476 resultados para ATTRIBUTES
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Identifying the design features that impact construction is essential to developing cost effective and constructible designs. The similarity of building components is a critical design feature that affects method selection, productivity, and ultimately construction cost and schedule performance. However, there is limited understanding of what constitutes similarity in the design of building components and limited computer-based support to identify this feature in a building product model. This paper contributes a feature-based framework for representing and reasoning about component similarity that builds on ontological modelling, model-based reasoning and cluster analysis techniques. It describes the ontology we developed to characterize component similarity in terms of the component attributes, the direction, and the degree of variation. It also describes the generic reasoning process we formalized to identify component similarity in a standard product model based on practitioners' varied preferences. The generic reasoning process evaluates the geometric, topological, and symbolic similarities between components, creates groupings of similar components, and quantifies the degree of similarity. We implemented this reasoning process in a prototype cost estimating application, which creates and maintains cost estimates based on a building product model. Validation studies of the prototype system provide evidence that the framework is general and enables a more accurate and efficient cost estimating process.
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LIP emplacement is linked to the timing and evolution of supercontinental break-up. LIP-related break-up produces volcanic rifted margins, new and large (up to 108 km2) ocean basins, and new, smaller continents that undergo dispersal and potentially reassembly (e.g., India). However, not all continental LIPs lead to continental rupture. We analysed the <330 Ma continental LIP record(following final assembly of Pangea) to find relationships between LIP event attributes (e.g., igneous volume, extent, distance from pre-existing continental margin) and ocean basin attributes (e.g., length of new ocean basin/rifted margin) and how these varied during the progressive break up of Pangea. No correlation exists between LIP magnitude and size of the subsequent ocean basin or rifted margin. Our review suggests a three-phased break-up history of Pangea: 1) “Preconditioning” phase (∼330–200 Ma): LIP events (n=7) occurred largely around the supercontinental margin clustering today in Asia, with a low (<20%) rifting success rate. The Panjal Traps at ∼280 Ma may represent the first continental rupturing event of Pangea, resulting in continental ribboning along the Tethyan margin; 2) “Main Break-up” phase (∼200–100 Ma): numerous large LIP events(n=10) in the supercontinent interior, resulting in highly successful fragmentation (90%) and large, new ocean basins(e.g., Central/South Atlantic, Indian, >3000 km long); 3) “Waning” phase (∼100–0 Ma): Declining LIP magnitudes (n=6), greater proximity to continental margins (e.g., Madagascar, North Atlantic, Afro-Arabia, Sierra Madre) producing smaller ocean basins (<2600 km long). How Pangea broke up may thus have implications for earlier supercontinent reconstructions and LIP record.
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Introduction to the topic or context and/or mapping of the literature Increasing degree-seeking, self-funded, international students from affluent Asian countries, who use English as an additional language (EAL), have contributed to cultural and linguistic diversities in Australian universities. Such diversities further posed challenges in pedagogy and assessment. In particular, these students' English proficiency and cultural attributes were highlighted as factors in productive group discussions, and equitable group assessment. The focus in the research literature thus far is on how EAL international students can better English proficiency and adaptability to group participation. However, little is known from sociological perspectives about the power relations involved in EAL students' choice of group members in group discussions.
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Attributed to the changing social, political and economic landscape of the ‘knowledge economy’, Australian universities are under pressure to produce researchers that have a variety of skills which meet the demands of an increasingly diverse job market. As a consequence, the Australian PhD now includes a range of doctoral degrees. This paper reports on the experiences of two PhD students engaged in an informally managed research higher degree program described in this paper as a Work Integrated Research Higher Degree (WIRHD). Their learning process shares the attributes from both the traditional PhD program and professional doctorates. However, because of the blended nature of the learning contexts, what students need to manage within the WIRHD is much more complicated than the established RHD programs. An exploratory case study approach exploring experiences, benefits, barriers and coping strategies was conducted with the view to develop a preliminary integrative framework that attempts to explain the various contexts that influence the learning experience of WIRHD candidates. The paper concludes with some recommended strategies for helping WIRHD candidates to manage the challenges associated with their learning process.
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Currently, recommender systems (RS) have been widely applied in many commercial e-commerce sites to help users deal with the information overload problem. Recommender systems provide personalized recommendations to users and thus help them in making good decisions about which product to buy from the vast number of product choices available to them. Many of the current recommender systems are developed for simple and frequently purchased products like books and videos, by using collaborative-filtering and content-based recommender system approaches. These approaches are not suitable for recommending luxurious and infrequently purchased products as they rely on a large amount of ratings data that is not usually available for such products. This research aims to explore novel approaches for recommending infrequently purchased products by exploiting user generated content such as user reviews and product click streams data. From reviews on products given by the previous users, association rules between product attributes are extracted using an association rule mining technique. Furthermore, from product click streams data, user profiles are generated using the proposed user profiling approach. Two recommendation approaches are proposed based on the knowledge extracted from these resources. The first approach is developed by formulating a new query from the initial query given by the target user, by expanding the query with the suitable association rules. In the second approach, a collaborative-filtering recommender system and search-based approaches are integrated within a hybrid system. In this hybrid system, user profiles are used to find the target user’s neighbour and the subsequent products viewed by them are then used to search for other relevant products. Experiments have been conducted on a real world dataset collected from one of the online car sale companies in Australia to evaluate the effectiveness of the proposed recommendation approaches. The experiment results show that user profiles generated from user click stream data and association rules generated from user reviews can improve recommendation accuracy. In addition, the experiment results also prove that the proposed query expansion and the hybrid collaborative filtering and search-based approaches perform better than the baseline approaches. Integrating the collaborative-filtering and search-based approaches has been challenging as this strategy has not been widely explored so far especially for recommending infrequently purchased products. Therefore, this research will provide a theoretical contribution to the recommender system field as a new technique of combining collaborative-filtering and search-based approaches will be developed. This research also contributes to a development of a new query expansion technique for infrequently purchased products recommendation. This research will also provide a practical contribution to the development of a prototype system for recommending cars.
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Pt/nanostructured ZnO/SiC Schottky contact devices were fabricated and characterized for hydrogen gas sensing. These devices were investigated in reverse bias due to greater sensitivity, which attributes to the application of nanostructured ZnO. The current-voltage (I-V) characteristics of these devices were measured in different hydrogen concentrations. Effective change in the barrier height for 1% hydrogen was calculated as 27.06 meV at 620°C. The dynamic response of the sensors was also investigated and a voltage shift of 325 mV was recorded at 620°C during exposure to 1% hydrogen in synthetic air.
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Speaker diarization is the process of annotating an input audio with information that attributes temporal regions of the audio signal to their respective sources, which may include both speech and non-speech events. For speech regions, the diarization system also specifies the locations of speaker boundaries and assign relative speaker labels to each homogeneous segment of speech. In short, speaker diarization systems effectively answer the question of ‘who spoke when’. There are several important applications for speaker diarization technology, such as facilitating speaker indexing systems to allow users to directly access the relevant segments of interest within a given audio, and assisting with other downstream processes such as summarizing and parsing. When combined with automatic speech recognition (ASR) systems, the metadata extracted from a speaker diarization system can provide complementary information for ASR transcripts including the location of speaker turns and relative speaker segment labels, making the transcripts more readable. Speaker diarization output can also be used to localize the instances of specific speakers to pool data for model adaptation, which in turn boosts transcription accuracies. Speaker diarization therefore plays an important role as a preliminary step in automatic transcription of audio data. The aim of this work is to improve the usefulness and practicality of speaker diarization technology, through the reduction of diarization error rates. In particular, this research is focused on the segmentation and clustering stages within a diarization system. Although particular emphasis is placed on the broadcast news audio domain and systems developed throughout this work are also trained and tested on broadcast news data, the techniques proposed in this dissertation are also applicable to other domains including telephone conversations and meetings audio. Three main research themes were pursued: heuristic rules for speaker segmentation, modelling uncertainty in speaker model estimates, and modelling uncertainty in eigenvoice speaker modelling. The use of heuristic approaches for the speaker segmentation task was first investigated, with emphasis placed on minimizing missed boundary detections. A set of heuristic rules was proposed, to govern the detection and heuristic selection of candidate speaker segment boundaries. A second pass, using the same heuristic algorithm with a smaller window, was also proposed with the aim of improving detection of boundaries around short speaker segments. Compared to single threshold based methods, the proposed heuristic approach was shown to provide improved segmentation performance, leading to a reduction in the overall diarization error rate. Methods to model the uncertainty in speaker model estimates were developed, to address the difficulties associated with making segmentation and clustering decisions with limited data in the speaker segments. The Bayes factor, derived specifically for multivariate Gaussian speaker modelling, was introduced to account for the uncertainty of the speaker model estimates. The use of the Bayes factor also enabled the incorporation of prior information regarding the audio to aid segmentation and clustering decisions. The idea of modelling uncertainty in speaker model estimates was also extended to the eigenvoice speaker modelling framework for the speaker clustering task. Building on the application of Bayesian approaches to the speaker diarization problem, the proposed approach takes into account the uncertainty associated with the explicit estimation of the speaker factors. The proposed decision criteria, based on Bayesian theory, was shown to generally outperform their non- Bayesian counterparts.
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It is commonly held that the ability of the estimator to apply professional skill and judgement is an important factor in the production of an accurate cost estimate. This chapter identifies these abilities and attributes of the individual estimator that affects estimating accuracy. These human factors are examined under the headings of the role of the estimators, skills of the estimator, characteristics of the estimator, interpretation of data, and the influence of expertise.
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The concept of market-driven rather than product-driven quality management has been given prominence through the report of a recent inquiry into the performance of the Hong Kong construction industry. The report submitted to the Government of Hong Kong in 2001 establishes a new vision of ‘an integrated industry that is capable of continuous improvement towards excellence in the market-driven environment’. Given the current economic downturn, major contractors are facing many challenges to realize this new quality oriented vision. This paper addresses the critical and timely issue of applying quality management to the project delivery process in Hong Kong. The paper attempts to capture and critically examine management perceptions of quality management aspects as applied to a local large-scale road construction project. Based on the analysis of questionnaire feedback and face-to-face interviews, the paper reveals key attributes of a successful application of quality management approaches, and identifies a mechanism for facilitating such implementation.
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Electronic word-of-mouth (eWOM) has gained significant attention from academics and practitioners since it has become an important source of consumers’ product information, which can influence consumer purchase intentions (Cheung & Lee, 2012). eWOM exchanges exist in two types of online communities: online communities of practice and online communities of interest. A few prior studies in online communities of interest have examined members’ motivations for product knowledge exchange (Hung & Li, 2007; Ma & Agarwal, 2007). However, there is a lack of understanding of member motivations for exchanging social bonds and enjoyment in addition to exchanging knowledge pertaining to products in the community. It is important to have an initial comprehension of motivation as an antecedent of these three eWOM exchanges so as to be able to determine the driving factors that lead members to generate eWOM communication. Thus, the research problem "What are the driving factors for members to exchange eWOM in an online community?" was justified for investigation. The purpose of this study was to examine different member motivations for exchanging three types of eWOM. Resource exchange theory and theory on consumer motivation and behavior were applied to develop a conceptual framework for this study. This study focused on an online beauty community since there is an increasing trend of consumers turning to online beauty resources so as to exchange useful beauty product information (SheSpot, 2011). As this study examined consumer motivation in an online beauty community, a web-based survey was the most effective and efficient way to gain responses from beauty community members and these members were appropriate samples from which to draw a conclusion about the whole population. Multiple regression analysis was used to test the relationships between member motivations and eWOM exchanges. It was found that members have different motivations for exchanging knowledge, social bonds, and enjoyment related to products: self-development, problem solving support, and relaxation, respectively. This study makes three theoretical contributions. First, this study identifies the influence of self-development motivation on knowledge exchange in an online community of interest, just as this motivation has previously been found in online communities of practice. This study highlights that members of the two different types of online communities share similar goals of knowledge exchange, despite the two communities evincing different attributes (e.g., member characteristics and tasks’ objectives). Further, this study will assist researchers to understand other motivations identified by prior research in online communities of practice since such motivations may be applicable to online communities of interest. Second, this study offers a new perspective on member motivation for social bonding. This study indicates that in addition to social support from friends and family, consumers are motivated to build social bonds with members in an online community of interest since they are an important source of problem solving support in regard to products. Finally, this study extends the body of knowledge pertaining to member motivation for enjoyment exchange. This study provides a basis for researchers to understand that members in an online community of interest value experiential aspects of enjoyable consumption activities, and thus based on group norms, members have a mutual desire for relaxation from enjoyment exchange. The major practical contribution is that this study provides an important guideline for marketing managers to develop different marketing strategies based on member motivations for exchanging three types of eWOM in an online community of interest, such as an online beauty community. This will potentially help marketing managers increase online traffic and revenue, and thus bring success to the community. Although, this study contributes to the literature by highlighting three distinctive member motivations for eWOM exchanges in an online community of interest, there are some possible research limitations. First, this study was conducted in an online beauty community in Australia. Hence, further research should replicate this study in other industries and nations so as to give the findings greater generalisability. Next, online beauty community members are female skewed. Thus, future research should examine whether similar patterns of motivations would emerge in other online communities that tend to be populated by males (e.g., communities focused on football). Further, a web-based survey has its limitations in terms of self-selection and self-reporting (Bhatnagar & Ghose, 2004). Therefore, further studies should test the framework by employing different research methods in order to overcome these weaknesses.
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Predicate encryption (PE) is a new primitive which supports exible control over access to encrypted data. In PE schemes, users' decryption keys are associated with predicates f and ciphertexts encode attributes a that are specified during the encryption procedure. A user can successfully decrypt if and only if f(a) = 1. In this thesis, we will investigate several properties that are crucial to PE. We focus on expressiveness of PE, Revocable PE and Hierarchical PE (HPE) with forward security. For all proposed systems, we provide a security model and analysis using the widely accepted computational complexity approach. Our first contribution is to explore the expressiveness of PE. Existing PE supports a wide class of predicates such as conjunctions of equality, comparison and subset queries, disjunctions of equality queries, and more generally, arbitrary combinations of conjunctive and disjunctive equality queries. We advance PE to evaluate more expressive predicates, e.g., disjunctive comparison or disjunctive subset queries. Such expressiveness is achieved at the cost of computational and space overhead. To improve the performance, we appropriately revise the PE to reduce the computational and space cost. Furthermore, we propose a heuristic method to reduce disjunctions in the predicates. Our schemes are proved in the standard model. We then introduce the concept of Revocable Predicate Encryption (RPE), which extends the previous PE setting with revocation support: private keys can be used to decrypt an RPE ciphertext only if they match the decryption policy (defined via attributes encoded into the ciphertext and predicates associated with private keys) and were not revoked by the time the ciphertext was created. We propose two RPE schemes. Our first scheme, termed Attribute- Hiding RPE (AH-RPE), offers attribute-hiding, which is the standard PE property. Our second scheme, termed Full-Hiding RPE (FH-RPE), offers even stronger privacy guarantees, i.e., apart from possessing the Attribute-Hiding property, the scheme also ensures that no information about revoked users is leaked from a given ciphertext. The proposed schemes are also proved to be secure under well established assumptions in the standard model. Secrecy of decryption keys is an important pre-requisite for security of (H)PE and compromised private keys must be immediately replaced. The notion of Forward Security (FS) reduces damage from compromised keys by guaranteeing confidentiality of messages that were encrypted prior to the compromise event. We present the first Forward-Secure Hierarchical Predicate Encryption (FS-HPE) that is proved secure in the standard model. Our FS-HPE scheme offers some desirable properties: time-independent delegation of predicates (to support dynamic behavior for delegation of decrypting rights to new users), local update for users' private keys (i.e., no master authority needs to be contacted), forward security, and the scheme's encryption process does not require knowledge of predicates at any level including when those predicates join the hierarchy.
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Understanding network traffic behaviour is crucial for managing and securing computer networks. One important technique is to mine frequent patterns or association rules from analysed traffic data. On the one hand, association rule mining usually generates a huge number of patterns and rules, many of them meaningless or user-unwanted; on the other hand, association rule mining can miss some necessary knowledge if it does not consider the hierarchy relationships in the network traffic data. Aiming to address such issues, this paper proposes a hybrid association rule mining method for characterizing network traffic behaviour. Rather than frequent patterns, the proposed method generates non-similar closed frequent patterns from network traffic data, which can significantly reduce the number of patterns. This method also proposes to derive new attributes from the original data to discover novel knowledge according to hierarchy relationships in network traffic data and user interests. Experiments performed on real network traffic data show that the proposed method is promising and can be used in real applications. Copyright2013 John Wiley & Sons, Ltd.
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Purpose – This paper adds to growing research of psychiatric intensive care units (PICU) by recounting descriptions of psychiatric intensive care settings and discusses the perceptions held by nurses of the organisational interfaces, arrangements and provisions of care in these settings. Design/methodology/approach – Data gathered from focus groups held with nurses from two PICUs was used to establish terminology, defining attributes, related concepts, antecedents, values, processes and concepts related to current practices. A literature search was conducted to permit a review of the conceptual arrangements and contemporary understanding of intensive care for people experiencing acute psychiatric illness based on the perspectives held by the nurses from the focus groups. Findings – Dissonance between service needs and the needs and management of individual patients overshadow strategies to implement comprehensive recovery-oriented approaches. Three factors are reported in this paper that influence standards and procedural practice in PICU; organisational structures; physical structures; and subtype nomenclature. Practical implications – Acute inpatient care is an important part of a comprehensive approach to mental health services. Commonly intensive acute care is delivered in specialised wards or units co-located with acute mental health inpatient units mostly known as PICU. Evidence of the most effective treatment and approaches in intensive care settings that support comprehensive recovery for improved outcomes is nascent. Originality/value – Current descriptions from nurses substantiate wide variations in the provisions, design and classifications of psychiatric intensive care. Idiosyncratic and localised conceptions of psychiatric intensive care are not adequately entailing effective treatment and methods in support of recovery principles for improved and comprehensive outcomes. The authors suggest that more concrete descriptions, guidelines, training and policies for provision of intensive psychiatric health care encompassing the perspective of nursing professionals, would reinforce conceptual construction and thus optimum treatments within a comprehensive, recovery-oriented approach to mental health services.
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Recent advances in the area of ‘Transformational Government’ position the citizen at the centre of focus. This paradigm shift from a department-centric to a citizen-centric focus requires governments to re-think their approach to service delivery, thereby decreasing costs and increasing citizen satisfaction. The introduction of franchises as a virtual business layer between the departments and their citizens is intended to provide a solution. Franchises are structured to address the needs of citizens independent of internal departmental structures. For delivering services online, governments pursue the development of a One-Stop Portal, which structures information and services through those franchises. Thus, each franchise can be mapped to a specific service bundle, which groups together services that are deemed to be of relevance to a specific citizen need. This study focuses on the development and evaluation of these service bundles. In particular, two research questions guide the line of investigation of this study: Research Question 1): What methods can be used by governments to identify service bundles as part of governmental One-Stop Portals? Research Question 2): How can the quality of service bundles in governmental One-Stop Portals be evaluated? The first research question asks about the identification of suitable service bundle identification methods. A literature review was conducted, to, initially, conceptualise the service bundling task, in general. As a consequence, a 4-layer model of service bundling and a morphological box were created, detailing characteristics that are of relevance when identifying service bundles. Furthermore, a literature review of Decision-Support Systems was conducted to identify approaches of relevance in different bundling scenarios. These initial findings were complemented by targeted studies of multiple leading governments in the e-government domain, as well as with a local expert in the field. Here, the aim was to identify the current status of online service delivery and service bundling in practice. These findings led to the conceptualising of two service bundle identification methods, applicable in the context of Queensland Government: On the one hand, a provider-driven approach, based on service description languages, attributes, and relationships between services was conceptualised. As well, a citizen-driven approach, based on analysing the outcomes from content identification and grouping workshops with citizens, was also conceptualised. Both methods were then applied and evaluated in practice. The conceptualisation of the provider-driven method for service bundling required the initial specification of relevant attributes that could be used to identify similarities between services called relationships; these relationships then formed the basis for the identification of service bundles. This study conceptualised and defined seven relationships, namely ‘Co-location’, ‘Resource’, ‘Co-occurrence’, ‘Event’, ‘Consumer’, ‘Provider’, and ‘Type’. The relationships, and the bundling method itself, were applied and refined as part of six Action Research cycles in collaboration with the Queensland Government. The findings show that attributes and relationships can be used effectively as a means for bundle identification, if distinct decision rules are in place to prescribe how services are to be identified. For the conceptualisation of the citizen-driven method, insights from the case studies led to the decision to involve citizens, through card sorting activities. Based on an initial list of services, relevant for a certain franchise, participating citizens grouped services according to their liking. The card sorting activity, as well as the required analysis and aggregation of the individual card sorting results, was analysed in depth as part of this study. A framework was developed that can be used as a decision-support tool to assist with the decision of what card sorting analysis method should be utilised in a given scenario. The characteristic features associated with card sorting in a government context led to the decision to utilise statistical analysis approaches, such as cluster analysis and factor analysis, to aggregate card sorting results. The second research question asks how the quality of service bundles can be assessed. An extensive literature review was conducted focussing on bundle, portal, and e-service quality. It was found that different studies use different constructs, terminology, and units of analysis, which makes comparing these models a difficult task. As a direct result, a framework was conceptualised, that can be used to position past and future studies in this research domain. Complementing the literature review, interviews conducted as part of the case studies with leaders in e-government, indicated that, typically, satisfaction is evaluated for the overall portal once the portal is online, but quality tests are not conducted during the development phase. Consequently, a research model which appropriately defines perceived service bundle quality would need to be developed from scratch. Based on existing theory, such as Theory of Reasoned Action, Expectation Confirmation Theory, and Theory of Affordances, perceived service bundle quality was defined as an inferential belief. Perceived service bundle quality was positioned within the nomological net of services. Based on the literature analysis on quality, and on the subsequent work of a focus group, the hypothesised antecedents (descriptive beliefs) of the construct and the associated question items were defined and the research model conceptualised. The model was then tested, refined, and finally validated during six Action Research cycles. Results show no significant difference in higher quality or higher satisfaction among users for either the provider-driven method or for the citizen-driven method. The decision on which method to choose, it was found, should be based on contextual factors, such as objectives, resources, and the need for visibility. The constructs of the bundle quality model were examined. While the quality of bundles identified through the citizen-centric approach could be explained through the constructs ‘Navigation’, ‘Ease of Understanding’, and ‘Organisation’, bundles identified through the provider-driven approach could be explained solely through the constructs ‘Navigation’ and ‘Ease of Understanding’. An active labelling style for bundles, as part of the provider-driven Information Architecture, had a larger impact on ‘Quality’ than the topical labelling style used in the citizen-centric Information Architecture. However, ‘Organisation’, reflecting the internal, logical structure of the Information Architecture, was a significant factor impacting on ‘Quality’ only in the citizen-driven Information Architecture. Hence, it was concluded that active labelling can compensate for a lack of logical structure. Further studies are needed to further test this conjecture. Such studies may involve building alternative models and conducting additional empirical research (e.g. use of an active labelling style for the citizen-driven Information Architecture). This thesis contributes to the body of knowledge in several ways. Firstly, it presents an empirically validated model of the factors explaining and predicting a citizen’s perception of service bundle quality. Secondly, it provides two alternative methods that can be used by governments to identify service bundles in structuring the content of a One-Stop Portal. Thirdly, this thesis provides a detailed narrative to suggest how the recent paradigm shift in the public domain, towards a citizen-centric focus, can be pursued by governments; the research methodology followed by this study can serve as an exemplar for governments seeking to achieve a citizen-centric approach to service delivery.
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This paper addresses the question of how interim financial reporting regulation varies across the Asia-Pacific region. Using a content analysis method, the study investigates the relevant regulations in eight selected countries in the Asia-Pacific region which differ in a number of country-level attributes. We find that the regulations in the region show considerable variation in terms of the form of regulatory enforcement, reporting lag, audit requirements, and reporting form. By providing the first in-depth review of the nature of differences in interim financial reporting in key countries in the Asia-Pacific region, the findings of this study will be of interest to investors, regulators and researchers in their quest for international “convergence” in financial reporting practices.