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This chapter emphasizes the interconnectedness of legal frameworks, socio-cultural norms, and policy interventions in forging a more inclusive and just society for girls and women. Despite substantial strides, gender disparities still persist across the Western world, highlighting the need for targeted actions. The chapter explores the “glass ceiling” phenomenon, the wage gap, gender-based violence, emphasizing their persistence, and the imperative of transformative policies. Shifting focus to the East, the narrative navigates through distinct trajectories of women’s rights advocacy. Religious beliefs have historically reinforced gender inequality in some Eastern societies, shaping cultural norms and limiting women’s public participation. In the context of Islam, varying interpretations have led to differing perspectives on gender roles. The chapter showcases instances of progress, such as Saudi Arabian women gaining voting rights, while acknowledging enduring challenges like female genital mutilation and forced marriages. In the conclusion part, the chapter highlights the need for sustained efforts to dismantle barriers and elevate women’s voices, fostering a global landscape marked by gender equality and women’s empowerment.

Artificial intelligence (AI) can assist in the worldwide shortage of cybersecurity workers in technical and managerial roles. Thus, the purpose of this study was to investigate the role of AI in automating many of the routine tasks associated with cybersecurity. As such, AI enables cybersecurity personnel to reduce their workloads and focus on more strategic aspects of their work.

This study is an exploratory field study. The authors started by conducting a literature review to assess the possibility that AI tools can provide and how they can improve cybersecurity efficacy. Following this, the authors identified the specific core tasks for two cybersecurity work roles (technical and managerial) and searched for specific commercial tools that can perform each of the tasks. Then, the authors used the free ChatGPT 3.5 to list the current cybersecurity systems that use AI for the associated tasks, which the authors then reviewed with the tools’ documentation and websites to confirm these tasks were conducted or assisted by AI.

Results indicated that all 14 cybersecurity tasks of the technical work role are currently noted to be performed by commercial cybersecurity systems with AI-integrated capabilities, while only 11 of the 17 managerial work role tasks currently appear to be performed by AI.

The rapid integration of AI capabilities into commercial cybersecurity systems may suggest that the cybersecurity workforce must be currently trained on how to use AI tools in their daily operations, especially as it pertains to technical cybersecurity work roles.

The cybersecurity workforce shortage is reported to exceed four million cybersecurity workers worldwide in 2023. Thus, further understanding of the role of AI in improving the efficiency of technical and managerial cybersecurity tasks is significant.

The value of this research lies in the initial assessment of the current AI capabilities of commercial cybersecurity systems, which will ultimately provide the “super-human” performances resulting from human-AI teaming.

A fleet of mobile robots has been effectively used in various application domains such as industrial plant inspection. This paper proposes a solution to the combined problem of task allocation and motion planning problem for a fleet of mobile robots which are requested to operate in an intelligent industry. More specifically, the robots are requested to serve a set of inspection points within given service time windows. In comparison with the conventional time windows, our problem considers fuzzy time windows to express the decision maker’s satisfaction for visiting an inspection point.

The paper develops a unified approach to the combined problem of task allocation and motion planning for a fleet of mobile robots with three objectives: (a) minimizing the total travel cost considering all robots and tasks, (b) balancing fairly the workloads among robots and (c) maximizing the satisfaction grade of the decision maker for receiving the services. The optimization problem is solved by using a novel combination of a Genetic Algorithm with pareto solutions and fuzzy set theory.

The computational results illustrate the efficiency and effectiveness of the proposed approach. The experimental analysis leverages the potential for using fuzzy time windows to reflect real situations and respond to demanding situations.

This paper provides trade-off solutions to a realistic combinatorial multi-objective optimization problem considering concurrently the motion and path planning problem for a fleet of mobile robots with fuzzy time windows.

Nowadays, there is a strong public interest in promoting transparency to be informed about the actions of the public sector. At the same time, there has been a significant change in society’s perceptions and concerns about sustainable development, with a marked increase in attention to this area. In this context, our main objective is to investigate the impact of transparency practices in local government on the implementation of the Sustainable Development Goals (SDGs) in Spanish municipalities.

We will analyse a sample of 84 municipalities, using the Dynamic Transparency Index published by Dyntra to measure transparency. For the level of implementation of the SDGs, we will use an index specifically created using data from the report “The SDGs in 100 Spanish Cities”, published by the Spanish Network for Sustainable Development in 2020.

Municipalities with a larger dependent population tend to achieve higher SDG levels. Municipalities with lower financial surpluses and more self-generated resources show better SDG implementation. Progressive political parties lean more towards sustainability, and coalition governments show higher SDG implementation than majority governments. Gender appears to play a minor role in SDG implementation, but male leadership is associated with higher levels. Factors such as population density and government transfers do not have a significant impact on SDG implementation levels.

This study seeks to address the lack of empirical research on the potential impact of transparency on the achievement of the SDGs, while also taking into account other socio-economic, financial and political aspects of the municipality. In doing so, it also contributes to the limited empirical literature on the determinants of the level of SDG implementation in local governments.

This study delves into the nuanced relationship between financial constraints, ownership structures (state-owned and foreign) and innovation engagement within China’s A-share market, aiming to uncover how these dynamics vary across different industries and regional contexts.

By retrieving data from various datasets in China (2010–2022), this study analyzed the effectiveness of each variable, employing various dimensions to reflect innovation engagement among Chinese listed companies. Meanwhile, for the measurement of financial constraints, this study tested all four typical ones and opted for the KZ Index, as it is the most suitable for China’s A-share market. Then, by fixing the industry and year effects, the study examined the main and moderating effects. At last, in order to address endogeneity issues and capture the dynamic nature of innovation activities, this study follow the suggestion of Khatib (2024) and employed the two-step system Generalized Method of Moments (GMM) estimation.

The results demonstrate that while the government has introduced many policies to promote innovation, state-owned ownership does not consistently enhance innovation engagement as expected, especially when firms are in financial dilemma. Particularly, in Hi-tech industries, foreign ownership demonstrates greater interest and confidence in the innovation capabilities of China’s A-share market. Findings also reveal significant regional heterogeneity in the moderating role of ownership structures. While state-owned and foreign ownerships have a buffering effect against financial constraints in the eastern and western regions, but this effect is notably different in the middle part, even though it is China’s political heartland.

The findings offer a different insight for policymakers and corporate strategists, suggesting that targeted financial and regulatory policies that leverage specific ownership structures can foster innovation in different ways, particularly in financially constrained environments. However, how to stimulate innovation vitality in the middle part of China still requires further research.

Gamification has been constantly demonstrated as an effective mechanism for employee engagement. However, little is known about how gamification reduces cyberloafing and the mechanism by which it affects cyberloafing in the workplace. This study draws inspiration from self-determination and social bonding theories to explain how game dynamics, namely, personalised challenges, social interactivity and progression status, enhance tacit knowledge sharing behaviour, which, in turn, reduces cyberloafing. In addition, the study also examines the negative moderating effect of fear of failure on the positive relationship between game dynamics and tacit knowledge sharing.

Using a sample of 250 employees from information technology organisations, the study employed a 3-wave study to examine the conditional indirect effects.

The results ascertain that tacit knowledge sharing plays a central role in the relationship between gamification and cyberloafing. Further, game dynamics positively influenced tacit knowledge sharing, which in turn reduced cyberloafing. Especially, social interactivity and progression status greatly reduced cyberloafing behaviour when the fear of failure was low.

This study is one of the initial studies that suggest gamification as a progressive tool to reduce workplace cyberloafing behaviours. It utilises a problematisation approach to analyse and criticise the in-house assumptions regarding cyberloafing prevention measures. Further, the study proposes a conceptual model explaining the link between gamification and cyberloafing through alternate assumptions.

To overcome economic hardship and survival, informal entrepreneurs must continually activate specific resilience capabilities and reassess their entrepreneurial intentions (EI). Accordingly, they may develop transformational characteristics to design a model supporting intersectorial business growth. This study aims to examine the EI ecosystem of change resulting from the above endeavors and proposes an entrepreneurial intention transformation model (EITM).

Using the EI questionnaire developed by Liñán and Chen, data was collected from street vendors in the main markets of the Cameroonian capital (N = 307) to capture the determinants of behavior reflecting the propensity to activate entrepreneurial events within informal ventures.

It was uncovered that perceived collective support, resilience, orientation capability and inferred policies influence the dynamics of EI in the informal sector. Additionally, while revisiting current entrepreneurial lifecycle models, the study distinguished between the entrepreneurial events of “renegare” and formalization. Furthermore, the construction of an informal entrepreneurial lifecycle model confirms the need to acknowledge the formalization and “deformalization” processes as integrative parts of an intersectorial entrepreneurial lifecycle model.

This study extends existing research by proposing an intersectorial entrepreneurial lifecycle to recognize the dynamics of EI on ventures’ formalization. The EITM encompasses the EI dynamic process model and the proposed entrepreneurial lifecycle.

The research paper aims to analyse the scholarly literature on advancing HR analytics as an intervention for attrition, a problem that lingers on organisational performance. This study aspires to provide an in-depth literature review and critically assess the knowledge gaps in HR analytics and attritions within organisational performance.

The review analyses the corpus of 196 research articles published in ostensible journals between 2011 and 2023. To identify research gaps and provide valuable insights, this study synthesises relevant studies using School of thought (S), Context (C), Methodology (M), Triggers (T), Barriers (B), Facilitators (F) and Outcomes (O) (SCM-TBFO framework). This study employs the R programming language to conduct a systematic literature review in accordance with the “preferred reporting items for systematic reviews and meta-analysis” (PRISMA) guidelines.

The emerging discipline of HR analytics encompasses the potential to manage attrition and drive organisational performance enhancements effectively. The study of SCM-TBFO encompasses a multidimensional approach, incorporating diverse perspectives and analysing its complex aspects compared to various approaches. The School of thought includes the human capital theory, expectancy theory and resource-based view. The varied research contexts entail the USA, United Kingdom, China, France, Italy and India. Further, the methodologies adopted in the studies are artificial neural networking (ANN), regression, structure equation modelling (SEM) case studies and other theoretical studies. HR analytics and attrition triggers are data mining decision systems, forecasting for firm performance and employee satisfaction. The barriers include leadership styles, cultural adaptability and lack of analytic skills, data security and organisational orientation. The facilitators were categorised into data and technology-related facilitators, human resource policies and organisational growth and performance-related facilitators. The study's primary outcomes are technology adoption, effective HR policies, HR strategies, employee satisfaction, career and organisational expansion and growth.

The primary goal of the literature review is to provide a comprehensive overview of the current state of HR analytics and its impact on organisational performance, particularly in relation to attrition. Further, the study suggests that attrition, a critical organisational concern, can be effectively managed by strategically utilising HR analytics and empowering data-driven interventions that optimise performance and enhance overall organisational outcomes.

Understanding linguistic profiling and its substantial consequences on employee career development is essential in diverse workplaces. This study utilizes Levinson’s eras and career development theories to analyze the complicated relationship between linguistic profiling and biases, which hamper employee career development.

This study used an interpretive methodology and conducted thematic data analysis. It documented lessons learned from diverse viewpoints through semi-structured interviews with 19 participants conducted in November and December 2022.

The study demonstrates that linguistic discrimination occurs in diverse workplaces. After data exploration, four intriguing themes appeared. The first theme was related to employees who were discriminated against because of various languages. This shows how often language choice affects employees. The second theme examined how linguistic profiling intersected with marginalized groups, increasing discrimination. The third theme, linguistic profiling and career development showed that bias had a huge influence on career progression. The fourth theme emphasizes organizational policies for preventing language discrimination, promoting career growth and inclusive organizations.

This study advances the understanding of linguistic profiling and career development in a multilingual society. In addition, it furthers discourse and provides ways to minimize biases, creating a more inclusive workplace environment.