Online Labor Platforms and the Role of Job Security and Compensation (Mis)Fits for Gig Workers

2023 | International Conference on Information Systems | Citations: 1

Authors: Adam, Martin; Wiener, Martin; Benlian, Alexander

Abstract: Online labor platforms (OLPs) use algorithms to manage their workers. Prior res ... Expand

Abstract: Online labor platforms (OLPs) use algorithms to manage their workers. Prior research has examined how OLP management shapes workers' attitudes, implicitly assuming that workers have the same preferences. However, research has largely neglected the role of (mis)fits between what workers need and what they receive from OLPs. Therefore, we conducted a survey with 121 Mechanical Turk workers and used polynomial regression analysis of workers' actual needs and perceived OLP supplies. Our results suggest that higher job security fit decreases perceived exploitation and increases system satisfaction, whereas higher compensation fit decreases perceived exploitation. In addition, we find that job security misfit has decreasing marginal effects on perceived exploitation and increasing marginal effects on system satisfaction. Overall, we contribute to a more nuanced understanding of workers' reactions to the design of OLPs by shedding light on the interplay between what gig workers need and what they perceive to receive from such platforms. Collapse

Topics: IS satisfaction platform worker algorithmic management digital platform ride sharing platform

Methods: survey regression analysis method cross sectional research polynomial regression theoretical contribution

Measuring Workers’ Perceptions of Algorithmic Control: Item Development and Content Validity Assessment

2023 | HICSS | Citations: 0

Authors: Alizadeh, Armin; Hirsch, Felix; Benlian, Alexander; Wiener, Martin; Cram, W. Alec

Abstract: Algorithmic control (AC) refers to organizations’ use of increasingly intelligen ... Expand

Abstract: Algorithmic control (AC) refers to organizations’ use of increasingly intelligent algorithms and related digital technology to steer worker behavior. While previous studies have identified and conceptualized various forms of AC in both platform and traditional work contexts, the presented conceptualizations lack measurability. This key shortcoming hampers further empirical research on the current use of AC and its manifold consequences. In this study, we report on the item development process for a scale for measuring perceived AC from a workers’ perspective. Following well-established approaches, an initial item pool was developed. The items were discussed and refined with the support of five academic experts and three AC workers. A subsequent rating study with 98 workers was conducted to ensure the content validity of all items. On this basis, the study at hand presents a comprehensive set of items for both AC in general and its seven sub-dimensions. Collapse

Topics: platform worker organizational context technostress database system ride sharing platform

Methods: qualitative interview survey design card sorting computational algorithm survey

Human versus automated agents: how user preferences affect future mobility systems

2023 | European Conference On Information Systems | Citations: 0

Authors: Ahadi, Ramin; Taudien, Anna; Ketter, Wolfgang

Abstract: Along with rapid advancements in digital, and physical technologies, shared aut ... Expand

Abstract: Along with rapid advancements in digital, and physical technologies, shared autonomous electric vehicles are forecasted to gradually complement and replace traditional human-based mobility systems. Information systems play a key role in such a deep socio-technical system to pave the path toward a more sustainable future. This study investigates a hybrid ride-hailing platform of automated and human-driven vehicles. Our focus lies on the demand side where we evaluate the influence of user behaviors on economic and environmental system performance. For this, we employ a data-driven agent-based simulation modeling heterogeneous vehicle and user agents calibrated by rental data of a leading vehicle-sharing company. Our findings declare that diverse customer responses to the introduction of shared autonomous electric vehicles yield significantly differing fleet performance and ecological costs. We also observe that the status quo customer communication design of ride-hailing platforms needs adjustments to maximize the potentials of future hybrid shared mobility systems. Collapse

Topics: ride sharing platform user behavior service quality decision making artificial intelligence

Methods: simulation agent based simulation experiment literature study sensitivity analysis

Theories: technology acceptance model general systems theory

Introduction to the Minitrack on Crowd-based Platforms

2023 | HICSS | Citations: 0

Authors: Chen, Pei-Yu; Huang, Nina; Gu, Bin

Abstract: ... Expand

Abstract: Collapse

Topics: crowdsourcing crowdfunding platform worker social media online labor market

Methods: difference in differences natural language processing longitudinal research natural experiment machine learning

Theories: signaling theory theory of affordance lemon market theory

Trust in Online Ride-Sharing Transactions: Impacts of Heterogeneous Order Features

2023 | Journal of Management Information Systems | Citations: 0

Authors: Cheng, Xusen; Fu, Shixuan; Sun, Jianshan; Zuo, Meiyun; Meng, Xiangsong

Abstract: With the development of the sharing economy, online ride-sharing has become a pr ... Expand

Abstract: With the development of the sharing economy, online ride-sharing has become a primary form of commuting. Using secondary transaction data, this study investigates the associations between the heterogeneous features and mutual trust in sharing economy-driven online ride-sharing transactions. Based on an examination of 12,404 ride-sharing orders in Beijing, we propose a set of trust distribution maps using order location data to reveal heterogeneous spatial patterns of the relationship between online ride-sharing transactions and mutual trust. The results show that the historical order completion rate and order distance are positively associated with mutual trust in ride-sharing transactions, whereas order time and departure density negatively and significantly influence mutual trust. Furthermore, we use machine learning algorithms to predict trust. The implications for theory and practice and future research directions are discussed. Collapse

Topics: ride sharing platform sharing platform logistics management geographic information system online review

Methods: machine learning computational algorithm regression analysis method experiment exploratory data analysis

Theories: signaling theory

To Speak up or Shut up? Revealing the Drivers of Crowdworker Voice Behaviors in Crowdsourcing Work Environments

2023 | Communications of the Association for Information Systems | Citations: 0

Authors: Deng, Xuefei (Nancy); Taylor, Joseph; Joshi, K.

Abstract: This study examines worker voice behaviors in the microtask crowdsourcing work ... Expand

Abstract: This study examines worker voice behaviors in the microtask crowdsourcing work environment (CSWE) where voice channels are absent. Informed by employee voice research, this study adopts the revealed causal mapping method to analyze the detailed narratives of 60 workers from Amazon Mechanical Turk. Our data analysis shows that the crowdworkers did engage in voice behaviors, but their voices were not always heard, depending on recipients. The crowdworker voice was directed to three different recipients (worker community, job requester, and platform) and influenced by six antecedents (duty orientation, efficacy judgment, workgroup identification, anger/frustration, futility, and achievement orientation). Based on the findings, we propose a model of worker voice antecedents and moderators in the CSWE. This study extends employee voice research by presenting a moderator perspective in the CSWE. Moreover, our study provides a nuanced understanding of crowdworker voice behaviors from two major aspectsantecedent and recipientcontributing to crowdsourcing research. Collapse

Topics: crowdsourcing online community virtual workplace platform worker IT work

Methods: conceptual modelling design artifact survey theoretical contribution qualitative coding

Evolution of Referrals over Customers’ Life Cycle: Evidence from a Ride-Sharing Platform

2023 | Information Systems Research | Citations: 0

Authors: Fernández-Loría, Carlos; Cohen, Maxime C.; Ghose, Anindya

Abstract: Online platforms often ask their users to refer friends in exchange for a reward ... Expand

Abstract: Online platforms often ask their users to refer friends in exchange for a reward. This paper addresses how referral generation and referral value evolve throughout the customer’s life cycle as a function of service usage, experience level, and past referral behavior. Our analysis is based on a longitudinal data set that comprises the transactions and referral actions of 400,000 users in a ride-sharing platform over a year. The richness of our data set allows us to address two shortcomings from previous studies: modeling dynamic behavior (i.e., the relationship between past and future referrals) and accounting for unobserved heterogeneity across users. Our results show that users make more referrals when they have used the service recently and intensively. For example, users become 9% less likely to make referrals for each week they have not used the service. Furthermore, users make more high-value referrals as they become more experienced with the service. The referral generation and referral value of the top 10% most experienced users are more than 18% higher relative to when they first used the service. Finally, as users make more referrals, they become more likely to run out of friends to whom they can refer the service, leading to less referrals in the future. After users make their first referral, the probability of making additional referrals decreases by more than 78% and the value of subsequent referrals reduces by 19% on average. The results imply that platforms should consider tailoring their referral programs according to how referral generation and referral value evolve over time.History: Xiaoquan (Michael) Zhang, Senior Editor; Khim Yong Goh, Associate Editor. Collapse

Topics: ride sharing platform mobile application logistics management accounting marketing management

Methods: longitudinal research robustness check instrumental variables estimation regression analysis method Poisson regression

Theories: social contagion theory

Influence of Media Capabilities on Trust in the Sharing Economy

2023 | Journal of Management Information Systems | Citations: 0

Authors: Harrison, Andrew; Mirsadikov, Akmal; Luu, Truong

Abstract: Media capabilities influence consumers' trust in online exchanges. However, in t ... Expand

Abstract: Media capabilities influence consumers' trust in online exchanges. However, in the sharing economy, where consumers interact with service providers through a platform, conventional models of trust must be revisited. Our research identifies how media synchronicity and anonymity influence the relative importance of institution-based trust in sharing economy exchanges. We collected data from 248 ride-hailing customers and 288 cryptocurrency users to test a moderated mediation model of trust. We find that in the sharing economy media synchronicity and anonymity lead customers to develop trust toward service providers directly and undermine the impact of institutional trust mechanisms. This indicates that in sharing economy exchanges, trust can be built directly with the service provider, or alternatively, indirectly through the platform. Consequently, organizations in the sharing economy can strategically design their systems to engender trust by choosing between (1) emphasizing the platform's reputation or (2) encouraging direct communication between the consumer and service providers. Collapse

Topics: anonymity ride sharing platform sharing platform cryptocurrency systems design

Methods: descriptive statistic statistical hypothesis test conditional process analysis mediation analysis factor analysis

Theories: media synchronicity theory

Algorithmic Control in Platform and Traditional Work Settings: An Updated Conceptual Framework

2023 | European Conference On Information Systems | Citations: 0

Authors: Hirsch, Felix; Alizadeh, Armin; Wiener, Martin; Cram, Alec

Abstract: Algorithmic control (AC) is an emerging phenomenon shaping the future of work. ... Expand

Abstract: Algorithmic control (AC) is an emerging phenomenon shaping the future of work. While AC is already well established in the platform economy, it is also gaining traction in traditional organizations. Given that AC represents a new phenomenon, it still suffers from a relatively immature conceptual basis. Here, an up-and-coming conceptual AC framework is the so-called "6R" framework by Kellogg et al. (2020). This framework, however, has not been conceptually and empirically validated yet, which is the focus of the study at hand. To validate the 6R framework, we use a combination of a literature review (topdown) and interviews (bottom-up). Our study sets forth to refine and extend the framework, resulting in an updated 5RSM framework of AC. The proposed framework represents an updated conceptualization of AC, applicable to both platform and traditional work settings, and lays the foundation for future research, including scale development. Collapse

Topics: algorithmic management ride sharing platform platform work logistics management Uber

Methods: qualitative interview literature sample structured literature research literature study qualitative coding

Theories: control theory organizational control theory theory of affordance

Workers' Perceived Algorithmic Exploitation on Online Labor Platforms

2023 | International Conference on Information Systems | Citations: 0

Authors: Jiang, Jennifer; Lippert, Isabell; Alizadeh, Armin

Abstract: Online labor platforms (OLPs) like Uber have become increasingly prevalent, att ... Expand

Abstract: Online labor platforms (OLPs) like Uber have become increasingly prevalent, attracting numerous workers with the appeal of flexible work arrangements. OLPs present themselves as an innovative alternative to traditional employment structures, but there remains a sense of exploitation among their workers. This perception is impelled by the platforms' heavy reliance on algorithmic management (AM), which often exerts a tighter form of management than traditional human-led oversight. This study examines how AM induces workers' exploitation perceptions (i.e., perceived algorithmic exploitation) by conducting a grounded theory methodology on 22 interviews with Uber drivers. We identified several forms of perceived algorithmic exploitation (i.e., manipulation, falsification, disempowerment, and dependency), which include AM practices that workers perceive as disadvantaging them to the potential benefit of the OLP. Overall, this study contributes to the "dark side" of AM and offers platform providers and policymakers crucial insights to create more sustainable working environments for platform workers. Collapse

Topics: Uber platform worker ride sharing platform electronic mail decision making

Methods: qualitative interview computational algorithm qualitative coding grounded theory theoretical contribution

Theories: lemon market theory