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A Liberating Curricula as a Social Responsibility for Promoting Social Justice and Student Success Within the UK Higher Education Institution (HEI)
No full textIntegrating corporate social responsibility (CSR) activities as part of a higher education institution (HEI) organisational strategies and practices to address economic and social inequality is no longer a new phenomenon. This promotes increased levels of involvement, choice, and diversity, and is aligned with recent initiatives to widen participation improve representation and promote attainment. CSR may also be encapsulated within frameworks through which HEIs may identify and self-reflect on institutional and cultural barriers that impede minority ethnic (ME) staff and students' progression and attainment. This chapter is informed by discussions concerning CSR within higher education in relation to the aims and objectives of education; student progression and attainment as a university's socially responsible business practice and act of due diligence, to improve representation, progression and success for ME students; curriculum vs. education and the function of a liberating curriculum as a vehicle to enhance academic attainment and promote student success
The Dynamics of Electronic Supply Chains and Enterprise Resource Planning Systems: The New Business Challenge
No full textBusinesses around the world experience many challenges to acquire raw materials, parts, subassemblies, and the other necessary inputs to their production systems. As businesses are all moving into the e-commerce platform to gain market shares, they realize that electronic supply chain management (e-SCM) powered by enterprise resource planning systems (ERPs) are the new norms and no business organization can operate without both in the new world of e-commerce. Little attention has been devoted to e-SCM dynamic with ERP and the challenges they pose to organizations. In the e-commerce environment, e-SCM is among the most important factors to organizational success. Effective e-SCM can enhance competitiveness and increase market share leading a higher profitability. Nevertheless, the new e-SCM professionals and other actors must understand the factors that undergird e-SCM performance, their drivers, and the necessity of fully functional ERPs for an effective e-SCM
Re-Imagining Data Governance
No full textContemporary business environments reflect the growing influence of data as a mission-critical resource of relevance across the enterprise, suggesting a need for robust infrastructures to enable good data management practice. This includes data governance, a particularly foundational infrastructure with a crucial role to play. Data governance models in common use however, reflecting traditional top-down, hierarchical structures, and relying on designated governance roles, are not equipped to effectively embed data accountability within dynamic business environments. In response, this chapter offers a new approach designed to foster accountability by cultivating data knowledge and promoting good data management behavior amongst all relevant staff. Drawing from an operational data governance framework developed for New Zealand government, the new model employs a core set of capabilities and a steady states model to map data flow. It provides a deliberately business-centric view of data accountability and offers a means of maturing data thinking to support improved integration across operating scales
Cross-Urban Point-of-Interest Recommendation for Non-Natives
No full textThis article describes how understanding human mobility behavior is of great significance for predicting a broad range of socioeconomic phenomena in contemporary society. Although many studies have been conducted to uncover behavioral patterns of intra-urban and inter-urban human mobility, a fundamental question remains unanswered: To what degree is human mobility behavior predictable in new cities—a person has never visited before? Location-based social networks with a large volume of check-in records provide an unprecedented opportunity to investigate cross-urban human mobility. The authors' empirical study on millions of records from Foursquare reveals the motives and behavioral patterns of non-natives in 59 cities across the United States. Inspired by the ideology of transfer learning, the authors also propose a machine learning model, which is designed based on the regularities that they found in this study, to predict cross-urban human whereabouts after non-natives move to new cities. The experimental results validate the effectiveness and efficiency of the proposed model, thus allowing us to predict and control activities driven by cross-urban human mobility, such as mobile recommendation, visual (personal) assistant, and epidemic prevention
The Dynamic Impacting Study of Competitive Strategies to Import Retail E-Commerce Sellers
No full textThe authors investigated several import retail e-commerce sellers through questionnaires and selected several types of variables based on Porter's competitive strategy theory. Then the authors used the panel data to empirically verify theoretical consumptions based on samples got by Python method from Jingdong Global Purchases and Tmall International, the top two e-commerce platforms in China. Results validated the three major competitive strategies that could enhance the competitive advantages to import retail e-commerce sellers. As it was not applied to all platforms and commodities, sellers should make different strategies through different platforms and commodities. This article has theoretical significance that filled in the gaps on import retail e-commerce sellers' competition. It also has certain practical significance by providing references for sellers on how to improve their competitive advantages, promote healthy competition and development of the import retail e-commerce, even to facilitate the structure adjustment of consumption and foreign trade in China
E-Assessment and Multiple-Choice Questions: A Literature Review
No full textThe use of information and communication technologies (ICT) in the assessment process is becoming an asset, giving rise to the so-called computer-based assessment or e-assessment. Nowadays, its use is becoming more usual in higher education institutions. Closed formats for questions, namely multiple choice, are the most commonly used. This chapter presents a literature review of the main aspects related to this topic, including the main modalities of assessment (summative assessment and continuous assessment). Issues related to multiple choice questions (MCQ) are discussed with more detail, referring to the various formats of MCQ, its advantages and limitations, with a particular focus on its use in mathematics tests. Also, some guidelines for the quality assurance of MCQ with quality are included
An Australian Longitudinal Study Into Remnant Data Recovered From Second-Hand Memory Cards
No full textConsumers demand fast, high capacity, upgradeable memory cards for portable electronic devices, with secure digital (SD) and microSD the most popular. Despite this demand, secure erasure of data is still not a composite part of disposure practices. To investigate the extent of this problem, second-hand memory cards were procured from the Australian eBay site between 2011 and 2015. Digital forensic tools were used to acquire and analyze each memory card to determine the type and quantity of remnant data. This paper presents the results of the 2014 and 2015 studies and compares these findings to the 2011–2013 research studies. The longitudinal comparison indicates resold memory cards are disposed insecurely, with personal, confidential and business data undeleted or easily recoverable. The impact of such discoveries, where information is placed in the public domain, has the potential to cause embarrassment and financial loss to individuals, business, and government organizations
Users' Distribution and Behavior in Academic Social Networking Sites
No full textAcademic social networking sites (SNSs) are growing rapidly. Worldwide, academicians use academic SNSs for many reasons regardless of their nation, gender, position, and discipline. In this paper, the authors extend their previous work in exploring the distribution and behavior of a particular academic SNS (academia.edu) on a large scale. The authors classify users into different groups based on their position, discipline, and continent. This study gives a better understanding of usage patterns in academic SNS, especially in the lack of large-scale studies about different classes of users on academic SNSs
Geographic Analysis of Domestic Violence Incident Locations and Neighborhood Level Influences
No full textDomestic violence is an important public health issue, and there is limited research to date that examines community-level influences on this serious form of violence. This article investigates the neighborhood characteristics of domestic violence incidents in the city of Greensboro, North Carolina. US Census block group boundaries and corresponding tables were used as proxies for neighborhoods. The article addresses an important gap in domestic violence research by combining geographic and statistical analyses at the block group level. Geographic data were analyzed using an Optimized Hot Spot Analysis (OHA) along with features selected by penalized Poisson regression model. The OHA was used to identify spatial clusters of high and low values while the penalized Poisson regression model was used to select the important variables from over 7000 candidates. The results of high-dimensional analysis produced six categories and 20 variables that were used to examine the characteristics of spatial clusters
A Novel Approach to Distributed Rule Matching and Multiple Firing Based on MapReduce
No full textIn order to solve the poor performance problem of massive rules reasoning, as well as the inconsistency problem of working memory in distributed rule matching, this article presents the formal definition of interference relations between rules, and proposes a novel approach to distributed rule matching and multiple firing based on MapReduce. This approach adopts the way of access request control to detect and exclude interference rules, then selects several rule instantiations to perform multiple firing and concurrent execution, thus reducing the number of inference cycles effectively. By detecting the interferences between rules, this method selects and executes compatible rule sets, and avoids the inconsistency problem of system working memory. In order to verify the validity of the authors' approach, this article developes a production system based on MapReduce, and applied this approach in the master server of a distributed production system. The experimental results show that their method can promote the performance of massive rules reasoning effectively