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Cesspits are the means for each house to dispose of wastewater in the Bani Kinanah District (BKD) of Jordan, which creates severe environmental complications. This research aimed to find a suitable site for a wastewater treatment plant (WWTP) in BKD.

Geographic Information System (GIS)-based multicriteria decision analysis (MCDA) was used for an optimal site selection for a sewage treatment plant. Several datasets were obtained to prepare the maps of the criteria influencing the choice of the most suitable site for the WWTP. The analytic hierarchy process was used to apply the weights for each factor.

Five classes of suitability were generated: 0.23% very high suitability, 8.49% high suitability, 47.12% moderate suitability, 37.67% low suitability and 6.49% very low suitability. According to Analytical Hierarchy Process (AHP) results, the elevations, slope and groundwater depth have high importance; where their weights 21%, 19% and 17%, respectively. The most suitable site for establishing a WWTP was found in the northern part of the study area, where it is characterized by relatively low elevations (−90 to −93 m), low slope (0–2.5 %), distance from groundwater level (47–82 m) and the space is sufficient for building the plant (25328 m², 8861 m² and 8586 m²).

This research is limited by the availability of data.

The research is invaluable for decision makers involved in urban planning.

Wastewater treatment plants are essential for communities with limited resources such as Jordan. It has also profound impacts on the surrounding environment.

From the present study, it can be concluded that GIS is essential in urban utility establishment, like urban domestic wastewater treatment site selection. Although the study area has adequate potential areas for establishing WWTP, further assessment of flood vulnerability, wastewater amount quantification, population growth and urban expansion must be seriously considered before implementation.

This study aims to evaluate performance and map the science of research on International Organization for Standardization (ISO) 31000 standard through published articles. Specifically, this study determines the current state of the art, identifies research gaps and guides future studies related to ISO 31000.

This work investigates and examines the research papers acquired from the Scopus and Web of Science databases. Inclusion and exclusion criteria were applied to obtain relevant papers. Bibliometric analysis using Biblioshiny was conducted to answer the research objectives.

The results show growing interest in ISO 31000 research but limited interconnectivity among articles. Influential journals have emerged, highlighting key research trends in risk management's (RM) practical application and its significance in organizational decision-making. Key research areas include risk assessment (RA) methods, enterprise RM and system integration, endorsing ISO 31000 as a valuable tool. Future research should prioritize longitudinal studies to track ISO 31000's impact, study effective risk communication strategies, explore sector-specific RM practices and assess ISO 31000's application in emerging technologies.

This research reveals key themes and diverse methods that aid practitioners in customizing industry risk strategies, adapting to emerging trends, engaging global collaboration and improving risk communication. Nevertheless, the study might overlook non-English contributions, urging broader language inclusion for ISO 31000's profundity.

This paper's originality lies in its comprehensive bibliometric analysis of ISO 31000 research, providing valuable insights into the standard's growing significance and global impact. The study identifies key research themes and influential authors, guiding future research and improving RM practices.

The purpose of this study is to examine the impact of mandatory corporate social responsibility (CSR) spending on firm value in the Indian context.

Using firm-level data over the period 2012–2017, this study uses the difference-in-differences (DID) technique combined with matching to control for potential endogeneity of the decision to comply with the CSR Act since the Act in its current form is applicable as a comply-or-explain obligation.

The results of this study suggest that mandatory CSR spending has a positive and statistically significant impact on firm value. These results remain robust to alternative econometric techniques such as regression discontinuity design (RDD) and randomization inference test as well as to alternative empirical specifications. Furthermore, the study demonstrates that the positive effect of CSR spending on firm value is more pronounced for firms with higher information asymmetry problem and lower institutional holdings.

This study explicitly considers the “comply-or-explain” flexibility option, in terms of spending on CSR, provided to Indian firms for the initial two to three years and investigates whether spending on CSR helps firms enhance their firm value. The study also finds that the positive effect of CSR spending on firm value is more pronounced for firms with higher information asymmetry problems and lower institutional holdings.

This paper investigates the relationship of both technological (product and process) and non-technological (organizational and marketing) innovation with the gender wage gap at firms.

Using employer–employee level data from Estonia, the authors estimate Mincerian wage equations, in order to show how innovation at the firm level is associated with the gender wage gap. Next, the authors use propensity score matching (PSM) to study the effects of the movement of men and women into innovative firms, how this shapes the gender wage gap at firms.

The authors find that both technological and non-technological innovation are associated with a larger gender wage gap at firms. The relationship between innovation and the contemporaneous gender wage gap at firms reflects to a significant extent the different selection of men and women with different time-invariant characteristics to innovative firms. Further, the authors find that movement of men and women to work at innovative firms is in longer term associated with larger gains in wages for men. The authors also observe that the relationship of innovation with gender wage gap is stronger in the case of women with children.

Much of the prior analysis focuses on the effects of technological innovation on gender-related labour market outcomes. The authors show here that the relationship of innovation at firms with higher gender wage gap is not only specific to technological innovation, but is more general, and is observed across different types of innovation indicators, including non-technological innovation. This study's results suggest that the effects of innovation on gender wage gap may reflect to an extent the higher demand for flexibility of employees for work purposes at innovative firms, which may increase the gender wage gap, especially between men and women with children.

This study aims to investigate the configurational effects of five rules – artificial intelligence (AI)-based hiring decision transparency, consistency, voice, explainability and human involvement – on applicants' procedural justice perception (APJP) and applicants' interactional justice perception (AIJP). In addition, this study examines whether the identified configurations could further enhance applicants' organisational commitment (OC).

Drawing on the justice model of applicants' reactions, the authors conducted a longitudinal survey of 254 newly recruited employees from 36 Chinese companies that utilise AI in their hiring. The authors employed fuzzy-set qualitative comparative analysis (fsQCA) to determine which configurations could improve APJP and AIJP, and the authors used propensity score matching (PSM) to analyse the effects of these configurations on OC.

The fsQCA generates three patterns involving five configurations that could improve APJP and AIJP. For pattern 1, when AI-based recruitment with high interpersonal rule (AI human involvement) aims for applicants' justice perception (AJP) through the combination of high informational rule (AI explainability) and high procedural rule (AI voice), there must be high levels of AI consistency and AI voice to complement AI explainability, and only this pattern of configurations can further enhance OC. In pattern 2, for the combination of high informational rule (AI explainability) and low procedural rule (absent AI voice), AI recruitment with high interpersonal rule (AI human involvement) should focus on AI transparency and AI explainability rather than the implementation of AI voice. In pattern 3, a mere combination of procedural rules could sufficiently improve AIJP.

This study, which involved real applicants, is one of the few empirical studies to explore the mechanisms behind the impact of AI hiring decisions on AJP and OC, and the findings may inform researchers and managers on how to best utilise AI to make hiring decisions.

This research assesses the economic impact of biomass plant installations on Brazilian municipalities, focusing on (1) labor income, (2) sectoral labor income and (3) income inequality.

Municipal data from the Annual Social Information Report, the National Electric Energy Agency and the National Institute of Meteorology spanning 2002 to 2020 are utilized. The Synthetic Difference-in-Differences methodology is employed for empirical analysis, and robustness checks are conducted using the Doubly Robust Difference in Differences and the Double/Debiased Machine Learning methods.

The findings reveal that biomass plant installations lead to an average annual increase of approximately R$688.00 in formal workers' wages and reduce formal income inequality, with notable benefits observed for workers in the industry and agriculture sectors. The robustness tests support and validate the primary results, highlighting the positive implications of renewable energy integration on economic development in the studied municipalities.

This article represents a groundbreaking contribution to the existing literature as it pioneers the identification of the impact of biomass plant installation on formal employment income and local economic development in Brazil. To the best of our knowledge, this study is the first to uncover such effects. Moreover, the authors comprehensively examine sectoral implications and formal income inequality.

The purpose of this paper is to evaluate if, given personal, supply-related features, and labour demand-related variables, there is a difference in the share of women finding more stable jobs with respect to men, in an eight-year time span.

Fragmentation leads to a lower probability of transitioning into more certain, full-time work positions. The authors analyse a rich cohort of dependent workers in Emilia-Romagna to investigate whether part-time jobs lead to full-time jobs in a “stepping-stone” fashion and whether this happens with the same probability for men and women. The focus is on the cost of part-time jobs rather than the contrast between permanent and temporary jobs, as often observed in the literature. The authors also evaluate the transition between part-time job formulae and open-ended work arrangements to determine whether women's transition to full-fledged, stable work positions is slightly rarer than their male counterparts. Even if the authors allow for the fact that part-time contracts can be a choice and not an obligation, these contracts generate more flexibility in managing the equilibrium between private and work life and create more uncertainty than full-time contracts because of the fragmentation associated with these arrangements.

The authors find that women have a more fragmented working career than men, in that they hold more contracts than men in the same time span; moreover, the authors find that part-time jobs act more as bottlenecks for women than for men.

The authors use a large administrative dataset with over 600,000 workers observed in the 2008–2015 time span, in Emilia Romagna, Italy. The authors can disentangle the number of contracts per worker and observe individual, anonymise personal features, that the authors consider in the authors' propensity score estimate. The authors ran a robustness check of the PSM estimates through coarsened exact matching (CEM).

This work aims to explore the effects of (equity and non-equity) strategic alliances between banks and FinTechs on FinTechs' online visibility.

For a sample of 124 Italian FinTechs, the authors measured online visibility through their website ranking (Google PageRank) and website traffic (Google Trends). Consistent to the historical depth of these measures, the authors separately investigated the effect of equity and non-equity (contractual) agreements on online visibility by means of ordinal logistic regressions and diff-in-diff analysis.

Strategic alliances with banks enhance FinTechs' online visibility. Although both equity and contractual agreements positively influence the popularity of FinTechs' website achieved through the activity of internal and external online content creators (websites ranking), only equity agreements are effective in attracting Internet users (website traffic).

When deciding to interact with banks, FinTechs' managers should consider that equity agreements may be a powerful strategic choice for enlarging the customer base and boosting visibility of FinTechs.

Fostering strategic alliances between banks and FinTechs contributes to FinTechs' growth, generating virtuous mechanisms of innovation, financial inclusion and better allocative efficiency of the financial system.

This work expands marketing knowledge and literature regarding online visibility determinants, by investigating the benefits of strategic alliances and cooperation in the market, while providing an empirical strategy replicable by future marketing studies.

The context of a long-standing research tradition, discrimination has emerged as a critical factor contributing to inequalities within the labor market. While existing studies have primarily focused on overt discrimination during the recruitment and selection process, influenced by biases, attitudes, or stereotypes, there remains a significant knowledge gap regarding discrimination within the workplace and its underlying structural dimensions. This article aims to address this gap by examining the impact of organizational culture, structure and policies on workplace discrimination, with a particular emphasis on women and ethnic minorities.

Utilizing a case study strategy centered around a Belgian branch of a multinational professional service agency, data was gathered through ten semi-structured in-depth interviews conducted with employees representing various organizational levels.

The findings reveal that organizational culture, structure and policies may pose inherent risks in perpetuating discrimination throughout individuals' professional trajectories. Furthermore, it becomes apparent that, albeit often unconscious, these elements exhibit biases against women and ethnic minorities.

Given the unintentional nature of structural discrimination, it is crucial to foster increased awareness and understanding of these dynamics.

The originality of this research article lies in its focus on addressing a critical knowledge gap in the existing research tradition on discrimination in the labor market. While previous studies have primarily concentrated on overt discrimination during recruitment and selection, this article delves into the often overlooked area of discrimination within the workplace itself. It explores the intricate interplay of organizational culture, structure and policies in perpetuating discrimination, particularly against women and ethnic minorities. By utilizing a case study approach within a multinational professional service agency in Belgium, the research uncovers hidden biases and unconscious elements contributing to structural discrimination. This emphasis on understanding unintentional discrimination adds a novel dimension to the discourse on workplace inequalities.

The purpose of this study was to gain a deeper understanding of the selection criteria used in preincubation programs. Particular focus has been placed on examining the exclusive and inclusive nature of these criteria, and how they relate to both egalitarian and utilitarian considerations.

The study used two data sources: archival available online data and semi-structured interviews. Forty-nine preincubation programs were examined, with 19 representatives interviewed. The data was analyzed using content analysis to understand the access and selection criteria applied at the preincubation stage.

The goals of preincubation programs vary, including developing students’ competencies, creating new companies or achieving the goals of the corporation that sponsored the program. preincubation programs use three levels of selection criteria, including entry criteria, the potential of the submitted idea and team and the personal characteristics and competencies of the applicants. The entry criteria varied across programs, with some programs being open only to university employees and students, while others were open to the public. The study found that the majority of preincubation programs used a combination of both egalitarian and utilitarian motivations in their selection criteria.

The criteria used to evaluate applications flowing into preincubation should be strongly related to the goals that preincubation is supposed to achieve. It is essential to consider that, contrary to previous knowledge, this process is not only aimed at supporting the creation of new businesses.

To the best of the author’s knowledge, this is the first study that analyzes the approach to selection criteria in preincubation programs with such diverse goals and in different countries as well as expanding the understanding of the criteria used at different stages of the incubation process and relating to the inclusiveness in entrepreneurship.