The Dual Effects of Algorithmic Management on Platform Workers: An Attribution Perspective

With the emergence of digital labour platforms (DLPs), we have witnessed a series of studies about DLPs, platform workers and algorithmic management (AM). In the current review, we summarize and synthesize the impact of each function of AM on workers, as well as workers’ responses to it. We find that AM in effect limits workers’ scheduling autonomy, work method autonomy, criteria autonomy, task choice autonomy, and locational autonomy. In addition, we also find some other impacts of AM, such as work precarity, unfairness and stress. We also notice the differences between web-based and location-based platforms, especially regarding workers’ autonomy. Regarding their responses, we discuss their compliance, unpaid labour, resistance, algoactivism, and sensemaking behaviours. We conclude that platform workers are virtual employees of virtual factories managed by invisible managers. Last, we suggest several study questions that appeal to a brighter future of platform work and workers and study questions that help scholars better understand platform workers’ behaviours.

Platform-mediated work (PMW) represents a highly unregulated and individualized segment of the labor market, with significant implications for psychosocial work environment and limited occupational health and safety (OHS) management efforts. The use of algorithmic management (AM) by digital platforms extensively directs and disciplines remote workers in PMW, and may exacerbate risks. This study employs the affordance concept initially introduced into safety science by Vicente and Rasmussen in 1992 and later applied in social media studies. Adopting a platform-sensitive approach, this study examines how digital mediation facilitates encounters between platform workers and customers across three types of PMW, and in turn affects harassment among platform workers. The analysis draws on 22 qualitative interviews with young platform workers supplemented by three workshops involving 13 stakeholder participants, informed by the Canadian Knowledge Transfer–Exchange approach. The findings identify three high-level affordances that significantly shape risks of harassment: (1) platforms’ ability to transcend physical space; (2) a digital blurring of private–professional boundaries; and (3) the amplification of asymmetric power relations among platform workers’ customers and platforms, relations that are gendered, classed, and racialized. The type and severity of harassment differ across the three types of platforms explored.

Platform work is a type of work using an online platform to intermediate between platform workers, who provide services, and paying clients. Platform work seems to be growing in size and importance. This study explores platform work in the EU28, Norway and Iceland, with a focus on the challenges it presents to working conditions and social protection, and how countries have responded through top-down (e.g. legislation and case law) and bottom-up actions (e.g. collective agreements, actions by platform workers or platforms). This national mapping is accompanied by a comparative assessment of selected EU legal instruments, mostly in the social area. Each instrument is assessed for personal and material scope to determine how it might impact such challenges. Four broad legal domains with relevance to platform work challenges are examined in stand-alone reflection papers. Together, the national mapping and legal analysis support a gap analysis, which aims to indicate where further action on platform work would be useful, and what form such action might take.

The ideology of the American medical profession: An attribution perspective∗

The development of digital technology has created new and flexible forms of employment. The online labor platform connects the employee and the employer through the Internet. Based on algorithm technology and data information, it rapidly and accurately matches the labor supply and demand. Previous studies reveal that the online labor platform, as a new place for workers to achieve flexible employment and create value under the gig economy background, provides a more flexible and independent work opportunity. The online platform has strengthened the control for the labor process by adopting algorithm technology, and the difference between the worker’s constrains of autonomy in workplace behavior and subjective perceptions of the increased autonomy, that is, the job autonomy paradox has gradually attracted attention from the academia circle.This paper systematically sorts out the related literature of online labor platform algorithm management and job autonomy, and discusses the core question of “is the platform work autonomous”. Subsequently, from the perspective of transaction cost theory, the representative research results of algorithm management affecting job autonomy are reviewed. At the same time, it explains the formation mechanism and influence effect of the autonomy paradox based on the theory of power dependence, and finally draws the following conclusions: Firstly, online labor platform algorithm management influences job autonomy from the work preparation stage, the work execution stage and the work feedback stage respectively. Specifically, in addition to the algorithm technology connectivity to realize the flexible and autonomous matching of labor supply and demand, which is conducive to the improvement of job autonomy, algorithm management weakens job autonomy from task allocation, behavior control, digital reputation, performance evaluation and dynamic compensation, etc. Secondly, algorithm management weakens the autonomy of workers and reduces job autonomy. In this case, platform workers are trapped in the negative cycle of autonomy paradox, which is constantly extending working hours and increasing labor intensity to strengthen labor. The formation mechanism of autonomy paradox can be based on the power dependence theory. Thirdly, the autonomy paradox will have a negative impact on workers from psychological and behavioral levels, which will eventually hinder the long-term development of the organization.However, there are still many deficiencies in existing studies, and future research could be done along the following lines: Firstly, the concept of algorithm management could be defined in a structured and systematic way. Secondly, future research could focus on promoting empirical study with multiple methods and technical means. Thirdly, future research could enrich theoretical perspectives to explain the mechanism of online labor platform algorithm management affecting job autonomy and the formation mechanism of autonomy paradox. Fourthly, future research could explore the boundary condition of autonomy paradox. Finally, future research could expand local studies in the context of China.

Design and performance evaluation of a fuzzy based traffic conditioner for differentiated services

Platform work is a form of employment that uses an online platform to match the supply of and demand for paid labour. In Europe, platform work is still small in scale but is rapidly developing. The types of work offered through platforms are ever-increasing, as are the challenges for existing regulatory frameworks. This report explores the working and employment conditions of three of the most common types of platform work in Europe. For each of these types, Eurofound assesses the physical and social environment, autonomy, employment status and access to social protection, and earnings and taxation based on interviews with platform workers. A comparative analysis of the regulatory frameworks applying to platform work in 18 EU Member States accompanies this review. This looks into workers? employment status, the formal relationships between clients, workers and platforms, and the organisation and representation of workers and platforms.

Drawing upon conservation of resources (COR) and attribution theories, we develop a help‐giving discontinuity model. From the COR perspective, we theorize that when help‐giving is perceived to be obligation, prevention‐focused self‐regulation is triggered, which induces help‐giving discontinuity to prevent further loss of resources. Additionally, when a low likelihood of receiving reciprocated help is perceived, prevention‐focused self‐regulation is activated, which induces help‐giving discontinuity due to insufficient replenishment of resources. From the attribution perspective, we propose that a co‐worker's lack of effort and recurrence of the same task‐related issue promote dispositional attributions, which result in help‐giving discontinuity. Our model, therefore, provides an important theoretical base for future research investigating why some employees continuously help others while others do not.

The supervision process is examined from an attributional perspective. Counselor supervision is conceptualized as an interactional process in which trainees learn to describe and manage cause‐effect relationships. Attribution theory from the social psychological literature is reviewed, and common biases and errors in the attribution process are discussed in terms of their relationship to supervision. Finally, several interventions are proposed to help supervisors minimize the influence of these attributional biases on their own and their trainees' perceptions and behaviors.

Many studies emphasize the importance of first-line employees, believing that they are a significant determinant of the quality of business service and operational success. The purpose of this study is to investigate the relationships among employee personality traits, service attitude, and service behavior in the leisure farm. The study surveys first-line employees in leisure farms and uses Analysis of Moment Structures (AMOS) software to test the model. The research result indicates that employee personal traits directly affect service attitude, but it does not have a direct effect on service behavior, rather, personality traits influence service behavior through service attitude. Therefore, service attitude plays a mediation role in the relationship between employee personality traits and service behavior in the leisure farm. Because personality traits could predict service attitude and affect service behavior, this research suggests that leisure farm operators could improve service quality through employee personality traits selection.

These days, more and more researchers are getting influenced by the big data analytics. “The big data is termed as the dataset, whose size is beyond the processing ability of conventional database or computers”. The four major aspects related to big data are: capture, store, management and analysis. The size of the data is a major concern in whichever field the big data is involved. Managing large scale data along with a commendable performance in defined frame of time is an issue in the big data analytics. In order to solve this issue optimization of the dataset is required. The swarm intelligence came out to be very much effective in networks. So, the proposed approach provides Quality of Service (QoS) optimization in networks through swarm intelligence algorithm for sustainable big data management. Swarm Intelligence optimization techniques have been emerged and successfully adopted by various researchers in recent times. As these techniques are nature inspired so, they proved to be much more effective in achieving better optimization results. So the proposed research work presented in this paper utilizes Swarm Intelligence Inspired Intelligent Water Drop (IWD) algorithm for throughput optimization for big data analytics in Zone Routing Protocol (ZRP) protocol of Mobile Ad-hoc Network (MANET).

This paper proposes algorithms for handoff, location, and connection management in a wireless asynchronous transfer mode (ATM) local-area network (LAN). Fast handoffs while maintaining cell sequence and quality-of-service (QoS) guarantees are achieved by distributing switching functionality to base stations, and using a networking scheme based on provisioned virtual trees. A new distributed location management scheme using a minimal registration procedure and broadcasts on wired links is proposed for this LAN. The detailed signaling procedures that support the algorithms for mobility and connection management are described. Finally, an implementation of these procedures and an analysis of the measured data is presented. Measurements of service times obtained from this implementation indicate that over 100 calls/s. can be handled by each node in 50-node network with a high-percentage of mobiles (75%) relative to fixed endpoints. This is comparable to current wired ATM switch call handling throughputs, in spite of the fact that these nodes perform additional handoff and location management functions. The data also indicates handoff latency times of 1.3 ms. This validates our proposal for maintaining cell sequence while performing handoffs.

Component technology is only available for business-oriented quality of service (QoS) management functions, can not satisfy the QoS requirements of soft real-time applications areas such as the multimedia and Web services. For real-time guarantee and improving resource utilization needs, this paper presents a real-time scheduling model for soft real-time component-oriented systems. First, the task model, component QoS specifications, resources container, resources container manager, and scheduler-related factors and their mutual relations are described. Second, the method for adding real-time mechanism to the component system is given. Finally, the scheduling algorithm is extended based on this model, and the resource container management algorithms are given, including access control algorithm, out of control algorithm, and QoS negotiation algorithm. The model meets the real-time requirements of applications and improves the system resource utilization together.

The development of 3G (the 3rd generation telecommunication) value-added services brings higher requirements of Quality of Service (QoS). Wideband Code Division Multiple Access (WCDMA) is one of three 3G standards, and enhancement of QoS for WCDMA Core Network (CN) becomes more and more important for users and carriers. The dissertation focuses on enhancement of QoS for WCDMA CN. The purpose is to realize the DiffServ (Differentiated Services) model of QoS for WCDMA CN. Based on the parallelism characteristic of Network Processors (NPs), the NP programming model is classified as Pool of Threads (POTs) and Hyper Task Chaining (HTC). In this study, an integrated programming model that combines both of the two models was designed. This model has highly efficient and flexible features, and also solves the problems of sharing conflicts and packet ordering. We used this model as the programming model to realize DiffServ QoS for WCDMA CN. The realization mechanism of the DiffServ model mainly consists of buffer management, packet scheduling and packet classification algorithms based on NPs. First, we proposed an adaptive buffer management algorithm called Packet Adaptive Fair Dropping (PAFD), which takes into consideration of both fairness and throughput, and has smooth service curves. Then, an improved packet scheduling algorithm called Priority-based Weighted Fair Queuing (PWFQ) was introduced to ensure the fairness of packet scheduling and reduce queue time of data packets. At the same time, the delay and jitter are also maintained in a small range. Thirdly, a multi-dimensional packet classification algorithm called Classification Based on Network Processors (CBNPs) was designed. It effectively reduces the memory access and storage space, and provides less time and space complexity. Lastly, an integrated hardware and software system of the DiffServ model of QoS for WCDMA CN was proposed. It was implemented on the NP IXP2400. According to the corresponding experiment results, the proposed system significantly enhanced QoS for WCDMA CN. It extensively improves consistent response time, display distortion and sound image synchronization, and thus increases network efficiency and saves network resource.

Motivated by the growing importance of demand response in modern power system's operations, we propose an architecture and supporting algorithms for privacy preserving thermal inertial load management as a service provided by the load serving entity (LSE). We focus on an LSE managing a population of its customers' air conditioners, and propose a contractual model where the LSE guarantees quality of service to each customer in terms of keeping their indoor temperature trajectories within respective bands around the desired individual comfort temperatures. We show how the LSE can price the contracts differentiated by the flexibility embodied by the width of the specified bands. We address architectural questions of (i) how the LSE can strategize its energy procurement based on price and ambient temperature forecasts, (ii) how an LSE can close the real time control loop at the aggregate level while providing individual comfort guarantees to loads, without ever measuring the states of an air conditioner for privacy reasons. Control algorithms to enable our proposed architecture are given, and their efficacy is demonstrated on real data.