CSR in Private Enterprises in Developing Countries : Evidences from the Ready-Made Garments Industry in Bangladesh

"This book examines the growing trend of recognition and practices of CSR in private enterprises in developing countries. It identifies the challenges and deficiencies in these practices and proposes means for improvement. Based on a sound theoretical foundation, this book focusses on the case of Bangladesh and the ready-made garment industry to exemplify the described developments. After a brief introduction the book outlines the standards of Corporate Social Responsibility. It compares the trends in CSR practices both in developed and developing countries and then embarks on CSR practices in the private sector in Bangladesh to finally present a detailed analysis of CSR and its practices in the ready-made garment industry. The book not only compares developing countries with developed, but as well provides an assessment and analysis of different stages of CSR within the South Asian area."--published website

Discovering interesting information with advances in web technology

The Web is a steadily evolving resource comprising much more than mere HTML pages. With its ever-growing data sources in a variety of formats, it provides great potential for knowledge discovery. In this article, we shed light on some interesting phenomena of the Web: the deep Web, which surfaces database records as Web pages; the Semantic Web, which de�nes meaningful data exchange formats; XML, which has established itself as a lingua franca for Web data exchange; and domain-speci�c markup languages, which are designed based on XML syntax with the goal of preserving semantics in targeted domains. We detail these four developments in Web technology, and explain how they can be used for data mining. Our goal is to show that all these areas can be as useful for knowledge discovery as the HTML-based part of the Web.

Justice for pollution-victims in China and Australia

The concept of environmental justice is well developed in North America, but is still at the evolutionary stage in most other jurisdictions around the globe. This paper seeks to explore two jurisdictions where incidents of environmental justice are likely to be seen in the future as a result of manufacturing and mining practices. The discussion will centre upon avenues to environmental justice for both private citizens and the public at large. The first jurisdiction considered is China, where environmental liability claims brought by Chinese citizens have increased at an annual average of 25% (Yang 2011). Manufacturing is at the core of the Chinese economy and is responsible for some of the unprecedented economic growth in the region. Less discussed are the industry impacts on water and air pollution levels and the associated implications of these pollutants on local communities. China introduced the Tort Liability Law (TLL) in 2010, which may provide avenues to justice for private citizens. The other jurisdiction considered by the paper is Australia, where the mining boom has buffered the Australian economy from the global financial crisis. There is some limited case law in Australia where private citizens have made a claim in toxic torts; however the framework is underdeveloped in terms of the significant risks facing indigenous and local communities in mining areas and also by comparison to the developments of the TLL framework in China. This paper traces the regulatory responses to the affects of major industries on communities in China and Australia. From this it examines the need for environmental justice avenues that align with rule of law principles.

A data mining framework for relevance feature discovery

This thesis is a study for automatic discovery of text features for describing user information needs. It presents an innovative data-mining approach that discovers useful knowledge from both relevance and non-relevance feedback information. The proposed approach can largely reduce noises in discovered patterns and significantly improve the performance of text mining systems. This study provides a promising method for the study of Data Mining and Web Intelligence.

Stitching at the boundaries : Vietnamese garment industry workers in transnational spaces

This paper explores the interfaces between the transnational politics of labour and the experiences of Vietnamese women garment workers both in Vietnam and as migrants to other countries. As the global industries have come to organise much of the contemporary economic system, so too have they crossed national boundaries in search of cheap labour. At the same time enclaves of migrant disadvantage within the multi-ethnic nation-states of the developed world have also provided workers for the manufacture of clothing. In the case of Australia, these workers are mostly home-based and not in factories. In this paper I explore Vietnamese women's different incorporations into the garment industry in various locations – in Australia, in Vietnam, and in American Samoa. In so doing, I provide an analysis of the links between gender, global power relations and the contradictory space of transnational exchange.

Mining temporal and spatial travel regularities for transit planning

Smart Card data from Automated Fare Collection system has been considered as a promising source of information for transit planning. However, literature has been limited to mining travel patterns from transit users and suggesting the potential of using this information. This paper proposes a method for mining spatial regular origins-destinations and temporal habitual travelling time from transit users. These travel regularity are discussed as being useful for transit planning. After reconstructing the travel itineraries, three levels of Density-Based Spatial Clustering of Application with Noise (DBSCAN) have been utilised to retrieve travel regularity of each of each frequent transit users. Analyses of passenger classifications and personal travel time variability estimation are performed as the examples of using travel regularity in transit planning. The methodology introduced in this paper is of interest for transit authorities in planning and managements

Practical applications for clay-derived zeolite N : an ammonium-selective ion exchanger for industry use

Over the past ten years, scaled-up utilisation of a previously under-exploited zeolite, Zeolite N1, has been demonstrated for selective ion exchange of ammonium and other ions in aqueous environments. As with many zeolite syntheses, the required source material should contain predictable levels of aluminium and silicon and, for full-scale industrial applications, kaolin and/or montmorillonite serve such a purpose. Field, pilot and commercial scale trials of kaolin-derived Zeolite N have focused on applications in agriculture and water treatment as these sectors are primary producers or users of ammonium. The format for the material – as fine powders, granules or extrudates – depends on the specific application albeit each has been evaluated.

Equal employment opportunity and its links to the participation of women in the construction industry : the case of Australia

Australia is currently experiencing a resources boom and jobs in the male dominated fields of construction and engineering are at a premium. Employment in the construction industry, historically and today, is overwhelmingly male and, with an ageing population this predominately older male workforce will be retiring in greater numbers in the coming decade. Despite more that 25 years of anti- discrimination legislation and equal opportunity legislation these industries still employ few women in operational roles. This paper investigates the issue of the low representation of women in the construction industry. Our investigation involves the analysis of 95 organisation progress reports on the equal opportunity strategic programs in the construction industry. Findings indicate that this industry is not engaging with equal employment opportunity programs and further that equity outcomes for women in the industry are not evident.

High-risk, high-stake relationships: building effective industry-university partnerships for Work Integrated Learning (WIL)

Many industry peak and professional bodies advocate students undertake professional work placements as a key work integrated learning (WIL) experience in accredited university degree courses. However, mismatched expectations and gaps in the way industry partners (IPs) are supported during these work placements can place these high-stake alliances at risk. A review of models and strategies supporting industry partners indicates many are contingent on the continued efforts of well-networked individuals in both universities and IP organisations to make these connections work. It is argued that whilst these individuals are highly valued they often end up representing a whole course or industry perspective, not just their area of expertise. Sustainable partnership principles and practices with shared responsibility across stakeholder groups are needed instead. This paper provides an overview of work placement approaches in the disciplines of business, engineering and urban development at an Australian, metropolitan university. Employing action research and participatory focus group methodologies, it gathers and articulates recommendations from associated IPs on practical suggestions and strategies to improve relationships and the resultant quality of placements.

Industry-school partnerships : an ecological approach

Internationally, Industry-School Partnerships (ISPs) are a ubiquitous government approach for enabling school to work transitions. Significant benefits of ISPs for centralised bureaucracies that are seeking to address common educational problems include: i) cost reduction; ii) supply to geographically dispersed locations, and; iii) industry access to innovative education solutions. In Queensland, there exists a government led ISP, the Gateway to Industry Schools Program. Under this initiative is the Queensland Minerals and Energy Academy, a lead industry organisation for 34 schools and 17 multinational sponsor companies. Acquiring an understanding of this strategic ISP is critical, given the current Resources Industry boom, and the workforce skills shortage experienced in Australia. This review paper adopts Ecological Systems Theory as a lens to understand the inner workings of ISPs. Acknowledging that ISPs will remain a key feature of government policy, this paper seeks to further illuminate the role of ISPs in transitioning young people from school to the working world.

School industry partnerships : An innovative strategy for vocational education

One of the challenges confronting contemporary education internationally is to ensure that students are provided with opportunities to make informed choices about future careers and to acquire the capacity to transition into these careers. Schools need to manage their curricula, teacher capacity, timetables, and diversity of student populations by offering pathways that are seen as engaging and meaningful to life beyond schooling. Traditionally, education in the senior years has privileged those students who intend to progress to advanced studies at university or in other professional careers. In more recent times, in response the need for more sophisticated technical knowledge in the trades and a growing skills shortages in these fields, schools have paid more attention to vocational education. It has been argued that the vocational aspect of the school curriculum is less well understood and poorly implemented in comparison with the traditional academic curricula. One attempt to address this issue is through the establishment of school-industry partnerships. This paper explores the process of knowledge transfer between industry and schools in these partnerships. The paper theorises how knowledge that is valued and foundational in workplace employment can inform school curricula and pedagogical practices. The paper draws on theories of organisational knowledge, workplace learning and experiential learning to explore strategies that enhance school-to-employment transition outcomes.

Industry school partnerships: Boundary crossing to enable school to work transitions

Industry-school partnerships (ISPs) are increasingly being recognised as a new way of providing vocational education opportunities. However, there is limited research investigating their impact on school to work transitions. This paper reports on a government-led ISP, the Gateway to Industry Schools Program, established in Queensland, Australia. Central to this initiative is the Queensland Minerals and Energy Academy (QMEA), a lead organisation for 28 schools and 17 multi-national sponsor companies. This research adopted a qualitative case study methodology and draws upon boundary crossing theory as means to understand a Minerals and Energy ISP. We distinguish four types of boundary crossing mechanisms, which align with principles for effectiveness in ISPs. The main findings were that boundary crossing mechanisms assist ISPs to develop industry-based contextualised curriculum and to prepare school students for employment.

Personalized ontology learning for enhancing text mining effectiveness

Over the last decade, the majority of existing search techniques is either keyword- based or category-based, resulting in unsatisfactory effectiveness. Meanwhile, studies have illustrated that more than 80% of users preferred personalized search results. As a result, many studies paid a great deal of efforts (referred to as col- laborative filtering) investigating on personalized notions for enhancing retrieval performance. One of the fundamental yet most challenging steps is to capture precise user information needs. Most Web users are inexperienced or lack the capability to express their needs properly, whereas the existent retrieval systems are highly sensitive to vocabulary. Researchers have increasingly proposed the utilization of ontology-based tech- niques to improve current mining approaches. The related techniques are not only able to refine search intentions among specific generic domains, but also to access new knowledge by tracking semantic relations. In recent years, some researchers have attempted to build ontological user profiles according to discovered user background knowledge. The knowledge is considered to be both global and lo- cal analyses, which aim to produce tailored ontologies by a group of concepts. However, a key problem here that has not been addressed is: how to accurately match diverse local information to universal global knowledge. This research conducts a theoretical study on the use of personalized ontolo- gies to enhance text mining performance. The objective is to understand user information needs by a \bag-of-concepts" rather than \words". The concepts are gathered from a general world knowledge base named the Library of Congress Subject Headings. To return desirable search results, a novel ontology-based mining approach is introduced to discover accurate search intentions and learn personalized ontologies as user profiles. The approach can not only pinpoint users' individual intentions in a rough hierarchical structure, but can also in- terpret their needs by a set of acknowledged concepts. Along with global and local analyses, another solid concept matching approach is carried out to address about the mismatch between local information and world knowledge. Relevance features produced by the Relevance Feature Discovery model, are determined as representatives of local information. These features have been proven as the best alternative for user queries to avoid ambiguity and consistently outperform the features extracted by other filtering models. The two attempt-to-proposed ap- proaches are both evaluated by a scientific evaluation with the standard Reuters Corpus Volume 1 testing set. A comprehensive comparison is made with a num- ber of the state-of-the art baseline models, including TF-IDF, Rocchio, Okapi BM25, the deploying Pattern Taxonomy Model, and an ontology-based model. The gathered results indicate that the top precision can be improved remarkably with the proposed ontology mining approach, where the matching approach is successful and achieves significant improvements in most information filtering measurements. This research contributes to the fields of ontological filtering, user profiling, and knowledge representation. The related outputs are critical when systems are expected to return proper mining results and provide personalized services. The scientific findings have the potential to facilitate the design of advanced preference mining models, where impact on people's daily lives.

A people-to-people matching system using graph mining techniques

A people-to-people matching system (or a match-making system) refers to a system in which users join with the objective of meeting other users with the common need. Some real-world examples of these systems are employer-employee (in job search networks), mentor-student (in university social networks), consume-to-consumer (in marketplaces) and male-female (in an online dating network). The network underlying in these systems consists of two groups of users, and the relationships between users need to be captured for developing an efficient match-making system. Most of the existing studies utilize information either about each of the users in isolation or their interaction separately, and develop recommender systems using the one form of information only. It is imperative to understand the linkages among the users in the network and use them in developing a match-making system. This study utilizes several social network analysis methods such as graph theory, small world phenomenon, centrality analysis, density analysis to gain insight into the entities and their relationships present in this network. This paper also proposes a new type of graph called “attributed bipartite graph”. By using these analyses and the proposed type of graph, an efficient hybrid recommender system is developed which generates recommendation for new users as well as shows improvement in accuracy over the baseline methods.