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

Will Algorithms Replace Managers? A Systematic Literature Review on Algorithmic Management

2023 | International Conference on Information Systems | Citations: 0

Authors: Becker, Luc; Wurm, Bastian; Hess, Thomas

Abstract: Algorithms increasingly take on tasks traditionally performed by humans. They n ... Expand

Abstract: Algorithms increasingly take on tasks traditionally performed by humans. They not only serve as co-workers to their human counterparts but increasingly take over management tasks by supervising and coordinating human workers -a phenomenon referred to as Algorithmic Management (AM). There is a growing research interest in this topic, but currently, the field lacks an overview and thorough understanding of what types of managerial work algorithms already perform. We address this with a structured literature review. We find that the automation of management work and workers' responses to it (so-called algoactivism) have received the most attention. However, the configuration of AM systems has so far received little systematic attention. We further analyze which management functions algorithms perform. We find that while algorithms primarily supervise and investigate workers, coordinating interdependent workers and tasks has not been addressed. We propose several avenues for future research. Collapse

Topics: algorithmic management database system organizational context Uber knowledge base

Methods: computational algorithm literature study literature sample structured literature research

Algorithmic Management: Its Implications for Information Systems Research

2023 | Communications of the Association for Information Systems | Citations: 4

Authors: Cameron, Lindsey; Lamers, Laura; Leicht-Deobald, Ulrich; Lutz, Christoph; Meijerink, Jeroen; Möhlmann, Mareike

Abstract: In recent years, the topic of algorithmic management has received increasing at ... Expand

Abstract: 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 emphasized 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. Collapse

Topics: algorithmic management sensemaking platform worker Uber pandemic

Methods: computational algorithm theory development group interview ethnography grounded theory

Theories: organizational behavior theory enactment theory

Algorithm as Boss or Coworker? Randomized Field Experiment on Algorithmic Control and Collaboration in Gig Platform

2023 | International Conference on Information Systems | Citations: 0

Authors: Chan, Jason; Kyung, Nakyung; Yoon, Sojung; Kim, Yeonseo

Abstract: ... Expand

Abstract: Collapse

Topics: artificial intelligence platform worker decision making mobile application human computer interaction

Methods: computational algorithm survey experiment field experiment robustness check

Fit into work! From formalizing governance of gig platform ecosystems to helping gig workers craft their platform work

2023 | Decision Support Systems | Citations: 0

Authors: Chen, Jianyu; Luo, Jinlian; Hu, Wenan; Ma, Jun

Abstract: The current governance model of gig platform ecosystems benefits gig platforms a ... Expand

Abstract: The current governance model of gig platform ecosystems benefits gig platforms and customers, but puts gig workers in the weakest position of the triangular relationship. Thus, gig workers experience difficulty in addressing hardships related to gig work. To this end, we must determine how gig platforms build a governance environment that matches gig workers to help them craft gig work. However, extant studies have remained in the qualitative research surface, lacked a certain empirical insight, and have not clarified the direction to creating an effective platform governance model. Thus, based on such literature, we first conceptualize platform formal­ ization governance. Drawing on person-environment fit theory, the PLS-SEM analysis of 290 data from gig workers finds that platform formalization governance directly promotes gig workers' job crafting and indirectly propels it by improving performance appraisal systems' transparency. However, platform work insecurity climate weakens such an direct/indirect positive relationship. These findings contribute to strategic values and effec­ tiveness of the governance model of gig platform ecosystems, thus balancing interests between gig platforms, gig workers, and customers. Gig platforms should consider appropriately formalizing the current governance model and improving work insecurity climate, which helps gig workers more easily address hardships associated with platform work through job crafting. Collapse

Topics: platform worker platform work digital ecosystem platform governance algorithmic management

Methods: survey partial least squares path modeling data transformation PLS tool double-barreled question

Artificial Intelligence and Digital Work: The Sociotechnical Reversal

2023 | HICSS | Citations: 0

Authors: Fischer, L.; Wunderlich, N.; Baskerville, R.

Abstract: A well-designed information system (IS) in the classical view comprises two int ... Expand

Abstract: A well-designed information system (IS) in the classical view comprises two interrelated yet different subsystems; one that represents the technological dimension of work; and one that represents the social dimension. When these subsystems are heralded as equally important, they constitute a sociotechnical whole, producing economic outcomes such as profit and efficiency, plus humanistic outcomes, such as engagement and well-being. We see, increasingly, this classical view becoming obliviated. In this conceptual paper, we reflect upon the role of humans and technology in these changing work environments. While technical aspects from Artificial Intelligence and digital technologies are dominating the social side of work, we suggest a sociotechnical reversal to happen. Whereas this technosocial reality might be well motivated by advances in efficiency and productivity, the effects on well-being and engagement are less well understood. Consequently, we provide a set of theoretically derived principles to guide these changes in the digital workplace. Collapse

Topics: artificial intelligence IT work datafication knowledge work societal evaluation criteria

Methods: theory development

Theories: socio technical theory sociotechnical systems theory

Task delegation from AI to humans: A principal-agent perspective

2023 | International Conference on Information Systems | Citations: 0

Authors: Guggenberger, Tobias; Lämmermann, Luis; Urbach, Nils; Walter, Anna; Hofmann, Peter

Abstract: Increasingly intelligent AI artifacts in human-AI systems perform tasks more au ... Expand

Abstract: Increasingly intelligent AI artifacts in human-AI systems perform tasks more autonomously as entities that guide human actions, even changing the direction of task delegation between humans and AI. It has been shown that human-AI systems achieve better results when the AI artifact takes the leading role and delegates tasks to a human rather than the other way around. This study presents phenomena, conflicts, and challenges that arise in this process, explored through the theoretical lens of principalagent theory (PAT). The findings are derived from a systematic literature review and an exploratory interview study and are placed in the context of existing constructs of PAT. Furthermore, this article paper identifies new causes of tensions that arise specifically in AI-to-human delegation and calls for special mechanisms beyond the classical solutions of PAT. The paper thus contributes to the understanding of autonomous AI and its implications for human-AI delegation. Collapse

Topics: artificial intelligence human computer interaction human AI collaboration explainable artificial intelligence software developer

Methods: qualitative interview personal interview structured literature research qualitative coding computational algorithm

Theories: lemon market theory agency 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

A Double-edged Sword? Algorithmic Management and Workers' Proactive Service

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Hu, Peng

Abstract: Platforms increasingly rely on AI algorithms to execute automated task allocati ... Expand

Abstract: Platforms increasingly rely on AI algorithms to execute automated task allocation, monitoring, and performance evaluation of workers in the gig economy. Platforms also expect AI algorithms can prompt gig workers to provide proactive services to customers for a better reputation. However, it remains unclear how algorithmic management impacts the proactive service behavior of gig workers. Based on self-determination theory, this emergent research forum paper proposes a double-edged sword effect of algorithmic management due to conflicting work motives: algorithmic management can increase gig workers' proactive service behavior via autonomy motivation, whereas it can also inhibit proactive service behavior via controlled motivation. A three-wave longitudinal survey will be conducted to test the posited double-edged sword effect. This study has the potential to contribute to the algorithmic management literature in IS field by uncovering the "black box" between algorithm management and proactive service behavior of gig workers from the perspective of work motivation. Collapse

Topics: algorithmic management platform worker

Methods: longitudinal research longitudinal survey computational algorithm

Theories: self determination theory

Algorithmic Personnel Management: A Personnel Slack View

2023 | International Conference on Information Systems | Citations: 0

Authors: Kakkar, Ishan; Sharma, Mayank; Krishnaswamy, Venkataraghavan

Abstract: This study delves into the potential influence of Algorithmic Personnel Managem ... Expand

Abstract: This study delves into the potential influence of Algorithmic Personnel Management (APM)-based systems on optimizing personnel management (PM) processes and their subsequent impact on personnel slack. Employing a multi-case study analysis, we probe the capabilities afforded by APM-based systems, with a keen focus on their potential effects on PM processes, personnel slack, and organizational outcomes. Our exploration intimates the possibility of APM-based systems augmenting talent acquisition, talent management, and performance management processes, aligning employee competencies with organizational opportunities, and fostering adaptability amidst tumultuous business landscapes. Furthermore, the study conjectures the metamorphosis of conventional personnel managerial roles within the APM-based systems context, accentuating the necessity for personnel managers to acclimate to strategic and analytical duties. This research endeavors to enrich the academic discourse on algorithmic personnel management, workforce optimization, and organizational outcomes, proffering pragmatic implications for organizations contemplating APMbased systems implementation and shedding light on prospective trajectories for future inquiries. Collapse

Topics: website artificial intelligence organizational productivity innovation management knowledge base

Methods: case study multiple case study qualitative coding computational algorithm qualitative content analysis