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This paper aims to appraise the effectiveness of gender quotas in breaking the glass ceiling for women on boards (WoBs) in companies that are legally obliged to comply with quotas (listed companies and state-owned companies, LP) and in those that are not (unlisted companies and nonstate-owned companies, NLNP). Furthermore, it investigates the glass cliff phenomenon, according to which women are more likely to be appointed to apical positions in underperforming companies.

A balanced panel data of the top 116 Italian companies by total assets, which are present in both 2010 and 2017, is used for estimating ANOVA tests across sectors and fixed-effects panel regression models.

WoBs significantly increased in both the LP and the NLNP companies, and this increase was greater in the financial sector. Furthermore, the relationship between the percentage of WoBs and firm performance is not linear but depends on the financial corporate health. Specifically, the situation in which a woman ascends to a leadership position in challenging circumstances where the risk of failure is high (glass cliff phenomenon) is only present in companies with the lowest performance in the sample, in other words, when negative values of Roe and negative or zero values of Roa occur together.

These findings have relevant policy implications that encourage the adoption of gender quotas even in specific top positions, such as CEO or president, as this could lead to a “double spillover effect” both vertically, that is, in other job positions, and horizontally, toward other companies not targeted by quotas. Practical interventions to support women in glass cliff positions, on the other hand, relate to the extent of supervisor mentoring and support to prevent women from leaving director roles and strengthen their chances for career advancement.

The authors explore the ability of gender quotas to break through the glass ceiling in companies that are not legally obliged to do so, and to the best of the authors’ knowledge, for the first time, the glass cliff phenomenon in the Italian context.

The paper aims at studying the effect of management practices on the extensive and intensive export margins of Egyptian manufacturing firms.

The study relies on the 2020/2021 Egyptian Industrial Firm Behavior Survey (EIFBS) which comprises 2,383 manufacturing firms representing small, medium, and large sized firms located in different regions of Egypt: Urban Governorates, Lower Egypt, and Upper Egypt. It constructs an overall management z score for each firm to estimate its effect on a firm’s probability of exporting and value of exports using Ordinary Least Squares (OLS) regressions.

Results indicate that good management is associated with a higher probability of firm exporting as well as higher export revenues conditional on exporting, robust to controlling for the level of domestic sales. These effects do not differ by firm ownership or type of sector, but rather by firm size, with managerial competence raising the probability of exporting more for large-sized firms. Additionally, good management is associated with higher firm productivity, innovation and worker training propensities which gives evidence that it is both an efficiency and a quality enhancer. Moreover, monitoring and targeting practices have significant positive effects on both margins, while incentives are only significant for the extensive margin.

Firms that aim at enhancing their export prospects and revenues should devote resources to review and upgrade their management systems to boost their product quality and production efficiency. Policy-wise, the government should create a competitive market environment that is open to both domestic and foreign firms’ entry to stimulate the adoption of better management practices.

The paper is the first to explore the link between firm management practices and export outcomes for a MENA country (Egypt). It makes use of a recent survey, the 2020/2021 Egyptian Industrial Firm Behavior Survey (EIFBS). The findings shed light on the importance of different management components (monitoring, targeting and incentives) in driving a manufacturing firm’s export performance.

The principal aim of this research is to acquire a deeper understanding of the opinion held by the training and development (T&D) professionals, regarding the use of artificial intelligence (AI) technology in the area of T&D. Particularly in response to the evolving needs of learners, the research aims to ascertain T&D professionals' perspective on the efficiency of AI in fostering T&D, while understanding the constraints and limitations associated with this technology.

The study is based on qualitative data. With the help of semi-structured interviews, qualitative data has been collected from 21 T&D professionals. Experts working with multinational corporations (MNCs) are selected as a study sample using a convenient sampling technique. Qualitative data were analysed using thematic analysis. Conclusions were drawn based on the results of thematic analysis.

The findings of the study have revealed a notable and rapid evolution in the requirements of learners, particularly during and post-COVID-19 period. AI-based technology has emerged as a significant contributor, offering learners distinct personalised experiences and enhanced convenience. However, the implementation of AI in training remains in its early stages and has not reached widespread adoption. The findings of the study also highlighted various challenges and limitations, while using AI-based technology for training. It has been found that AI complements rather than replaces the role of a physical trainer.

The originality of this study lies in the application of AI-based training for professional learners, from the perspective of the T&D practitioners working with MNCs in Maharashtra, India. Numerous studies that have recently been published, emphasise the areas in which AI technology can transform the T&D industry. Yet, there are currently very less studies that have attempted to understand the evolving needs of learners and support of AI-based training for the same, from the perspective of the T&D professionals working in Maharashtra, India.

Construction accidents cause as much harm in Bangladeshi construction as it does globally. This study examines the primary causes of accidents and undertakes an impact assessment of neglecting safety protocols in construction projects in Bangladesh, funded publicly, privately and through a Public-Private Partnership (PPP).

Research was initiated with a comprehensive questionnaire from experts, sourcing data in Bangladesh's construction sector. Data analysis utilized Cronbach's alpha, relative important index and a fishbone diagram for causal visualization.

The study identified the three major causes of safety negligence as “Poor safety culture (RII = 0.857),” “Top management's inattention (RII = 0.825)” and “Lack of personal care (RII = 0.825).” Effects: “Rising project expenses (RII = 0.88),” “Increased medical costs (RII = 0.87)” and “Worker compensation expenses (RII = 0.87).” The study also used the Ishikawa-Fishbone and effect-flow diagrams to highlight accident causes/effects and compare their primary causes in PPP, public and private projects.

Research on construction safety in Bangladesh has mainly focused on identifying factors within specific construction sectors. Since the rules and regulations vary across these three sectors, different health and safety hazards may arise. As a result, this research fills a critical gap by providing a comparative study that examines the causes and impacts of different project types in the Bangladeshi construction industry. By pinpointing the result, this research aims to enhance the safety and well-being of the construction workers sector-wise, thereby contributing to the industry's sustainable growth.

This paper examines the relationship between open innovation (measured by exploratory and exploitative linkages) and firm-level innovative activity in the offshore renewable energy (ORE) sector.

A unique, purpose-built survey that targeted firms operating in the ORE sector and its supply chain was used. The data provides novel insights into the research activities and networking capabilities of an industry in its infant stages of development. Regression models are used to estimate the relationship between firm-level external linkages and innovative activity.

Exploratory linkages are positively related to more innovative activity. This relationship is subject to diminishing returns, distinguishing the ORE sector from other sectors. Collaborating with suppliers and accessing scientific journals are conducive to research and development (R&D) activity and process innovation, whilst collaborating with customers is associated with the decision to introduce new products and processes.

This study provides evidence of a positive, but curvilinear, relationship between external knowledge linkages and innovative activity, adding novel insights into the relationship between open innovation (OI) strategies, research and innovation outcomes for firms predominantly in the introductory stages of the technological life cycle with limited commercialisation experience. The nuanced finding that specific linkages matter for certain research and innovation (R&I) outcomes adds deeper complexity to March’s (1991) framework, where tailoring certain exploratory or exploitative linkages to specific innovation activities is important.

This paper aims to define the efficiency achieved by urban transport companies in Spain concerning the resources they use, considering the type of management used for implementation, public-private, and size.

This study consisted of an analysis of the efficiency of 229 public-private urban transport operators during the period 2012–2021 using Data Envelopment Analysis, the Malmquist Index and inference estimators to determine productivity, efficiency change into Pure Technical Efficiency Change (PTECH), and scale efficiency change.

Based on the efficiency analysis, the authors concluded that of the 229 companies studied, more than 35 were inefficient in all analysed periods. Considering the sample used, direct management is considered significantly more efficient. It cannot be concluded that the size of these companies influences their efficiency, as the data show unequal development behaviours in the studied years.

This study provides arguments on whether there is a significant difference between the two types of management in the urban transport sector. It also includes firm size as a study variable, which has not been previously considered in other studies related to urban transport efficiency. Efficiency should be a crucial factor in determining funding allocation in this sector, as it encourages operators to optimize and improve their services.

This chapter reviews the evidence on the role of physicians in shaping inequalities in access to and utilisation of healthcare. The authors examine three types of physician decisions that can influence inequalities in access and utilisation: location decisions, decisions to work in the public and/or private sector, and decisions or behaviours in the doctor–patient encounter. For each, the authors summarise the issues and empirical evidence on possible policies to help reduce inequalities in access. Future research to reduce inequalities should focus on changes to health systems that influence physician decisions, such as health insurance expansions, the public–private mix and financial incentives, as well as physician training and policies for a more diverse physician workforce.

The authors mobilise stewardship theory, which delves into trust and collaboration dynamics, advocating for long-term gains through actions beneficial to the broader community. Used as a fundamental framework to conceptualise the model, stewardship theory enhances the understanding of the effect of purchasing social responsibility (PSR) practices to foster innovativeness and performance through the supply chain (SC). This study aims to examine the relationship between PSR, SC innovativeness (SC-INNO) and SC operational performance (SCOP). In addition, the moderating effect of sustainability labels on these relationships will be studied.

Based on survey data from 177 organisations analysed through partial least square structural equation modelling, the results suggest that PSR has a positive and significant effect on SC-INNO and SCOP. In addition, SC-INNO plays a partial mediation role since the direct effect between PSR and SCOP is validated. Furthermore, the moderating effects of holding a sustainability label and industry type about PSR and SCOP are supported.

The results indicate a significant positive influence of PSR on both SC-INNO and operational performance. SC-INNO is found to partially mediate the PSR–SCOP relationship. Moreover, sustainability labels and industry type significantly moderate the effects of PSR on SCOP.

The findings extend stewardship theory into the sustainable purchasing and supply management field by providing empirical support for PSR as a reflection of stewardship behaviours by fostering innovation and performance throughout the SC.

The purpose of this research is to delve into the scientific literature on hotel housekeepers in family hotel businesses to suggest new research directions in this field.

This paper is based on a concise literature review to discuss the past and future of research on family hotel business.

Research on family hotel businesses and the relationships and working conditions of their employees is limited. Most studies are focused on family businesses in general, without specific emphasis on a particular sector, or a specific job within each sector, or the type of company within a sector.

This paper synthesizes existing research on family businesses, particularly family hotel businesses, to delve into work conditions in both fields. It seeks to establish connections with the job conditions of hotel housekeepers as a means of addressing some of the challenges they face in their working environment.

This study attempts to explore the linkages between reliable big and cloud data analytics capabilities (RB&CDACs) and the comparative advantage (CA) that applies in the manufacturing sector in the countries located in North Africa (NA). These are considered developing countries through generating green product innovation (GPI) and using green process innovations (GPrLs) in their processes and functions as mediating factors, as well as the moderating role of data-driven competitive sustainability (DDCS).

To achieve the aim of this study, 346 useable surveys out of 1,601 were analyzed, and valid responses were retrieved for analysis, representing a 21.6% response rate by applying the quantitative methodology for collecting primary data. Convergent validity and discriminant validity tests were applied to structural equation modeling (SEM) in the CB-covariance-based structural equation modeling (SEM) program, and the data reliability was confirmed. Additionally, a multivariate analysis technique was used via CB-SEM, as hypothesized relationships were evaluated through confirmatory factor analysis (CFA), and then the hypotheses were tested through a structural model. Further, a bootstrapping technique was used to analyze the data. We included GPI and GPrI as mediating factors, while using DDCS as a moderated factor.

The empirical findings indicated that the proposed moderated-mediation model was accepted due to the relationships between the constructs being statistically significant. Further, the findings showed that there is a significant positive effect in the relationship between reliable BCDA capabilities and CAs as well as a mediating effect of GPI and GPrI, which is supported by the proposed formulated hypothesis. Additionally, the findings confirmed that there is a moderating effect represented by data-driven competitive advantage suitability between GPI, GPrI and CA.

One of the main limitations of this study is that an applied cross-sectional study provides a snapshot at a given moment in time. Furthermore, it used only one type of methodological approach (i.e. quantitative) rather than using mixed methods to reach more accurate data.

This study developed a theoretical model that is obtained from reliable BCDA capabilities, CA, DDCS, green innovation and GPrI. Thus, this piece of work bridges the existing research gap in the literature by testing the moderated-mediation model with a focus on the manufacturing sector that benefits from big data analytics capabilities to improve levels of GPI and competitive advantage. Finally, this study is considered a road map and gaudiness for the importance of applying these factors, which offers new valuable information and findings for managers, practitioners and decision-makers in the manufacturing sector in the NA region.