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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 study aims to investigate the direct effect of intellectual capital on the organizational performance of Indonesian state-owned enterprises (SOEs) and their subsidiaries. Furthermore, it also examines whether the relationship is mediated by open innovation and moderated by organizational inertia.

This study is designed as quantitative research. A survey method is employed to collect data by distributing questionnaires to the upper-level managers of the SOEs and their subsidiaries. A total of 293 questionnaires were distributed to the respondents, and 97 responses were obtained for further analysis. The partial least square structural equation modeling (PLS-SEM) is used to test the hypotheses. A mediation-moderation research framework is employed.

The results show that intellectual capital has a positive effect on organizational performance. Further results also demonstrate that open innovation mediates the intellectual capital–organizational performance relationship and organizational inertia moderates the intellectual capital–organizational performance relationship. Theoretically, the findings contribute to the resource-based view (RBV) and knowledge-based view (KBV) by providing empirical evidence of the importance of distinctive internal resources in achieving superior organizational performance. Practically, the findings provide strategic information for managers that they should properly manage intellectual capital, open innovation and organizational inertia because of their effects on organizational performance.

First, this study addresses the previous research gaps by confirming that intellectual capital has a positive effect on organizational performance in the research setting of an emerging market. Second, by using a mediation research framework, this study shows that open innovation mediates the relationship between intellectual capital and organizational performance. Third, by using a moderating research framework, this study also reveals that organizational inertia weakens the relationship between intellectual capital and organizational performance. Those associations are rarely researched.

This paper aims to examine the impact of announcements related to 77 interventions by 46 listed Indian pharmaceutical firms during COVID-19 on the abnormal returns of the firms. The study also finds the variables which explain cumulative abnormal returns (CARs).

This study uses standard event methodology to compute the abnormal returns of firms announcing pharmaceutical interventions in 2020 and 2021. Besides this, the multilayer perceptron technique is applied to identify the variables that influence the CARs of the sample firms.

The results show the presence of abnormal returns of 0.64% one day before the announcement, indicating information leakage. The multilayer perceptron approach identifies five variables that explain the CARs of the sample companies, which are licensing_age, licensing_size, size, commercialization_age and approval_age.

The study contributes to the efficient market literature by revealing how firm-specific nonfinancial disclosures affect stock prices, especially in times of crisis like pandemics. Prior research focused on determining the effect of COVID-19 variables on abnormal returns. This is the first research to use artificial neural networks to determine which firm-specific variables and pharmaceutical interventions can influence CARs.

The study’s objective was to ascertain the connection between secondary school students' test anxiety, academic self-concept, motivation and academic performance in mathematics. The difference between the academic performances of male and female secondary school students who exhibit high and low test anxiety, academic self-concept and motivation levels in mathematics.

Four hypotheses and four research questions were adopted. The design is a correlation. 42,299 mathematics students in senior school year two (SS2) made up the research population. A sample of 1,650 students was selected through a multi-stage sampling procedure. The main instruments used were the Mathematics Test Anxiety Questionnaire (MTAQ), Academic Self-Concept Questionnaire (ASQ) and Academic Motivation Questionnaire (AMQ) and students’ math scores. These instruments were validated by three experts and the reliability coefficients of 0.69, 0.68 and 0.68 were obtained for MTAQ, ASQ and AMQ, respectively, using Cronbach alpha. Pearson product moment correlation was used to analyze the data.

The study’s results showed a correlation between secondary school students' academic performance in mathematics and test anxiety, academic self-concept and motivation. There was a significant difference between secondary school male and female students' test anxiety; there was a significant difference between secondary school male and female students' self-concept and academic performance in mathematics, and there was a significant difference between secondary school male and female students' motivation and academic performance in mathematics.

The major contribution of this study is to investigate the connection between test anxiety, academic self-concept motivation and students’ mathematics performance. There is a difference between psychological variables, gender and mathematics performance.

Food literacy is a multidimensional concept that prioritises the aspects individuals require to navigate the contemporary foodscape successfully. The study aims to map the knowledge base and intellectual structure of the concept of food literacy to assess if the most cited definitions reflect these constructs.

The inclusion criteria of full-text, peer-reviewed articles or conference papers, in English, using “food literacy” within the title, abstract, keywords or linked to the research focus produced 538 articles from the Scopus database from its inception until January 31, 2023. Articles were analysed according to exponential growth, geolocations, authors, articles, research areas and keywords using VOSviewer, CiteSpace and Excel.

Food literacy research grew exponentially between 2012 and 2022 at a rate of 50% and spanned 62 research areas, with nutrition and dietetics being the most common. Vidgen and Gallegos were the most cited authors of the most cited article, and Australia was the most influential food literacy research geolocation. Research originating from developing countries within Asia, the Middle East, Africa and South America was underrepresented, and COVID-19 impacted research trends between 2020 and 2023.

It is recommended to link “food literacy” to appropriate publications to increase its visibility and that food literacy be redefined and conceptualised to better reflect its intellectual structure. To complete this task, further research guided by keyword clustering can enhance conceptual understanding.

This study provides new insight into the knowledge base and intellectual structure of food literacy and provides scope for future research to develop the concept further.

The coronavirus disease (COVID-19) pandemic continues to impact economic systems, with devastating consequences on livelihoods. Anecdotal evidence has predicted the adverse effects of COVID-19 on the livelihood of food system actors. Uganda experienced two lockdowns in March 2020 and June 2021 with varying government containment measures. During the first lockdown, fresh food market vending was deemed essential to meet urban food demand, and was consequently exempted from a total shutdown despite the ban on public and private transport. Thus, this study sought to examine the effect of COVID-19 containment measures on fresh food market vending businesses in Uganda.

Using primary data collected from fresh food market vendors, this study applied a pooled time-series estimation to examine the effect of the first lockdown COVID-19 containment measures on fresh food vendors' welfare.

The study revealed that COVID-19 had a significant negative impact on the income of fresh food vendors, with female vendors being the most affected. COVID-19 containment measures reduced the diversity of buyers, individual customers and the number of commodities traded in causing a greater impact on vendors' income.

The unavailability of data for vendors who did not return to the market at the time of data collection limits the scope of the study. Additionally, the absence of data for the second lockdown limited the analysis to only March 2020 lockdown period.

The empirical analysis highlights how vulnerabilities of different gender categories could be exacerbated by crises. The study provides empirical evidence of various market distortions caused by the COVID-19 pandemic and the disproportionate impact on women and men market vendors which calls for the need to integrate women's perspectives in future planning for market systems as well as advocating for gender-sensitive recovery responses.

This study introduces an ecological framework for disabilities meant to provide a new model of viewing and learning about disabilities and special education. This model projects a multi-systemic view of factors that influence a person's life, where people with disabilities are active actors in the development of the world. The increased awareness about interconnectedness, globalization, inter- and trans-disciplinarity, influences on human experience, greening, sustainability, inequality, inequity and lack of opportunities is shifting how people think about potential and growth.

The methodological approach is qualitative, interpretive research.

In disability studies, the Ecological Model of Disabilities helps reframe this uniqueness as part of the spectrum of human experiences. In special education, the Ecoducation Model helps reframe the learning experience.

This research is conceptual, but it is also all-inclusive, rendering itself to a wide application in educational settings.

The Ecoducation Model for Special Education is specific to the education of children and adults with disabilities, and it is directly compatible with the broader Ecological Model of Disabilities. These ecological models can be applied to all levels of the ecological system, and to different ecodemes of population. Nevertheless, the ecological models need to be locally implemented, with general principles tailored to national traditions, laws and resources.

Advocating for the pursuit of individual well-being within the larger society, both models call for practical changes in a multitude of areas, including legislation and policy, training of professional personnel, sufficient financial input in programs designed for the care of children and adults with disabilities, change in societal mentalities to fight discrimination, disempowerment and isolation. Because the scope of ecological frameworks is incommensurate, being both interdisciplinary and transdisciplinary, further research possibilities are countless. The ecological perspective opens the fields of disability studies and special education to new theoretical and empirical possibilities.

Two epistemological models are described as new frameworks in disability studies: the Ecological Model of Disabilities and the Ecoducation Model for Special Education. Both are original models that look into the education and inclusion of the person with disabilities.

This paper explores how adaptive organizations, companies capable of continuously adapting their organizational model, dynamically solve the universal problems of organizing.

The authors applied grounded theory to data acquired from six interpretative case studies, collected in two rounds of interviews (15 in total), then completing and validating the study’s evidence through triangulation with several secondary data sources.

In adaptive organizations, polyarchies and intrapreneurial employees are essential to shape the division of labour, leading to high levels of autonomy and empowering individuals and teams, while reducing bureaucracy and hierarchy. In terms of the integration of effort, digital solutions are preferred to social proof in the provision of information, while the authors note that incentives are always geared towards developing strong higher-order dynamic capabilities.

This paper has some limitations that could be addressed in future research, including longitudinal studies to analyse the link between the universal problems of organizing and a company's dynamic capabilities.

Adaptive organizations go beyond tech firms in responding to the universal problems of organizing work by making specific use of digital technologies.

The paper studies how companies should organize themselves so that they continuously adapt to an ever-changing competitive environment.

Social media is widely used to capture citizens' opinions and topics deemed important. The importance or interest social media users attribute to a topic is traditionally measured by tweet frequency. This approach is practical but overlooks other user engagement tools such as retweets, likes, quotes, and replies. As a result, it may lead to a misinterpretation of social media signals. This paper aims to propose a method that considers all user engagement indicators and ranks the topics based on the interest attributed by social media users.

A multi-criteria decision-making framework was proposed, which calculates the relative importance of user engagement tools using objective (information entropy) and subjective (Bayesian Best-Worst Method) methods. The results of the two methods are aggregated with a combinative method. Then, topics are ranked based on their user engagement levels using Multi-Objective Optimization by Ratio Analysis.

The proposed approach was used to determine citizens' priorities in transport policy, and the findings are compared with those obtained solely based on tweet frequency. The results revealed that the proposed multi-criteria decision-making framework generated more comprehensive and robust results.

The proposed method provides a systematic way to interpret social media signals and guide institutions in making better policies, hence ensuring that the demands of users/society are properly addressed.

This study presents a systematic method to prioritize user preferences in social media. It is the first in the literature to discuss the necessity of considering all user engagement indicators and proposes a reliable method that calculates their relative importance.

The study aims to investigate the effect of corruption and crime on the investments by firms in emerging economies (EEs).

The study adopts the generalised methods of moments (GMM) estimator and data across 57 EEs.

The study shows that crime management, corruption and external quality assurance drive-up investments. Additionally, investments decline with firm age and crime incidence. Corruption and crime managements increase investments by exporting firms more than non-exporting firms investments. Also, external auditor services benefit investments by large firms more than small-medium firms.

There is a need for EEs to implement policies that will curtail corruption and create a level playing field and sustainable firm growth. EEs firms must be innovative to expand their productive investments and grow over time. Also, EEs firms should seek external quality certification, invest in internal security and monitor goods in transit.