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The adoption of electronic health records (EHRs) and digitization of health data over the past decade is ushering in the next generation of digital health tools that leverage artificial intelligence (AI) to improve varied aspects of health system performance. The decade ahead is therefore shaping up to be one in which digital health becomes even more at the forefront of health care delivery – demanding the time, attention, and resources of health care leaders and frontline staff, and becoming inextricably linked with all dimensions of health care delivery. In this chapter, we look back and look ahead. There are substantive lessons learned from the first era of large-scale adoption of enterprise EHRs and ongoing challenges that organizations are wrestling with – particularly related to the tension between standardization and flexibility/customization of EHR systems and the processes they support. Managing this tension during efforts to implement and optimize enterprise systems is perhaps the core challenge of the past decade, and one that has impeded consistent realization of value from initial EHR investments. We describe these challenges, how they manifest, and organizational strategies to address them, with a specific focus on alignment with broader value-based care transformation. We then look ahead to the AI wave – the massive number of applications of AI to health care delivery, the expected benefits, the risks and challenges, and approaches that health systems can consider to realize the benefits while avoiding the risks.

Mauritius is a Small Island Development State (SIDS) with limited resources, and it has been witnessed that many containers used for storing household and industrial products are made from plastic. When discarded as waste, those plastic containers pose a serious environmental and economic challenge for Mauritius. Moreover, landfill space is getting increasingly scarce, and plastic waste is contaminating both land and water. Therefore, it is of the utmost necessity to develop solutions for Mauritius' plastic wastes. Due to its abundance and accessibility, plastic waste is a promising material for recycling and energy production. One potential solution is the use of machine learning and artificial intelligence (AI) to predict household plastic consumption, allowing policymakers to design effective strategies and initiatives to reduce plastic waste. Such information is a critical component to be able to efficiently plan for the collection and routing of trucks when collecting recyclable plastics. The development of new strategies for the recycling of plastic waste and development of new industry can address the import and export potential of the country to achieve self-sustainability as well as contribute to reduction in plastic pollution and amount of waste landfilled. These plastics can thereafter be used effectively for recycling and for the making of 3D printing filaments which fall under the SDGs 9 (Industry, Innovation and Infrastructure) and 12 (Responsible consumption and production).

In this chapter, the authors undertake a systematic review of the literature to identify research exploring the use of new information and communication technologies (ICT). New ICT include the use of the Internet, mobile communications, and social technologies. The authors find that while interest in the area is increasing, especially among marketing and information systems scholars, there seems to be far less research interest among international business (IB) and strategy scholars. This chapter provides a summary of the research that has been done and discusses some potential future research areas that IB and strategy researchers might wish to pursue. Among these projects are investigating the use of ICT as a tool to aid the internationalization process, improve location choice and entry mode decisions, and identify and create a sustainable competitive advantage. The use of ICT in business is pervasive; As research scholars, we need to build these technologies into our theories and research to help managers determine what works and where certain technologies can help create better performing firms.

Discourses on critical librarianship have been mainly theoretical. However, discourses with a practical application of Critical Theory in librarianship, critical librarianship, or library management and operations are limited. Yet, librarianship underscores efficiency and practicality in service provision with the dominant ideology in librarianship being practicality. Based on Critical Theory and emerging power dynamics in e-services, this chapter presents a discussion on the practical application of Critical Theory in academic libraries. The Web 2.0 technologies have triggered a shift in information seeking and use by empowering the academic library users to seek and use information from nontraditional sources. This shift in information seeking behavior and the resultant power dynamics has an impact on strengthening of the academic library as a public sphere; a public virtual space where people can meet and exchange ideas with the eventual outcome of democratization of knowledge. This chapter analyses the practical implications of power dynamics in academic libraries and the need for realignment of academic library functions to key Critical Success Factors (CSFs) including the role of library management, a focus on librarian power, a focus on user empowerment, creating awareness of the Web 2.0 services, and maximizing the use of Web 2.0 technologies. A proper realignment of the shifting power is necessary and must be pursued as a deliberate strategy by academic libraries to facilitate generation and sharing of information. It concludes by presenting the practical implications of power dynamics in academic libraries and recommendations on dealing with the emerging paradigm shifts.

Internet + and Electronic Business in China is a comprehensive resource that provides insight and analysis into E-commerce in China and how it has revolutionized and continues to revolutionize business and society. Split into four distinct sections, the book first lays out the theoretical foundations and fundamental concepts of E-Business before moving on to look at internet+ innovation models and their applications in different industries such as agriculture, finance and commerce. The book then provides a comprehensive analysis of E-business platforms and their applications in China before finishing with four comprehensive case studies of major E-business projects, providing readers with successful examples of implementing E-Business entrepreneurship projects.

Internet + and Electronic Business in China is a comprehensive resource that provides insights and analysis into how E-commerce has revolutionized and continues to revolutionize business and society in China.

This article contributes to the fuzzy logic application literature in accounting by examining a key issue in the use of fuzzy logic: how to find an optimum number of classes to minimize the decision maker's cost. Two costs are assumed: (1) we assume fuzziness is costly and thus should be minimized and (2) we assume that adding categories is costly. In order to address the issue of finding the optimal number of classes, we define the objective function as being cost minimization. We seek to determine the costs and benefits of increasing the number of classifications and ask whether an internal optimum is identifiable and achievable. We assume, ceteris paribus, less fuzziness is preferable to more fuzziness, but fuzziness can only be reduced through the use of more categories whose creation is costly. More fuzziness is costly, but so is the creation of additional categories to alleviate the fuzziness. When we arrive at the optimal number of clusters that corresponds to a minimal total cost, that number may not be the same as the “natural” number of categories. It is, nonetheless, a useful and practical way of deciding on the number of classifications. The approach we employ in this study is not confined to a management accounting information environment. It can be applied to any information environment where measurable classifications exist.