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

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

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

Content Creators Between Platform Control and User Autonomy

2023 | Business & Information Systems Engineering | Citations: 0

Authors: Hödl, Tatjana; Myrach, Thomas

Abstract: Content creators generate and upload content on social media platforms. If these ... Expand

Abstract: Content creators generate and upload content on social media platforms. If these platforms have a revenue-sharing policy, content creators earn income from advertising revenue. This income is heavily dependent on the distribution of the content and the resulting view counts. Platform owners may exert algorithmic control that impacts content distribution, advertising income, and, consequently, the behaviour of content creators. The objectives of the platform owners combined with the interests of the content creators may lead to paradoxical tensions between the aims of control and autonomy. The opaque nature of algorithms coupled with the need to be recognised by the algorithm further reinforces this phenomenon. This study follows an interpretive qualitative research approach applying grounded theory methodology. This research uses semi-structured interviews with content creators to develop a theory explaining the tension between control and autonomy on revenue-sharing social media platforms. The study shows that algorithmic control and incentivisation create paradoxical tensions that affect the autonomy of content creators. Content creators attempt to minimise tensions of algorithm versus audience, regularity versus scheduling autonomy, and analytics versus decision-making autonomy in two ways: through self-centred measures such as improving metrics, pre-production, and being a pioneer and extraneous measures involving their own businesses, products, and sponsorships. This study sheds some light on the phenomenon of paradoxical tensions and provides guidance and strategies for content creators and platform owners about proceeding with their relationship. This study’s findings provide platform owners and decision-makers with a deeper understanding of the behaviour of content creators and the hurdles they face in platform work. The findings help them identify challenges, draw conclusions, and implement changes. Collapse

Topics: social media YouTube Twitch advertising management price management

Methods: qualitative interview computational algorithm grounded theory theory development personal interview

Trust transfer effects and associated risks in telemedicine adoption

2023 | Electronic Markets | Citations: 0

Authors: Kuen, Leonie; Schürmann, Fiona; Westmattelmann, Daniel; Hartwig, Sophie; Tzafrir, Shay; Schewe, Gerhard

Abstract: Telemedicine has the potential to address considerable challenges in the efficie ... Expand

Abstract: Telemedicine has the potential to address considerable challenges in the efficient provision of health care services. However, this will not be realized until a high acceptance rate among patients is achieved. We address the research gap that arises from the need to explore the interplay of different trust referents (physician, technology, treatment) and perceived risk dimensions (performance, privacy, time, psychological) in patients’ telemedicine adoption considering two different symptom types (physical vs. mental). We conducted a scenario-based online survey and performed t-tests, scenario-specific structural equation modeling, and multi-group analysis. T-tests and multi-group analysis do not indicate differences in perceptions and path coefficients between the symptoms. Furthermore, scenario-specific structural equation modeling reveals that for both scenarios, trust in physician is less important for trust transfer effects and intention to use than trust in technology and trust in treatment. Trust in treatment has similar effects for all risk dimensions, while only performance risk relates to use intention. Moreover, the results indicate a considerable intention-behavior gap. We advance IS research by emphasizing the relevance of considering multiple trust referents, trust transfer effects, and a multidimensional perspective on perceived risk. Collapse

Topics: electronic health usage intention privacy technology adoption health information system

Methods: survey structural equation modeling partial least squares path modeling Student's t-test factor analysis

Theories: unified theory of acceptance and use of technology

Unemployment and Online Labor: Evidence from Microtasking

2023 | Management Information Systems Quarterly | Citations: 0

Authors: Laitenberger, Ulrich; Viete, Steffen; Slivko, Olga; Kummer, Michael; Borchert, Kathrin; Hirth, Matthias

Abstract: We analyze the relationship between unemployment and the supply of online labor ... Expand

Abstract: We analyze the relationship between unemployment and the supply of online labor for microtasking. Using detailed U.S. data from a large microtasking platform between 2011 and 2015, we study the participation and the number of hours supplied by workers in the U.S. We found that more individuals registered on the platform and completed microtasks as the unemployment level in the commuting zone increased. This effect was strongest in regions with a high share of low-skilled workers. Our analyses of the intensive margin, wage elasticity, and temporal work patterns suggest that the increased participation was likely motivated by an effort to substitute income. Our findings suggest that microtasking platforms are an interesting online labor market for less educated workers. However, we also observed very low retention rates, indicative of a solely transient participation effect. Collapse

Topics: online labor market Facebook task complexity information technology infrastructure accounting

Methods: instrumental variables estimation survey archival research autocorrelation analysis longitudinal research

Job Crafting in The Era of Algorithmic Management

2023 | International Conference on Information Systems | Citations: 0

Authors: Lippert, Isabell; Kirchner, Kathrin; Wiener, Martin; Saunders, Carol

Abstract: Companies increasingly rely on algorithmic management (AM) to efficiently contr ... Expand

Abstract: Companies increasingly rely on algorithmic management (AM) to efficiently control and coordinate workers, especially in the quick commerce sector, where workers are required to work particularly fast. AM often implies that workers face cognitive demands, such as behavioral constraints imposed by a tight management regime, or significant physical demands, such as a high work pace. Against this backdrop, we interviewed 18 food delivery couriers about how they try to cope with these demands. We find that, despite AM-induced behavioral constraints, workers engage in job crafting to better cope with demanding work conditions, to enrich work roles, and to add or extend resources, thereby increasing their job satisfaction and the perceived meaningfulness of their work. In contrast to previous studies where job crafting is strategically enacted by workers for long-term benefits, our study finds that jobs can also be successfully crafted short-term in an ad hoc manner. Collapse

Topics: mobile application algorithmic management Twitter job satisfaction platform work

Methods: qualitative interview personal interview ethnography experience sampling theoretical contribution

Fairness in Algorithmic Management: How Practices Promote Fairness and Redress Unfairness on Digital Labor Platforms

2023 | HICSS | Citations: 0

Authors: Schulze, L.; Trenz, M.; Cai, Z.; Tan, C.

Abstract: Algorithmic management (AM) is employed on digital labor platforms (DLPs) to e ... Expand

Abstract: Algorithmic management (AM) is employed on digital labor platforms (DLPs) to efficiently manage interactions between workers and clients. However, AM comes with ethical challenges, such as unfairness. Identifying best practices that counter these challenges promises to deliver actionable solutions. Therefore, we identify AM practices that workers deem particularly fair. We conduct seven online focus groups with a diverse set of platform workers and analyze the data through an organizational justice lens. Our findings reveal that AM practices can promote fairness by providing information, empowering workers, or autonomously executing tasks in their interest. Alternatively, in the case unfairness occurred, AM practices can redress unfairness. These practices include delegating dispute resolution to the involved actors, investigating evidence, and autonomously determining restorative consequences. Our findings have theoretical implications for fairness in algorithms, AM, and organizational justice literature. They might also be adopted in practice to improve workers' conditions on DLPs. Collapse

Topics: decision making ride sharing platform video conference platform work WeChat

Methods: focus group computational algorithm grounded theory qualitative coding group interview

Algorithmic Interactions in Open Source Work

2023 | Information Systems Research | Citations: 0

Authors: Shaikh, Maha; Vaast, Emmanuelle

Abstract: This study focuses on algorithmic interactions in open source work. Algorithms a ... Expand

Abstract: This study focuses on algorithmic interactions in open source work. Algorithms are essential in open source because they remedy concerns incompletely addressed by parallel development or modularity. Following algorithmic interactions in open source allows us to map the performance of algorithms to understand the nature of work conducted by multiple algorithms functioning together. We zoom to the level of algorithmic interactions to show how residual interdependencies of modularity are worked around by algorithms. Moreover, the dependence on parallel development does not suffice to resolve all concerns related to the distributed work of open source. We examine the Linux Kernel case that reveals how algorithmic interactions facilitate open source work through the three processes of managing, organizing, and supervising development work. Our qualitative study theorizes how algorithmic interactions intensify through these processes that work together to facilitate development. We make a theoretical contribution to open source scholarship by explaining how algorithmic interactions navigate across module rigidity and enhance parallel development. Our work also reveals how, in open source, developers work to automate most tasks and augmentation is a bidirectional relationship of algorithms augmenting the work of developers and of developers augmenting the work of algorithms.History: Hemant Jain, Balaji Padmanabhan, Paul Pavlou, and Raghu Santanam, Senior Editors; Likoebe Maruping, Associate Editor.Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.1153. Collapse

Topics: open source Linux platform work electronic mail robotic

Methods: computational algorithm theory development qualitative interview literature study theoretical contribution

Algorithmic control and gig workers: a legitimacy perspective of Uber drivers

2023 | European Journal of Information Systems | Citations: 8

Authors: Wiener, Martin; Cram, W. Alec; Benlian, Alexander

Abstract: Organisations increasingly rely on algorithms to exert automated managerial cont ... Expand

Abstract: Organisations increasingly rely on algorithms to exert automated managerial control over workers, referred to as algorithmic control (AC). The use of AC is already commonplace with platform-based work in the gig economy, where independent workers are paid for completing a given task (or “gig”). The combination of independent work alongside intensive managerial monitoring and guidance via AC raises questions about how gig workers perceive AC practices and judge their legitimacy, which could help explain critical worker behaviours such as turnover and non-compliance. Based on a three-dimensional conceptualisation of micro-level legitimacy tailored to the gig work context (autonomy, fairness, and privacy), we develop a research model that links workers’ perceptions of two predominant forms of AC (gatekeeping and guiding) to their legitimacy judgements and behavioural reactions. Using survey data from 621 Uber drivers, we find empirical support for the central role of micro-level legitimacy judgements in mediating the relationships between gig workers’ perceptions of different AC forms and their continuance intention and workaround use. Contrasting prior work, our study results show that workers do not perceive AC as a universally “bad thing” and that guiding AC is in fact positively related to micro-level legitimacy judgements. Theoretical and practical implications are discussed. Collapse

Topics: platform worker Uber privacy ride sharing platform system quality

Methods: survey theory development partial least squares path modeling computational algorithm survey design