The role and ethics of professionals in business and economics have been questioned, especially after the financial crisis of 2008. Some suggest a reorientation using concepts such as craftsmanship. In this article, I will explore professional practices within the context of behavioural theory and business ethics. I suggest that scholars of behavioural theory need a strategy to deal with normative questions to meet their ambition of practical relevance. Evidence-based management (EBMgt), a recent behavioural approach, may assist business ethics scholars in understanding how professionals infer ‘evidence’ to make decisions. For a professional, ethical issues are an integral part of decision-making at critical moments. As reflective practitioners, they develop insights related to ethical concerns when collecting and assessing evidence within decision-making processes.
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This paper discusses sustainable real estate and the role of ethics within real estate. Both terms ‘sustainability’ and ‘ethics’ needs an explanation. With this discussion the tripartite system of ‘morals – principles - laws’ is described in order to have more grip on sustainable real estate and ethics.
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A reflective practitioners'anlaysis of student responses to ethical issues encountered during a workshop on International Business. The research was conducted with 1st year students of Bedrijfsmanagement MKB. The papaer reviews the literature and makes recoomendations for the business studies curriculum.
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This paper discusses sustainable real estate and the role of ethics within real estate. Both terms ‘sustainability’ and ‘ethics’ needs an explanation. With this discussion the tripartite system of ‘morals – principles - laws’ is described in order to have more grip on sustainable real estate and ethics.
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Moral food lab: Transforming the food system with crowd-sourced ethics
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Aim: Midwives are expected to identify and help resolve ethics problems that arise in practice, skills that are presumed to be taught in midwifery educational programs. In this study, we explore how midwives recognize ethical dilemmas in clinical practice and examine the sources of their ethics education. Methods: We conducted semi-structured, individual interviews with midwives from throughout the United States (U.S.) (n = 15). Transcripts of the interviews were analysed using an iterative process to identify themes and subthemes. Findings: Midwives described a range of professional ethical dilemmas, including challenges related to negotiating strained interprofessional relationships and protecting or promoting autonomy for women. Ethical dilemmas were identified by the theme of unease, a sense of distress that was expressed in three subthemes: uncertainty of action, compromise in action, and reflecting on action. Learning about ethics and ethical dilemmas occurred, for the most part, outside of the classroom, with the majority of participants reporting that their midwifery program did not confer the skills to identify and resolve ethical challenges. Conclusion: Midwives in this study reported a range of ethical challenges and minimal classroom education related to ethics. Midwifery educators should consider the purposeful and explicit inclusion of midwifery-specific ethics content in their curricula and in interprofessional ethics education. Reflection and self-awareness of bias were identified as key components of understanding ethical frameworks. As clinical preceptors were identified as a key source of ethics learning, midwifery educators should consider ways to support preceptors in building their skills as role models and ethics educators.
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Artificial intelligence (AI) is a technology which is increasingly being utilised in society and the economy worldwide, but there is much disquiet over problematic and dangerous implementations of AI, or indeed even AI itself deciding to do dangerous and problematic actions. These developments have led to concerns about whether and how AI systems currently adhere to and will adhere to ethical standards, stimulating a global and multistakeholder conversation on AI ethics and the production of AI governance initiatives. Such developments form the basis for this chapter, where we give an insight into what is happening in Australia, China, the European Union, India and the United States. We commence with some background to the AI ethics and regulation debates, before proceedings to give an overview of what is happening in different countries and regions, namely Australia, China, the European Union (including national level activities in Germany), India and the United States. We provide an analysis of these country profiles, with particular emphasis on the relationship between ethics and law in each location. Overall we find that AI governance and ethics initiatives are most developed in China and the European Union, but the United States has been catching up in the last eighteen months.
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A transition from a linear economy to a more sustainable and circular economy requires different business models. In this chapter, we provide you with an introduction to the nature and logic of business models. In essence, a business model is a description of how value creation between parties or partners is organized, at a particular moment, in a specific context, and given available resources. Conventional business modelling approaches have several weaknesses---the main point of criticism being their focus on creating financial value. With the Business Model Template (BMT), we try to resolve most of these criticisms. To do so we introduce three archetypal business models: the platform, community, and circular economy business models. This chapter provides an overview on how, over three stages and ten building blocks that together make up the Business Model Template, these archetypal business models will be used.
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The BMT provides the building blocks to develop a logic for a business model. In such a model the nature of value creation, how value creation is organized, and how transactions are taking shape are operationalized so that they meet the proposition. Practice shows that at present business models aimed at capturing multiple value creation can be divided into three major categories: (1) platform business models, (2) community-based (or collective) business models, and (3) circular business models. The three archetypes differ mainly in the way in which they create value, as well as the objective, the mechanism through which value creation takes place, and the infrastructural and technological requirements. When using the BMT, it is useful to consider at an early stage which business model archetype is dominant in the realization of the intended value proposition. Choosing a business model archetype might look straightforward, but it can be quite a tricky task.
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