Asset revaluations and earnings management: Evidence from Australian companies

This paper examines the association between asset revaluations and discretionary accruals (a proxy for earnings management) using a sample of the largest 300 Australian companies. The results from this study indicate that the revaluation of non-current assets is positively associated with discretionary accruals. This finding is consistent with the argument that revaluation of assets reflects higher agency problems in the form of increased earnings management. Additional findings are that discretionary accruals are higher for firms reporting their non-current assets at fair values appraised by directors, than those of firms that use external appraisers. As well, the choice of auditors and the strength of corporate governance can constrain the opportunistic behaviour of managers in the accounting choice to revalue non-current assets.

Generating product feature hierarchy from product reviews

User generated information such as product reviews have been booming due to the advent of web 2.0. In particular, rich information associated with reviewed products has been buried in such big data. In order to facilitate identifying useful information from product (e.g., cameras) reviews, opinion mining has been proposed and widely used in recent years. In detail, as the most critical step of opinion mining, feature extraction aims to extract significant product features from review texts. However, most existing approaches only find individual features rather than identifying the hierarchical relationships between the product features. In this paper, we propose an approach which finds both features and feature relationships, structured as a feature hierarchy which is referred to as feature taxonomy in the remainder of the paper. Specifically, by making use of frequent patterns and association rules, we construct the feature taxonomy to profile the product at multiple levels instead of single level, which provides more detailed information about the product. The experiment which has been conducted based upon some real world review datasets shows that our proposed method is capable of identifying product features and relations effectively.

Modeling multi-stakeholder multi-objective decisions during public participation in major infrastructure and construction projects: A decision rule approach

Major infrastructure and construction (MIC) projects are those with significant traffic or environmental impact, of strategic and regional significance and high sensitivity. The decision making process of schemes of this type is becoming ever more complicated, especially with the increasing number of stakeholders involved and their growing tendency to defend their own varied interests. Failing to address and meet the concerns and expectations of stakeholders may result in project failures. To avoid this necessitates a systematic participatory approach to facilitate decision-making. Though numerous decision models have been established in previous studies (e.g. ELECTRE methods, the analytic hierarchy process and analytic network process) their applicability in the decision process during stakeholder participation in contemporary MIC projects is still uncertain. To resolve this, the decision rule approach is employed for modeling multi-stakeholder multi-objective project decisions. Through this, the result is obtained naturally according to the “rules” accepted by any stakeholder involved. In this sense, consensus is more likely to be achieved since the process is more convincing and the result is easier to be accepted by all concerned. Appropriate “rules”, comprehensive enough to address multiple objectives while straightforward enough to be understood by multiple stakeholders, are set for resolving conflict and facilitating consensus during the project decision process. The West Kowloon Cultural District (WKCD) project is used as a demonstration case and a focus group meeting is conducted in order to confirm the validity of the model established. The results indicate that the model is objective, reliable and practical enough to cope with real world problems. Finally, a suggested future research agenda is provided.