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Social engineering is crucial in today’s digital landscape. As technology advances, malicious individuals exploit human judgment and trust. This study explores how age, education and occupation affect individuals’ awareness, skills and perceptions of social engineering.

A quantitative research approach was used to survey a diverse demographic of Egyptian society. The survey was conducted in February 2023, and the participants were sourced from various Egyptian social media pages covering different topics. The collected data was analyzed using descriptive and inferential statistics, including independent samples t-test and ANOVA, to compare awareness and skills across different groups.

The study revealed that younger individuals and those with higher education tend to research social engineering more frequently. Males display a higher level of awareness but score lower in terms of social and psychological consequences as well as types of attacks when compared to females. The type of attack cannot be predicted based on age. Higher education is linked to greater awareness and ability to defend against attacks. Different occupations have varying levels of awareness, skills, and psychosocial consequences. The study emphasizes the importance of increasing awareness, education and implementing cybersecurity measures.

This study’s originality lies in its focus on diverse Egyptian demographics, innovative recruitment via social media, comprehensive exploration of variables, statistical rigor, practical insights for cybersecurity education and diversity in educational and occupational backgrounds.

This paper aims to provide insight into the evolving relationship between humans and machines, understanding its multifaceted impact on our lifestyle and landscape in the past as well as in the present, with implications for the near future. It uses bibliometric analysis combined with a systematic literature review to identify themes, trace historical developments and offer a direction for future human–machine interactions (HMIs).

To provide thorough coverage of publications from the previous four decades, the first section presents a text-based cluster bibliometric analysis based on 305 articles from 2,293 initial papers in the Scopus and Web of Science databases produced between 1984 and 2022. The authors used VOS viewer software to identify the most prominent themes through cluster identification. This paper presents a systematic literature review of 63 qualified papers using the PRISMA framework.

Next, the systematic literature review and bibliometric analysis revealed four major historical themes and future directions. The results highlight four major research themes for the future: from Taylorism to advanced technologies; machine learning and innovation; Industry 4.0, Society 5.0 and cyber–physical system; and psychology and emotions.

There is growing anxiety among humankind that in the future, machines will overtake humans to replace them in various roles. The current study investigates the evolution of HMIs from their historical roots to Society 5.0, which is understood to be a human-centred society. It balances economic advancement with the resolution of social problems through a system that radically integrates cyberspace and physical space. This paper contributes to research and current limited knowledge by identifying relevant themes and offering scope for future research directions. A close look at the analysis posits that humans and machines complement each other in various roles. Machines reduce the mechanical work of human beings, bringing the elements of humanism and compassion to mechanical tasks. However, in the future, smart innovations may yield machines with unmatched dexterity and capability unthinkable today.

This paper attempts to explore the ambiguous and dynamic relationships between humans and machines. The present study combines systematic review and bibliometric analysis to identify prominent trends and themes. This provides a more robust and systematic encapsulation of this evolution and interaction, from Taylorism to Society 5.0. The principles of Taylorism are extended and redefined in the context of HMIs, especially advanced technologies.

The purpose of the study is to identify the soft skills and abilities that are crucial to success in the fields of operations management (OM) and supply chain management (SCM), using the O*NET database and the classification of a set of professional figures integrating values for task skills and abilities needed to operate successfully in these professions.

The study used the O*NET database to identify the soft skills and abilities required for success in OM and SCM industries. Correlation analysis was conducted to determine the tasks required for the job roles and their characteristics in terms of abilities and soft skills. ANOVA analysis was used to validate the findings. The study aims to help companies define specific assessments and tests for OM and SCM roles to measure individual attitudes and correlate them with the job position.

As a result of the work, a set of soft skills and abilities was defined that allow, through correlation analysis, to explain a large number of activities required to work in the operations and SCM (OSCM) environment.

The work is inherently affected by the database used for the professional figures mapped and the scores that are attributed within O*NET to the analyzed elements.

The information resulting from this study can help companies develop specific assessments and tests for the roles of OM and SCM to measure individual attitudes and correlate them with the requirements of the job position. The study aims to address the need to identify soft skills in the human sphere and determine which of them have the most significant impact on the OM and SCM professions.

The originality of this study lies in its approach to identify the set of soft skills and abilities that determine success in the OM and SCM industries. The study used the O*NET database to correlate the tasks required for specific job roles with their corresponding soft skills and abilities. Furthermore, the study used ANOVA analysis to validate the findings in other sectors mapped by the same database. The identified soft skills and abilities can help companies develop specific assessments and tests for OM and SCM roles to measure individual attitudes and correlate them with the requirements of the job position. In addressing the necessity for enhanced clarity in the domain of human factor, this study contributes to identifying key success factors. Subsequent research can further investigate their practical application within companies to formulate targeted growth strategies and make appropriate resource selections for vacant positions.

The accelerating business transformation through Industry 4.0 (I4.0) is expected to create significant value in the manufacturing industry by delivering considerably high productivity, superior quality, better efficiency and effectiveness. However, its evolutionary processes have far-reaching challenging for humanity. This has triggered a need to analyze the impact of I4.0 on various people-centric variables (PCVs).

This paper attempts to analyze the interrelationship dynamics between the PCVs in the current digital-industry ecosystem using a focus-group approach and causal loop diagrams. Application of the SWARA (stepwise weight assessment ratio analysis) methodology has provided its prioritized ranking in terms of importance.

The study has highlighted that I4.0 has a significant influence on five of the 13 PCVs – human quality of life, digital dexterity, high-skilled talent, low-skilled employment and creativity which contribute to 80% of the total impact.

The prioritized weights of the human factors from the SWARA approach have facilitated the assessment of the Human Resource Development Index (HRDI). The study is also contributing in enriching the literature on the human impact of the growing I4.0 and triggered the researchers to study further its adverse impact on critical human factors.

1. The paper pertains to debates on a very critical issue of impact of integration of the current intelligent digital technologies in manufacturing and services to transform businesses to be more flexible and agile.

2. This paper features I4.0 as a technology that allows integration of new products in the existing production lines, one-off manufacturing runs and high mix manufacturing.

3. The paper also highlights major adjustments in operational activities, processes, supply chain, and organizational redesign due to I4.0 adoption.

4. The current research study has significantly enriched the literature on the I4.0 impact on people-centric variables (PCVs) using the SWARA method. The use of the Causal Loop Diagram has very aptly brought out the type of causality (polarity) between the different PCVs in the growth of I4.0.

The paper pertains to debates on a very critical issue of impact of integration of the current intelligent digital technologies in manufacturing and services to transform businesses to be more flexible and agile.

This paper features I4.0 as a technology that allows integration of new products in the existing production lines, one-off manufacturing runs and high mix manufacturing.

The paper also highlights major adjustments in operational activities, processes, supply chain, and organizational redesign due to I4.0 adoption.

The current research study has significantly enriched the literature on the I4.0 impact on people-centric variables (PCVs) using the SWARA method. The use of the Causal Loop Diagram has very aptly brought out the type of causality (polarity) between the different PCVs in the growth of I4.0.

The current era of the fourth industrial revolution has attracted significant research on the use of digital technologies in improving construction project delivery. However, less emphasis has been placed on how these digital tools will influence the management of the construction workforce. To this end, using a review of existing works, this chapter explores the fourth industrial revolution and its associated technologies that can positively impact the management of the construction workforce when implemented. Also, the possible challenges that might truncate the successful deployment of digital technologies for effective workforce management were explored. The chapter submitted that implementing workforce management-specific digital platforms and other digital technologies designed for project delivery can aid effective workforce management within construction organisations. Technologies such as cloud computing, the Internet of Things, big data analytics, robotics and automation, and artificial intelligence, among others, offer significant benefits to the effective workforce management of construction organisations. However, several challenges, such as resistance to change due to fear of job loss, cost of investment in digital tools, organisational structure and culture, must be carefully considered as they might affect the successful use of digital tools and by extension, impact the success of workforce management in the organisations.

Following the recent rise in generative artificial intelligence (GenAI) tools, fundamental questions about their wider impacts have started to reverberate around various disciplines. This study aims to track the unfolding landscape of general issues surrounding GenAI tools and to elucidate the specific opportunities and limitations of these tools as part of the technology-assisted enhancement of mechanical engineering education and professional practices.

As part of the investigation, the authors conduct and present a brief scientometric analysis of recently published studies to unravel the emerging trend on the subject matter. Furthermore, experimentation was done with selected GenAI tools (Bard, ChatGPT, DALL.E and 3DGPT) for mechanical engineering-related tasks.

The study identified several pedagogical and professional opportunities and guidelines for deploying GenAI tools in mechanical engineering. Besides, the study highlights some pitfalls of GenAI tools for analytical reasoning tasks (e.g., subtle errors in computation involving unit conversions) and sketching/image generation tasks (e.g., poor demonstration of symmetry).

To the best of the authors’ knowledge, this study presents the first thorough assessment of the potential of GenAI from the lens of the mechanical engineering field. Combining scientometric analysis, experimentation and pedagogical insights, the study provides a unique focus on the implications of GenAI tools for material selection/discovery in product design, manufacturing troubleshooting, technical documentation and product positioning, among others.

Civil engineering projects around the world have been underperforming for a long time. While the complexity of these projects will continue to increase, there is an urgent need to perform better. Although the integrated design process is critical for project success, the literature lacks studies describing the link to project performance. Therefore, this study aims to investigate the dominant variables that affect the integrated design process and consequently project performance.

A multiple case study was conducted to determine the dominant variables that affect the integrated design process and project performance. The research included four projects. Semi-structured interviews were the main source of data.

The cases indicated that the extent to which an integrated approach is achieved in the design process is essential for project performance. This applies to the integration of stakeholders’ interests as well as the integration of disciplines. Above all, it was concluded that the project team participants’ competencies for integration are a dominant factor for project performance, as the integrated design process has changed from a technical challenge to an integrative one.

This study provides insights into the dominant variable of the integrated design process that affects project performance, which is underexposed in the literature. The study results reveal the importance of competencies related to integration and adoption of the design problem context, which are not yet included in civil engineering design methods. In this respect, empathy is introduced as a new and critical competence for the civil engineering industry, which needs further research.

The set of 2,509 documents related to the human-centric aspect of manufacturing were retrieved from Scopus database and systmatically analyzed. Using an unsupervised machine learning approach based on Latent Dirichlet Allocation we were able to identify latent topics related to human-centric aspect of Industry 5.0.

This study aims to create a scientific map of the human-centric aspect of manufacturing and thus provide a systematic framework for further research development of Industry 5.0.

In this study a 140 unique research topics were identified, 19 of which had sufficient research impact and research interest so that we could mark them as the most significant. In addition to the most significant topics, this study contains a detailed analysis of their development and points out their connections.

Industry 5.0 has three pillars – human-centric, sustainable, and resilient. The sustainable and resilient aspect of manufacturing has been the subject of many studies in the past. The human-centric aspect of such a systematic description and deep analysis of latent topics is currently just passing through.

The objective of this research is to investigate the capabilities of the ChatGPT GPT-4 model, a form of artificial intelligence (AI), in comparison to human experts in the context of construction project risk management.

Employing a mixed-methods approach, the study draws a qualitative and quantitative comparison between 16 human risk management experts from Finnish construction companies and the ChatGPT AI model utilizing anonymous peer reviews. It focuses primarily on the areas of risk identification, analysis, and control.

ChatGPT has demonstrated a superior ability to generate comprehensive risk management plans, with its quantitative scores significantly surpassing the human average. Nonetheless, the AI model's strategies are found to lack practicality and specificity, areas where human expertise excels.

This study marks a significant advancement in construction project risk management research by conducting a pioneering blind-review study that assesses the capabilities of the advanced AI model, GPT-4, against those of human experts. Emphasizing the evolution from earlier GPT models, this research not only underscores the innovative application of ChatGPT-4 but also the critical role of anonymized peer evaluations in enhancing the objectivity of findings. It illuminates the synergistic potential of AI and human expertise, advocating for a collaborative model where AI serves as an augmentative tool, thereby optimizing human performance in identifying and managing risks.

The study aims to investigate the integration of human and machine intelligence in Industry 4.0 (I4.0), particularly in the convergence of industrial revolutions 4.0 (IR4.0) and 5.0. It seeks to identify employee competencies aligned with industry 5.0 (I5.0) and propose a framework for deep multi-level cooperation to improve human integration within the intelligence system.

This study uses bibliometric analysis to review 296 research papers retrieved from the Scopus database between 2002 and 2022. The prominence of the research is evaluated by analyzing the publication trend, sample statistics, theoretical foundation, commonly used keywords, thematic evolution, country-based contributions and top-cited documents.

The study observed that research in I5.0 has been limited in the past but has gained momentum since 2015. An analysis of research papers from 2002 to 2022 reveals a gradual shift toward human-centric practices. The literature on I4.0, the internet of things (IoT), artificial intelligence (AI), cloud manufacturing, blockchain and big data analysis has been increasingly highlighting the growing importance of digitalization in the future. An increase in the number of countries contributing to the field of study has also been observed.

This analysis offers valuable insights for managers, policymakers, information technology (IT) developers and stakeholders in understanding and implementing human-centric practices in I5.0. It emphasizes staying current with trends, embracing workforce empowerment through reskilling and upskilling, and prioritizing data privacy and security in adaptable systems. These strategies contribute to developing effective, inclusive and ethically sound approaches aligned with the principles of I5.0.