Evaluating e-commerce trust using fuzzy logic [article]

Trust is widely recognized as an essential factor for the continual development of business to customer electronic commerce (B2C EC). Many trust models have been developed, however, most are subjective and do not take into account the vagueness and ambiguity of EC trust and the customers’ intuitions and experience when conducting online transactions. In this article, we develop a fuzzy trust model using fuzzy reasoning to evaluate EC trust. This trust model is based on the information customers expect to find on an EC Website and is shown to increase customers trust towards online merchants. We argue that fuzzy logic is suitable for trust evaluation as it takes into account the uncertainties within e-commerce data and like human relationships; it is often expressed by linguistics terms rather then numerical values. The evaluation of the proposed model will be illustrated using two case studies and a comparison with two evaluation models was conducted to emphasise the importance of usin fuzzy logic

Italian translation of the questionnaire for professional training evaluation

This works illustrates the psychometric properties of the Italian version of the Questionnaire for Professional Training Evaluation (Q4TE), validated by Grohmann and Kauffeld (2013). This 12-item questionnaire provides evaluation for different training outcomes, it is time efficient and applicable to several professional contexts, and it shows sound psychometric properties. In order to test the Italian form, we led two studies. In study 1 (N=125), an EFA led to a two-factor solution accounting for short and long-term training outcomes. In study 2 (N=122) a five-model comparison was performed. Although at a first stage a two factor solutions seemed to emerge, CFA found the best fit in a 6 inter-correlated first-order factors model (satisfaction, utility, knowledge, application to practice, individual organizational results and global organizational results). Relationships with learning transfer, transfer quantity, type of training, training methodologies, and individual variables (gender, age, tenure) are explored. Limitations, research and practical implications are discussed

Measuring Institutions: The Zimbabwe Case

The current, persistent growth problem in Zimbabwe is often attributed to poor economic and political institutional frameworks characterised by insecure property rights and an unreliable rule of law. An empirical test of this hypothesis presents some methodological difficulties. Although political scientists have been constructing measures of social and political dimensions of societies for some time, such measures are not available over sufficiently long time runs to inspire confidence in their usefulness in being able to address the long-run and dynamic questions that arise when linking economic performance and institutions. The aim of the paper is to assemble a new set of political and economic institutional indicators for Zimbabwe covering the period 1946 to 2005. While the new indices span for a significantly long time period, they are highly correlated with existing, widely used institutional indices produced by the Freedom House, the Heritage Foundation and the Fraiser Institute. The new data set will contribute towards understanding the institutional dimension of Zimbabwe’s persistent economic decline.

A case-based reasoning approach to improve risk identification in construction projects

Risk management is an important process to enhance the understanding of the project so as to support decision making. Despite well established existing methods, the application of risk management in practice is frequently poor. The reasons for this are investigated as accuracy, complexity, time and cost involved and lack of knowledge sharing. Appropriate risk identification is fundamental for successful risk management. Well known risk identification methods require expert knowledge, hence risk identification depends on the involvement and the sophistication of experts. Subjective judgment and intuition usually from par1t of experts’ decision, and sharing and transferring this knowledge is restricted by the availability of experts. Further, psychological research has showed that people have limitations in coping with complex reasoning. In order to reduce subjectivity and enhance knowledge sharing, artificial intelligence techniques can be utilised. An intelligent system accumulates retrievable knowledge and reasoning in an impartial way so that a commonly acceptable solution can be achieved. Case-based reasoning enables learning from experience, which matches the manner that human experts catch and process information and knowledge in relation to project risks. A case-based risk identification model is developed to facilitate human experts making final decisions. This approach exploits the advantage of knowledge sharing, increasing confidence and efficiency in investment decisions, and enhancing communication among the project participants

A semantic Bayesian network for automated share evaluation on the JSE

Advances in information technology have presented the potential to automate investment decision making processes. This will alleviate the need for manual analysis and reduce the subjective nature of investment decision making. However, there are different investment approaches and perspectives for investing which makes acquiring and representing expert knowledge for share evaluation challenging. Current decision models often do not reflect the real investment decision making process used by the broader investment community or may not be well-grounded in established investment theory. This research investigates the efficacy of using ontologies and Bayesian networks for automating share evaluation on the JSE. The knowledge acquired from an analysis of the investment domain and the decision-making process for a value investing approach was represented in an ontology. A Bayesian network was constructed based on the concepts outlined in the ontology for automatic share evaluation. The Bayesian network allows decision makers to predict future share performance and provides an investment recommendation for a specific share. The decision model was designed, refined and evaluated through an analysis of the literature on value investing theory and consultation with expert investment professionals. The performance of the decision model was validated through back testing and measured using return and risk-adjusted return measures. The model was found to provide superior returns and risk-adjusted returns for the evaluation period from 2012 to 2018 when compared to selected benchmark indices of the JSE. The result is a concrete share evaluation model grounded in investing theory and validated by investment experts that may be employed, with small modifications, in the field of value investing to identify shares with a higher probability of positive risk-adjusted returns

Computer modeling of human decision making

Models of human decision making are reviewed. Models which treat just the cognitive aspects of human behavior are included as well as models which include motivation. Both models which have associated computer programs, and those that do not, are considered. Since flow diagrams, that assist in constructing computer simulation of such models, were not generally available, such diagrams were constructed and are presented. The result provides a rich source of information, which can aid in construction of more realistic future simulations of human decision making

Integrated Solution Support System for Water Management

Solving water management problems involves technical, social, economic, political and legal challenges and thus requires an integrated approach involving people from different backgrounds and roles. The integrated approach has been given a prominent role within the European Union¿s Water Framework Directive (WFD). The WFD requires an integrated approach in water management to achieve good ecological status of all water bodies. It consists amongst others of the following main planning stages: describing objectives, assessing present state, identifying gaps between objectives and present state, developing management plan, implementing measures and evaluating their impacts. The directive prescribes broad participation and consultation to achieve its objectives. Besides the obvious desktop software, such an integrated approach can benefit from using a variety of support tools. In addition to tools for specific tasks such as numerical models and questionnaires, knowledge bases on options and process support tools may be utilized. Water stress, defined as the lack of water of appropriate quality is one issue related to, but not specifically addressed by the WFD. However, like in the WFD, a participatory approach could be used to mitigate water stress. Similarly various tools can or need to be used in such a complex process. In the AquaStress Integrated project the Integrated Solution Support System (I3S ¿ I-triple-S) is developed. One of the cornerstones of the approach taken in AquaStress is that organizing available knowledge provides sufficient information to improve the possibility to make a water stress mitigation process truly end-user driven, meaning that dedicated local information is only collected after specific need is expressed by the stakeholders in the process. The novelty of the I3S lies in the combination of such knowledge stored in knowledge-bases, with adaptable workflow management facilities and with specific task-oriented tools ¿ all originating from different sources. This paper describes the I3S