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The aim of this paper is to use a new approach of performance evaluation, grey relation analysis (GRA), which is a concept borrowed from the study of industry and is increasingly applied to commerce. GRA is used to evaluate the relative performance of three of Australia's major banks The result of the study indicates that although the sample size is small and the distribution of data is unknown, GRA can still be successfully used in evaluating bank performance. In addition, this paper compares the GRA results with the financial statement analysis and shows that the same result can be obtained.

This paper aims to present a study which uses an innovative two‐stage data envelopment analysis (DEA) model that separates efficiency and effectiveness to evaluate the performance of 28 online stockbrokers in Taiwan from 2003 to 2005.

The approach is based on two‐stage DEA.

The results show that seven companies are CCR‐efficient in their operating efficiency; five companies are CCR‐efficient operating effectiveness and only two companies are CCR‐efficient both in operating efficiency and effectiveness. There is no apparent correlation between efficiency and effectiveness.

This paper presents a two‐stage DEA study to investigate the efficiency and effectiveness in the online stockbroking sector. The online stockbroking business is a development from the integration of the internet and the stock trading. As the stock brokerage industry is undergoing a rapid change due to the proliferation of the internet, analyzing the relative efficiency and effectiveness of online stockbrokers is important for management to understand, monitor and sustain performance.

The originality of this paper is in the use of a new conceptual framework to assess the performance of online stockbrokers in Taiwan. This study uses the two‐stage DEA in conjunction with return on assets ratio, which is widely used in financial analysis, to define and assess performance in the framework.

The purpose of this paper is to develop a multiple item scale for measuring internet banking service quality.

This research adopts the dimensions of electronic service quality (e‐service quality) and customer‐perceived service quality to develop a framework that can be used to measure internet banking service. Also, this research uses Taiwan's internet banking users as survey targets for its empirical studies.

Through the process of factor analysis, the refined scale is identified. There are five dimensions and 17 items in the measurement scale for measuring the service quality of internet banking. The five dimensions are named customer service, web design, assurance, preferential treatment, and information provision.

Based on the understanding of the key service quality dimensions and the perception of customers toward e‐service quality, managers may discover methods to improve customer satisfaction, build customer trust, and create loyal customers.

This paper adapts an e‐service quality model as the basis to measure internet banking service. This method is more suitable than that of the previous studies that are based on the traditional service quality model.

The purpose of this paper is to investigate the usage of business and simulation games in classroom teaching in the businesses schools of Taiwan and Australia.

An online questionnaire was developed and sent to 2,500 professors in Australia and 1,500 professors in Taiwan. The paper reports the survey results and compares the findings with those existing in the literature. Some of the similarities and differences are also addressed in the paper.

The study found that most of Australian and Taiwanese respondents expressed the need of a feedback system of games. In addition, most former and current users in these two countries think the web‐based games will replace the traditional ones.

The originality of this paper is the survey of game application in Taiwan and Australia. Also, its main value is for practitioners to know what, how and when gaming and simulation can be used in classroom teaching.

The purpose of this paper is to propose a “plug and play” (PnP) approach to decision modelling. An approach to building models from components based on a “LEGO block” style of manufacturing simulation and analysis. The objective of this paper is to present ideas central to PnP modelling for throughput analysis.

Firstly, the PnP concept is introduced and the proposed framework is described. Then different techniques adopted in the framework are explained, and their applications are illustrated using a case example on manufacturing throughput analysis. Finally, the implications of this research are discussed and plans for further work are outlined.

The proposed PnP approach for rapid decision modelling was capable to support two important goals: productivity improvement to ensure that managers can rapidly build up models, and increase communication and decision support efficiency to ensure that those who should be using it, can and will use it.

This research has so far introduced, described, and explained the PnP approach. The idea of PnP to support manufacturing decision modelling is new and not yet well developed. It is recognised that there are a number of additional issues that must be addressed before the proposed PnP approach is ready to make a practical impact.

The paper introduces a PnP approach to decision modelling.

The purpose of this paper is to evaluate the productivity and efficiency of Taiwan's integrated circuit (IC) industry using DEA analysis and the Malmquist index (MI).

The Malmquist index, as a total factor productivity index based on distance functions, is estimated using DEA in this study.

Results indicate that as the asset size class becomes larger and larger, the associated companies become more and more inefficient. Also, results indicate a possible scale inefficiency in the IC industry investigated.

This paper presents a DEA study to investigate the productivity and efficiency in IC industry. This performance analysis is important because Taiwan's IC industry stands in a critical global position as indicated by analysis of market share across various sub‐components of the industry. The resulting analysis might provide valuable managerial insights.

The originality of this paper is its application of specific analytical techniques to the productivity and efficiency if IC companies in Taiwan's companies. The MI is appropriate for measuring the productivity change because it does not require the assumption of a possibly unwarranted functional form on the structure of production technology, as required by the econometric method.

The purpose of this paper is to provide a novel domain‐concept association rules (DCAR) mining algorithm that offers solutions to complex cell formation problems, which consist of a non‐binary machine‐component (MC) matrix and production factors for fast and accurate decision support.

The DCAR algorithm first identifies the domain‐concept from the demand history and then performs association rule mining to find associations among machines. After that, the algorithm forms machine‐cells with a series of inclusion and exclusion processes to minimize inter‐cell material movement and intra‐cell void element costs as well as to maximize the grouping efficacy with the constraints of bill of material (BOM) and the maximum number of machines allowed for each cell.

The DCAR algorithm delivers either comparable or better results than the existing approaches using known binary datasets. The paper demonstrates that the DCAR can obtain satisfying machine‐cells with production costs when extra parameters are needed.

The DCAR algorithm adapts the idea of the sequential forward floating selection (SFFS) to iteratively evaluate and arrange machine‐cells until the result is stabilized. The SFFS is an improvement over a greedy version of the algorithm, but can only ensure sub‐optimal solutions. Practical implications – The DCAR algorithm considers a wide range of production parameters, which make the algorithm suitable to the real‐world manufacturing system settings.

The proposed DCAR algorithm is unlike other array‐based algorithms. It can group non‐binary MC matrix with considerations of real‐world factors including product demand, BOM, costs, and maximum number of machines allowed for each cell.

The purpose of this paper is to examine the use of e‐security seals on web sites and their relative impact on e‐commerce firm reputation in influencing customers' perceptions of trust in a service provider.

Two interrelated empirical studies are conducted to evaluate the use and impacts of e‐security seals in e‐commerce. An exploratory study methodology investigates the use of e‐security seals and a questionnaire survey is used to gauge consumer knowledge of seals.

Using survey data from 211 web users, the results show that 106 respondents are cognitive and affective of e‐security seals. The results also provide further clarification of the relationship between e‐security seals and sales effectiveness. The findings point towards a positive belief by consumers in e‐security seals.

Third‐party e‐security seals organisations should undertake more promotional activities and advertising to educate comsumers about the use and benefits of e‐security seals.

An important issue in e‐commerce is how trust is developed between consumers and e‐vendors. This paper investigates the use of e‐security seals and their influence on consumer confidence in the online environment.