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Although the Trip‐ticket System (TTS) has been implemented to manage construction and demolition (C&D) waste in Hong Kong for over three years, problems still exist in the landfill disposal of the C&D waste. For example, it is reported that fees are difficult to collect from waste transporters for tipping the C&D waste at the landfill site. Based on an examination of the flexibility of the TTS, this paper proposes an e‐commerce model, namely the Webfill system, in order to enhance the TTS. The computational structure of the Webfill system is described and the usefulness of Webfill is evaluated based on a simulation which provides a direct comparison between the existing TTS and the Webfill‐enhanced TTS.

A quantitative approach for construction pollution control that is based on construction resource levelling is presented. The parameters of construction pollution index (CPI) and hazard magnitude (hi) are treated as a pseudo resource and integrated with a project’s construction schedule. When the level of pollution for site operations exceeds the permissible limit identified by a regulatory body, a Genetic Algorithm (GA) enhanced levelling technique is used to re‐schedule project activities so that the level of pollution can be re‐distributed and thus reduced. The GA enhanced resource levelling technique is demonstrated using 20 on‐site construction activities in a project. Experimental results indicate that the proposed GA enhanced resource levelling method performs better than the traditional resource levelling method used in MS Project©. The proposed method is an effective tool that can be used by project managers to reduce the level of pollution at a particular period of time; when other control methods fail.

Optimizing both qualitative and quantitative factors is a key challenge in solving construction finance decisions. The semi‐structured nature of construction finance optimization problems precludes conventional optimization techniques. With a desire to improve the performance of the canonical genetic algorithm (CGA) which is characterized by static crossover and mutation probability, and to provide contractors with a profit‐risk trade‐off curve and cash flow prediction, an adaptive genetic algorithm (AGA) model is developed. Ten projects being undertaken by a major construction firm in Hong Kong were used as case studies to evaluate the performance of the genetic algorithm (GA). The results of case study reveal that the AGA outperformed the CGA both in terms of its quality of solutions and the computational time required for a certain level of accuracy. The results also indicate that there is a potential for using the GA for modelling financial decisions should both quantitative and qualitative factors be optimized simultaneously.

A quantitative approach for managing construction pollution control that is based on construction resource leveling is presented. The parameters of construction pollution index, hazard magnitude are treated as a pseudo resource and integrated with a project’s construction schedule. When the level of pollution for site operations exceeds the permissible limit identified by a regulatory body, a genetic algorithm (GA) enhanced leveling technique is used to re‐schedule project activities so that the level of pollution can be re‐distributed and thus reduced. The GA enhanced resource leveling technique is demonstrated using 20 on‐site construction activities in a project. Experimental results indicate that proposed GA enhanced resource leveling method performs better than the traditional resource leveling method used in MS Project© The proposed method is an effective tool that can be used by project managers to reduce the level of pollution at a particular period of time; when other control methods fail.

Modelling of the multiproject cash flow decisions in a contracting firm facilitates optimal resource utilization, financial planning, profit forecasting and enables the inclusion of cash‐flow liquidity in forecasting. However, a great challenge for contracting firm to manage his multiproject cash flow when large and multiple construction projects are involved (manipulate large amount of resources, e.g. labour, plant, material, cost, etc.). In such cases, the complexity of the problem, hence the constraints involved, renders most existing regular optimization techniques computationally intractable within reasonable time frames. This limit inhibits the ability of contracting firms to complete construction projects at maximum efficiency through efficient utilization of resources among projects. Recently, artificial neural networks have demonstrated its strength in solving many optimization problems efficiently. In this regard a novel recurrent‐neural‐network model that integrates multi‐objective linear programming and neural network (MOLPNN) techniques has been developed. The model was applied to a relatively large contracting company running 10 projects concurrently in Hong Kong. The case study verified the feasibility and applicability of the MOLPNN to the defined problem. A comparison undertaken of two optimal schedules (i.e. risk‐avoiding scheme A and risk‐seeking scheme B) of cash flow based on the decision maker's preference is described in this paper.

Prior research finds evidence that audit quality is positively associated with the joint purchase of tax nonaudit services (NAS) and concludes that jointly provided tax services result in audit-related knowledge spillovers that lead to improved audit quality. We extend this line of research. We examine the relation between auditor-provided tax services and restatements and determine whether this relation differs when the auditor is a small or large accounting firm. We also examine whether the Securities Exchange Commission’s restrictions on certain tax consulting practices (SEC, 2006) altered this relation. Specifically, we measure whether the probability of financial statement restatements varies with (1) variation in accounting firm size (measured as PCAOB annually inspected firms versus PCAOB triennially inspected firms), and (2) the joint provision of audit and tax services. We find a negative relation between auditor-provided tax services and restatements which is consistent with prior research. We also find that this relation is significantly more negative when the auditor is a small accounting firm. Finally, we find that the lower probability of a restatement associated with the joint provision of audit and tax services persists regardless of auditor size after the SEC-imposed restrictions on certain tax consulting services in 2006. Our study provides evidence that accounting firms, and particularly small accounting firms, benefit from knowledge spillovers when jointly providing audit and tax services and these benefits lead to improved audit quality. Prior research concludes that large auditors provide higher audit quality and that the provision of tax services improves audit quality. Our results provide evidence that audit quality improvements are greater for small auditors and their clients. This improvement narrows that audit quality gap between large and small auditors. We do not find evidence that the SEC’s restrictions on certain tax consulting services altered the relation between audit quality and tax services.

The demand for including enterprise in the education system, at all levels and for all pupils is now a global phenomenon. Within this context, the use of competitions and competitive learning activities is presented as a popular and effective vehicle for learning. The purpose of this chapter is to illustrate how a realist method of enquiry – which utilises theory as the unit of analysis – can shed new light on the assumed and unintended outcomes of enterprise education competitions. The case developed here is that there are inherent flaws in assuming that competitions will ‘work’ in the ways set out in policy and guidance. Some of the most prevalent stated outcomes – that competitions will motivate and reward young people, that they will enable the development of entrepreneurial skills, and that learners will be inspired by their peers – are challenged by theory from psychology and education. The issue at stake is that the expansion of enterprise education policy into primary and secondary education increases the likelihood that more learners will be sheep dipped in competitions, and competitive activities, without a clear recognition of the potential unintended effects. In this chapter, we employ a realist-informed approach to critically evaluate the theoretical basis that underpins the use of competitions and competitive learning activities in school-based enterprise education. We believe that our findings and subsequent recommendations will provide those who promote and practice the use of competitions with a richer, more sophisticated picture of the potential flaws within such activities.