Target costing in construction: a comparative study

Target costing is an approach for the development of new products in the automobile industry, aimed at reducing their life-cycle costs while ensuring quality, reliability and other client requirements, by examining all possible ideas for cost reduction at the product planning, research and development and prototyping phases. Prior studies have attempted to adapt the manufacturing target costing process to the project-based nature of the construction industry. This paper aims to provide insights for future target costing implementations in the public sector projects. A qualitative comparison of three studies is performed through the lens of a set of target costing influencing factors. Similarities and differences revealed in the comparison suggest that factors related to supplier-base strategy and to the nature of customer are potentially relevant to future target costing implementations in public sector projects

Arena: A General Evaluation Platform and Building Toolkit for Multi-Agent Intelligence

Learning agents that are not only capable of taking tests, but also innovating is becoming a hot topic in AI. One of the most promising paths towards this vision is multi-agent learning, where agents act as the environment for each other, and improving each agent means proposing new problems for others. However, existing evaluation platforms are either not compatible with multi-agent settings, or limited to a specific game. That is, there is not yet a general evaluation platform for research on multi-agent intelligence. To this end, we introduce Arena, a general evaluation platform for multi-agent intelligence with 35 games of diverse logics and representations. Furthermore, multi-agent intelligence is still at the stage where many problems remain unexplored. Therefore, we provide a building toolkit for researchers to easily invent and build novel multi-agent problems from the provided game set based on a GUI-configurable social tree and five basic multi-agent reward schemes. Finally, we provide Python implementations of five state-of-the-art deep multi-agent reinforcement learning baselines. Along with the baseline implementations, we release a set of 100 best agents/teams that we can train with different training schemes for each game, as the base for evaluating agents with population performance. As such, the research community can perform comparisons under a stable and uniform standard. All the implementations and accompanied tutorials have been open-sourced for the community at https://sites.google.com/view/arena-unity/

Athletes' perceptions of coaching effectiveness and athlete-related outcomes in rugby union: An investigation based on the coaching efficacy model

This study examined the relationships between athletes' perceptions of coaching effectiveness, based on the coaching efficacy model, and their effort, commitment, enjoyment, self-efficacy, and prosocial and antisocial behavior in rugby union. Participants were 166 adult male rugby-union players (M age = 26.5, SD = 8.5 years), who completed questionnaires measuring their perceptions of four dimensions of coaching effectiveness as well as their effort, commitment, enjoyment, self-efficacy, and prosocial and antisocial behavior. Regression analyses, controlling for rugby experience, revealed that athletes' perceptions of motivation effectiveness predicted effort, commitment, and enjoyment. Further, perceptions of technique effectiveness predicted self-efficacy, while perceptions of character-building effectiveness predicted prosocial behavior. None of the perceived coaching effectiveness dimensions were related to antisocial behavior. In conclusion, athletes' evaluations of their coach's ability to motivate, provide instruction, and instill an attitude of fair play in his athletes have important implications for the variables measured in this study

Coaching efficacy and coaching effectiveness: examining their predictors and comparing coaches' and athletes' reports

Research on the conceptual model of coaching efficacy (Feltz, Chase, Moritz, & Sullivan, 1999) has increased dramatically over the past few years. Utilizing this model as the guiding framework, the current study examined: (a) coaching experience and sex as predictors of coaches' coaching efficacy; (b) sport experience, sex, and the match/mismatch in sex between coach and athlete as predictors of athletes' perceptions of their coach's effectiveness on the four coaching efficacy domains; and (c) whether coaches' reports of coaching efficacy and athletes' perceptions of coaching effectiveness differed. Coaches (N = 26) and their athletes (N = 291) from 8 individual and 7 team sports drawn from British university teams (N = 26) participated in the study. Coaches completed the Coaching Efficacy Scale (CES), while athletes evaluated their coach's effectiveness using an adapted version of the CES; coaches and athletes also responded to demographic questions. Results indicated that, in coaches, years of coaching experience positively predicted technique coaching efficacy, and males reported higher game strategy efficacy than females. In athletes, sport experience negatively predicted all perceived coaching effectiveness dimensions, and the mismatch in sex between athletes and their coach negatively predicted perceived motivation and character building coaching effectiveness. Finally, on average, coaches' ratings of coaching efficacy were significantly higher than their athletes' ratings of coaching effectiveness on A dimensions. The findings are discussed in terms of their implications for coaching effectiveness

Business Models and their Implications for Skills

The dominant political-economic narrative of our time is that, under conditions of global competition with low-wage economies able to undercut even efficient western firms, the only viable and sustainable route to competitiveness is to trade on high value-added goods and services and that these in turn require enhanced skills and knowledge. This kind of analysis finds echo and sustenance in the management literature concerning 'knowledge'. Drawing upon a series of case studies this monograph reveals a more varied and complex pattern of possibilities

Understanding collaborative supply chain relationships through the application of the Williamson organisational failure framework

Many researchers have studied supply chain relationships however, the preponderance of open markets situations and ‘industry-style’ surveys have reduced the empirical focus on the dynamics of long-term, collaborative dyadic relationships. Within the supply chain the need for much closer, long-term relationships is increasing due to supplier rationalisation and globalisation (Spekman et al, 1998) and more information about these interactions is required. The research specifically tested the well-accepted Williamson’s (1975) Economic Organisations Failure Framework as a theoretical model through which long term collaborative relationships can be