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This research aims to explore the research data ethics governance framework and collaborative network to optimize research data ethics governance practices, to balance the relationship between data development and utilization, open sharing, data security and to reduce the ethical risks that may arise from data sharing and utilization.

This study explores the framework and collaborative network of research data ethics policies by using the UK as an example. 78 policies from the UK government, university, research institution, funding agency, publisher, database, library and third-party organization are obtained. Adopting grounded theory (GT) and social network analysis (SNA), Nvivo12 is used to analyze these samples and summarize the research data ethics governance framework. Ucinet and Netdraw are used to reveal collaborative networks in policy.

Results indicate that the framework covers governance context, subject and measure. The content of governance context contains context description and data ethics issues analysis. Governance subject consists of defining subjects and facilitating their collaboration. Governance measure includes governance guidance and ethics governance initiatives in the data lifecycle. The collaborative network indicates that research institution plays a central role in ethics governance. The core of the governance content are ethics governance initiatives, governance guidance and governance context description.

This research provides new insights for policy analysis by combining GT and SNA methods. Research data ethics and its governance are conceptualized to complete data governance and research ethics theory.

A research data ethics governance framework and collaborative network are revealed, and actionable guidance for addressing essential aspects of research data ethics and multiple subjects to confer their functions in collaborative governance is provided.

This study analyzes policy text using qualitative and quantitative methods, ensuring fine-grained content profiling and improving policy research. A typical research data ethics governance framework is revealed. Various stakeholders' roles and priorities in collaborative governance are explored. These contribute to improving governance policies and governance levels in both theory and practice.

The purpose of this study is to propose a world-class good governance ethics framework that leads to better corporate performance. ethics among managers, executives and members of the board of directors working in public-listed companies brings grave concern because of the increasing number of criminal acts reported by the Security Commission of Malaysia.

This study introduces a world-class good governance ethics framework for curbing criminal acts in public-listed companies in Malaysia. This study used a mixed method to gather data, and the methods used are appropriate for answering the research questions based on the World-Class Good Governance Ethics framework.

The finding of this study reveals high expectations for a corporate organization to improve individual and team performance while undertaking their corporate responsibilities, and a matter of choice, to adopt world-class good governance ethics in their policies and practices.

This study could be a reference for corporate management to regulate policies monitoring management's and employees' conduct at the workplace. This study's theoretical and practical significance would guide the stakeholders in corporate management to regulate governance policies based on the right ethical values and promote personalities with high integrity in management conduct.

This study promotes a world-class good governance ethics framework in curbing criminal acts for better corporate performance. This new framework is formulated based on the concept of a caliph and other essential elements envisaged by the Quranic verses.

The purpose of this study is to examine how the adoption of blockchain technology can improve organizational sustainability and what are the contributions of morality, ethics and governance in this scenario.

This study has used different literature and theories to build a successful theoretical model and then validated it using the partial least squares structural equation modeling approach. Various statistical modeling analyses have been performed to test the robustness of the proposed model, which is found to be effective and unique as it has a high explanatory power.

This study has found that adoption of blockchain technology can improve the sustainability performance of organizations. It has also highlighted that organizational sustainability will be further enhanced if the underlying algorithms of blockchain technology are transparent to make the applications moral and ethical. This study has further demonstrated that appropriate governance of blockchain technology can support the organizations to enhance their sustainability performance.

This study demonstrates the importance of an organization’s governance over blockchain technology and its impact on sustainability. The study provides valuable input to practitioners and policy makers regarding blockchain technology and its governance models. Also, the study provides valuable recommendations to leaders and managers of organizations on how to successfully adopt blockchain technology.

This study presents a unique theoretical model to explain the influence of the adoption of blockchain technology and an organization’s sustainability. The study also adds value to the overall body of literature in the areas of ethics, governance and blockchain technology along with sustainability.

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 study aims to analyse the components of sustainable business models (SBMs) in the dairy industry, in relation to firm-relevant organisational features (size, ownership structure and production process) and through the lenses of the business model framework and the sustainable value exchange matrix (SVEM). This contribution proposes a taxonomy of emerging SBMs and sustainable value creation in the dairy industry.

This research makes use of a multiple case study approach, with cases selected in collaboration with industry experts. The selected firms are highly committed to sustainability transition. Results are drawn from qualitative data obtained from in-depth interviews and secondary sources. The interpretation phases, initially based on open coding, have been enriched by applying the components of business models (BMs) frameworks and the SVEM, and the analyses have been enhanced through an additional interpretative workshop with experts.

The authors related the BMs characteristics of some typical dairy firms transitioning to sustainability, using SBM components and taxonomies emerging in the literature, based on the formalisation of sustainability practices, the scope of operations, and the degree of integration of the three dimensions of sustainable value. These findings led to the discovery of three types of SBM in this dairy industry, referred to as “Milky Ways”.

This paper contributes to the scant literature on sustainability in dairy firms, highlighting the different paths followed by small and medium-sized enterprises (SMEs), cooperatives and large companies in remoulding their business models towards sustainability and thus achieving sustainable value creation.

Situated in the context of India, where women’s representation on corporate boards remains low, this study aims to explore whether and how tokenism impacts the behaviours of female directors.

The boardroom experiences and perceptions of 14 women directors are explored through semi-structured interviews and analysed using an inductive and interpretive process. Also, to get a counter perspective and avoid the social desirability bias from the women participants’ responses, 16 men directors are interviewed.

The study finds that, as gender minorities, women directors' visibility on boards can create performance pressures on these women. To counter gender-based prejudices, women directors consciously alter their behaviours and project both male and female traits consistent with the director role. By doing so, women directors overcome tokenistic stereotypes and are accepted as part of the director in-group, irrespective of their numeric representation on the board.

The research has implications for governments attempting to increase women’s board presence through affirmative actions and for firms aiming to improve the gender diversity of their board composition.

These findings present an alternative perspective on women directors’ board behaviour by exploring the applicability of Western trends on tokenism and critical mass in the context of India, adding to the vast body of literature concerned with minorities on corporate boards.

Despite technological advancements to enhance patient health, the risks of not discovering the correct interactions and trends in digital health are high. Hence, a careful policy is required for health coverage tailored to needs and capacity. Therefore, this study aims to explore the adoption of a cognitive computing decision support system (CCDSS) in the assessment of health-care policymaking and validates it by extending the unified theory of acceptance and use of technology model.

A survey was conducted to collect data from different stakeholders, referred to as the 4Ps, namely, patients, providers, payors and policymakers. Structural equation modelling and one-way ANOVA were used to analyse the data.

The result reveals that the behavioural insight of policymakers towards the assessment of health-care policymaking is based on automatic and reflective systems. Investments in CCDSS for policymaking assessment have the potential to produce rational outcomes. CCDSS, built with quality procedures, can validate whether breastfeeding-supporting policies are mother-friendly.

Health-care policies are used by lawmakers to safeguard and improve public health, but it has always been a challenge. With the adoption of CCDSS, the overall goal of health-care policymaking can achieve better quality standards and improve the design of policymaking.

This study drew attention to how CCDSS as a technology enabler can drive health-care policymaking assessment for each stage and how the technology enabler can help the 4Ps of health-care gain insight into the benefits and potential value of CCDSS by demonstrating the breastfeeding supporting policy.

The purpose of this study is to examine the relationship between the ownership concentration and cost of equity of firms in Pakistan context. Moreover, this study also investigates how the presence of disclosure quality and governance quality affects the relationship between ownership concentration and the cost of equity of firms.

Data are collected from six non-financial sectors listed on Pakistan Stock Exchange during the period of 2015–2019. This study uses pooled ordinary least square (OLS) method to validate the proposed hypothesis in STATA.

The study found a positive and significant relationship between ownership concentration and cost of equity. The results also show that better disclosure and governance quality negatively moderates the relationship between ownership concentration and cost of equity.

The findings of this study will help firm managers to implement a high level of disclosure and governance quality in firms to reduce agency problems which will further help a firm in reducing the firm's cost of equity. Furthermore, this study is valuable for practitioners regarding thinking about the process of designing ownership structures to protect minority shareholders' rights, especially in emerging markets.

The novelty of this study is having better disclosure quality and more board independence members helps firms with higher ownership concentration in reducing the cost of equity.