The impact of board independence and ownership structure on the timeliness of corporate internet reporting of Irish-listed companies

Purpose – This study seeks to provide valuable new insight into the timeliness of corporate internet reporting (TCIR) by a sample of Irish-listed companies. Design/methodology/approach – The authors apply an updated version of Abdelsalam et al. TCIR index to assess the timeliness of corporate internet reporting. The index encompasses 13 criteria that are used to measure the TCIR for a sample of Irish-listed companies. In addition, the authors assess the timeliness of posting companies’ annual and interim reports to their web sites. Furthermore, the study examines the influence of board independence and ownership structure on the TCIR behaviour. Board composition is measured by the percentage of independent directors, chairman’s dual role and average tenure of directors. Ownership structure is represented by managerial ownership and blockholder ownership. Findings – It is found that Irish-listed companies, on average, satisfy only 46 per cent of the timeliness criteria assessed by the timeliness index. After controlling for size, audit fees and firm performance, evidence that TCIR is positively associated with board of director’s independence and chief executive officer (CEO) ownership is provided. Furthermore, it is found that large companies are faster in posting their annual reports to their web sites. The findings suggest that board composition and ownership structure influence a firm’s TCIR behaviour, presumably in response to the information asymmetry between management and investors and the resulting agency costs. Practical implications – The findings highlight the need for improvement in TCIR by Irish-listed companies in many areas, especially in regard to the regular updates of information provided on their web sites. Originality/value – This study represents one of the first comprehensive examinations of the important dimension of the TCIR in Irish-listed companies.

Adoption of electronic commerce tools in business procurement:enhanced buying center structure and processes

Modern procurement is being shifted from paper-based, people-intensive buying systems toward electronic-based purchase procedures that rely on Internet communications and Web-enhanced buying tools. Develops a typology of e-commerce tools that have come to characterize cutting-edge industrial procurement. E-commerce aspects of purchasing are organized into communication and transaction tools that encompass both internal and external buying activities. Further, a model of the impact of e-commerce on the structure and processes of an organization's buying center is developed. The impact of the changing buying center on procurement outcomes in terms of efficiency and effectiveness is also analyzed. Finally, implications for business-to-business marketers and researchers are discussed.

A method for automatically eliciting node weights in a hierarchical knowledge-based structure for reasoning with uncertainty

Hierarchical knowledge structures are frequently used within clinical decision support systems as part of the model for generating intelligent advice. The nodes in the hierarchy inevitably have varying influence on the decisionmaking processes, which needs to be reflected by parameters. If the model has been elicited from human experts, it is not feasible to ask them to estimate the parameters because there will be so many in even moderately-sized structures. This paper describes how the parameters could be obtained from data instead, using only a small number of cases. The original method [1] is applied to a particular web-based clinical decision support system called GRiST, which uses its hierarchical knowledge to quantify the risks associated with mental-health problems. The knowledge was elicited from multidisciplinary mental-health practitioners but the tree has several thousand nodes, all requiring an estimation of their relative influence on the assessment process. The method described in the paper shows how they can be obtained from about 200 cases instead. It greatly reduces the experts’ elicitation tasks and has the potential for being generalised to similar knowledge-engineering domains where relative weightings of node siblings are part of the parameter space.

Clustering web documents using hierarchical representation with multi-granularity

Web document cluster analysis plays an important role in information retrieval by organizing large amounts of documents into a small number of meaningful clusters. Traditional web document clustering is based on the Vector Space Model (VSM), which takes into account only two-level (document and term) knowledge granularity but ignores the bridging paragraph granularity. However, this two-level granularity may lead to unsatisfactory clustering results with “false correlation”. In order to deal with the problem, a Hierarchical Representation Model with Multi-granularity (HRMM), which consists of five-layer representation of data and a twophase clustering process is proposed based on granular computing and article structure theory. To deal with the zero-valued similarity problemresulted from the sparse term-paragraphmatrix, an ontology based strategy and a tolerance-rough-set based strategy are introduced into HRMM. By using granular computing, structural knowledge hidden in documents can be more efficiently and effectively captured in HRMM and thus web document clusters with higher quality can be generated. Extensive experiments show that HRMM, HRMM with tolerancerough-set strategy, and HRMM with ontology all outperform VSM and a representative non VSM-based algorithm, WFP, significantly in terms of the F-Score.

The impact of board independence and ownership structure on the timeliness of corporate internet reporting of Irish-listed companies

Purpose – This study seeks to provide valuable new insight into the timeliness of corporate internet reporting (TCIR) by a sample of Irish-listed companies. Design/methodology/approach – The authors apply an updated version of Abdelsalam et al. TCIR index to assess the timeliness of corporate internet reporting. The index encompasses 13 criteria that are used to measure the TCIR for a sample of Irish-listed companies. In addition, the authors assess the timeliness of posting companies’ annual and interim reports to their web sites. Furthermore, the study examines the influence of board independence and ownership structure on the TCIR behaviour. Board composition is measured by the percentage of independent directors, chairman’s dual role and average tenure of directors. Ownership structure is represented by managerial ownership and blockholder ownership. Findings – It is found that Irish-listed companies, on average, satisfy only 46 per cent of the timeliness criteria assessed by the timeliness index. After controlling for size, audit fees and firm performance, evidence that TCIR is positively associated with board of director’s independence and chief executive officer (CEO) ownership is provided. Furthermore, it is found that large companies are faster in posting their annual reports to their web sites. The findings suggest that board composition and ownership structure influence a firm’s TCIR behaviour, presumably in response to the information asymmetry between management and investors and the resulting agency costs. Practical implications – The findings highlight the need for improvement in TCIR by Irish-listed companies in many areas, especially in regard to the regular updates of information provided on their web sites. Originality/value – This study represents one of the first comprehensive examinations of the important dimension of the TCIR in Irish-listed companies.

Infer user interests via link structure regularization

Learning user interests from online social networks helps to better understand user behaviors and provides useful guidance to design user-centric applications. Apart from analyzing users' online content, it is also important to consider users' social connections in the social Web. Graph regularization methods have been widely used in various text mining tasks, which can leverage the graph structure information extracted from data. Previously, graph regularization methods operate under the cluster assumption that nearby nodes are more similar and nodes on the same structure (typically referred to as a cluster or a manifold) are likely to be similar. We argue that learning user interests from complex, sparse, and dynamic social networks should be based on the link structure assumption under which node similarities are evaluated based on the local link structures instead of explicit links between two nodes. We propose a regularization framework based on the relation bipartite graph, which can be constructed from any type of relations. Using Twitter as our case study, we evaluate our proposed framework from social networks built from retweet relations. Both quantitative and qualitative experiments show that our proposed method outperforms a few competitive baselines in learning user interests over a set of predefined topics. It also gives superior results compared to the baselines on retweet prediction and topical authority identification. © 2014 ACM.

Representing human expertise by the OWL web ontology language to support knowledge engineering in decision support systems

Clinical decision support systems (CDSSs) often base their knowledge and advice on human expertise. Knowledge representation needs to be in a format that can be easily understood by human users as well as supporting ongoing knowledge engineering, including evolution and consistency of knowledge. This paper reports on the development of an ontology specification for managing knowledge engineering in a CDSS for assessing and managing risks associated with mental-health problems. The Galatean Risk and Safety Tool, GRiST, represents mental-health expertise in the form of a psychological model of classification. The hierarchical structure was directly represented in the machine using an XML document. Functionality of the model and knowledge management were controlled using attributes in the XML nodes, with an accompanying paper manual for specifying how end-user tools should behave when interfacing with the XML. This paper explains the advantages of using the web-ontology language, OWL, as the specification, details some of the issues and problems encountered in translating the psychological model to OWL, and shows how OWL benefits knowledge engineering. The conclusions are that OWL can have an important role in managing complex knowledge domains for systems based on human expertise without impeding the end-users' understanding of the knowledge base. The generic classification model underpinning GRiST makes it applicable to many decision domains and the accompanying OWL specification facilitates its implementation.

Integrating service user and practitioner expertise within a web-based system for collaborative mental-health risk and safety management

Objectives: To develop a decision support system (DSS), myGRaCE, that integrates service user (SU) and practitioner expertise about mental health and associated risks of suicide, self-harm, harm to others, self-neglect, and vulnerability. The intention is to help SUs assess and manage their own mental health collaboratively with practitioners. Methods: An iterative process involving interviews, focus groups, and agile software development with 115 SUs, to elicit and implement myGRaCE requirements. Results: Findings highlight shared understanding of mental health risk between SUs and practitioners that can be integrated within a single model. However, important differences were revealed in SUs' preferred process of assessing risks and safety, which are reflected in the distinctive interface, navigation, tool functionality and language developed for myGRaCE. A challenge was how to provide flexible access without overwhelming and confusing users. Conclusion: The methods show that practitioner expertise can be reformulated in a format that simultaneously captures SU expertise, to provide a tool highly valued by SUs. A stepped process adds necessary structure to the assessment, each step with its own feedback and guidance. Practice Implications: The GRiST web-based DSS (www.egrist.org) links and integrates myGRaCE self-assessments with GRiST practitioner assessments for supporting collaborative and self-managed healthcare.