Search results

An important issue in online auditing is how to improve the reliability of online auditing in order to reduce the overall audit risk. In this paper, a reliability assessment and early-warning method of online auditing based on RC (rank centroid), AHP (analytic hierarchy process) and GM (1,1) is proposed from the perspective of information technology (IT) audit risk control.

The paper begins by structuring the AHP hierarchy to the reliability assessment of online auditing used in China. Then, RC is used to rank the importance of the assessment criteria. Pairwise comparisons of criteria are made based on the rank results of RC, and this leads to a matrix of comparisons. Next, the comparison matrices are translated into weights, and the reliability assessment and early-warning model of online auditing is constructed using the GM (1,1) model. A case illustration is given to analyze the application of this method.

Research results show that the reliability of the evaluation method designed in this paper is rigorous and effective. The reliability assessment and early-warning method of online auditing based on RC/AHP/GM (1,1) can assess and give an effective early warning of reliability changes in an online auditing system, which can meet the needs of current online auditing projects.

The results of this study have good potential for widespread future implementation of online auditing projects.

An effective reliability assessment and early-warning method of online auditing is proposed from the perspective of IT audit risk control in this study.

The purpose of this paper is to overcome the drawbacks of analytic hierarchy process in solving complex decision-making problems, especially for the evaluation of enterprise technology innovation ability (ETIA). Because interval type-2 fuzzy sets (IT2 FSs) can handle uncertainty linguistic variables in a more flexible and precise way than type-1 fuzzy sets with their second fuzzy membership functions, a fuzzy ANP method with IT2 FSs is proposed to evaluate the ETIA.

The criteria of evaluation on ETIA are identified and an evaluation model for ETIA is constructed on the basis of the application analysis of ETIA and theoretical design of ANP. In addition, two different ranking methods of IT2 FSs are applied in processing the relationships between influence factors of ETIA.

By using the proposed interval type-2 fuzzy ANP (IT2 FANP) method, the efficiencies of the whole evaluation of ETIA can be measured and the important factors in the ETIA can also be determined. Compared with the type-1 FANP through the ranking results, the proposed IT2 FANP is more reasonable and robust for the evaluation of ETIA.

The proposed IT2 FANP method is applied on the evaluation of ETIA. With respect to the application, the proposed method can be used to evaluate many more complex problems that contain feedback and circular relationships.

The proposed IT2 FANP approach can solve the complexities and uncertainties at the same time. Considering the subjective initiative of decision-makers and the feedback between influence factors, the proposed method is more efficient than the existing type-1 approaches in the literature.

The purpose of this paper is to evolve a guideline for scientists and development engineers to the failure behavior of electro-optical target tracker system (EOTTS) using fuzzy methodology leading to success of short-range homing guided missile (SRHGM) in which this critical subsystems is exploited.

Technology index (TI) and fuzzy failure mode effect analysis (FMEA) are used to build an integrated framework to facilitate the system technology assessment and failure modes. Failure mode analysis is carried out for the system using data gathered from technical experts involved in design and realization of the EOTTS. In order to circumvent the limitations of the traditional failure mode effects and criticality analysis (FMECA), fuzzy FMCEA is adopted for the prioritization of the risks. FMEA parameters – severity, occurrence and detection are fuzzifed with suitable membership functions. These membership functions are used to define failure modes. Open source linear programming solver is used to solve linear equations.

It is found that EOTTS has the highest TI among the major technologies used in the SRHGM. Fuzzy risk priority numbers (FRPN) for all important failure modes of the EOTTS are calculated and the failure modes are ranked to arrive at important monitoring points during design and development of the weapon system.

This paper integrates the use of TI, fuzzy logic and experts’ database with FMEA toward assisting the scientists and engineers while conducting failure mode and effect analysis to prioritize failures toward taking corrective measure during the design and development of EOTTS.

The purpose of this paper is to develop a systematic approach for business customer segmentation.

This study proposes an approach for business customer segmentation that integrates clustering and multi-criteria decision making (MCDM). First, proper segmentation variables are identified and then customers are grouped by using hierarchical and partitional clustering algorithms. The approach extended the recency-frequency-monetary (RFM) model by proposing five novel segmentation variables for business markets. To confirm the viability of the proposed approach, a real-world application is presented. Three agglomerative hierarchical clustering algorithms namely “Ward’s method,” “single linkage” and “complete linkage,” and a partitional clustering algorithm, “k-means,” are used in segmentation. In the implementation, fuzzy analytic hierarchy process is employed to determine the importance of the segments.

Business customers of an international original equipment manufacturer (OEM) are segmented in the application. In this regard, 317 business customers of the OEM are segmented as “best,” “valuable,” “average,” “potential valuable” and “potential invaluable” according to the cluster ranks obtained in this study. The results of the application reveal that the proposed approach can effectively be used in practice for business customer segmentation.

The success of the proposed approach relies on the availability and quality of customers’ data. Therefore, design of an extensive customer database management system is the foundation for any successful customer relationship management (CRM) solution offered by the proposed approach. Such a database management system may entail a noteworthy level of investment.

The results of the application reveal that the proposed approach can effectively be used in practice for business customer segmentation. By making customer segmentation decisions, the proposed approach can provides firms a basis for the development of effective loyalty programs and design of customized strategies for their customers.

The proposed segmentation approach may contribute firms to gaining sustainable competitive advantage in the market by increasing the effectiveness of CRM strategies.

This study proposes an integrated approach for business customer segmentation. The proposed approach differentiates itself from its counterparts by combining MCDM and clustering in business customer segmentation. In addition, it extends the traditional RFM model by including five novel segmentation variables for business markets.

The aims of the article are to not only review existing competency models and offer a comprehensive performance-linked competency model towards sustaining competitive advantage, but also validate the proposed model in an Indian textile organisation.

The article operationalises the term “competency” and intends to develop a comprehensive performance-linked competency model after analysing the existing models with respect to competitive advantage; and the model has been validated empirically in an Indian textile company using data envelopment analysis (DEA), cross-efficiency DEA, and rank order centroid (ROC) methods.

It reveals that the comprehensive performance-linked competency model focuses on competency identification, competency scoring and aligning competency with other strategic HR functions in a three-phase systematic method which will subsequently help the organisation to sustain in the competition. It has further been shown how using DEA, cross-efficiency DEA and ROC, an organisation can align individual performances and their competencies in terms of efficiency.

If the number of competencies get increased, DEA cannot be used.

This can be applied to industry for more efficient and effective performance measurement tool.

The paper enables organizations to systematically manage their employee competences to ensure high-performance level and competitive advantage.

The paper aims to provide insight into the opportunities and impact of political risks in China and selected Asian countries on opportunities in infrastructure projects under public‐private partnership (PPP) schemes.

The impact of political risks on PPPs was investigated through an international survey among senior staff of international lenders, investors, insurers, and legal and financial advisors from the public and private sector. The surveyed political risk categories base on the Multilateral Investment Guarantee Agency Convention and literature review. They comprise six categories: currency inconvertibility and transfer restriction, expropriation, breach of contract, political violence, legal, regulatory and bureaucratic risks, and non‐governmental action risks. The survey evaluation uses fuzzy sets and non‐parametric statistics.

The findings comprise rankings of political risk factors within China and Asian countries as well as rankings of these countries with respect to the risk categories and rankings of future PPP opportunities over time. Also, survey comments are discussed.

The survey response rate is relatively low with 29 respondents. This is attributed to the specialized nature of the survey questions and topic area. It also indicates that political risks are little understood and paid attention to, though significant in impact. Owing to the chosen evaluation methods for small sample sizes, the results are robust and show high correlations with market data.

The results provide insight into the impact of political risks and the perceived magnitude of each risk category. It supports decision makers prioritizing and analyzing country risks.

The value and originality is in the use of a fuzzy‐coded survey scale to quantify perceptions on single political risk factors across China and Asian countries with focus on PPP infrastructure projects. The paper demonstrated that robust results from small sample sizes can be derived with the employed methods.

The aim of this work is to evaluate Greek newspaper websites using clustering and a number of criteria obtained from the Alexa search engine. Furthermore, a recommendation approach is proposed for matching Greek online newspapers with the profiles of potential readers. The paper presents the implementation and validation of a recommender tool that suggests to a user (based on age, education and income) an optional Greek newspaper's website to read.

A total of 25 newspaper websites were selected from the Greek information bank http://edoellada.gr. After investigating these websites one by one, this number was decreased to 16 websites due to their printing prevention, cessation or no coverage by Alexa.

Based on data obtained from Alexa, the Naftemporiki newspaper has the highest traffic rank and the Eleftherotypia newspaper the largest number of links among others. The Macedonia newspaper has the largest number of foreign users. The results of the study also show that most newspaper websites' visitors come from the UK. The expectation‐maximisation (EM) clustering algorithm classifies the 16 websites into two groups based on some common characteristics.

The proposed recommendation approach is generic because it can be applied as a recommendation solution on various types of website, such as educational or commercial. However, slight adjustments are needed depending on the nature of recommending websites.

A website administrator of an online newspaper can adapt the newspaper's features such as content and layout according to the prevailing user profile of the online newspaper. For example, a website administrator of an online newspaper whose dominant user education is “no‐college” should enable the writing style of this newspaper in a more naive way. The administrator can also add advertisements that are more suitable to readers aged between 35 and 55 years, if the most frequent age of users of this online newspaper is between 35 and 55.

The results of this research will be important not only to administrators of Greek newspaper websites but also to anyone with a need to increase the usage of a website.

The purpose of this paper is to use soft computing technique and fuzzy statistical tool to evaluate people's performance on the marketing research and time management.

Through standardized measurement system, the authors come up with real-value data to satisfy not the current needs but data itself. This is when fuzzy classification stands out and highlights the area of in-between and undefined.

The proposed metric system helps the authors to assess the distance among trapezoidal fuzzy data. The index of efficiency between observed time and ideal time is also presented.

With the ranking of fuzzy sample, the authors can examine the decision process by non-parametric testing hypothesis.

The purpose of this study is to develop a methodology in which alternate Six Sigma projects are prioritized and selected using appropriate multi-criteria decision-making (MCDM) methods in healthcare organizations. This study addresses a particular gap in implementing a systematic methodology for Six Sigma project prioritization and selection in the healthcare industry.

This study develops a methodology in which alternate Six Sigma projects are prioritized and selected using a modified Kemeny median indicator rank accordance (KEMIRA-M), an MCDM method based on a case study in healthcare organizations. The case study was hypothetically developed in the healthcare industry and presented to demonstrate the proposed framework’s applicability and validity for future decision-makers who will take place in Six Sigma project selection processes.

The study reveals that the Six Sigma project prioritized by KEMIRA-M assign the highest ranks to patient satisfaction, revenue enhancement and sigma level benefit criteria, while resource utilization and process cycle time receive the lowest rank.

The methodology developed in this paper proposes an MCDM-based approach for practitioners to prioritize and select Six Sigma projects in the healthcare industry. The findings regarding patient satisfaction and revenue enhancement mesh with the current trends that dominate and regulate the industry. KEMIRA-M provides flexibility for Six Sigma project selection and uses multiple criteria in two-criteria groups, simultaneously. In this study, a more objective KEMIRA-M method was suggested by implementing two different ranking-based weighting approaches.

This is the first study that implements KEMIRA-M in Six Sigma project prioritization and selection process in the healthcare industry. To overcome previous KEMIRA-M shortcomings, two ranking based weighting approaches were proposed to form a weighting procedure of KEMIRA-M. As the first implementation of the KEMIRA-M weighting procedure, the criteria weighting procedure of the KEMIRA-M method was developed using two different weighting methods based on ranking. The study provides decision-makers with a methodology that considers both benefit and cost type criteria for alternates and gives importance to experts’ rankings related to criteria and the performance values of alternates for criteria.

The purpose of this paper is to report a case study carried out to assess the agility and identify obstacles to agility in a supply chain. A human perception-based framework is used for the calculation of agility. The case study was carried out in a North India-based manufacturing organization.

In this study, the concept of a multi-grade fuzzy logic approach is used. Using this concept, the overall agility index has been determined. The fuzzy logic approach has been used to overcome the disadvantages such as impreciseness and vagueness using a scoring method.

From the analysis, it is observed that the organization on which the study was performed is “very agile.” After evaluating the agility level, the fuzzy performance importance index is calculated, which helps to identify the barriers of agility in the supply chain. These barriers help decision makers to implement appropriate improvement measures for improving agility level. Overall, 11 barriers were identified in the study.

Managers of the contemporary manufacturing organization have to measure the agility level of the organization and identify barriers to agility in order to survive in a competitive environment. The obstacles identified in this study are used to improve the performance of the organization. The enterprise should improve on the weak areas in order to achieve the highest agility level.

The agile supply chain (ASC) enablers proposed by previous researchers are not sufficient for the evaluation of agility of a supply chain. There are a few more ASC enablers such as customer satisfaction, flexibility and adaptability that also play a vital role in making a supply chain agile. Adding these three ASC enablers, a total of seven ASC enablers along with their attributes are being considered for the development of a conceptual model.