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The aim of this study is to improve software effort estimation by incorporating straightforward mathematical principles and artificial neural network technique. Our process consists of three major steps. The first step concerns data preparation from each considered database. The second step is to reduce the number of given features by considering only those relevant ones. The final step is to transform the problem of estimating software effort to the problems of classification and functional approximation by using a feedforward neural network. Experimental data are taken from well-known public domains. The results are systematically compared with related prior works using only a few features so obtained, yet demonstrate that the proposed model yields satisfactory estimation accuracy based on MMRE and PRED measures.

Purpose – The purpose of this paper is to explore the adoption of a mobile insurance claim system (M-insurance) and develops a framework for the adoption of M-insurance by consumers. Design/methodology/approach – This study assesses mobile technology for claim management through the lens of the technology acceptance model (TAM) and diffusion of innovation (DOI) models as a major guideline, using exploratory research through in-depth interviews with four executive experts who are first movers in mobile claim motor insurance in Thailand. Semi-structured interviews and open-ended questions were used to conduct group interviews of insurance consumers who mostly use smartphones. The data were collected in a qualitative research approach from Thai insurance consumers (n=177), and contents were classified and analysed to gain strong insights into respondent opinions, comments, attitudes, behaviour, and experiences. Findings – The results indicate that the external (social) factors influence attitude and behaviour of consumers which link to their intention to adopt M-insurance. These external factors include: preference for face-to-face service; confidence of insurers in accepting claim; and risk of claim knowledge that might cause legal issues among others. In application, the findings shall meaningfully enhance insurer firms’ improvement of adoption rate and development of future features and functions of M-insurance. Research limitations/implications – This study is based on insurance consumers in each region of Thailand but focuses only on mobile claim management for motor insurance. Although the findings bring new insight and understanding of consumer preferences and behaviours, they were not tested statistically. Practical implications – The study has practical implications for motor insurance claimants who are concerned over the complicated policy conditions, the perspective risk of claim knowledge and fault admission, and the on-site investigation by surveyor for another party. These are the guidance impediments to overcome M-insurance adoption improvement. Originality/value – Previously, TAM and DOI approaches have been employed to study general adoption of M-banking by quantitative research which confirmed descriptive data and tested the hypothesis, but neglected crucial data. However, M-insurance is different from M-banking in term of features and functions, purpose and process of usage, and legal liability. Therefore, this study is one of a few empirical studies that attempt to identify insightful factors to consumer uptake of M-insurance which is in its early stage and lacks an underpinning TAM model. This study contributes by identifying insights of “pull” factors to successfully develop M-insurance in Thailand.

The increasing demand for accessing heterogeneous information sources to support global applications and decision-making requirements forces organizations to solve heterogeneity problems. One of the important problems stemming from accessing the heterogeneous data is semantic heterogeneity. A number of research efforts have been proposed to address this problem, ranging from mediator-based systems, description logic-based systems to content-descriptive metadata systems. In this paper, we propose a metadata dictionary as an assistant mechanism for solving semantic heterogeneity. The proposed metadata dictionary is designed based on domain ontology where the constituent components are defined in terms of object-oriented and set theory. An XML-based data model is employed to manipulate and express the metadata dictionary contents. The inherent flexibility of XML technology permits systemwide interoperability suitable for a web-based environment.

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