work conditions inherent in the on-demand economy. Focusing on the practices and perspectives of the two most salient features of their work environment—customers and technology—I explore how these interactions lead drivers to understand their work. Seeing their relationship with work as either an alliance or as adversarial, workers tend to view features of the work environment as either working on their behalf or against them. Over time these practices and perspectives culminate in different outcomes. In the second study, I begin by describing how algorithm-based control systems differ from prior systems and conceptualize algorithmic work. Algorithms manage by structuring choice at each human-algorithm interaction, to which drivers respond with a set of tactics: compliance, engagement, or deviance. While these tactics appear to be at odds, drivers describe their responses as evidence of their personal autonomy, in that the system allows them to maximize earnings and create a continuous stream of work from a discontinuous set of tasks. This autonomy demonstrates that although the algorithmic-manager may be an unforgiving taskmaster, workers perceive otherwise, thus suggesting that workers feel they have more autonomy in algorithmic rather than traditional work. This dissertation provides several theoretical and empirical contributions. First, I summarize perspectives of algorithms across the social sciences laying out several unanswered questions at the intersection of work, organizations, and algorithms. Further, I propose a definition of how algorithms operate in the workplace which I expand on. In contrast to iron cage metaphors, this dissertation suggests that workers do indeed experience a great deal of autonomy in the algorithmic workplace. This study thus has implications for our understanding of algorithms, organizational control, autonomy and the meaning of work.PHDBusiness AdministrationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/155277/1/ldcamer_1.pd
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