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This study aims to investigate the influence of two perceived organizational ethics systems (perceived ethics training quality and integrity-based climate) on the ethical decision-making (EDM) of tax accountants in Ghana. The study also examines the moderating role of the decision-makers’ financial situation on the quality ethics training–EDM relationship.

Survey data from 356 tax accountants were analyzed using the partial least squares structural equation modeling technique.

The results show that the two ethics systems influence EDM, but their extent of influence varies across the stages of EDM. Specifically, quality ethics training is a better predictor of EDM at the ethical issue recognition stage, whereas integrity-based climate is a better predictor of EDM at the ethical intention stage. The study also found that decision-makers’ financial situation predicts the ethical recognition stage of EDM but does not moderate the quality ethics training–EDM relationship.

This study recommends the concurrent deployment of quality ethics training and an integrity-based work climate to improve ethical behavior. Policymakers should also emphasize a work climate that promotes honesty, conscientiousness and ethical principles (integrity-based climate) to improve ethical intentions.

This study applied the interactionist theory by capturing the relative effects of two organizational ethics systems and an individual-level situational factor in a single model. To the best of the authors’ knowledge, this is the first study that tests the moderation effect of decision-makers’ financial situation on the ethics training–EDM relationship in a developing country context.

Artificial intelligence (AI) offers many benefits to improve predictive marketing practice. It raises ethical concerns regarding customer prioritization, market share concentration and consumer manipulation. This paper explores these ethical concerns from a contemporary perspective, drawing on the experiences and perspectives of AI and predictive marketing professionals. This study aims to contribute to the field by providing a modern perspective on the ethical concerns of AI usage in predictive marketing, drawing on the experiences and perspectives of professionals in the area.

The study conducted semistructured interviews for 6 weeks with 14 participants experienced in AI-enabled systems for marketing, using purposive and snowball sampling techniques. Thematic analysis was used to explore themes emerging from the data.

Results reveal that using AI in marketing could lead to unintended consequences, such as perpetuating existing biases, violating customer privacy, limiting competition and manipulating consumer behavior.

The authors identify seven unique themes and benchmark them with Ashok’s model to provide a structured lens for interpreting the results. The framework presented by this research is unique and can be used to support ethical research spanning social, technological and economic aspects within the predictive marketing domain.

La Inteligencia Artificial (IA) ofrece muchos beneficios para mejorar la práctica del marketing predictivo. Sin embargo, plantea preocupaciones éticas relacionadas con la priorización de clientes, la concentración de cuota de mercado y la manipulación del consumidor. Este artículo explora estas preocupaciones éticas desde una perspectiva contemporánea, basándose en las experiencias y perspectivas de profesionales en IA y marketing predictivo. El estudio tiene como objetivo contribuir a la literatura de este ámbito al proporcionar una perspectiva moderna sobre las preocupaciones éticas del uso de la IA en el marketing predictivo, basándose en las experiencias y perspectivas de profesionales en el área.

Para realizar el estudio se realizaron entrevistas semiestructuradas durante seis semanas con 14 participantes con experiencia en sistemas habilitados para IA en marketing, utilizando técnicas de muestreo intencional y de bola de nieve. Se utilizó un análisis temático para explorar los temas que surgieron de los datos.

Los resultados revelan que el uso de la IA en marketing podría tener consecuencias no deseadas, como perpetuar sesgos existentes, violar la privacidad del cliente, limitar la competencia y manipular el comportamiento del consumidor.

El estudio identifica siete temas y los comparan con el modelo de Ashok para proporcionar una perspectiva estructurada para interpretar los resultados. El marco presentado por esta investigación es único y puede utilizarse para respaldar investigaciones éticas que abarquen aspectos sociales, tecnológicos y económicos dentro del ámbito del marketing predictivo.

人工智能（AI）为改进预测营销实践带来了诸多益处。然而, 这也引发了与客户优先级、市场份额集中和消费者操纵等伦理问题相关的观点。本文从当代角度深入探讨了这些伦理观点, 充分借鉴了人工智能和预测营销领域专业人士的经验和观点。旨在通过现代视角提供关于在预测营销中应用人工智能时所涉及的伦理观点, 为该领域做出有益贡献。

本研究采用了目的性和雪球抽样技术, 与14位在人工智能营销系统领域具有丰富经验的参与者进行为期六周的半结构化访谈。研究采用主题分析方法, 旨在深入挖掘数据中显现的主要主题。

研究结果表明, 在营销领域使用人工智能可能引发一系列意外后果, 包括但不限于加强现有偏见、侵犯客户隐私、限制竞争以及操纵消费者行为。

本研究通过明确定义七个独特的主题, 并采用阿肖克模型进行基准比较, 为读者提供了一个结构化的视角, 以解释研究结果。所提出的框架具有独特之处, 可有效支持在跨足社会、技术和经济领域的预测营销中展开的伦理研究。

This paper aims to explore the common ethical decision-making challenges faced by financial advisers and how they meet these challenges. The purpose is to identify successful decision-making tools used by investment advisers in doing business ethically. Additionally, the authors uncover common challenges and offer decision-making tools to provide support for supplemental ethics training in the future.

Questions were analyzed through a qualitative approach using individual interviews to examine a range of experiences and attitudes of active financial advisers. The sample was represented by 11 practicing financial advisers affiliated with US independent broker-dealers: six women and five men, each with 10 or more years of experience, ranging in age from 35 to 75. Grounded in four ethical decision-making models, this research examines individual ethical decision-making using individual (internal, personal) and organizational (external, situational) factors.

The method used uncovered struggles and revealed strategies used in making ethical decisions. Two research questions were examined: what are the common ethical decision-making challenges faced by financial advisers in the US financial industry? How do financial advisers handle ethical decision-making challenges? Four themes emerged that impacted ethical decision-making: needs of the individual, needs of others, needs of the firm and needs of the marketplace. Financial advisers identified moral obligation, self-control and consulting with others as major considerations when they contemplate difficult decisions.

A limitation of this review is its small sample size. A more robust sample size from investment advisers with a broader range of experiences could have widened the findings from the study.

Investment advisers can use the findings of this study as a tool for improving their own ethical decision-making or designing training for their employees to be better decision-makers.

The study explores the decision-making experiences of investment advisers to reveal multifaceted, often private struggles that qualitative methods can uncover. The study provides support for the development of additional training in ethical decision-making specific to investment advisers.

This paper aims to analyze the relationships between human resource supply chain management (HRSCM), corporate culture (CC) and the code of business ethics (CBE) in the MENA region.

In this study, the author adopted a quantitative approach through an online Google Form survey for the data-gathering process. All questionnaires were distributed to the manufacturing and service firms that are listed in the Chambers of the Industries of Jordan, Saudi Arabia, Morocco and Egypt in the MENA region using a simple random sampling method. About 567 usable and valid responses were retrieved out of 2,077 for analysis, representing a 27.3% response rate. The sample unit for analysis included all middle- and senior-level managers and employees within manufacturing and service firms. The conceptual model was tested using a hypothesis-testing deductive approach. The findings are based on covariance-based analysis and structural equation modeling (SEM) using PLS-SEM software. The author performed convergent validity and discriminant validity tests, and bootstrapping was also applied.

The empirical results display a significant and positive association between HRSCM and the CBE. The CC and the CBE tend to be positively and significantly related. Therefore, HRSCM can play a key role in boosting and applying the CBE in firms. For achieving the firm purposes, more attention to the HR personnel should be paid to implement the CBE. The high importance of the CBE becomes necessary for both the department and the firm.

Such results can provide insightful information for HR personnel, managers and leaders to encourage them to develop and maintain an effective corporate code of conduct within their organizations.

This paper tries to explore the linkages between HRSCM, CC and CBE in the Middle East region due to the lack of research available that analyzes the relationship between them. Not only that, but it also offers great implications for Middle Eastern businesses.

The purpose of this paper is to contribute knowledge on ethical issues and reasoning in expert reports concerning healthcare governance, commissioned by the Swedish healthcare system.

An in-depth analysis of ethical issues and reasoning in 36 commissioned expert reports was performed. Twenty-seven interviews with commissioners and producers of the reports were also carried out and analysed.

Some ethical issues were identified in the reports. But ethical reasoning was rarely evident. The meaning of ethical concepts could be devalued and changed over time and thereby deviate from statutory ethical goals and values. Several ethical issues of great concern for the Swedish public healthcare were also absent.

The commissioner of expert reports needs to ensure that comprehensive ethical considerations and ethical analysis are integrated in the expert reports.

Based on an extensive data material this paper reveals an ethical void in expert reports on healthcare governance. By avoiding ethical issues there is a risk that the expert reports could bring about reforms and control models that have ethically undesirable consequences for people and society.

A new triage method, MBCE (Medical Bio Social Ethics), is presented with social justice, bio, and medical ethics for critical resource distribution during a pandemic. Ethical triage is a complex and challenging process that requires careful consideration of medical, social, cultural, and ethical factors to guide the decision-making process and ensure fair and transparent allocation of resources. When assigning priorities to patients, a clinician would evaluate each patient’s medical condition, age, comorbidities, and prognosis, as well as their cultural and social background and ethical factors.

A statistical analysis shows no interactions among the ethical triage factors. It implies the ethical components have no moderation effect; hence, each is independent. The result also points out that medical and bioethics may have an affinity for interactions. In such cases, there seem to be some ethical factors related to bio and medical ethics that are correlated. Therefore, the triage team should be careful in evaluating patient cases. The algorithm is explained with case histories of the selected patient. A group of triage nurses and general medical practitioners assists with the triage.

The MBCE triage algorithm aims to allocate scarce resources fairly and equitably. Another ethical principle in this triage algorithm is the principle of utility. In a pandemic, the principle of utility may require prioritizing patients with a higher likelihood of survival or requiring less medical care. The research presents a sensitivity analysis of a patient’s triage score to show the algorithm’s robustness. A weighted score of ethical factors combined with an assessment of triage factors combines multiple objectives to assign a fair triage score. These distinctive features of the algorithm are reasonably easy to implement and a new direction for the unbiased triage principle.

The idea is to make decisions about distributing and using scarce medical resources. Triage algorithms raise ethical issues, such as discrimination and justice, guiding medical ethics in treating patients with terminal diseases or comorbidity. One of the main ethical principles in triage algorithms is the principle of distributive justice.

The purpose of this paper is to consider the ethical and environmental implications of allowing space resource extraction to disrupt existing fuel economies, including how companies can be held accountable for ensuring the responsible use of their space assets. It will also briefly consider how such assets should be taxed, and the cost/benefit analyses required to justify the considerable expense of supporting this emerging space industry.

This paper adopts theoretical bioethics methodologies to explore issues of normative ethics and the formulation of moral rules to govern individual, collective and institutional behaviour. Specifically, it considers social justice and social contract theory, consequentialist and deontological accounts of ethical evaluation. It also draws on sociological and organisational literature to discuss Dowling and Pfeffer’s (1975) and Suchman’s (1995) theories of pragmatic, cognitive and moral legitimacy as they may be applied to off-world mining regulations and the handling of space assets.

The findings of this conceptual paper indicate there is both a growing appetite for tighter resource extraction regulations to address climate change and wealth concentration globally, and an opportunity to establish and legitimise new ethical norms for commercial activity in space that can avoid some of the challenges currently facing fossil fuel divestment movements on Earth.

By adopting methodologies from theoretical bioethics, sociology and business studies, including applying a legitimacy lens to the issue of off-world mining, this paper synthesises existing knowledges from these fields and brings them to the new context of the future space resource economy.

How can large international financial firms go green in authentic ways? What enhances ‘Net Zero action’? Changes in global banks, fund managers, and insurance firms are at the heart of green finance. External change pressures – combined with problematic firm predispositions – exacerbate barriers to change and promote scepticism about authentic Net Zero change. Field research reveals main elements, connections, and interactions of this question by considering financial firms as complex socio-technical systems (Mitleton-Kelly, 2003). An interdisciplinary/holistic narrative approach (De Bakker et al., 2019) is adopted to design a conceptual framework that can support a green ‘behavioural theory of the financial firm’ (green BTFF). The BTFF presents an international version (Peng, 2001) of the resource-based view (RBV) of the firm (Barney, 1991; Hart, 1995; Teece et al., 1997).

The approach of this chapter is aimed at closing knowledge gaps and realign values in financial markets and society. By raising awareness about organised hypocrisy and facades (Brunsson, 1993; Cho et al., 2015; Schoeneborn et al., 2020) in financial firms the chapter aims at overcoming the gap between ‘talking’ and ‘walking’ in the financial sector. The chapter defines testable firm-level hypotheses for ‘Green Finance’ (Poterba, 2021) as well as – by implication – tests for ‘greenwashing’.

This study aims to identify and assess the key ethical challenges associated with integrating artificial intelligence (AI) in knowledge-sharing (KS) practices and their implications for decision-making (DM) processes within organisations.

The study employs a mixed-methods approach, beginning with a comprehensive literature review to extract background information on AI and KS and to identify potential ethical challenges. Subsequently, a confirmatory factor analysis (CFA) is conducted using data collected from individuals employed in business settings to validate the challenges identified in the literature and assess their impact on DM processes.

The findings reveal that challenges related to privacy and data protection, bias and fairness and transparency and explainability are particularly significant in DM. Moreover, challenges related to accountability and responsibility and the impact of AI on employment also show relatively high coefficients, highlighting their importance in the DM process. In contrast, challenges such as intellectual property and ownership, algorithmic manipulation and global governance and regulation are found to be less central to the DM process.

This research contributes to the ongoing discourse on the ethical challenges of AI in knowledge management (KM) and DM within organisations. By providing insights and recommendations for researchers, managers and policymakers, the study emphasises the need for a holistic and collaborative approach to harness the benefits of AI technologies whilst mitigating their associated risks.