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In this chapter, we critically interrogate Pakistani Higher Education Commission (HEC)'s “Policy Guidelines against Sexual Harassment in Institutions of Higher Learning” (HEC, 2011, 2020) to reveal that the policy represents a form of rhetorical genderwashing, rather than a concerted attempt to effect structural change (Fox-Kirk et al., 2020). Through this critical interrogation, we introduce a new methodological approach to investigate genderwashing, that of collaborative feminist policy analysis. This chapter is based on the theoretical framework of Sara Ahmed's concept of “institutional nonperformativity” (2012). Pakistan recognized workplace harassment as a legal issue for the first time in the 2010 Sexual Harassment Act (Jabbar & Imran, 2013). The Act, and subsequent policies, was an attempt to practice equity and fairness in sexual harassment cases. Our investigation revealed that the policy reinforces gender power inequality, gendered language, and is an example of institutional silence, and genderwashing in the workplace (Fox-Kirk et al., 2020).

In the era of new technological revolution, seeking to survive and guarantee business sustainability in their digital internationalization, enterprises choose to become environmentally oriented. The need for new green business models has become evident in recent years, and enterprises offer green services in creative and eco-friendly ways. However, does the display of a green label on hotels' websites really promote the eco-conscious tourists' online booking intention? This study aims to examine the impact of the perceived label on the online sustainable hotel booking intention of the eco-conscious tourists, using the foundations of signal theory.

This study adopted a structural equation model to integrate several constructs with a sample of 349 validated responses.

The empirical results highlight, the importance of the green label perception on the eco-conscious tourists' booking intention of online sustainable hotel and the role that green trust and green perceived risk play as a mediating variable between the perception of the exposed label and the booking intention. Indeed, when booking a sustainable hotel online, the tourists may be sensitive to the exposure of a green label. Therefore, this signal decreases the perceived risk of unsustainability and ultimately increases the trust in hotel's sustainability.

The first limitation is related to the sample employed in this study. Given that most of the participants were residents of France, the results of this study may not be generalized to the entire population. Secondly, a range of other factors can affect the eco-conscious tourists' intentions to book online a hotel with green label, such as their attitude, social media influence, tourists' satisfaction, etc. Indeed, other variables and/or signals could be adopted to study online booking intention in the pandemic era.

In light of these results, theoretical and managerial implications are discussed. The findings make an important contribution to SMEs sustainability and internationalization by exploring new ties. This study considers how SMEs and specifically hotels start following green practices (e.g. adoption of an eco-label) relevant to their international environment where they operate and in response to global pressures. SMEs can survive better in the highly competitive global environment where they need to employ more green practices, however, managers should consider how green trust and green perceived risk can affect customer behavior. It also adds to the existing literature by dealing with customer perceptions about the green label of sustainable hotels and its subsequent effect on booking intention.

This study had shown the importance of the display of green label on the eco-conscious tourist's online booking intention.

Blockchain technology (BCT) can play a vital role in manufacturing industries by providing visibility and real-time transparency. With BCT adoption, manufacturers can achieve higher productivity, better quality, flexibility and cost-effectiveness. The current study aims to prioritize the performance metrics and ranking of enablers that may influence the adoption of BCT in manufacturing industries through a hybrid framework.

Through an extensive literature review, 4 major criteria with 26 enablers were identified. Pythagorean fuzzy analytical hierarchy process (AHP) method was used to compute the weights of the enablers and the Pythagorean fuzzy combined compromise solution (Co-Co-So) method was used to prioritize the 17-performance metrics. Sensitivity analysis was then carried out to check the robustness of the developed framework.

According to the results, data security enablers were the most significant among the major criteria, followed by technology-oriented enablers, sustainability and human resources and quality-related enablers. Further, the ranking of performance metrics shows that data hacking complaints per year, data storage capacity and number of advanced technologies available for BCT are the top three important performance metrics. Framework robustness was confirmed by sensitivity analysis.

The developed framework will contribute to understanding and simplifying the BCT implementation process in manufacturing industries to a significant level. Practitioners and managers may use the developed framework to facilitate BCT adoption and evaluate the performance of the manufacturing system.

This study can be considered as the first attempt to the best of the author’s knowledge as no such hybrid framework combining enablers and performance indicators was developed earlier.

Young graduates in Morocco are encountering an increasingly challenging labor market environment. Confronted with intense competition, job insecurity, and unclear career trajectories, many find themselves in low-skilled positions despite possessing relevant qualifications. This issue is particularly pronounced among vocational training graduates, who experience professional downgrading at a rate three times higher (33.6%) compared to their peers from general education (11.6%) (HCP, 2018). Our study aims to investigate professional downgrading among young vocational training graduates in Morocco, focusing on the factors contributing to this phenomenon and identifying potential solutions to address it.

Our study is based on the insertion and career path survey conducted by the Department of Professional Training with graduates of professional training programs in Morocco. For this edition, the survey was conducted in 2020, encompassing all 31,498 graduates of the 2016 professional training programs. The Heckman self-selection model is employed to analyze and explore various dimensions of downgrading. Factors such as gender, age, marital status, parental education, and the choice of vocational training field are scrutinized to understand their influence on downgrading.

The study reveals several key findings: Women exhibit a lower probability of professional downgrading compared to men. Young graduates are more vulnerable to downgrading, emphasizing the necessity for career guidance and mentorship programs to facilitate their entry into the job market. Marital status plays a role, with married individuals having a higher likelihood of downgrading. Parental education, particularly that of mothers, proves critical in preventing subjective downgrading of vocational training graduates, highlighting the need for adult literacy and education programs. The effectiveness of the National Agency for the Promotion of Employment and Competencies (ANAPEC) programs in preventing downgrading among vocational training graduates is questioned, suggesting the need for program revisions tailored to this population. The choice of vocational training field significantly impacts downgrading, with graduates of technical training programs experiencing advantages. This emphasizes the importance of diversifying training fields and aligning them with market demands.

This study provides valuable insights into the phenomenon of professional downgrading among young vocational training graduates in Morocco. The findings emphasize the need for targeted policy interventions. Recommendations include supporting young graduates, reassessing programs offered by the ANAPEC, and enhancing technical training to better align with the evolving demands of the labor market.

Cilia serves numerous biological functions in the human body. Malfunctioning of nonmotile or motile cilia will have different kinds of consequences for human health. More specifically, the directed and rhythmic beat of motile cilia facilitates the unidirectional flow of fluids that are crucial in both homeostasis and the development of ciliated tissues. In cilia-dependent hydrodynamic flows, tapering geometries look a lot like the structure of biological pathways and vessels, like airways and lymphatic vessels. In this paper, the Carreau fluid model through the cilia-assisted tapered channel (asymmetric) under the influence of induced magnetic field and convective heat transfer is investigated.

Lubrication theory is a key player in the mathematical formulation of momentum, magnetic field and energy equations. The formulated nonlinear and coupled differential equations are solved with the aid of the homotopy perturbation method (HPM). The graphical results are illustrated with the help of the computational software “Mathematica.”

The impact of diverse emerging physical parameters on velocity, induced magnetic field, pressure rise, current density and temperature profiles is presented graphically. It is observed that the cilia length parameter supported the velocity and current density profiles, while the Hartman number and Weissenberg number were opposed. A promising effect of emerging parameters on streamlines is also perceived.

The study provides novel aspects of cilia-driven induced magnetohydrodynamics flow of Carreau fluid under the influence of induced magnetic field and convective heat transfer through the asymmetric tapered channel.

The purpose of this study is to assess the incorporation of fiber reinforced polymer (FRP) bars in concrete as a reinforcement enhances the corrosion resistance in a concrete structure. However, FRP bars are not practically used due to a lack of standard codes. Various codes, including ACI-440-17 and CSA S806-12, have been established to provide guidelines for the incorporation of FRP bars in concrete as reinforcement. The application of these codes may result in over-reinforcement. Therefore, this research presents the use of a machine learning approach to predict the accurate flexural strength of the FRP beams with the use of 408 experimental results.

In this research, the input parameters are the width of the beam, effective depth of the beam, concrete compressive strength, FRP bar elastic modulus and FRP bar tensile strength. Three machine learning algorithms, namely, gene expression programming, multi-expression programming and artificial neural networks, are developed. The accuracy of the developed models was judged by R², root means squared and mean absolute error. Finally, the study conducts prismatic analysis by considering different parameters. including depth and percentage of bottom reinforcement.

The artificial neural networks model result is the most accurate prediction (99%), with the lowest root mean squared error (2.66) and lowest mean absolute error (1.38). In addition, the result of SHapley Additive exPlanation analysis depicts that the effective depth and percentage of bottom reinforcement are the most influential parameters of FRP bars reinforced concrete beam. Therefore, the findings recommend that special attention should be given to the effective depth and percentage of bottom reinforcement.

Previous studies revealed that the flexural strength of concrete beams reinforced with FRP bars is significantly influenced by factors such as beam width, effective depth, concrete compressive strength, FRP bars’ elastic modulus and FRP bar tensile strength. Therefore, a substantial database comprising 408 experimental results considered for these parameters was compiled, and a simple and reliable model was proposed. The model developed in this research was compared with traditional codes, and it can be noted that the model developed in this study is much more accurate than the traditional codes.

This paper aims to unravel the impact of post-pandemic COVID-19 on foreign direct investment (FDI) and its determinants in the South Asian Association for Regional Cooperation (SAARC) Countries.

The study utilized four macroeconomic variables includes growth domestic product growth rate (GDPG), inflation rate (IR), exchange rate (ER), and unemployment rate (UR) to assess their impact on post-pandemic FDI, along with two variables control of corruption (CC) and political stability (PS) to measure the influence of good governance. Random effects, fixed effects, cluster random effects, cluster fixed effects and generalized method of moments (GMM) models were applied to a balanced panel dataset comprising eight SAARC countries over the period 2010–2021. To identify the random trend component in each variable, three renowned unit root tests (Levin, Lin and Chu LLC, Im-Pesaran-Shin IPS and Augmented Dickey-Fuller ADF) were used, and co-integration associations between variables were verified through the Pedroni and Kao approaches. Data analysis was performed using STATA 17 software.

The major findings revealed that the variables have an order of integration at the first difference I (1). Nonetheless, this situation suggests the possibility of a long-term link between the series. And the main results of the findings show that the coefficients of GDPG, CC and PS are positive and significant in the long run, showing that these variables boosted FDI inflows in the SAARC region as they are significantly positively linked to FDI inflows. Similarly, the coefficients of UR, IR, ER and COVID-19 are negative and significant.

By identifying the specific impacts of the post-pandemic FDI and its determinants, governments and policymakers can formulate targeted policies and measures to mitigate the adverse effects and enhance investment attractiveness. Additionally, investors can gain a deeper understanding of the risk factors and adapt their strategies accordingly, ensuring resilience and sustainable growth. Finally, this paper adds value to the literature on the post-pandemic impact on FDI inflows in the SAARC region.

This paper is the first attempt to trace the impact of COVID-19 on Foreign Direct Investment and its determinants in the SAARC Countries. Most of the previous studies were analytical in nature and, if empirical, excluded some countries due to the unviability of the data set. This study includes all the SAARC member countries, and all variables' data are completely available. There is still a lack of empirical studies related to the SAARC region; this study attempts to fill the gap.

The study aims to examine the role of green learning orientation, green knowledge acquisition and green knowledge management in fostering corporate environmental performance of small and medium-sized enterprises (SMEs) in China. In addition, this research assesses the moderating role of chief executive officer (CEO) gender between green knowledge management and corporate environmental performance. Finally, this study examines the sequential mediating role of green knowledge acquisition and green knowledge management.

The study collected the data of 300 SMEs’ CEOs taken from five different provinces in China. The study used a partial least squares regression-based structural equation modelling technique.

The findings revealed that green learning orientation plays an important role in increasing SMEs’ corporate environmental performance. The results showed that green knowledge acquisition and green knowledge management serially and completely mediate the relationship between green learning orientation and corporate environmental performance.

To the best of the authors’ knowledge, this is the first study addressing the sequence of knowledge orientation, acquisition, management and results in terms of corporate environmental performance. Meanwhile, this study is the first to examine the indirect role of CEO gender on the relationship between green knowledge management and corporate environmental performance. As decisions are taken by the top management and CEO, especially in the case of SMEs, the role of top management and how well top management uses the knowledge acquired by the organization matters significantly.

The study aims to promote the use of qualitative methods in service research by investigating how these methods are reported in service journals, how the level of reporting has evolved and whether methodological reporting influences the downloads or citations received by qualitative articles.

Methodological reporting practices were identified through content analysis of 318 qualitative articles published in three major service research journals and comparison with prior methodological literature. Regression analysis was used to test how the level of methodological reporting influences article downloads and citations.

The study identifies 29 reporting practices related to 9 key methodological reporting areas. The overall level of methodological reporting in published qualitative articles has increased over time. While differences in the level of reporting between service journals persist, they are narrowing. The level of methodological reporting did not influence downloads or citations of qualitative articles.

Service scholars using qualitative methods should pay attention to methodological reporting as it can improve the chances of being published. Factors such as theoretical contributions are likely to have a greater influence on article impact than methodological reporting.

No prior study has explored methodological reporting practices across different qualitative methodologies or how reporting influences article impact. For authors, reviewers and editors, the study provides an inventory of reporting practices relevant for evaluating qualitative articles, which should lower barriers for qualitative methods in service research by providing practical guidelines on what to focus on when reporting and assessing qualitative research.

The present research aims to analyze the influence of Green Supply Chain Management (GSCM) on the Sustainable Performance (SP) of Spanish wineries, examining the intermediary roles of Circular Economy Capability (CEC) and Green Ambidexterity Innovation (GAI) within this primary relationship. In particular, the study seeks to answer the following Research Questions (RQs): (RQ1), does GSCM exert a positive impact on wineries’ SP? (RQ2), does CEC play a mediating role in the interconnection between GSCM and wineries’ SP? And (RQ3), does GAI function as a mediator in the interplay between GSCM and wineries’ SP?

The research utilizes Partial Least Squares Structural Equation Modeling (PLS-SEM) to evaluate the hypothesized theoretical model using primary data collected from 196 Spanish wineries from September 2022 to January 2023.

The results reveal a positive relationship between GSCM and SP in Spanish wineries, as well as the existence of positive partial mediations of CEC and GAI in this main linkage, which allows an affirmative answer to the three RQs formulated.

Distinguished by its innovative exploration, this research marks a pioneering effort in the uncharted field of scrutinizing CEC and GAI as mediating factors in the GSCM-SP nexus, thereby enriching the existing body of knowledge and opening new avenues for future academic research on sustainability in the wine industry.