Showing papers in "International Journal of Information and Decision Sciences in 2010"

One-shot decision approach and its application to duopoly market

Abstract: In this paper, one-shot decision framework is initially proposed. The procedure for one-shot decision involves two steps. The first step is to identify which state of nature should be taken into account for each alternative amongst all states of nature. The states of nature chosen are called focus points. The second step is to evaluate alternatives based on focus points. As an application a newly emerging duopoly market with a short life cycle is analysed. The analysis results show that the proposed decision models can explain the behaviour of firms in such a market well. Hence, the proposed decision framework may provide appropriate approaches for analysing one-shot decision problems, which are extensively encountered in business and economics.

The application of intelligent and soft-computing techniques to software engineering problems: a review

Abstract: This paper presents a comprehensive review of the work done during 1990-2008 in the application of intelligent techniques to solve software engineering (SE) problems. The review is categorised according to the type of intelligent technique applied viz. (1) neural networks (NNs), (2) fuzzy logic, (3) genetic algorithm, (4) decision tree, (5) case base reasoning and (6) other techniques subsuming soft computing. Further, the source of the data set and the results whenever available are also provided. We find that NNs is the most often used non-parametric method in SE and there exists immense scope to apply other equally famous methods such as fuzzy logic, decision trees and rough sets. The review is going to be useful to researchers as a starting point as it provides important future research directions. For practitioners also, the review would be useful. This would eventually lead to better decision making in SE thereby ensuring better, more reliable and cost effective software products. Reference to this paper should be made as follows: Mohanty, R., Ravi, V. and Patra, M.R. (2010) 'The application of intelligent and soft-computing techniques to software engineering problems: a review', Int. J. Information and Decision Sciences, Vol. 2, No. 3, pp.233-272.

Analysing global railway passenger transport through two-staged efficiency model

Abstract: Public passenger transports have increased their popularity in recent years, however, we know very little about the technical and financial efficiency of this sector. In this study, we analyse global railway passenger countries with data envelopment analysis (DEA) method from the performance hierarchy perspective. Findings reveal that railways do not follow proposed hierarchy (only with small sub-sample exception), but instead amount of resources and completed investments play most important role regarding to performance. Efficiency level overall in passenger transportation is low, and differences between actors is significant. However, during recent decade most of the actors show increasing returns on scale.

Accuracy-based learning classification system

Abstract: In order to implement a multi-category classification system, an efficient rule set is imperative for its investigation. In this paper, such a system is being introduced. In the first phase of its kind, the C4.5 rule induction algorithm is adopted to obtain useful rule set from classification problem, following a new data set partitioning approach. Next, the presented genetic algorithm (GA) is implemented to refine the learned rules in more efficient way. The resultant system has been compared with UCS (GA-based classification system) and C4.5 (non GA-based rule induction algorithm) on a number of benchmark data sets collected from UCI (University of California at Irvine) machine learning repository. Results demonstrate that the proposed genetic approach provides marked improvement in a number of cases.

Non-linear principal component analysis-based hybrid classifiers: an application to bankruptcy prediction in banks

Abstract: This paper presents various non-linear principal component analysis (NLPCA)-based two-phase hybrid classifiers for predicting bankruptcy in banks. The first phase of the hybrids performs dimensionality reduction using NLPCA, which is implemented as a threshold accepting trained auto associative neural network (TAAANN). By considering the non-linear principal components as new inputs, second phase is invoked. In the second phase, which is essentially a classifier, we employed threshold accepting neural network (TANN), TANN without hidden layer, threshold accepting trained logistic regression (TALR) and multi layer perceptron (MLP). The results are compared with that of MLP, radial basis function neural network and found that the proposed hybrids performed well. It was observed that the NLPCA-TANN hybrid outperformed other hybrids over all data sets studied here. Further, TALR outperformed all the hybrids over all data sets. Based on the results, we infer that the hybrid classifiers performed very well by yielding high accuracies.

Adaptive record-to-record travel method to solve lexicographic goal programming models

Abstract: In this paper, a record-to-record travel (RRT) algorithm with an adaptive memory named taboo central memory (TCM) is adapted to solve the lexicographic goal programming problem. The proposed method can be applied to non-linear, linear, integer and combinatorial goal programmes. Because that the RRT has no memory, the adaptive memory TCM is inserted to diversify research. Computational experiments in several types of problems with different variable types (integer, continuous, zero-one and discrete) collected from the literature demonstrate that the proposed metaheuristic reaches high-quality solutions in short computational times. Furthermore, it requires very few user-defined parameters.

A hybrid algorithm of improved case-based reasoning and multi-attribute decision making in fuzzy environment for investment loan evaluation

Abstract: This paper presents a model to support the banking managerial decisions in the evaluation of investment plans, especially on rejecting inappropriate plans that can be done in short time (less than hour) and with minimal cost. Because there are some uncertainties in the evaluation process, our proposed model utilises fuzzy set theory to define the problem space in which an acceptance or rejection decision for a submitted investment plan is made. The model is based on lessons-learned concept and developed through the combination of case-based reasoning (CBR) and multiple attribute decision making in fuzzy environment. The model uses an enhanced version of CBR in which a novel concept as solution's truth value is implemented. A set of investment plans is evaluated to show the applicability and efficiency of the model. Different scenarios in terms of sensitivity analysis are also mentioned to capture managerial insights. Comparing the obtained results of the model with those of other algorithms shows its better proximity to human reasoning and decision making.

Identifying buyers with similar seller rating models and using their opinions to choose sellers in electronic markets

Abstract: In this paper, we provide a model for designing buyers that can learn to identify trustworthy friends that are honest and share similar opinions in a decentralised electronic market The buyer rates a seller after having purchased goods from it It also evaluates friends who provide seller information when requested, to determine their truthfulness, similarity in opinions regarding product expectations, and to identify the differences between its own and its friends' seller rating mechanisms Trustworthy friends are identified, and the seller ratings provided by them are adjusted to account for the differences in rating systems and then utilised to evaluate sellers We conducted experiments to confirm that a buyer using the proposed model is able to accurately identify trustworthy friends, accurately adjust the seller reputation ratings provided by them and has higher gains than a buyer acting alone

A comparative study of tourism performance in the Mediterranean region: a multicriteria approach

Abstract: The aim of this study is to develop and implement a methodology for the evaluation of tourism performance of some Mediterranean countries. In this paper, the multicriteria method PROMETHEE II, based on outranking relations, will be used to evaluate ten Mediterranean countries, namely Portugal, Spain, Italy, Malta, Greece, Turkey, Cyprus, Egypt, Tunisia and Morocco. For the above mentioned evaluation, 13 different criteria will be examined. These criteria contain both qualitative and quantitative information. The analysis effects of an overall ranking of the examined countries will be provided by classifying the strong and weak points of each country. Assessment of the analysis results is important in order to assist professionals in the tourism sector to make recommendations concerning marketing strategies and government policies. The study will come up with remarks about the direction of future research.

Users and information technology: analysis of task information fit model

Abstract: The objective of information technologies is multifold including many ranging from collection to presenting vital information for decision makers. It is more valuable to design systems that suits better the information requirements of the business than a tightly integrated one. This paper combines task and information characteristics at conceptual level from business management perspective. We propose a task information fit (TIF) model, which addresses the user acceptance of information systems by means of information quality provided. The model is applied and validated on a case study, which demonstrated the effect of power users on product development and user acceptance in correlation with TIF model.

Evaluating stocks in the presence of multiple criteria

Abstract: A fundamental principle of modern portfolio theory is that portfolio selection decisions are generally made using two criteria, corresponding to the first two moments of return distributions, namely the expected return and portfolio variance. One criticism over this theory, which has often been addressed both by practitioners and academics, is that it fails to embody all the decision maker's (DM's) objectives, through the various stages of the decision process. The aim of this paper is to present an alternative methodological approach for modelling one of the most crucial phases of the portfolio management process, the security evaluation phase. The main characteristic of the proposed approach is that it fully takes into account the inherent multidimensional nature of the problem, while allowing the DM to incorporate his preferences in the decision process. The validity of the proposed approach is tested through an illustrative application in Athens Stock Exchange.

Do what yourself: reevaluation of the value created by online and traditional intermediary

Abstract: Information system research posits that online intermediaries could reduce consumer search cost and improve market efficiency, and traditional intermediary would lose market share upon the advent of online intermediary. However, in reality, traditional intermediaries still hold strong market share positions. What are the advantages and disadvantages of online intermediaries and traditional intermediaries? Our research is an effort to address these questions so that we can better explain and predict intermediary's performance. We develop our analysis based on financial intermediation theory, and adopt delegated monitoring model to compare the intrinsic structures and efficiency of online intermediaries and traditional intermediaries. We achieve two important conclusions: first, when information asymmetry exists, traditional intermediary could improve consumer welfare. Second, traditional intermediary improves market welfare because it can diversify its delegated tasks. Based on these results, we also identify market segments and marketing strategies of online and traditional intermediaries.

Mathematical formulation for the second derivative of backpropagation error with non-linear output function in feedforward neural networks

Abstract: The feedforward neural network architecture uses the backpropagation learning for determination of optimal weights between different interconnected layers in order to perform as the good approximation and generalisation. The determination of the optimal weight vector is possible only when the total minimum error or global error (mean of the minimum local errors) for all patterns from the training set is supposed to minimise. In this paper, we are presenting the generalised mathematical formulation for second derivative of the error function for feedforward neural network to obtain the optimal weight vector for the given training set. The new global minimum error point can evaluate with the help of current global minimum error and the current minimised local error. The proposed method indicates that weights, which are determined from the minimisation of mean error, are more close to the optimal solution with respect to the conventional gradient descent approaches.

HAH-tree: towards a multidimensional index structure supporting different video modelling approaches in a video database management system

Abstract: This paper proposes a multidimensional distance-based index structure for video data which supports the three important video modelling approaches namely hierarchical unit-based modelling, feature-based modelling and video semantics modelling seamlessly within one single framework. These three modelling techniques collectively capture and contain the important aspects of the users' information need during content-based video retrieval. The index is built based on the low-level features of the video data, and the hierarchical containment relationships as well as the video semantics are introduced into the index space with an efficient data signature and a stochastic model, respectively. Efficient k-NN algorithms are proposed to emulate popular content-based video retrieval approaches in a multidimensional distance-based index structure. Extensive experimental results demonstrate the capability of the index structure to generate relevant query results with low computational overhead.

Building a valid web service composition using integrated service substitution and adaptation

Abstract: Traditional web service composition is often statically generated using knowledge available at the design time. In addition, they assume the final composition workflows are always executable. However, this assumption might be false since the environment can change during the execution time. Therefore, it is essential that the correctness of a partial/full composition needs to be validated and maintained during its execution. This paper utilises the notion of workflow exception handling to generate valid web service compositions. More specifically, we propose the concepts of synchronous exception handling and asynchronous service interrupt (ASI). The synchronous workflow exception is used in the initial service configuration which contains static service substitution, planning time-service adaptation and mapping time-service adaptation, while the ASI is implemented via dynamic service substitution and binding time-service adaptation. The integrated usage of the above approaches is demonstrated by an implementation of an e-hospital application.

Open source software: emerging business models

Abstract: Several small and large firms have devised business models and strategies to use open source software (OSS) gainfully. However, despite the increasing popularity and success of some OSS, there is very little academic literature that provides clarity and guidance on developing business models with OSS. This paper contributes to the existing knowledge by critically analysing the various open source business models and then building a set of business models that encompass the current trends in this field. The models presented are supported by descriptions of organisations that have used them successfully.

Analysing programming tools for the development of quality function deployment software

Abstract: Quality function deployment (QFD) is a customer focused product development process through which the quality of the product can be enormously improved. Companies in practice of utilising QFD are incessantly seeking for efficient QFD software that could facilitate designers and engineers to evaluate company's decision-making process. Development of QFD software can be accomplished through the use of a suitable programming language. The attempt is to explore the various available programming languages, analyse them and pick a suitable one for the QFD software automation. Along with an insight into traditional QFD, this paper also explores QFD from the software automation perspective. It then, provides overview of the available programming tools and comparative analysis of the same for the QFD software automation. Finally, this paper makes an attempt to justify how the chosen tool will be effective in carrying-out the task and concludes with a real life example to automate a section of QFD.

Retailer's optimal replenishment policy under cash discount and trade credit linked to order quantity

Abstract: This paper develops a model to investigate the optimal retailer's replenishment decisions when the supplier provides cash discount and delay in payments if the retailer's order quantity is greater than or equal to a predetermined quantity, and the retailer adopts the trade credit policy to stimulate his/her customer. Under these assumptions, we model the retailer's inventory system as a profit maximisation problem. Then, we establish an algorithm to locate the optimal replenishment cycle time for the retailer. Furthermore, numerical examples are presented to illustrate the results of the proposed model. Based on our analysis, it is found that the predetermined order quantity could be a successful strategy for the supplier to encourage the retailer to order large quantity and it should be set carefully since the retailer may decide not to order a quantity greater than the threshold to obtain delayed payments if the predetermined order quantity is too high.

On the integration of hybrid recommendation techniques into an agent-based transportation transactions management platform

Abstract: Diverse recommendation techniques have been already proposed and encapsulated into several e-business applications, aiming to perform a more accurate evaluation of the existing information and accordingly augment the assistance provided to the users involved. This paper reports on the development and integration of a recommendation module in an agent-based transportation transactions management system. The module is built according to a novel hybrid recommendation technique, which combines the advantages of collaborative filtering and knowledge-based approaches. The proposed technique and supporting module assist customers in considering in detail alternative transportation transactions that satisfy their requests, as well as in evaluating completed transactions. The related services are invoked through a software agent that constructs the appropriate knowledge rules and performs a synthesis of the recommendation policy.

Theory and evidence of social influence on NBA officials' decision making

Abstract: The social facilitation theory suggests that the presence of others affects an individual's behaviour. Aligned with this theory, this study theoretically investigates the impact of social influence on the decision making of sports officials, and empirically examines officials' decisions and their subsequent effects. Using archival data of 4,879 National Basketball Association games, we find that officials make decisions in favour of a home team by giving it fewer foul calls and awarding it with more free throws. This study contributes to the decision science not only by identifying a relevant social psychology theory and applying it to individuals' decision making, but also by transcending the boundaries of traditional decision-making studies and facilitating the community to conduct research in new frontiers.

Book Review: Intelligent Systems for Automated Learning and Adaptation: Emerging Trends and Applications by Raymond Chiong

Abstract: Intelligent Systems for Automated Learning and Adaptation: Emerging Trends and Applications, by Raymond Chiong. Hershey, PA, IGI Global, 2010. 401pp. ISBN: 9781605667980

Book Review: Grid Technology for Maximising Collaborative Decision Management and Support: Advancing Effective Virtual Organisations by N. Bessis

Abstract: Grid Technology for Maximising Collaborative Decision Management and Support: Advancing Effective Virtual Organisations, by N. Bessis. Hershey, USA/London, UK, Information Science Reference, 2009. 336pp. ISBN: 978-160566364-7