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This study aims to explore the emergence of the human resource (HR) analyst role. The job posts on LinkedIn display the industry demand and skills required by the organizations. This study identifies the different knowledge, skills and abilities (KSA) required for an HR analyst role in different stages of professional growth (i.e. entry-level, middle-senior level and top-level) across different industries/sectors as applicable to the crisis.

A total of 80 job posts were extracted from LinkedIn. Details such as industry, job levels, qualifications, job experience, job functions, job descriptions (JDs) and job skills (JS) were collected. Further, 30 videos were extracted from YouTube and converted into text. Text analysis was conducted using NVivo software to analyze JDs, JS and job functions. Using NVivo, word frequency, word cloud, word tree and treemap were created to visualize the data. Finally, ten in-depth interviews were conducted with senior HRA managers based in India to understand the essential competencies required for the HR analyst role and the strategies to develop them.

The findings indicate that not only technical skills are needed, but business and communication skills are particularly important for all job levels during a crisis. The JD word cloud showed words, such as data, business, support and management, and the word tree depicted HR data and change agents as important words with many related sentences as branches. General JS included analytical, communication, problem-solving and management. Technical JS were the most widely used and included structure query language, system applications & products in data processing, human capital management, TABLEAU, management information system and PYTHON. Strategies to develop these competencies included case studies, live projects, internships on HR analytics (HRAs) assignments and mentoring by senior HRA professionals.

The sample used was small, as the study included 80 job posts available on LinkedIn restricted to India. The study was restricted to qualitative approach and text analytics was used. Survey methods and a quantitative approach can be used to collect data from HR recruiters, job holders and senior leaders to understand the role of HRAs in the job market and then these variables can be tested empirically.

Based on the McCartney et al.’s (2020) competency model for the HR Analyst role, this study has explored the KSA framework using data visualization techniques and used text analytics to analyze LinkedIn job posts for different levels, videos from YouTube and in-depth interviews. It also mapped the KSA for the HR analyst role to the various stages of crisis system management given by Mitroff (2005). The use of social media analytics, such as analyzing LinkedIn data and YouTube videos, are highlighted.

Industry 4.0 has been identified as a key cornerstone to modernise economies where man and machines complement each other seamlessly to achieve synergies in decision-making and productivity for contributing to SDG 8: Decent Work and Economic Growth and SDG 9: Industry, Innovation and Infrastructure. The integration of Industry 4.0 remains a challenge for the developing world, depending on their current status in the industrial revolution journey from its predecessors 1.0, 2.0 and 3.0. This chapter reviews reported findings in literature to highlight how robotics and automated systems can pave the way to implementing and applying the principles of Industry 4.0 for developing countries like Mauritius, where data collection, processing and analysis for decision-making and prediction are key components to be integrated or designed into industrial processes centred heavily on the use of artificial intelligence (AI) and machine learning techniques. Robotics has not yet found its way into the various industrial sectors in Mauritius, although it has been an important driver for Industry 4.0 across the world. The inherent barriers and transformations needed as well as the potential application scenarios are discussed.

This article seeks to enhance the understanding as to why head coaches and general managers (GMs) in the National Basketball Association (NBA) and the National Football League (NFL) exit from their positions.

Three hypotheses were investigated using a series of quantitative and qualitative data from the past 30 years. The samples analyzed are comprised of 891 GM and coach annual observations for the NBA clubs and 949 GM and coach observations for the NFL clubs. Analyses include a logit analysis for coach exit/retention, a logit analysis for GM exit/retention and textual analysis via topic modeling via latent Dirichlet allocation.

Results show a correlation between a coach exiting and a GM exiting simultaneously, thus amplifying the importance of these two roles in enhancing or destroying the success of a club and supporting the need for a deeper understanding of both roles, particularly the GM. The results further highlight cultural differences across clubs in terms of GM and coach turnover, a factor that often is heavily influenced by club ownership.

The results support the role of owners in exits, confirm the importance of winning in avoiding an exit, find a high level of interrelationship between GM and coach exits and show that past culture of firings influences future exit decisions.

The purpose of this study is to address the challenges faced by rural areas and promote their sustainable development. It emphasizes the importance of re-establishing connections and cultivating a sense of belonging within rural communities, while safeguarding their cultural heritage. The study explores the potential of digital and creative tools in enhancing learning, supporting food production and tourism, facilitating research and providing engaging experiences. It also examines the economic condition of rural areas and the potential for their contribution to the national economy. Additionally, the study highlights the significance of sustainable community development, the role of rural areas in resilience and climate change adaptation and the complexities surrounding rural migration. The aim is to provide insights and recommendations for policymakers and stakeholders involved in rural development initiatives, focusing on the Mediterranean region.

This study develops an understanding of the role of digital and creative strategies in rural communities, highlighting their significance in preserving food heritage, culture and community capital while driving economic development. It specifically focuses on the Unesco Intangible Mediterranean Diet (UIMD) as a potential catalyst for regeneration through the integration of creative and digital tools and three cases are presented. The first is the impact of the Future Food Institute (FFI) ecosystem in the Living Lab in Pollica (Salerno, Italy); the second focuses on the digital tools provided by the CKF to support rural areas; and the third is a new identity and promotion of territorial development, co-designed in the Val di Vara (VdV) a rural region of the Ligurian inland in Italy, through digital strategies, heritage preservation and slow tourism development. The three cases highlight different ways of enhancing environmental and cultural heritage and demonstrate how collaborative creativity and digital tools contribute to the co-construction of knowledge and addressing critical issues to promote sustainable growth in rural areas.

The findings of this study indicate that re-establishing connections and fostering a sense of belonging within rural communities is crucial for their sustainable development. The use of digital and creative tools presents significant opportunities in enhancing various aspects such as learning, food production, tourism and research in rural areas. The study also reveals the potential economic contributions of rural areas to the national economy. It emphasizes the importance of sustainable community development and highlights the role of rural areas in resilience and climate change adaptation. Additionally, the study addresses the complexities surrounding rural migration and emphasizes the need for comprehensive policies to ensure the well-being and rights of migrant workers. The insights and recommendations provided in this study aim to guide policymakers and stakeholders involved in rural development initiatives, particularly in the Mediterranean region.

Nonetheless, it is imperative to acknowledge certain limitations within the scope of this study, primarily associated with the specific sample selection, potentially influencing the broader applicability of the findings. There is potential to explore a wider geographic area in future research. Additionally, the research underscores the importance of conducting further inquiries into certain aspects that have received limited attention. Living labs are a relatively recent phenomenon, warranting further in-depth scientific research. Additionally, the existing literature on this subject is often limited in scope.

The study and project aim to illustrate the feasibility of initiating a transformative process, centered on a visionary approach with a core focus on creative knowledge and the Mediterranean diet as a way of life, to revitalize marginalized communities. Furthermore, it seeks to emphasize that these neglected regions possess untapped potential for innovative ideas and opportunities. Rural communities, in their role as farmers of primary goods, are the ones who nurture the environment, and the landscape, and are the true protagonists of every era. Rurality is the place that preserves the most resources and potential in terms of biodiversity and rural knowledge. Every territory, like every human being, has its own characteristics and vocations to pursue. The existing Genius Loci is already an existing value that requires policies and governance to rediscover roots, identity and worth. The stratification of existing collective intelligence must become central and must be individually assessed and enhanced, also taking advantage of new digital technologies.

The social implications of this study are significant. By emphasizing the importance of re-establishing connections and cultivating a sense of belonging within rural communities, the study recognizes the social value of strong community ties. This can lead to increased social cohesion, a sense of identity and improved overall well-being within rural areas. The study also highlights the potential of digital and creative tools in enhancing learning, which can contribute to the empowerment and educational opportunities of individuals in rural communities. Furthermore, by promoting sustainable community development and addressing the complexities surrounding rural migration, the study acknowledges the social impact of inclusive policies that protect the rights and well-being of both local populations and migrant workers. Overall, the study's recommendations have the potential to foster social resilience, equity and a more vibrant social fabric within rural areas.

This study can offer valuable insights and recommendations for policymakers and stakeholders involved in rural development initiatives, particularly those focused on preserving food and cultural heritage in rural areas. By analyzing real-life examples, it bridges the gap between theory and practice, illustrating how these ideas have been effectively applied in specific contexts. This paper emphasizes the potential of the Mediterranean Diet as a sustainable and nutritious model with sociocultural, health, economic and environmental benefits, highlighting the importance of bottom-up approaches that empower local communities as custodians of knowledge and culture. It also provides practical strategies, such as investments in educational programs, the establishment of international campuses and the use of multichannel platforms for immersive experiences, which can be adapted for broader rural development initiatives, promoting sustainability and community engagement.

Visual aesthetics are a vital aspect of environmental quality. The objective of this study is to demonstrate the implementation of visibility analysis and visual quality standards on a campus to enhance productivity and effectiveness.

This study has identified the most crucial and valuable metrics for evaluating the visual quality of open spaces through an analysis of theoretical foundations and relevant background information. To achieve research goal, a multi-method approach was employed, incorporating a survey, user satisfaction ratings and ISOVIST simulation techniques. Specifically, this study focused on assessing the quality of open spaces in three open areas located on the campus of the Iran University of Science and Technology.

Based on the study’s findings, the most significant factors that students considered when evaluating the visual quality of open spaces on the Iran University of Science and Technology campus were green areas, gathering spaces and architectural elements such as furniture, color and texture. Among the three open areas examined, “Open Space One” was identified as the most satisfactory location for students. According to the study, “sensory richness,” “complexity” and “mystery” were significant indicators of students' satisfaction in this area. This area also had the widest radius and field of view feasible, which gave it a feeling of openness and spaciousness.

This study explores the influence of students' experiences, behavioral patterns and visual analyses on their use of open spaces on university campuses, with a focus on the Iran University of Science and Technology. By assessing students' satisfaction levels with these spaces, this research provides valuable insights that can guide the initial analysis stage before the design process and facilitate design optimization during the development stages. The results highlight the importance of considering user experiences and visual analysis when planning and creating open spaces on university campuses.

Highlights

1. Conducting an initial analysis before developing a design plan can be very helpful in understanding how users think and behave.

2. The three criteria of visual quality that have the strongest correlation with students' satisfaction with “open space” are “mystery,” “sensory richness” and “complexity.”

3. Two factors, namely the “radius of vision” and the “area” index, significantly influence students' satisfaction with open spaces.

4. Outdoor designers should incorporate “green space” and “gathering spaces” into their designs since the presence of these is effective in attracting and satisfying students.

5. The number of people using an open space has little to do with how satisfied students are with it.

6. Half of the students use open areas between 11:00 and 14:00, so the provision of “canopy” and “shelter” in these spaces is essential.

Conducting an initial analysis before developing a design plan can be very helpful in understanding how users think and behave.

The three criteria of visual quality that have the strongest correlation with students' satisfaction with “open space” are “mystery,” “sensory richness” and “complexity.”

Two factors, namely the “radius of vision” and the “area” index, significantly influence students' satisfaction with open spaces.

Outdoor designers should incorporate “green space” and “gathering spaces” into their designs since the presence of these is effective in attracting and satisfying students.

The number of people using an open space has little to do with how satisfied students are with it.

Half of the students use open areas between 11:00 and 14:00, so the provision of “canopy” and “shelter” in these spaces is essential.

This research aims to propose a model for the complex decision-making involved in the ecological restoration of mega-infrastructure (e.g. railway engineering). This model is based on multi-source heterogeneous data and will enable stakeholders to solve practical problems in decision-making processes and prevent delayed responses to the demand for ecological restoration.

Based on the principle of complexity degradation, this research collects and brings together multi-source heterogeneous data, including meteorological station data, remote sensing image data, railway engineering ecological risk text data and ecological restoration text data. Further, this research establishes an ecological restoration plan library to form input feature vectors. Random forest is used for classification decisions. The ecological restoration technologies and restoration plant species suitable for different regions are generated.

This research can effectively assist managers of mega-infrastructure projects in making ecological restoration decisions. The accuracy of the model reaches 0.83. Based on the natural environment and construction disturbances in different regions, this model can determine suitable types of trees, shrubs and herbs for planting, as well as the corresponding ecological restoration technologies needed.

Managers should pay attention to the multiple types of data generated in different stages of megaproject and identify the internal relationships between these multi-source heterogeneous data, which provides a decision-making basis for complex management decisions. The coupling between ecological restoration technologies and restoration plant species is also an important factor in improving the efficiency of ecological compensation.

Unlike previous studies, which have selected a typical section of a railway for specialized analysis, the complex decision-making model for ecological restoration proposed in this research has wider geographical applicability and can better meet the diverse ecological restoration needs of railway projects that span large regions.

This study aims to extend and explore patterns and trends of research in the linkage of big data and knowledge management (KM) by identifying growth in terms of numbers of papers and current and emerging themes and to propose areas of future research.

The study was conducted by systematically extracting, analysing and synthesizing the literature related to linkage between big data and KM published in top-tier journals in Web of Science (WOS) and Scopus databases by exploiting bibliometric techniques along with theory, context, characteristics, methodology (TCCM) analysis.

The study unfolds four major themes of linkage between big data and KM research, namely (1) conceptual understanding of big data as an enabler for KM, (2) big data–based models and frameworks for KM, (3) big data as a predictor variable in KM context and (4) big data applications and capabilities. It also highlights TCCM of big data and KM research through which it integrates a few previously reported themes and suggests some new themes.

This study extends advances in the previous reviews by adding a new time line, identifying new themes and helping in the understanding of complex and emerging field of linkage between big data and KM. The study outlines a holistic view of the research area and suggests future directions for flourishing in this research area.

This study highlights the role of big data in KM context resulting in enhancement of organizational performance and efficiency. A summary of existing literature and future avenues in this direction will help, guide and motivate managers to think beyond traditional data and incorporate big data into organizational knowledge infrastructure in order to get competitive advantage.

To the best of authors’ knowledge, the present study is the first study to go deeper into understanding of big data and KM research using bibliometric and TCCM analysis and thus adds a new theoretical perspective to existing literature.

The purpose of this study/paper is conducting a Systematic mapping review, as a systematic literature review method for reviewing the literature of new product development by textmining and mapping the results of this review.

This research has been conducted with the aim of systematically reviewing the literature on the field of design and development of products based on textual data. This research wants to know, how text data and text mining methods, can use for the design and development of new products.

This review finds out what are the most popular algorithms in this field? What are the most popular areas in using these approaches? What types of data are used in this area? What software is used in this regard? And what are the research gaps in this area?

The contribution of this review is creating a macro and comprehensive map for research in this field of study from various aspects and identifying the pros and cons of this field of study by systematic mapping review.

Because of the global increase of climate change effects, floods are becoming more frequent and severer, especially in urban areas of coastal cities and islands where floodplains have turned into buildings because of rapid urbanisation, leading to a higher risk of damages. Urban heritage areas should be highly considered in the time of evacuation because of the vulnerability of streets and buildings and limitations on taking counteractions. Given these limitations, this study aims to propose a network of potential evacuation routes based on spatial configuration analysis of the heritage areas.

Penang Island's heritage site, namely, George Town, located on the northwest coast of Malaysia, is chosen as the case study. By using an approach of spatial configuration analysis using space syntax techniques in addition to considering the potential starting points for evacuation and flood risk map of the area, this study analysed the area's street network values for evacuation function during flood crisis time.

Potential evacuation routes were identified for flood disasters in the George Town heritage area. Furthermore, the proposed evacuation routes were evaluated in terms of time for evacuation by metric step-depth analysis of space syntax.

A few studies have focused on practical guidelines for evacuation routes based on spatial configuration analysis, an important yet neglected approach in this regard, especially concerning urban island areas. This study can contribute to providing strategies to reduce vulnerability and casualties in urban heritage areas.

In recent years, there has been a growing interest in the potential of data analytics to enhance project delivery. Yet many argue that its application in projects is still lagging behind other disciplines. This paper aims to provide a review of the current use of data analytics in project delivery encompassing both academic research and practice to accelerate current understanding and use this to formulate questions and goals for future research.

We propose to achieve the research aim through the creation of a systematic review of the status of data analytics in project delivery. Fusing the methodology of integrative literature review with a recently established practice to include both white and grey literature amounts to an approach tailored to the state of the domain. It serves to delineate a research agenda informed by current developments in both academic research and industrial practice.

The literature review reveals a dearth of work in both academic research and practice relating to data analytics in project delivery and characterises this situation as having “more gap than knowledge.” Some work does exist in the application of machine learning to predicting project delivery though this is restricted to disparate, single context studies that do not reach extendible findings on algorithm selection or key predictive characteristics. Grey literature addresses the potential benefits of data analytics in project delivery but in a manner reliant on “thought-experiments” and devoid of empirical examples.

Based on the review we articulate a research agenda to create knowledge fundamental to the effective use of data analytics in project delivery. This is structured around the functional framework devised by this investigation and highlights both organisational and data analytic challenges. Specifically, we express this structure in the form of an “onion-skin” model for conceptual structuring of data analytics in projects. We conclude with a discussion about if and how today’s project studies research community can respond to the totality of these challenges. This paper provides a blueprint for a bridge connecting data analytics and project management.