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In Bangladesh, there are only 0.2 million Internet users out of a population of 140 million. Because there is a lack of academic research on Internet usage, the prime objective of this study is to report the level of Internet use by university academics for their information and communication needs. The study also sought to find out whether differences exist among the various levels of academics in terms of their use of the Internet. Six categories of information and communication needs were identified and a survey conducted among the lecturers of Rajshahi University where the Internet was introduced in 2001. Findings showed that Internet use by academics is useful for some common needs and that the academic rank of users is an important factor in determining the priority of needs. It also showed that there are some barriers to adequate use of Internet resources. Suggestions are made for increased use of the Internet, to benefit the nation as a whole.

To evaluate the magnitude of public library uses and resulting values among the general people with associated socio‐economic‐cultural features of Bangladesh and thus to indicate strategies for better library impact in societal, cultural and economic development.

Primary data were collected from the users of four public libraries in the cities of Dhaka and Rajshahi considering rich library profiles and wide variety of users. Interviews were conducted based on a structured questionnaire by visiting the sample libraries that also result in studying the users and libraries closely.

Some factors like age, income, education, and gender are very important in using public library in relation to particular socio‐economic features of Bangladesh. Though the study reveals dissatisfaction in library resources, it shows a strong library impact on recreation and culture, self‐learning, social welfare, and on economic development of the country. The findings lead some recommendations for improved utilization of library.

The paper provides focus on studying the demographic variables of users to measure public library values and benefits in the areas of learning, recreation, culture, social welfare, and development.

Concerned authorities should come forward to minimize the funding and administrative barriers to make public library exclusively worthy to all with quality access.

Studying social factors are unavoidable to understand the magnitude of social inclusiveness of libraries and their strength of impact, and importantly, to ascertain the ways of comprehensive access to libraries by acquiring indication of realistic policy implementation from empirical evidence.

Development of an effective search system and interface largely depends on usability studies. The aim of this paper is to present the results of an empirical evaluation of a prototype web site search and browsing tool based on multidimensional taxonomies derived from the use of faceted classification.

A prototype Faceted Classification System (FCS), which classifies and organizes web documents under different facets (orthogonal sets of categories), was implemented on the domain of an academic institute. Facet are created from content oriented metadata, and then assembled into multiple taxonomies that describe alternative classifications of the web site content, such as by subject and location. The search and browsing interfaces use these taxonomies to enable users to access information in multiple ways. The paper compares the FCS interfaces to the existing single‐classification system to evaluate the usability of the facets in typical navigation and searching tasks.

The findings suggest that performance and usability are significantly better with the FCS in the areas of efficient access, search success, flexibility, understanding of content, relevant search result, and satisfaction. These results are especially promising since unfamiliarity often leads users to reject new search interfaces.

The results of the study in this paper can significantly contribute to interface research in the IR community, emphasizing the advantages of multidimensional taxonomies in online information collections.

The aim of this paper is to develop and implement a multidimensional classification system in the web that can provide an alternative but convenient structure for organising and finding information content.

A prototype system is developed following the views of Ranganathan's faceted classification, which is to provide multiple classifications of the web documents through content oriented metadata organised under different facets (orthogonal groups of categories).

Based on an architectural framework this study demonstrates a prototype faceted classification system (FCS) that is integrated into a general open‐source content management system and populated with a sample collection of institutional web pages/documents.

The study provides significant grounds for the IR community to improve interface structure for easy access, management, and retrieval of web information. In addition, the integration of content management tools with multidimensional taxonomies can be a new instance of a corporate web system for easy content creation, organisation, and navigation.

The purpose of this paper is to develop and implement a faceted classification structure to improve web information organization, access and navigability.

Some case studies of commercial web sites using faceted metadata were analyzed to develop the classification approach. The proposed framework adapts the facet analysis theory from Faceted Classification System (FCS) to use semantic web tools especially XML and RDF store, and ontology, and is designed to be integrated within a Content Management System (CMS). A detailed example of a faceted classification system for an academic information system is used to demonstrate the construction of an FCS from metadata.

Detailed examples show how classifying and organizing information in multidimensional hierarchies is more accessible than simple one‐dimensional taxonomic hierarchies.

A prototype, based on the proposed framework, is being developed using the web site of an academic institution as a case study.

Enhances the FCS research with a notion of integrating ontology driven faceted classification structures by XML/RDF language and content management tools. A dynamic approach to organizing and searching web information provides users with multiple ways of accessing information based on their knowledge and information needs.

There is a strong prerequisite for organizations to analyze customer review behavior to evaluate the competitive business environment. The purpose of this study is to analyze and predict customer reviews of halal restaurants using machine learning (ML) approaches.

The authors collected customer review data from the Yelp website. The authors filtered the reviews of only halal restaurants from the original data set. Following cleaning, the filtered review texts were classified as positive, neutral or negative sentiments, and those sentiments were scored using the AFINN and VADER sentiment algorithms. Also, the current study applies four machine learning methods to classify each review toward halal restaurants into its sentiment class.

The experiment showed that most of the customer reviews toward halal restaurants were positive. The authors also discovered that all of the methods (decision tree, linear support vector machine, logistic regression and random forest classifier) can correctly classify the review text into sentiment class, but logistic regression outperforms the others in terms of accuracy.

The results facilitate halal restaurateurs in identifying customer review behavior.

Sentiment and emotions, according to appraisal theory, form the basis for all interactions, facilitating cognitive functions and supporting prospective customers in making sense of experiences. Emotion theory also describes human affective states that determine motives and actions. The study looks at how potential customers might react to a halal restaurant’s consensus on social media based on reviewers’ opinions of halal restaurants because emotions can be conveyed through reviews.

This study applies machine learning approaches to analyze and predict customer sentiment based on the review texts toward halal restaurants.

The construction industry contributes to economic development by providing physical equipment and infrastructures. However, it also generates some undesirable outputs such as waste and environmental pollution, especially in developing countries. Due to the importance of the green supply chain management (GSCM) philosophy, for solving these problems, the current study aims to evaluate the drivers of GSCM adoption in the construction industry of Iran.

This research uses a descriptive and practical methodology. The participated experts in the study include senior managers of the construction department in Rasht municipality who had relevant academic education and suitable experiences in urban and industrial construction. The experts took part in both qualitative and quantitative phases of the research, namely verification of the drivers extracted from literature and ranking them in ascending order. In the quantitative phase, Step-Wise Weight Assessment Ratio Analysis (SWARA) as a new multi-criterion decision-making (MCDM) method is used to evaluate the drivers of GSCM adoption using MATLAB software.

The results show that environmental management systems, green product design and innovational capability with weights of 0.347, 0.218 and 0.143 are the most significant sub-drivers, respectively. The less important factor is an investment in environmental technology.

This study evaluated the motivational factors of GSCM in the construction industry. The findings help governments, companies and green supply chain (GSC) managers to improve their knowledge about GSCM and make the best decisions to decrease environmental pollution.

Pakistan's present war against extremists has many folds and sheds. The country's initial participation in the Afghan War in 1979 later gave birth to different extremist trends in the country. State patronage of the extremist Wahabi Islamists during the Afghan jihad opened another conflict in Pakistan, and things became more complicated. The combination of external and internal factors gave birth to the worst kind of conflict, which now has not only become dangerous for the country's own existence but also a major threat for global peace. The Afghan jihad initially started as a war against Soviet occupation and later became the hub of global jihad-war against infidels.

This chapter analyzes how external factors promoted internal contradictions in Pakistan due to which the country became not only an exporter of jihadis for the world but also the worst kind of sectarian conflicts, including. Shia–Sunni, Deobandi–Wahabi clashes, entered into in the past two decades. Such a strong link exists with Pakistan's official support to global jihad. Draft sectarian groups now head to head with their opponents have killed thousands of members of rival sectors, have strong support from external sympathizers, and have spread in the country. The well planned terrorist activities of these groups reflect the fact that support to these groups in the past is now leading to a severe crisis in Pakistan. The nexuses of these indigenous extremists like Lashkar-e-Jhangvi, Lashkar-e-Taiba, Tehrik-e-Taliban Pakistan, and Hizb-ul-Mujahideen with external terrorist organizations like Al-Qaeda, the Taliban, and Islamic Movement of Uzbekistan of Tahir Yuldasher Chechen Guerilla War has led to several bloody clashes in the country and outside.