Enforcing reputation constraints on business process workflows

The problem of trust in determining the flow of execution of business processes has been in the centre of research interst in the last decade as business processes become a de facto model of Internet-based commerce, particularly with the increasing popularity in Cloud computing. One of the main mea-sures of trust is reputation, where the quality of services as provided to their clients can be used as the main factor in calculating service and service provider reputation values. The work presented here contributes to the solving of this problem by defining a model for the calculation of service reputa-tion levels in a BPEL-based business workflow. These levels of reputation are then used to control the execution of the workflow based on service-level agreement constraints provided by the users of the workflow. The main contribution of the paper is to first present a formal meaning for BPEL processes, which is constrained by reputation requirements from the users, and then we demonstrate that these requirements can be enforced using a reference architecture with a case scenario from the domain of distributed map processing. Finally, the paper discusses the possible threats that can be launched on such an architecture

Taylorism, targets and the pursuit of quantity and quality by call centre management

The paper locates the rise of the call centre within the context of the development of Taylorist methods and technological change in office work in general. Managerial utilisation of targets to impose and measure employees' quantitative and qualitative performance is analysed in four case-study organisations. The paper concludes that call centre work reflects a pardigmic re-configuration of customer servicing operations, and that the continuing application of Taylorist methods appears likely

QoS-Aware Middleware for Web Services Composition

The paradigmatic shift from a Web of manual interactions to a Web of programmatic interactions driven by Web services is creating unprecedented opportunities for the formation of online Business-to-Business (B2B) collaborations. In particular, the creation of value-added services by composition of existing ones is gaining a significant momentum. Since many available Web services provide overlapping or identical functionality, albeit with different Quality of Service (QoS), a choice needs to be made to determine which services are to participate in a given composite service. This paper presents a middleware platform which addresses the issue of selecting Web services for the purpose of their composition in a way that maximizes user satisfaction expressed as utility functions over QoS attributes, while satisfying the constraints set by the user and by the structure of the composite service. Two selection approaches are described and compared: one based on local (task-level) selection of services and the other based on global allocation of tasks to services using integer programming

A Reputation-Based Approach to Self-Adaptive Service Selection

Service-orientation provides concepts and tools for flexible composition and management of largescale distributed software applications. The automated run-time management of such loosely coupled software systems, however, poses still major challenges and is therefore an active research area, including the use of novel computing paradigms. In this context, the dynamic and adaptive selection of best possible service providers is an important task, which can be addressed by an appropriate middleware layer that allows considering different service quality aspects when managing the adaptive execution of distributed service workflows dynamically. In such an approach, service consumers are enabled to delegate the adaptive selection of service providers at run-time to the execution infrastructure. The selection criteria used are based on the cost of a service provision and the continuous, dynamic evaluation of reputations of providers, i.e. maintained track records of meeting the respective service commitments. This paper discusses the design and operating principle of such an automatic service selection middleware extension. Its ability to balance different quality criteria for service selection, such as service cost vs. the reliability of provision, is empirically evaluated based on a multi-agent platform approach

Reputation Agent: Prompting Fair Reviews in Gig Markets

Our study presents a new tool, Reputation Agent, to promote fairer reviews from requesters (employers or customers) on gig markets. Unfair reviews, created when requesters consider factors outside of a worker's control, are known to plague gig workers and can result in lost job opportunities and even termination from the marketplace. Our tool leverages machine learning to implement an intelligent interface that: (1) uses deep learning to automatically detect when an individual has included unfair factors into her review (factors outside the worker's control per the policies of the market); and (2) prompts the individual to reconsider her review if she has incorporated unfair factors. To study the effectiveness of Reputation Agent, we conducted a controlled experiment over different gig markets. Our experiment illustrates that across markets, Reputation Agent, in contrast with traditional approaches, motivates requesters to review gig workers' performance more fairly. We discuss how tools that bring more transparency to employers about the policies of a gig market can help build empathy thus resulting in reasoned discussions around potential injustices towards workers generated by these interfaces. Our vision is that with tools that promote truth and transparency we can bring fairer treatment to gig workers.Comment: 12 pages, 5 figures, The Web Conference 2020, ACM WWW 202

Design Considerations for Incorporating Flexible Workflow and Multi-AgentInteractions in Agent Societies

In this paper, we present our conception of a Flexible Agent Society (FAS), an extension of the Contractual Agent Society (CAS) idea. Essentially, a FAS is a distributed information system modeling an agent society, providing agents with the ability to collaborate in order to meet certain common goals. In a FAS, unlike the CAS, the agents themselves have control over the workflow processesand multi-agent conversations that they need to execute in order to meet their common goals