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Discussions of ethics and Artificial Intelligence (AI) usually revolve around the ethical implications of the use of AI in multiple domains, ranging from whether machine learning trained algorithms may encode discriminatory standards for face recognition, to discussions of the implications of using AI as a substitute for human intelligence in warfare. In this chapter, I will focus on one particular strand of ethics and AI that is often neglected: whether we can use the methods of AI to build or train a system which can reason about moral issues and act on them. Here, I discuss (1) what an “artificial conscience” consists of and what it would do, (2) why we collectively should build one soon given the increasing use of AI in multiple areas, (3) how we might build one in both architecture and content, and (4) concerns about building an artificial conscience and my rejoinders. Given the increasing importance of artificially intelligent semi- or fully autonomous systems and platforms for contemporary warfare, I conclude that building an artificial conscience is not only possible but also morally required if our autonomous teammates are to collaborate fully with human soldiers on the battlefield.

Harnessing the power and potential of Artificial Intelligence (AI) continues a centuries-old trajectory of the application of science and knowledge for the benefit of humanity. Such an endeavor has great promise, but also the possibility of creating conflict and disorder. This chapter draws upon the strengths of the previous chapters to provide readers with a purposeful assessment of the current AI security landscape, concluding with four key considerations for a globally secure future.

We review and discuss theoretical approaches from both within and outside of institutional organization theory with regard to their specific insights on what we call “regionalized zones of meaning” – that is, clusters of social meaning that can be distinguished from one another, but at the same time interact and, in specific configurations, form distinct societies. We suggest that bringing meaning structures back into focus is important and may counter-balance the increasing preoccupation of institutional scholars with micro-foundations and the related emphasis on micro-level activities. We bring together central ideas from research on institutional logics with some foundational insights by Max Weber, Alfred Schütz, and German sociologists Rainer Lepsius and Karl-Siegbert Rehberg. In doing so, we also take a cautious look at “practices” by discussing their potential place and role in an institutional framework as well as by exploring generative conversations with proponents of practice theory. We wish to provide inspiration for institutional research interested in shared meaning structures, their relationships to one another, and how they translate into institutional orders.

The purpose of this study is to explore the investment of supply chain technology-to-performance path relationship through the lens of the resource-based view (RBV) as illuminated by the organizational learning literature.

This study surveyed top-level managers who are registered members of the Council of Supply Chain Management Professionals.

Using factor analysis and OLS regression on 300+ supply chain professionals, this study confirms that investments in both enterprise- and radio frequency identification (RFID)-specific knowledge management (KM) tools yield substantial benefits to the firm’s knowledge management system (KMS) which is the dependent path to higher supply chain performance.

This sample was taken with supply chain professionals who are more likely to value supply chain investments as part of their responsibility.

The authors believe that the empirical study on supply chain investment from a resource-based perspective will contribute to the ongoing RBV theoretical discussions while providing insights for practitioners in the realm of supply chain investment.

Every investment in supply technology should be driven by an understanding of the inextricably inter-connectedness of knowledge management capabilities and the firm’s ability to effectively implement its corporate strategies. By emphasizing the inter-connection between knowledge management and supply chain technology investments, firms improve their potential for developing a competitive advantage.

The purpose of this paper is to define a new conceptual framework or model, to measure and manage organizational performance, both financial/non-financial and intellectual capital (IC), in a healthcare organization.

The integrated new model is produced by integrating the common assessment framework (CAF) model with two other frameworks representing the IC and leadership. These already existing models are originated, respectively by the Health Agency of Emilia-Romagna Region (Italy) and the National Healthcare System (NHS – UK). The integration phase is operated by comparing the CAF and IC models so as to assess the determinant factors that are present in both frameworks and eliminating such redundancies. Concerning the leadership determinant factor, the relevant conceptual framework of CAF model is substituted by the new leadership model proposed by the NHS.

A new integrated model is made available for a subsequent step of empirical implementation and validation through its application in a healthcare organization. The main advantage of this model is the ability to measure and manage IC and financial/non-financial performance. Moreover, the use of a single measurement system facilitates the interpretation and coherency assessment of measured data so originated.

The added value this work provides will enrich the academic literature regarding performance measurement systems in healthcare organizations, also providing an original integrated model that is able to exhibit the advantages highlighted above.

Manufacturing companies continue to encounter a diverse set of obstacles while embracing sustainable development goals. Accordingly, the purpose of this study is to explore critical sustainable development-related barriers to flexible packaging manufacturing companies in the New Zealand context.

Drawing on a qualitative multiple case studies approach, the authors collected data from the New Zealand flexible packaging industry. Semistructured interviews were conducted with the senior corporate managers in two large flexible packaging companies. Following the thematic analysis approach, the authors analyzed the information collected from the participants and synthesized our findings under the key dimensions of internal and external barriers to sustainable development.

The findings revealed that internal barriers to sustainable flexible packaging are linked to economic, operational and technical issues. Conversely, external barriers include global crises and disruption, customer behavior and preferences and institutional and infrastructural-related aspects. Based on the analysis of empirical findings, the authors further identified the underlying reasons for sustainable flexible packaging barriers and recommended guidelines that could assist corporate managers and policymakers in addressing obstacles inhibiting the flexible packaging industry from adopting sustainable business practices.

The authors argue that this study is one of the early studies to consider inhibiting factors to incorporate sustainable development into the New Zealand flexible packaging industry context. Building on a range of theoretical perspectives, the authors extend the current body of knowledge seeking to advance the sustainable development agenda in the New Zealand flexible packaging industry and offer recommended pathways fostering sustainable development in a distinctive manufacturing context.

This paper attempts to explore the green-lean-six sigma (GLSS) practices in the continuous process industry particularly in the flexible packaging (FP) industry in an emerging economy for addressing environmental sustainability issues.

The authors have employed a qualitative multiple-case approach to examine managerial perspectives on GLSS adoption in the flexible packaging industry. Semi-structured interviews with senior corporate managers in two large FP organizations in Pakistan were conducted as the primary source of data collection.

Drawing on the natural resource-based view (NRBV), the analysis revealed that organizations are implementing key GLSS practices such as environmental management system (ISO 14001), cause–effect analysis, renewable energy sources, total productive maintenance, and statistical process control to effectively manage waste, conserve resources, control air emissions, and improve environmental and workplace safety.

The authors argue that this is one of the first research studies that has utilized NRBV to investigate the application of the GLSS approach in the process industry, specifically in the FP industry in an emerging economy.