Hyperlink Analysis of E-commerce Websites for Business Intelligence: Exploring Websites of Top Retail Companies of Asia Pacific and USA

Hyperlinks, which connect web pages on the World Wide Web, are rich sources of hidden information. ECommerce Websites, which are created for different purposes from online sales to company promotion, would benefit if they receive more links from other websites as this would lead to increase the traffic to these websites. This paper analyses the structure of e-commerce websites using webometric approach to uncover any hidden information from the hyperlinks. The top 50 retail companies’ e-commerce websites each from Asia Pacific and USA are chosen for this study. Our results found a positive relationship between the external inlinks count pointing to a retail company e-commerce website and one of its business measures, sales. But no association has been found between hyperlink metrics and business measure like revenue. However this conclusion does not hold good for all categories of companies. Comparing the web presence, US private retail companies are more visible on the Web than the Asia pacific retailers. Furthermore this study has found that counts of links pointing to a retail websites are positively correlated with the website age. That is older websites in English language received more external inlinks. Such a correlation does not exist for Japan, China and Korean language websites

Characterisation of e-commerce website structures using webometrics and social network analysis methods

The hyperlinks among Web pages of intra- and inter- Websites, are believed to have valuable information that is hidden in the structure. Exploitation of these hyperlinks using Web structure mining methods is expected to increase the understanding about how Website’s internal and external hyperlink structures are interlinked and what information they hold. This research aims to characterise the commercial Website structure of a company and investigate its relationship with the company’s Web traffic and business performance. It attempts to extract the overall structure of commercial Websites and identify the optimal internal structural design. This structure represents the Website page organisation that ensures easy navigation and improved usability which subsequently increases the Web traffic. Data for this study comes from the top five hundred Asia Pacific retail companies as they are the leaders in the retail industry of Asia Pacific region and have well established Websites. The retail companies are divided into seven subgroups based on their retail sector

Modelling Efficiency of Electric Utilities Using Three Stage Virtual Frontier Data Envelopment Analysis with Variable Selection by Loads Method

Electric utility regulators and policy makers implement incentive-based regulation to improve electric utilities efficiency or to manage the cost of electricity. However, poorly implemented regulation may produce undesired results such as low reliability or poor quality of service. Moreover, the competition within the electricity sector is likely to be low because of the high barriers to entry, vertically integrated electric utilities, and high capital requirements. Therefore, benchmarking exercises allow policy makers and regulators to gauge the relative efficiency of electric utilities and help them to reward or penalize the electric utilities accordingly. In this study, we examined the variables that significantly influence the efficiency of electric utilities and developed an optimum method to measure the efficiency of the electric utilities. The results of the efficiency measurement were then used to rank the electric utilities. The result of this study indicates that there are 13 variables that significantly affect the efficiency score of electric utilities and three stage virtual frontier data envelopment analysis (3S-VF-DEA) is the optimum method to measure the efficiency of the electric utilities

Social Networking Sites as Communication Tool for Dengue Related Healthcare and Wellness Information

Despite the fact the government agencies and healthcare organizations make numerous efforts to prevent and control dengue epidemic, still it is a challenge. Lack of citizen's awareness of the infectious disease is one of the reasons that hampers their effectiveness. The need to re-examine and understand how the public at large view the dengue monitoring and prevention efforts motivates this study. Knowing the popularity and reach of social networking sites (SNS), understanding their strengths and weaknesses as health education tool would be a timely call. This empirical study aims to integrate social support theory to an existing theoretical model to test the users' intention to use SNS for healthcare and wellness information focusing on dengue related information. The current study found that Malaysians preferred to use SNS for dengue related healthcare and wellness information. This result suggests that dengue related monitoring and prevention activities can consider to use SNS as a potential communication tool to increase its reach to citizens

Exploring hyperlink structure of electronic commerce websites: A webometric study

Hyperlink analysis, an emerging research area in web structure mining, extracts hidden information from hyperlink data. This study analyses the websites of USA's best 50 small companies to determine the association between the Webometrics data and business performance measures as well as traffic ranking. The results show that there is an association between the Webometrics data and the company's business information as well as traffic ranking. This suggests that Webometrics data could be used as an indicator for evaluating the business performance of the company as well as the visibility of its website to a target audience

Measuring Efficiency of Electric Utilities Using Hybrid Algorithm

Electric utility regulators and policy makers implement incentive-based regulations to improve electric utilities’ efficiency and to manage the cost of electricity. However, poorly implemented regulations may produce undesired results such as low reliability and poor quality of service. Purpose- The purpose of this study is to measure the efficiency of electric utilities and benchmark electric utilities in Malaysia against other utilities worldwide. Since benchmarking of electric utilities is a fairly under researched subject, this study will contribute to the existing body of knowledge by improving the understanding of this subject.

Predicting Student's Soft Skills Based on Socio-Economical Factors: An Educational Data Mining Approach

Recent changes in the labor market and higher education sector have made graduates' employability a priority for researchers, governments, and employers in developed and emerging nations. There is, however, still a dearth of study about whether graduate students acquire the employability skills that businesses want of them because of their higher education. To determine a student's future employment and career path, it is critical to evaluate their soft skills. An emerging area called educational data mining (EDM) aims to gather enormous volumes of academic data produced and maintained by educational institutions and to derive explicit and specific information from it. This paper aims to predict students' soft skills such as professional, analytical, linguistic, communication, and ethical skills, based on their socio-economic, academic, and institutional data by leveraging data mining methods and machine learning techniques. All five soft skills were predicted using prediction models created using linear regression, probabilistic neural networks, and simple regression tree techniques. This study used a dataset from an open source that Universidad Technologica de Bolivar published. It covers academic, social, and economic data for 12,411 students. The experimental results demonstrated that the linear regression algorithm performed better than the others in predicting all five soft skills compared to machine learning methods. This finding can assist higher education institutions in making informed decisions, providing tailored support, enhancing student success and employability, and continuously modifying their programs to meet the needs of students

Real-time prediction of free lime in cement clinker using support vector machine algorithm

Free lime content is an important quality parameter in the production of clinker, targeted between 0.5% to 1.5%. Existing studies have tried to predict absolute free lime content, using soft sensors data, with limited success due to the complexity of the clinker burning process. Subject matter experts believe that, instead of predicting the free lime absolute value, predicting free lime quality as good, over-burn, or under-burn is more practically beneficial. This study aims to predict the free lime clinker quality as good or under-burn by leveraging data mining methods and machine learning techniques. Seven months of hourly data pertinent to rotary kiln feed chemistry and operation parameters were collected from a real operational cement plant. Classification models were built using support vector machine (SVM). The SVM produced a sensitivity value of 0.998 for good clinker class and 0.865 for under-burn class with an accuracy of 96%. The availability of these predictions in real time can help plant operators to avoid under-burning and over-burning. Such insights will assist relevant cement plants to reduce off-specification products, coal usage, production cost, and carbon emissions

Social Media Analytics for Dengue Monitoring in Malaysia

Social Media provides the ability to have preventative and reactive information widely available thus enabling the detection of public healthcare problems such as disease outbreaks at an early stage. Identifying public opinions about dengue fever will be an interesting point of reference to understand the sentiments shared by people. The aim of this paper is to study how Malaysians are actually tweeting and reacting to dengue related information. The research methodology includes data collection from social media, specifically Twitter, pre-processing, feature extraction and application of topic modelling techniques to determine the topics that are shared in tweets related to dengue information. This paper shows the preliminary results obtained from the data analysis which enhances our understanding about dengue related tweets and the users' preferences. Since using social media has become a part of daily routine for most of the Malaysians living in urban areas, it is a timely call to explore social media as a potential tool to disseminate real-time information about dengue monitoring and prevention