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The originality of the crowd cyber system lies in the fact that it possesses the intelligence of multiple groups including intelligence of people, intelligence of objects and intelligence of machines. However, quantitative analysis of the level of intelligence is not sufficient, due to many limitations, such as the unclear definition of intelligence and the inconformity of human intelligence quotient (IQ) test and artificial intelligence assessment methods. This paper aims to propose a new crowd intelligence measurement framework from the harmony of adaption and practice to measure intelligence in crowd network.

The authors draw on the ideas of traditional Confucianism, which sees intelligence from the dimensions of IQ and effectiveness. First, they clarify the related concepts of intelligence and give a new definition of crowd intelligence in the form of a set. Second, they propose four stages of the evolution of intelligence from low to high, and sort out the dilemma of intelligence measurement at the present stage. Third, they propose a framework for measuring crowd intelligence based on two dimensions.

The generalized IQ operator model is optimized, and a new IQ algorithm is proposed. Individuals with different IQs can have different relationships, such as cooperative, competitive, antagonistic and so on. The authors point out four representative forms of intelligence as well as its evolution stages.

The authors, will use more rigorous mathematical symbols to represent the logical relationships between different individuals, and consider applying the measurement framework to a real-life situation to enrich the research on crowd intelligence in the further study.

Intelligence measurement is one of foundations of crowd science. This research lays the foundation for studying the interaction among human, machine and things from the perspective of crowd intelligence, which owns significant scientific value.

The purpose of this paper is to illuminate the ethical concerns associated with the use of artificial intelligence (AI) in the medical sector and to provide solutions that allow deriving maximum benefits from this technology without compromising ethical principles.

This paper provides a comprehensive overview of AI in medicine, exploring its technical capabilities, practical applications, and ethical implications. Based on our expertise, we offer insights from both technical and practical perspectives.

The study identifies several advantages of AI in medicine, including its ability to improve diagnostic accuracy, enhance surgical outcomes, and optimize healthcare delivery. However, there are pending ethical issues such as algorithmic bias, lack of transparency, data privacy issues, and the potential for AI to deskill healthcare professionals and erode humanistic values in patient care. Therefore, it is important to address these issues as promptly as possible to make sure that we benefit from the AI’s implementation without causing any serious drawbacks.

This paper gains its value from the combined practical experience of Professor Elhassan gained through his practice at top hospitals worldwide, and the theoretical expertise of Dr. Arabi acquired from international institutes. The shared experiences of the authors provide valuable insights that are beneficial for raising awareness and guiding action in addressing the ethical concerns associated with the integration of artificial intelligence in medicine.

This article explores the emergence of organizational digital transformation in the rapidly advancing technological era. It discusses the origins, driving forces, strategies, challenges and broader implications.

The article employs a scoping review methodology that synthesizes knowledge from the existing literature, research, case studies and other relevant sources.

The findings underscore the pivotal role that organizational digital transformation plays in an era of relentless technological advancement. Leadership, organizational culture and technological enablers are identified as crucial drivers of innovation and competitiveness within organizations. The article also emphasizes ethics as a crucial element of digital transformation, focusing in particular on concerns about data privacy and the morality of artificial intelligence. Additionally, the author talks about anticipated future trends that are anticipated to influence the future of digital transformation, such as the growing influence of artificial intelligence, the trend toward hyper-personalization and the emergence of quantum computing.

The assessment has failed to provide recommendations for the actual implementation because it has mainly concentrated on conceptual and strategic aspects. Furthermore, it does not clearly define the criteria for choosing real-world examples, which limits the representation of the different industries, size ranges of organizations and outcomes associated with digital transformation.

The article stresses the significance of paying attention to the forces driving digital transformation while navigating ethical and societal concerns. In addition to highlighting the importance of anticipating future trends for strategic planning in the rapidly changing digital landscape, it emphasizes the advantages as incentives for organizations to invest in digital initiatives.

The investigation demonstrates how technology contributes to progress while posing complex ethical and change management issues. In light of increased connectivity, data analytics and artificial intelligence, it highlights the crucial need for societal adaptability and highlights the crucial role that cooperative human–machine coexistence plays in responsible development and transformative societal evolution.

The article stands out because it examines organizational digital transformation in-depth while considering its historical roots, ethical implications and future prospects. It is a priceless contribution to the field because real-world case studies and a scoping review provide a distinctive viewpoint and a comprehensive view of the effects of digital transformation on organizations and society.

The aim of this study is to examine the existing literature on service robots in order to identify prominent themes, assess the present state of service robotics research and highlight the contributions of seminal publications in the business, management and hospitality domain.

This study analysed 332 Scopus papers from 1985 to 2022 using bibliometric techniques like citation and co-citation analysis.

The study findings highlighted that there has been a consistent rise in publications related to service robots. The paper identifies three significant themes in the service robot literature: adoption of service robots in the context of customer service, anthropomorphism and integration of artificial intelligence in robotic service. Furthermore, this study highlights prominent authors, journals, institutions and countries associated with research on service robots and discusses the future research opportunities in this domain.

This study contributes to the service robots’ literature in the hospitality context by compilation of various reference materials using a comprehensive bibliometric analysis. Previous studies do not point out crucial themes in this area, nor do they provide an overview of prominent journals, institutions, authors and trends in this field. Therefore, this study attempts to fill the lacunae.

The rapid development of Intelligent and Connected Vehicles (ICVs) has boomed a new round of global technological and industrial revolution in recent decades. The Technology Roadmap of Intelligent and Connected Vehicles (2020) comprehensively analyzes the technical architecture, research status and future trends of ICVs. The methodology that supports the roadmap should get studied.

This paper interprets the roadmap from the aspects of strategic significance, technical content and characteristics of the roadmap, and evaluates the impact of the roadmap on researchers, industries and international strategies.

The technical architecture of ICVs as the “three rows and two columns” structure is studied, the methodology that supported the roadmap is explained with a case study and the influence of key technologies with proposed development routes is analyzed.

This paper could help researchers understand both thoughts and methodologies behind the technology roadmap of ICVs.

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 business intelligence (BI) research witnessed a proliferation of contributions during the past three decades, yet the knowledge about the interdependencies between the BI process and organizational context is scant. This has resulted in a proliferation of fragmented literature duplicating identical endeavors. Although such pluralism expands the understanding of the idiosyncrasies of BI conceptualizations, attributes and characteristics, it cannot cumulate existing contributions to better advance the BI body of knowledge. In response, this study aims to provide an integrative framework that integrates the interrelationships across the BI process and its organizational context and outlines the covered research areas and the underexplored ones.

This paper reviews 120 articles spanning the course of 35 years of research on BI process, antecedents and outcomes published in top tier ABS ranked journals.

Building on a process framework, this review identifies major patterns and contradictions across eight dimensions, namely, environmental antecedents; organizational antecedents; managerial and individual antecedents; BI process; strategic outcomes; firm performance outcomes; decision-making; and organizational intelligence. Finally, the review pinpoints to gaps in linkages across the BI process, its antecedents and outcomes for future researchers to build upon.

This review carries some implications for practitioners and particularly the role they ought to play should they seek actionable intelligence as an outcome of the BI process. Across the studies this review examined, managerial reluctance to open their intelligence practices to close examination was omnipresent. Although their apathy is understandable, due to their frustration regarding the lack of measurability of intelligence constructs, managers manifestly share a significant amount of responsibility in turning out explorative and descriptive studies partly due to their defensive managerial participation. Interestingly, managers would rather keep an ineffective BI unit confidential than open it for assessment in fear of competition or bad publicity. Therefore, this review highlights the value open participation of managers in longitudinal studies could bring to the BI research and by extent the new open intelligence culture across their organizations where knowledge is overt, intelligence is participative, not selective and where double loop learning alongside scholars is continuous. Their commitment to open participation and longitudinal studies will help generate new research that better integrates the BI process within its context and fosters new measures for intelligence performance.

This study provides an integrative framework that integrates the interrelationships across the BI process and its organizational context and outlines the covered research areas and the underexplored ones. By so doing, the developed framework sets the ground for scholars to further develop insights within each dimension and across their interrelationships.

The metaverse is a virtual world where users can communicate with each other in a computer-generated environment. The use of metaverse technology has the potential to revolutionize the way businesses operate, interact with customers, and collaborate with employees. However, several obstacles must be addressed and overcome to ensure the successful implementation of metaverse technology. This study aims to examine the implementation of metaverse technology in the management of an organization's supply chain, with a focus on predicting potential barriers to provide suitable strategies.

Covariance-based structural equation modeling (CB-SEM) was used to test the model. In addition, artificial neural network modeling (ANN) was also performed.

The CB-SEM results revealed that a firm's technological limitations are among the most significant barriers to implementing metaverse technology in the supply chain management (SCM). The ANN results further highlighted that the firm's technological limitations are the most crucial input factors, followed by a lack of governance and standardization, integration challenges, poor diffusion through the network, traditional organizational culture, lack of stakeholder commitment, lack of collaboration and low perception of value by customers.

Because metaverse technology has the potential to provide organizations with a competitive advantage, increase productivity, improve customer experience and stimulate creativity, it is crucial to discuss and develop solutions to implementation challenges in the business world. Companies can position themselves for success in this fascinating and quickly changing technological landscape by conquering these challenges.

This study provides insights to metaverse technology developers and supply chain practitioners for successful implementation in SCM, as well as theoretical contributions for supply chain managers aiming to implement such environments.

This study aims to investigate how living lab (LL) activities align with responsible research and innovation (RRI) principles, particularly in artificial intelligence (AI)-driven digital transformation (DT) processes. The study seeks to define a framework termed “responsible living lab” (RLL), emphasizing transparency, stakeholder engagement, ethics and sustainability. This emerging issue paper also proposes several directions for future researchers in the field.

The research methodology involved a literature review complemented by insights from a workshop on defining RLLs. The literature review followed a concept-centric approach, searching key journals and conferences, yielding 32 relevant articles. Backward and forward citation analysis added 19 more articles. The workshop, conducted in the context of UrbanTestbeds.JR and SynAir-G projects, used a reverse brainstorming approach to explore potential ethical and responsible issues in LL activities. In total, 13 experts engaged in collaborative discussions, highlighting insights into AI’s role in promoting RRI within LL activities. The workshop facilitated knowledge sharing and a deeper understanding of RLL, particularly in the context of DT and AI.

This emerging issue paper highlights ethical considerations in LL activities, emphasizing user voluntariness, user interests and unintended participation. AI in DT introduces challenges like bias, transparency and digital divide, necessitating responsible practices. Workshop insights underscore challenges: AI bias, data privacy and transparency; opportunities: inclusive decision-making and efficient innovation. The synthesis defines RLLs as frameworks ensuring transparency, stakeholder engagement, ethical considerations and sustainability in AI-driven DT within LLs. RLLs aim to align DT with ethical values, fostering inclusivity, responsible resource use and human rights protection.

The proposed definition of RLL introduces a framework prioritizing transparency, stakeholder engagement, ethics and sustainability in LL activities, particularly those involving AI for DT. This definition aligns LL practices with RRI, addressing ethical implications of AI. The value of RLL lies in promoting inclusive and sustainable innovation, prioritizing stakeholder needs, fostering collaboration and ensuring environmental and social responsibility throughout LL activities. This concept serves as a foundational step toward a more responsible and sustainable LL approach in the era of AI-driven technologies.

This study aims to undertake a comprehensive analysis of innovation models, tracing their evolution from Innovation 1.0 to Innovation 4.0 and introducing the concept of Innovation 5.0. It explores the intersection between innovation models and the principles of sustainability, resilience and human-centeredness, providing insights into their implications for Industry 5.0, and their potential to foster a resilient ecosystem amidst challenges and multiple crisis.

To achieve this objective, the authors used a systematic literature review approach, considering academic articles on Innovation 4.0, Industry 5.0 (specifically in the context of innovation) and helix models of innovation. The authors conducted thematic analysis and content analysis, followed by keyword co-occurrence analysis, enabling us to systematically synthesize and interpret the relevant literature.

The results conclude that Innovation 5.0 is a new paradigm for innovation that fosters broader societal engagement, and emphasizes sustainability, resilience and human-centeredness. Innovation 5.0 is evolving, but it has the potential to transform the way we produce, consume and live. Using insights from the sextuple helix model, this research leverages media and ICT as sixth helix vital role of knowledge sharing, digital transformation, innovation ecosystem and next industrial revolution in this process.

This study contributes to the ongoing discourse on exploring Innovation 5.0 through the sextuple helix model, offering a fresh perspective on innovation models and their collaborative potential. Its contribution lies in providing practical insights into the transition to Innovation 5.0, emphasizing the need for sustainability, regulatory support and awareness while also offering clear recommendations for future research.