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The objective of this study is to systematically identify, categorize and assess the driving factors and interdependencies associated with various types of healthcare waste. The study specifically focuses on waste that has been managed or is recommended for treatment through the application of Lean Six Sigma (LSS) methodologies.

To accomplish the study’s objectives, interpretive structural modeling (ISM) was utilized. This analytical tool aided in quantifying the driving power and dependencies of each form of healthcare waste, referred to as “enablers,” as well as their related variables. As a result, these enablers were classified into four distinct categories: autonomous, dependent, linkage and drivers or independents.

In the healthcare sector, the “high cost” (HC) emerges as an autonomous variable, operating with substantial independence. Conversely, variables such as skill wastage, poor service quality and low patient satisfaction are identified as dependent variables. These are distinguished by their low driving power and high dependency. On the flip side, variables related to transportation, production, processing and defect waste manifest strong driving forces and minimal dependencies, categorizing them as independent factors. Notably, inventory waste (IW) is highlighted as a salient issue within the healthcare domain, given its propensity to engender additional forms of waste.

Employing the ISM model, along with comprehensive case study analyses, provides a detailed framework for examining the complex hierarchies of waste existing within the healthcare sector. This methodological approach equips healthcare leaders with the tools to accurately pinpoint and eliminate unnecessary expenditures, thereby optimizing operational efficiency and enhancing patient satisfaction. Of particular significance, the study calls attention to the key role of IW, which often acts as a trigger for other forms of waste in the sector, thus identifying a crucial area requiring focused intervention and improvement.

This research reveals new insights into how waste variables are structured in healthcare, offering a useful guide for managers looking to make their waste-reduction strategies more efficient. These insights are highly relevant not just for healthcare providers but also for the administrators and researchers who are helping to shape the industry. Using the classification and ranking model developed in this study, healthcare organizations can more easily spot and address common types of waste. In addition, the model serves as a useful tool for practitioners, helping them gain a deeper, more detailed understanding of how different factors are connected in efforts to reduce waste.

This paper aims to analyze the impact of the adoption of ISO 14001 and ISO 9001 on the performance of Portuguese companies. The sample includes the companies listed on Euronext Lisbon, with economic, financial and specific information – the specific being environmental information and quality information – for the period between 2015 and 2019, which corresponds to the post-Troika period when some economic growth started to be witnessed. The specific information of each area is translated into the environmental certification by the ISO 14001 standard, the quality certification by the ISO 9001 standard, and sustainability reports.

To achieve this aim, four variables were used as a measure of the companies' performance, Return on Assets (ROA), Return on Equity (ROE); Tobin's Q and EBITDA Margin. With this data, different panel models were tested to validate if ISO 9001 and ISO 14001 certifications impact Portuguese listed companies performance. Specifically, the authors have used the Generalized Method of Moments, GMM-System, an estimation method proposed by Arellano and Bover (1995) and Blundell and Bond (1998).

The results show that, in general, the environment and quality variables fail to explain the dependent variables, that is, ISO certifications do not provide positive or negative variations in the performance of companies, suggesting that they are not yet as much for civil society, as well as for current or potential shareholders. When used as an independent variable, certification according to the ISO 14001 or 9001 standards, negative and significant oscillations were verified in the dependent variable, MgEBITDA, suggesting that only for managers this variable is determinant, but with a negative impact, given the high costs, it entails without pressure from other stakeholders.

This study is the first to analyze the impact of the adoption of ISO 14001 and ISO 9001 on Portuguese companies' performance. This empirical study aims to show all investors, managers, regulators and civil society itself the long path that still needs to be taken toward sustainability.

The purpose of this study is to analyse cyberfraud in the South African banking industry using a multiple regression approach and develop a predictive model for the estimation and prediction of financial losses due to cyberfraud.

To mitigate the occurrence of cyberfraud, this study uses the multiple regression approach to correlate the relationship between financial loss and cyberfraud activities. The cyberfraud activities in South Africa are classified into three, namely, digital banking application, online and mobile banking fraud. Secondary data that captures the rate of cyberfraud occurrences within these three major categories with their resulting financial losses were used for the multiple regression analysis that was carried out in the Statistical Package for Social Science (SPSS, 2022 environment).

The results obtained indicate that the South African financial institutions still incur significant financial losses due to cyberfraud perpetration. The two main independent variables used to estimate the magnitude of financial loss in the South Africa’s banking industry are online (internet) banking fraud (X2) and mobile banking fraud (X3). Furthermore, a multiple regression model equation was developed for the prediction of financial loss as a function of the two independent variables (X2 and X3).

This study adds to the literature on cyberfraud mitigation. The findings may promote the combat against cyberfraud in the South Africa’s financial institutions. It may also assist South Africa’s financial institutions to predict the financial loss that financial institutions can incur over time. It is recommended that South Africa’s financial institutions pay attention to these two key variables and mitigate any associated risks as they are crucial in determining their profitability.

Existing literature indicated significant financial losses to cyberfraud perpetration without establishing any relationship between the magnitude of losses incurred and the prevalent forms of cyberfraud. Thus, the novelty of this study lies in the analysis of cyberfraud in the South African banking industry using a multiple regression approach to link financial losses to the perpetration of the prevalent forms of cyberfraud. It also develops a predictive model for the estimation and projection of financial losses.

This study aims to develop an educational tourism demand model, particularly in respect to dynamic effects, university quality (QU) and competitor countries. Educational tourism has been identified as a new tourism sub-sector with high potential, and is thus expected to boost economic growth and sustainability.

This study reviews the literature on the determinants of educational tourism demand. Even though the existing literature is intensively discussed, mostly focusing on the educational tourism demand from an individual consumer's perspective, this study makes an innovation in line with the aggregate demand view. The study uses data that consist of the enrolment of international students from 47 home countries who studied in Malaysia from 2008 to 2017. The study utilised the dynamic panel method of analysis.

This study affirms that income per capita, educational tourism price, price of competitor countries and quality of universities based on accredited programmes and world university ranking are the determinants of educational tourism demand in both the short and the long term. Also, a dynamic effect exists in educational tourism demand.

The results imply that government should take the quality of services for existing students, price decisions and QU into account to promote the country as a tertiary education hub and achieve sustainable development.

Research on the determinants of the demand for educational tourism is rare in terms of macro data, and this study includes the roles of QU, competitor countries and dynamic effects.

This study aims to investigate the factors influencing the adoption intention of artificial intelligence (AI) by micro, small and medium enterprises (MSMEs) in Jordan.

The study adopts the technology–organization–environment (TOE) model. It examines the moderating effects of innovation culture, employee digital skill level and market competition on the relationships between the independent and dependent variables. A survey was utilized to collect data from 537 MSME owners or managers in Jordan and employed partial least squares structural equation modeling to test the hypotheses.

The results of the study support seven out of eight hypotheses. Business innovativeness, management support, perceived benefits and technological infrastructure have positive and significant effects on AI adoption intention, while perceived costs have no significant effect. However, the innovation culture, employee digital skill level and market competition were found to moderate the relationships between some of the independent variables and dependent variables.

The study provides valuable insights and recommendations for MSME owners, managers, employees, policymakers, educators and researchers interested in promoting and facilitating AI adoption by MSMEs in Jordan.

The current attempt extends the TOE framework by adding significant constructs representing the three contexts. Moreover, it is one of the few studies that analyzed the factors influencing the adoption intention of AI by MSMEs in Jordan, which are significant to the Jordanian economy and represent 99.5% of enterprises.

Sustainability represents innovative elements in determining the profitability of real estate investments, among other factors, including the green component in real estate. Evidence from the literature has pointed out that incorporating green features into residential buildings can reduce operational costs and increase the building’s value. Although green real estate is considered the future trend of choice, it is still being determined whether prospective buyers are willing to accept the extra cost of green residential investment. Therefore, this study aims to investigate the effect of housing attributes and green certification on residential real estate prices.

The impact of the housing attribute and green certification in the residential sectors was assessed using a transaction data set comprising approximately 861 residential units sold in Selangor, Malaysia, between 2014 and 2022. Linear and quantile regression were used in this study by using SPSS software for a robust result.

The findings indicate that the market price of residential properties in Malaysia is influenced by housing attributes, transaction types and Green Building Index certification. The empirical evidence from this study suggests that green certification significantly affects the sales price of residential properties in Malaysia. The findings of this research will help investors identify measurable factors that affect the transaction prices of green-certified residential real estate. These identifications will facilitate the development of strategic plans aimed at achieving sustainable rates of return in the sustainable residential real estate market.

Specifically, this research will contribute to achieving area 4 of the 11th Malaysia Plan, which pertains to pursuing green growth for sustainability and resilience. This will be achieved by enhancing awareness among investors and homebuyers regarding the importance of green residential buildings in contributing to the environment, the economy and society.

The regression model for housing attributes and green certification on house price developed in this study could offer valuable benefits to support and advance Malaysia in realising its medium and long-term goals for green technology.

The purpose of this study is to investigate the impact of Corona Virus Disease 2019 (COVID-19) on the outcome of construction projects and explore the moderating effects of emerging technologies on the relationship between COVID-19 and construction project outcomes.

Data for the study was collected through a Web-based, semistructured questionnaire. The responses of 62 construction practitioners were analyzed using a hierarchical linear regression model. The model consists of 16 independent variables, three control variables (organization size, organization type and project size), one moderator (adoption level of emerging technologies) and three dependent variables (project time, project cost and project quality).

The study confirms the negative significant impact of the COVID-19 pandemic on the performance of construction projects. It also identifies the significant moderating effects of emerging technologies in mitigating the impact of COVID-19 on construction projects. Further, it shows a significant increase in the application of emerging technologies in construction projects during the COVID-19 pandemic. Based on the findings related to the moderating impact of the technology, this study provides a clear set of recommendations for construction firms, public sector and research community in combating the unavoidable situation similar to the COVID-19 pandemic in the future.

To the best of the authors’ knowledge, this is the first study to identify the moderating role of technology on the impact of COVID-19 on the performance of the construction sector in Pakistan. The findings can also be used for the construction sectors of other developing countries.

This study empirically demonstrates a contradiction between pillar 3 of Basel norms III and the designation of Systemically Important Banks (SIBs), also known as Too Big to Fail (TBTF). The objective of this study is threefold, which has been approached in a phased manner. The first is to determine the systemic importance of the banks under study; second, to examine if market discipline exists at different levels of systemic importance of banks and lastly, to examine if the strength of market discipline varies at different levels of systemic importance.

This study is based on all the public and private sector banks operating in the Indian banking sector. The Gaussian Mixture Model algorithm has been utilized to classify banks into distinct levels of systemic importance. Thereafter, market discipline has been observed by analyzing depositors' sentiments toward banks' risk (CAMEL indicators). The analysis has been performed by employing the system Generalized Method of Moments (GMM) to estimate models with different dependent variables.

The findings affirm the existence of market discipline across all levels of systemic importance. However, the strength of market discipline varies with the systemic importance of the banks, with weak market discipline being a negative externality of the SIBs designation.

By employing the Gaussian Mixture Model algorithm to develop a framework for categorizing banks on the basis of their systemic importance, this study is the first to go beyond the conventional method as outlined by the Reserve Bank of India (RBI).

This study aims to investigate whether gender diversity in audit committees affects the purchase of nonaudit services in China. Results from family and nonfamily firms are compared and the critical mass participation of females are further examined.

The sample comprises 1,834 Chinese listed companies from 2012 to 2021, among which 910 are family firms. The Heckman (1979) two-stage model is used to mitigate the potential endogeneity issue in the selection of gender diversity. Propensity score matching is also used to further alleviate the endogeneity problem in relation to family firms.

Results show a significant and negative correlation between the gender diversity in audit committees and nonaudit service fees. This association is more apparent in nonfamily than in family firms. Findings are consistent and robust to endogeneity tests and sensitivity analyses. The analysis of critical mass and symbolic participation shows that three female directors can more significantly restrain nonaudit fees than one to two females on the board.

This study contributes to literature on resource dependence theory, which posits that audit committees help enterprises establish contact with auditors, improve the company legitimacy, assist in communication and provide relevant expertise. This study also relates to agency theory, which holds that differences in the severity of types I and II agency problems between family and nonfamily firms lead to differences in auditor selection and related costs.

Extending from previous research on the relation between the gender diversity in audit committees and nonaudit fees, the present study delves into this connection within the context of China, an emerging economy. As a result, this investigation offers novel insights and expands upon current knowledge. In addition, the correlation between the gender diversity of audit committees and nonaudit fees is explored for family and nonfamily firms.

Motivation of the employees is extensively considered as an antidote for the overall success of the organizations. This study primarily aims to investigate the impact of motivation on the job performance of university librarians in Pakistan.

Quantitative research design followed by a survey method under an extended theory of motivation was applied. Data were collected from 123 professional librarians of 79 university libraries in Punjab province, Pakistan. The study tested hypotheses having used regression statistical test through Statistical Package for Social Sciences Software (Version 26).

Results of the study revealed that motivation (intrinsic and extrinsic), the expectation of benefits, satisfaction of meta needs and challenging situations have a strong positive impact on the optimum job performance of university librarians.

This research has theoretical implications for the researchers and practical insights for human resource managers to get maximum outcomes for organizational development. The results of the study may be generalized to the university libraries of other countries having similar socio-economic and cultural situations.

This study developed a framework based upon empirically tested hypotheses that might be used as drivers for different motivation practices to augment employees’ commitment to the organizations.