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The purpose of the paper is to analyze the new Bankruptcy Law in Saudi Arabia (KSA Bankruptcy Law) under both a comparative lens and a policy-oriented one, while highlighting some of the most essential operational steps and procedures in a bankruptcy proceeding under the law.

The approach adopted analyzes the specific mechanics and procedures of a bankruptcy law under the general policies and goals of bankruptcy. Additionally, where appropriate, a brief comparison to the US Bankruptcy code and its provisions is presented to provide an alternative approach on how similar issues are handled under a reputable and proven bankruptcy system.

Overall, the KSA Bankruptcy Law is a major accomplishment and advancement to the Kingdom’s insolvency regime. The law consolidated and codified the laws governing bankruptcy under the Kingdom’s prior regime, and followed the structure of a modern bankruptcy regime. In doing so, several of the law’s policies and objectives have been fulfilled by providing an effective, predictable and reliable bankruptcy system.

Given the relatively recent adoption of the KSA Bankruptcy Law, the paper provides a comprehensive assessment of the law’s operation and its effectiveness in achieving its policy goals as a modern bankruptcy law.

This study analyzes how tech firms can implement the modern wave of subscription-based business model (SBBM), including value proposition, value creation, value capture and performance. In fact, these elements push tech firms to move from traditional to SBBMs.

To achieve the objectives of this study, we initially construct a theoretical framework for applying SBBM. Subsequently, we employ qualitative research to examine the current implementation of the subscription-based economy within tech firms.

A successful SBBM necessitates capturing value through sustainable revenue transactions and revising aspects of the value proposition, creation and capture. Continuous improvement through business value analysis is imperative. Additionally, an agile operations system is vital to address revenue complexities, enable data collection and enhance value proposition, service innovation, churn rate and customer retention, which are essential for SBBM maintenance.

This study delves into how the subscription-based economy is reshaping the business models of tech firms. Beyond exploring the theoretical foundation of this transformative path, this study offers actionable insights on enhancing the value proposition, creation, capture and business value within subscription-based economy frameworks.

The main aim of this article is to broaden the notion of strategic intent in public relations. It also develops an understanding of the social value of what can be defined as the first modern health communication campaign in Europe based on strategic intents and the development of modernity.

The study is based on both historical research and empirical material from the Norwegian tuberculosis campaign from 1889 up to 1913, when Norwegian women achieved suffrage. The campaign is analysed in the framework of modernity and social theory. The literature on lobbying and social movements is also used to develop a theoretical framework for the notion of strategic intent.

The study shows that strategic intent can be divided into two layers: (1) the implicit strategic intent is the real purpose behind the communication efforts, whereas (2) the explicit intent is found directly in the communication efforts. The explicit intent may be presented as a solution for the good of society at the right political moment, giving an organisation the possibility to mobilise for long-term social changes, in which could be the implicit intent.

The distinction between explicit and implicit strategic intent broadens our understanding on how to make long-term social changes as well as how social and political changes occur in modern societies. The article also gives a historical account of what is here defined as the first modern health communication campaign in Europe and its social value.

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。

The study aims to explore the validity of the modern renewable energy-environmental Kuznets curve (REKC) while considering the relevance of financial development in the consumption of modern renewable energy in East Africa Community (EAC). Modern renewable energy in this study includes all other forms of renewable energy except traditional use of biomass. The authors controlled for the effects of urbanization, governance, foreign direct investment (FDI) and trade openness.

Panel data of the five EAC countries of Burundi, Kenya, Rwanda, Tanzania and Uganda for the period 1996–2019 were used. The analysis relied on the use of the autoregressive distributed lag–pooled mean group (ARDL-PMG) model, and the data were sourced from the World Development Indicators (WDI), World Governance Indicators (WGI) and International Energy Agency (IEA).

The REKC hypothesis is supported for modern renewable energy consumption in the EAC region. Financial development positively and significantly affects modern renewable energy consumption, whereas urbanization, FDI and trade openness reduce modern renewable energy consumption. Governance is insignificant.

The concept of the REKC, although explored in other contexts such as aggregate renewable energy and in other regions, has not been used to explain the consumption of modern renewable energy in the EAC.

In this study, the authors examine artificial knowledge as a fundamental stream of knowledge management for sustainable and resilient business models in supply chain management (SCM). The study aims to provide a comprehensive overview of artificial knowledge and digitalization as key enablers of the improvement of SCM accountability and sustainable performance towards the UN 2030 Agenda.

Using the SCOPUS database and Google Scholar, the authors analyzed 135 English-language publications from 1990 to 2022 to chart the pattern of knowledge production and dissemination in the literature. The data were collected, reviewed and peer-reviewed before conducting bibliometric analysis and a systematic literature review to support future research agenda.

The results highlight that artificial knowledge and digitalization are linked to the UN 2030 Agenda. The analysis further identifies the main issues in achieving sustainable and resilient SCM business models. Based on the results, the authors develop a conceptual framework for artificial knowledge and digitalization in SCM to increase accountability and sustainable performance, especially in times of sudden crises when business resilience is imperative.

The study results add to the extant literature by examining artificial knowledge and digitalization from the resilience theory perspective. The authors suggest that different strategic perspectives significantly promote resilience for SCM digitization and sustainable development. Notably, fostering diverse peer exchange relationships can help stimulate peer knowledge and act as a palliative mechanism that builds digital knowledge to strengthen and drive future possibilities.

This research offers valuable guidance to supply chain practitioners, managers and policymakers in re-thinking, re-formulating and re-shaping organizational processes to meet the UN 2030 Agenda, mainly by introducing artificial knowledge in digital transformation training and education programs. In doing so, firms should focus not simply on digital transformation but also on cultural transformation to enhance SCM accountability and sustainable performance in resilient business models.

This study is, to the authors' best knowledge, among the first to conceptualize artificial knowledge and digitalization issues in SCM. It further integrates resilience theory with institutional theory, legitimacy theory and stakeholder theory as the theoretical foundations of artificial knowledge in SCM, based on firms' responsibility to fulfill the sustainable development goals under the UN's 2030 Agenda.