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This paper synthesizes the extant feedback literature, focusing on how feedback affects an auditor’s learning, performance, and motivation. Performance feedback is an important component in the auditing environment for ensuring quality control and for developing and coaching staff auditors. However, the literature on feedback in the audit environment is fragmented and limited making it difficult to assess its behavioral effects on auditors. This paper has three main objectives. The first is to review some of the influential research in psychology and management to identify key variables and issues that appear to be critical in the study of behavioral consequences of feedback in organizational settings. The second is to review performance feedback research specifically in auditing to identify the areas previously examined and synthesize the findings. The third is to suggest a variety of future research opportunities that may assist in developing an understanding and knowledge of the behavioral effects of feedback on auditors. The literature analysis has significant implications for audit research and practice. In particular, the analysis provides important insights into understanding who, how, and when performance feedback should be given to improve its effectiveness in the audit environment.

The purpose of this paper is to investigate the impact of the salient task environment on reverse logistics (RL) practices and organizational performance in the context of Taiwanese computer, communication, and consumer (3C) electronics retail industry.

A hierarchical regression analysis was employed to test relationships between four constituents of the task environment and RL, as well as relationships between RL and environmental/economic performance. In addition, a regression analysis was used to examine the mediating effect of RL on relationships between the constituents of the task environment and environmental/economic performance. Data and information collected from a sample of 284 companies from the Taiwanese 3C retail industry were used for analysis.

Results suggest that three out of four constituents of task environment including government agencies, suppliers, and customers are associated positively with RL activities. In other words, as the salience of the constituents of the task environment increases, their level of influence on the firm’s RL also increases. This study also found the mediating effect of RL, indicating that superior performance emerges when a company’s RL matches the salient task environment.

The findings provide an insight into the relationships between the constituents of the task environment, RL, and environmental/economic performance which can assist firms within 3C retail industry in designing and developing appropriate strategy for RL. In practice, some retailers, especially SMEs, have outsourced their RL to professional recyclers. Investment in RL activity may be an option for some 3C retailers.

While previous research provides a strong foundation to further develop RL and subsequent policies, analysis of the factors affecting the decision processes to implement RL specially in the retail sector is scarce. This study fills this gap.

To describe some research done, as part of an EPSRC funded project, to assist engineers working together on collaborative tasks.

Distributed finite state modelling and agent techniques are used successfully in a new hybrid self‐organising decision making system applied to collaborative work support. For the particular application, analysis of the tasks involved has been performed and these tasks are modelled. The system then employs a novel generic agent model, where task and domain knowledge are isolated from the support system, which provides relevant information to the engineers.

The method is applied in the despatch of transmission commands within the control room of The National Grid Company Plc (NGC) – tasks are completed significantly faster when the system is utilised.

The paper describes a generic approach and it would be interesting to investigate how well it works in other applications.

Although only one application has been studied, the methodology could equally be applied to a general class of cooperative work environments.

One key part of the work is the novel generic agent model that enables the task and domain knowledge, which are application specific, to be isolated from the support system, and hence allows the method to be applied in other domains.

On shield tunnel construction (STC) site, human error is widely recognized as essential to accident. It is necessary to explain which factors lead to human error and how these factors can influence human performance. Human reliability analysis supports such necessity through modeling the performance shaping factors (PSFs). The purpose of this paper is to establish and validate a PSF taxonomy for the STC context.

The approach taken in this study mainly consists of three steps. First, a description of the STC context is proposed through the analysis of the STC context. Second, the literature which stretch across the PSF methodologies, cognitive psychology and human factors of STC and other construction industries are reviewed to develop an initial set of PSFs. Finally, a final PSF set is modified and validated based on STC task analysis and STC accidents cases.

The PSF taxonomy constituted by 4 main components, 4 hierarchies and 85 PSFs is established for human behavior modeling and simulation under the STC context. Furthermore, by comparing and evaluating the performance of STC PSF and existing PSF studies, the proposed PSF taxonomy meets the requirement for qualitative and quantitative analysis.

The PSF taxonomy can provide a basis and support for human behavior modeling and simulation under the STC context. Integrating PSFs into a behavior simulation model provides a more realistic and integrated assessment of human error by manifesting the influence of each PSFs on the cognitive processes. The simulation results can suggest concrete points for the improvement of STC safety management.

This paper develops a taxonomy of PSFs that addresses the various unique influences of the STC context on human behaviors. The harsh underground working conditions and diverse resources of system information are identified as key characteristics of the STC context. Furthermore, the PSF taxonomy can be integrated into a human cognitive behavior model to predict the worker’s behavior on STC site in future work.

The purpose of this paper is to present a novel approach to coordination of multi‐agent teams, and in particular multi‐robot teams. The new approach is based on models of organisational sociology, namely the concept of social networks. The social relationships used in the model that is presented in this paper are trust and kinship relationships, but modified for use in heterogeneous multi‐robot teams.

The coordination of a robot team is achieved through task allocation. The proposed task allocation mechanism was tested in the multi‐robot team task allocation simulation.

The social networks‐based task allocation algorithm has performed according to expectations and the obtained results are very promising. Some intriguing similarities with higher mammalian societies were observed and they are discussed in this paper. The social networks‐based approach also exhibited the ability to learn and store information using social networks.

The research focused on simulated environments and further research is envisaged in the physical environments to confirm the applicability of the presented approach.

In this paper, the proposed coordination was applied to simulated multi‐robot teams. It is important to note that the proposed coordination model is not robot specific, but can also be applied to almost any multi‐agent system without major modifications.

The paper emphasizes applicability of considering multi‐robot teams as socially embodied agents. It also presents a novel and efficient approach to task allocation.

This chapter discusses the SETT Framework – an acronym for Student, Environments, Tasks and Tools – a decision-making tool originally designed to help collaborative teams gather and organise information that can be used to guide decisions about assistive technology (AT) devices and services that foster the educational success of students with disabilities (Zabala, 1995). Explanations and examples are provided both related to the original intent of the framework and how the principles of the SETT Framework have expanded to include not only AT but also other educational services, noneducational environments and other beneficiaries. This commentary is organised around key questions designed to foster rich conversations around the use the SETT Framework in all phases of AT service delivery to support the development of inclusive learning environments and to consider supports and services needed for staff, families and other supporters of students.

Integrating supplier innovation is considered an effective strategy to reduce uncertainty at the fuzzy front end (FFE). However, the large number of supplier innovation resources and the task environment forces buying firms to precisely identify more valuable or interesting innovation resources for integration. The impact of the interaction between supplier innovation and task environment on FFE performance needs to be further explored. Therefore, this paper aims to propose a contingency framework to examine the relationship between supplier innovation (technology-push and market-pull) and buying firm’s FFE performance in different task environments, with the aim of clarifying which supplier innovation resources should be integrated to create high FFE performance in the face of an uncertain task environment.

Survey data from new product development team leaders in Chinese high-tech firms were collected and analyzed. Furthermore, using multiple regression analysis, the relationship among supplier innovation, task environment and FFE performance was examined.

The results show that although both technology-push and market-pull supplier innovation can improve FFE performance, there are significant differences between the influences of these two types of supplier innovation in the face of different task environments.

Practical guidelines are provided for buyer managers on how to effectively identify the “best” supplier innovation resources to improving the effectiveness and efficiency of supplier involvement in the FFE.

This paper deepens the knowledge of identifying supplier innovation resources in the FFE and enriches the research on supplier-enable FFE innovation.

This paper aims to present a hybrid control approach that combines learning-based reactive control and affordance-based deliberate control for autonomous mobile robot navigation. Unlike many current navigation approaches which only use learning-based paradigms, the authors focus on how to utilize the machine learning methods for reactive control together with the affordance knowledge that is simultaneously inherent in natural environments to gain advantages from both local and global optimization.

The idea is to decompose the complex and large-scale robot navigation task into multiple sub-tasks and use the hierarchical reinforcement learning (HRL) algorithm, which is well-studied in the learning and control algorithm domains, to decompose the overall task into sub-tasks and learn a grid-topological map of the environment. An affordance-based deliberate controller is used to inspect the affordance knowledge of the obstacles in the environment. The hybrid control architecture is then designed to integrate the learning-based reactive control and affordance-based deliberate control based on the grid-topological and affordance knowledge.

Experiments with computer simulation and an actual humanoid NAO robot have demonstrated the effectiveness of the proposed hybrid approach for mobile robot navigation.

The main contributions of this paper are a new robot navigation framework that decomposes a complex navigation task into multiple sub-tasks using the HRL approach, and hybrid control architecture development that integrates learning-based and affordance-based paradigms for autonomous mobile robot navigation.

This is the first part of a two-part paper. The purpose of this paper is to report on methods that use the Response Surface Methodology (RSM) to investigate an Evolutionary Algorithm (EA) and memory-based approach referred to as McBAR – the Mapping of Task IDs for Centroid-Based Adaptation with Random Immigrants. Some of the methods are useful for investigating the performance (solution-search abilities) of techniques (comprised of McBAR and other selected EA-based techniques) for solving some multi-objective dynamic resource-constrained project scheduling problems with time-varying number of tasks.

The RSM is applied to: determine some EA parameters of the techniques, develop models of the performance of each technique, legitimize some algorithmic components of McBAR, manifest the relative performance of McBAR over the other techniques and determine the resiliency of McBAR against changes in the environment.

The results of applying the methods are explored in the second part of this work.

The models are composite and characterize an EA memory-based technique. Further, the resiliency of techniques is determined by applying Lagrange optimization that involves the models.

In this paper, we present a proposed information environment (PROPIE) for enhanced interaction and value‐adding of electronic documents (e‐documents). The design of PROPIE was based on a thorough user needs and requirements assessment in interacting with information through well‐documented findings, and a focus group with twelve participants to elicit features that were deemed desirable in future interactions. The design was also based on an earlier work which reviewed the advancements in various user interface (UI) technologies, visualisation and interactive techniques, and a consideration of novel information structuring and organisation techniques that pose important implications for the design of more advanced UIs. Providing a suite of novel features and interactive tools that can be flexibly combined, PROPIE allows users to apply multiple novel ways to query intuitively and navigate information in an e‐document. The querying and browsing processes in PROPIE are supported by various interactive and visualisation techniques. Users work within a visually sovereign, integrated environment for information gathering and organising, based on navigable, fractional information objects that are also affiliated with rich metadata and additional layers of value‐adding information. A set of interface mock‐ups was developed to demonstrate the potential of the environment in supporting the design of a new generation of electronic journals (e‐journals). We report here empirical results from a study conducted to obtain representative users‘ feedback with regard to using PROPIE for interacting with e‐journals. Twenty‐two participants from a variety of academic backgrounds participated in the evaluation. Overall, PROPIE was found to have the potential both for enhancing the user’s interaction with information captured within e‐journals and for adding value to e‐documents in various ways.