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Purpose — The chapter presents the practical applications of web search statistics analysis. The process description highlights the potential use of search queries and statistical data and how they could be used in various forecasting situations. The presented case is an example of applied computational intelligence and the main focus is oriented towards the decision support offered by the software mechanism and its capabilities to automatically gather, process and analyse data.

Methodology/approach — The statistics of the search queries as a source of prognostic information are analysed in a step-by-step process, starting from their content and scope, their processing and applications, and concluding with usage in a software-based intelligent framework.

Research implications — The analysis of search engine trends offers a great opportunity for many areas of research. Into the future, deploying this information in the prognosis will further develop intelligent data processing.

Practical implications — This functionality offers a unique possibility, impossible until now, to observe, estimate and predict various processes using wide, precise and accurate behaviour observations. The scope and quality of data allow practitioners to successfully use it in various prognostic problems (i.e. political, medical, or economic).

Originality/value of paper — The chapter presents practical implications of technology. The chapter then highlights potential areas that would benefit from the analysis of queries statistics. Moreover, it introduces ‘WebPerceiver’, an intelligent platform, built to make the analysis and usage of search trends easier and more generally available to a wide audience, including non-skilled users.

Intensive traffic often occurs in web‐enabled business processes hosted by travel industry and government portals. An extreme case for intensive traffic is flash crowd situations when the number of web users spike within a short time due to unexpected events caused by political unrest or extreme weather conditions. As a result, the servers hosting these business processes can no longer handle overwhelming service requests. To alleviate this problem, process engineers usually analyze audit trail data collected from the application server and reengineer their business processes to withstand unexpected surge in the visitors. However, such analysis can only reveal the performance of the application server from the internal perspective. This paper aims to investigate this issue.

This paper proposes an approach for analyzing key performance indicators of traffic intensive web‐enabled business processes from audit trail data, web server logs, and stress testing logs.

The key performance indicators identified in the study's approach can be used to understand the behavior of traffic intensive web‐enabled business processes and the underlying factors that affect the stability of the web server.

The proposed analysis also provides an internal as well as an external view of the performance. Moreover, the calculated key performance indicators can be used by the process engineers for locating potential bottlenecks, reengineering business processes, and implementing contingency measures for traffic intensive situations.

This paper aims to share some experiences and practical activities related to the use and management of usage data in the Digital Resource Acquisition Alliance of Chinese Academic Libraries (DRAA) as a reference for library consortia engaged in providing usage statistics services of e-resources to member libraries.

A literature review and online survey are used to analyze the research and practice of e-resources usage statistics conducted internationally. The case of DRAA is introduced to present how DRAA develops usage statistics services and promotes the implementation of the Standardized Usage Statistics Harvesting Initiative (SUSHI) to deliver usage statistics to member libraries. Future developments and enhancements are also described.

The main actions taken by DRAA to develop usage statistics services are as follows: development of the DRAA Usage Statistics Portal to provide a single point of access to usage statistics from participating publishers on behalf of member libraries; development of a SUSHI client, taking the lead in promoting SUSHI implementation to automatically obtain usage statistics in Chinese academic libraries; establishment of a working group on usage statistics and the China Academic Library and Information System/DRAA Standards and Recommended Practices Research Task Group to form a long-term mechanism for monitoring and gathering usage statistics; and strengthening of the understanding and application of standards and best practices for libraries and vendors in China. Scheduled enhancements in the future include a deep analysis and utilization of usage statistics, the promotion of Counting Online Usage of NeTworked Electronic Resources and SUSHI to Chinese academic resource publishers and raising awareness about normalizing usage statistics.

This paper has pertinence and wider implications for library consortia engaged in providing e-resources usage statistics services to member libraries.

This paper aims to explore the developing trend of higher pedagogy, to promote the research of higher pedagogy to be more canonical and scientific and to improve the higher education theory.

The utility research uses a method of quantitative study, namely “content analysis”, to estimate and analyze the higher education theory literature on ten dimensionalities which include theme, author, abstract, keywords, subject, proposing of the issue, definition of key terms, research methods, conclusion, reference and annotations from 1996 to 2006 in China.

The analysis of the selected 250 academic theses and reports in the field of higher education shows that academic research and theoretical standard have been improved, meanwhile academic criterion have been formed by degrees in higher pedagogy within ten years. At the same time, there are still some problems in the papers and reports the authors have selected such as title, key words, proposing of the issue, researching method and conclusion.

This paper sums up the trend of research on higher education in China for the past ten years, and points out the problems in this trend and then proposes ways to improve the research of higher education in China.

This paper aims to contribute to the approaches based on traditional industry concentration statistics for identifying clusters by complementing them with the techniques of exploratory spatial data analysis (ESDA).

Using a sample with 34,500 observations retrieved from the social information annual report released by Brazil Ministry of Labor and Employment, the methodology was designed to make a comparison between the application of industry concentration statistics and ESDA statistics.

As the results show, the geographic distribution measures proved to be fundamental for longitudinal studies on regional dynamics and industrial agglomerations, and the local indicator of spatial association statistic tends to overcome the limitation of the industry concentration approach.

In the period considered, due to economic, structural and circumstantial questions, activities linked to the transformation industry have been losing ground in the value creation process in Brazil. In this sense, the study of other industries may generate other types of insights that should be considered in the process of regional development.

This paper offers a critical analysis of empirical approaches and methodological advances with an emphasis on the treatment of special effects: spatial dependence, spatial heterogeneity and spatial scale. However, the regional dynamic presents a temporal dimension and a spatial dimension. The role of space has increasingly attracted attention in the analysis of economic changes. This work has identified opportunities for incorporating spatial effects in regional analysis over time.

The purpose of this paper is to discuss the reliability of official Chinese government statistics in general, overview the evolution of China's S&T (science and technology) statistical system while highlighting the main sources of such statistics, point out some of the particular problems related to China's S&T statistics, and provide perspectives about how to best use and interpret these numbers.

Statistics of China's human resources in science and technology has been used to illustrate how such S&T statistics should be interpreted.

While the S&T data collection involving multiple government ministries causes problems, the interpretation of the data, including reconciling data from different sources and piecing information together, poses challenges to drawing an appropriate and overall picture of the development of S&T in China. In order to achieve a better understanding of China's S&T statistics, student researchers of Chinese science and technology have to comprehend the definitions, exhaust all the sources, and find and recognize discrepancies.

This paper represents the first effort to examine China's S&T statistical system, an important source of information regarding China's S&T development.

The purpose of this paper is to emphasize the need to engender a positive attitude toward business analytics in order for firms to more effectively transform into data-driven businesses, and for business schools to better prepare future managers.

This paper develops and validates a measurement instrument that captures the attitude toward business statistics, the foundation of business analytics. A multi-stage approach is implemented and the validation is conducted with a sample of 311 students from a business school.

The instrument has strong psychometric properties. It is designed so that it can be easily extrapolated to professional contexts and extended to the entire domain of business analytics.

As the advent of a data-driven business world will impact the way organizations function and the way individuals think, work, communicate and interact, it is crucial to engage a transdisciplinary dialogue among domains that have the expertise to help train and transform current and future professionals.

The contribution provides educators and organizations with a means to measure and monitor attitudes toward statistics, the most anxiogenic component of business analytics. This is a first step in monitoring and developing an analytics mindset in both managers and students.

By demonstrating how the advent of the data-driven business era is transforming the DNA and functioning of organizations, this paper highlights the key importance of changing managers’ and all employees’ (to a lesser extent) mindset and way of thinking.

This study aims to identify the appropriate combination of attributes that must be present to deliver value in a new product for a pharmaceutical enterprise.

The application object was the Metronidazole analytical standard, using choice experiments to product attributes and price.

The practical results indicate that consumer value anticipation allows entry into the market with higher competitiveness.

Conceptually, it uses a value delivery approach, generally applied to large companies, in a case aimed at enterprises. In practice, for the enterprise studied, the value anticipation by the consumer allows entry into the market with higher competitiveness.

The purpose of this paper is to attempt to verify the quality of the survey instrument of office investors in rationalising green office building investment in the city of Kuala Lumpur using the Rasch measurement method. It investigates whether the quality of the data obtained from the survey is statistically acceptable and aims to ensure that the scales used are based on the same measurement model and fit with the Rasch model.

In achieving this objective, a questionnaire survey was developed consisting of six sections. Some 394 questionnaires were distributed, and in total, 106 responses were received from office investors who own and lease office buildings in the Federal Territory of Kuala Lumpur. The data obtained from this survey were entered into Rasch software, and the analysis aims to consider three main parameters, specifically: point measure correlation 0.32 < x < 0.8; outfit mean squared 0.5 < y < 1.5; and outfit z-standard −2 < z < 2. It also provides a separable or independent measurement instrument for the parameters of the research object.

The analysis performed using the Rasch model confirmed that all items in the questionnaire construct were statistically reliable and valid. The Rasch analysis consists of, namely, the summary statistics; item unidimensionality to provide interval measures of item endorsements and fit statistics on persons involved; and items for further investigation. Unidimensionality, as a pre-requisite to the Rasch analysis, provides statistics on whether the items are on the same latent variable intended by the instrument. The results were also supported by Cronbach’s alpha at 0.91 which showed excellent reliability for person data. The results showed that the summary statistics, unidimensionality and item fit analysis were excellent.

This paper introduces the application of the Rasch analysis as a provision for a new dimension and technique in examining data reliability and validity of the instrument.