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Wool fiber is accepted as one of the natural and renewable sources and has been used in the apparel and textile industry since ancient times. However, wool fiber has the highest global warming potential value among conventional fibres due to its high land use and high methane gas generation. This study aimed to recycle the wool fabric wastes and also to create a mini eco-collection by using the produced yarns.

This manuscript aimed to evaluate the fabric wastes of a woolen fabric producer company. Fabric wastes were opened with two different opening systems and fiber properties were determined. First, conventional ring yarns were produced in the company’s own spinning mill by mixing the opened fibres with the long fiber wastes of the company. In addition, opening wastes were mixed with different fibres (polyester, long wool waste, and Tencel fibres) between 25% and 70% in the short-staple yarn spinning mill and used in the production of conventional ring and OE-rotor yarns. Most of the yarns contained waste fibres at 50%. Recycled and virgin yarns were used as a weft and warp yarn and a total of 270 woven fabric samples were obtained and fabric properties were examined. Also, a fabric collection was created. A life cycle assessment (LCA) was made for one of the selected yarns.

At the end of the study, it was determined that it was possible to produce yarn and fabric samples from fiber blends containing high waste fiber ratios beyond 50%. All the woven fabric samples produced from conventional ring and OE-rotor yarns gave higher breaking, tearing and stitch slip strength values in the weft and warp direction than limit quality values of the company. In addition, abrasion resistance and WIRA steam stability properties of the fabric samples were also sufficient. Environmental analysis of the recycling of the wastes showed a possible decrease of about 9940034.3 kg CO2e per year in the global warming potential. In addition, fiber raw material expenses reduced yarn production cost about 50% in case of opened fabric waste usage. However, due to insufficient pilling resistance results, it was decided to evaluate the woven fabrics for the product groups such as shawls and blankets, where pilling resistance is less sought.

The original aspects of the article can be summarized under two headings. First, there are limited studies on the evaluation of wool wastes compared to cotton and polyester fibres and the number of samples examined was limited. However, this study was quite comprehensive in terms of opening type (rag and tearing), spinning systems (long and short spinning processes), fiber blends (waste 100% and blends with polyester, long wool waste and Tencel fibres) and yarn counts (coarser and finer). Recycled and virgin yarns were used as a weft and warp yarn and a total of 270 woven fabric samples were obtained using different colour combinations and weave types. All processes from fabric waste to product production were followed and evaluated. Life cycle assessment (LCA) and cost analysis was also done. The second unique aspect is that the problem of a real wool company was handled by taking the waste of the woolen company and a collection was created for the customer group of the company. Production was made under real production conditions. Therefore, this study will provide important findings to the research field about recycling, sustainability etc.

The purpose of this study is to provide an overview of the research conducted on hospitality and tourism articles published in Q1 category journals from 1990 to 2023. This study also aims to measure the topic prevalence in selected journals throughout the years, their change over time and similarities of journals.

Latent dirichlet allocation algorithm is used as a topic modeling method to identify and analyze topics in hospitality and tourism research over the past 30 years.

The results of the study indicate that hospitality and tourism research has recently focused on topics such as employee behavior, customer satisfaction, online reviews, medical tourism and tourist experience. However, the results also indicate a negative trend in topics such as hotel management, sustainability, profession, economic growth and tourist destination.

This study can be used to examine the evolution of research patterns over time, find hot and cold themes and uncover untapped or understudied areas. This can aid academics in their investigations and practitioners in making sound strategic decisions.

This study contributes to the existing literature by providing a new approach and comprehensive analysis of hospitality and tourism research topics. It delineates an overview of the progression of hospitality and tourism research over the past 30 years, identifies the trending topics and explores the potential impacts that these identified topics may have on future studies.

Entrepreneurship, sustainability, and the creation of a resilient, green economy are intricately linked, particularly as conventional economic models grapple with existential challenges. However, empirical research addressing the connection between entrepreneurship and sustainability for a more balanced and resilient future is notably scarce. This chapter aims to bridge this gap by investigating the role of entrepreneurship in advancing sustainability and establishing a resilient, green economy. Through comprehensive research utilizing critical discourse analysis (CDA), three research questions were explored to draw insightful managerial and practical implications. In the intersection of entrepreneurship, sustainability, and a green, resilient economy, opportunities are seized by entrepreneurship amid limitations, while sustainability presupposes responsible management of resources for current needs without compromising the future. A green economy ensures adaptability, growth, and ecological stability even in resource-scarce conditions. The CDA affirms the influential role of entrepreneurship in pursuing sustainability and a green, resilient economy, drawing from 18 cases across public, private, and social sectors to highlight environmental, social, and economic impacts. Furthermore, the CDA uncovers power dynamics, ideologies, and social structures affecting entrepreneurship’s role in fostering sustainable and resilient, green economies. Collaborations between governments, corporations, and social ventures in diverse countries promote sustainability within existing social structures, fostering comprehensive development. However, imbalanced power dynamics pose challenges, risking potential social exclusion. This chapter concludes by addressing practical implications and limitations, aiming to contribute to an ecologically balanced and socially equitable future by understanding entrepreneurship’s role in promoting sustainability and green resilience within the context of power dynamics, ideologies, and social structures.

This study aims to assess the effects of natural disasters on food security in a sample of 40 sub-Saharan African countries. First, the authors assess the effects of natural disasters on the four dimensions of food security and second, the authors disaggregate natural disaster using the two dimensions that are most representative, namely, hydrological and biological disasters.

The regressions are based on the generalised method of moments on a data set covering the period 2005–2020. Natural disasters are measured by the total number of people affected and food security by its characteristics: access, availability, use and sustainability.

The results show that natural disasters increase the prevalence of undernourishment but reduce dependence on cereal imports. An increase in natural disasters by 1% increases the prevalence of undernourishment by the same proportion. As for import dependency, a 1% increase in natural disasters reduces dependency by 2.2%. The disaggregated effects show that hydrological disasters are more significant than biological disasters in impacting food security. Floods reduce the average energy supply adequacy but also dependence on cereal imports. Policy implications are discussed.

The study complements the extant literature by assessing the effects of natural disasters on food security in a region where food insecurity is one of the worst in the world.

Disaster management and humanitarian logistics (HT) play crucial roles in large-scale events such as earthquakes, floods, hurricanes and tsunamis. Well-organized disaster response is crucial for effectively managing medical centres, staff allocation and casualty distribution during emergencies. To address this issue, this study aims to introduce a multi-objective stochastic programming model to enhance disaster preparedness and response, focusing on the critical first 72 h after earthquakes. The purpose is to optimize the allocation of resources, temporary medical centres and medical staff to save lives effectively.

This study uses stochastic programming-based dynamic modelling and a discrete-time Markov Chain to address uncertainty. The model considers potential road and hospital damage and distance limits and introduces an a-reliability level for untreated casualties. It divides the initial 72 h into four periods to capture earthquake dynamics.

Using a real case study in Istanbul’s Kartal district, the model’s effectiveness is demonstrated for earthquake scenarios. Key insights include optimal medical centre locations, required capacities, necessary medical staff and casualty allocation strategies, all vital for efficient disaster response within the critical first 72 h.

This study innovates by integrating stochastic programming and dynamic modelling to tackle post-disaster medical response. The use of a Markov Chain for uncertain health conditions and focus on the immediate aftermath of earthquakes offer practical value. By optimizing resource allocation amid uncertainties, the study contributes significantly to disaster management and HT research.

The purpose of this study is to present a bibliometric and network analysis that uses the Scopus and Dimension databases to provide new insights into the progression toward the study of sustainable economic development.

This analysis has been drawn on 665 papers published between 2015 and 2023. Bibliometric analysis characterizes a research topic by identifying leading nations, the most significant authors and expressive publications. Network analysis revealed keyword evolution over time, co-citation patterns and study grouping. Content analysis was used to identify major topic in the discipline, with a focus on their interrelationships. Each publication in the data set is briefly described, along with its methodological approach.

The results of this study show that green finance plays a major role in long-term economic growth, having a significant influence on the preservation of environmental quality, economic efficacy and a more comprehensive economic system. Financial technology also accelerates the transition to a carbon-neutral economy by enhancing the beneficial effects of green finance on aspects of the economic system and environmental conservation.

The investigation is based only on Scopus and Dimensions-indexed journal articles. However, additional studies should incorporate publications from other reputable databases, such as Web of Science, PubMed and Science Direct, for the bibliometric analysis, so that the findings of the model analysis become more reliable and valid with examination of more documents. The visualization of similarity viewer was used for data analysis in the study, there is a scope for using other tools such as Biblioshiney and CitNet Explorer.

To support long-term economic growth, authorities should encourage Fintech companies to actively participate in various green finance initiatives and environmental conservation businesses. Financial managers should facilitate the integration of technology and green finance for financial services. It is important to encourage institutional and individual investors alike to look into more environmentally friendly ways to invest and save money. Policymakers should provide a platform for global awareness and government agencies should enhance their recommendations to state governments to increase the efficacy of green finance.

This study contributes to the literature by investigating the relationship between Fintech and green financing. This study holds significance for financial intermediaries, industrialists, investors and policymakers by providing insights into the integration of Fintech with green finance for sustainable development. These findings affirm the pivotal role of Fintech and green finance in fostering sustainable economic development. The novelty of the topic and the variety of publications in which it has been published demonstrate that sustainable economic development has piqued the interest of a wide range of areas.

During the COVID-19 pandemic, the public relied heavily on digital media to stay tuned for the latest update. Media preference could increase risk perceptions, although the influence of diverse media exposure remains unknown. Based on protection motivation theory, this study aims to investigate how digital media exposure diversity and information verification influence vaccination intention.

Analyzing survey data from 837 respondents in China, this study examined the effects of digital media exposure on information verification, including their influences on the threat appraisal, coping appraisal, vaccine misinformation beliefs, subjective norms and trust in vaccines.

Results indicate that diversity of digital media exposure increased threat appraisal (perceived severity) and coping appraisal (response efficacy and self-efficacy), while information verification increased only coping appraisal (response efficacy and self-efficacy). In addition, diversity of digital media exposure decreased vaccine misinformation beliefs. Furthermore, digital media exposure and information verification were linked to vaccination intention via the mediations of response efficacy, subjective norms and trust in vaccines.

This study is the first of its kind to investigate media exposure diversity in the context of vaccination and health crises. Our findings extended the PMT framework by exploring proactive information-related behaviors as antecedents of mediation processes. In addition, we examined misinformation beliefs, social norms and trust as societal influences. Theoretical and practical implications are also discussed.

The exchange rate is an important driver of a country’s economic growth, influencing trade, investment, inflation, and employment. This study’s main objective was to investigate the threshold effects of exchange rates on economic growth.

In this research, innovative endogenous threshold autoregressive (TAR) models introduced by Hansen (2000) are employed for estimation and inference. The dataset comprises secondary annual time series data from Ghana, covering thirty-one years from 1990 to 2021. Economic growth is represented by GDPPC, with the growth exchange rate serving as the crucial threshold variable.

The finding suggests a single exchange rate threshold for Ghana, indicating a nonlinear relationship with economic growth. However, above 8.97%, the exchange rate considerably slows growth, harming the economy. The exchange rate negatively influences growth in both low and high-exchange-rate regimes, but it is insignificant in the high regime. In addition, inflation has a significant negative influence on growth in the low regime but a positive impact on the high regime. In contrast, interest rates positively impact growth in both regimes, though not as significantly in the high regime.

The findings from this study offer valuable insights to the Ghanaian government and policymakers as they consider choosing an exchange rate target that helps minimise the negative impact of a high exchange rate to promote economic growth.

This paper is remarkable for being one of the few studies that have explored the relationship between exchange rates and economic growth, exploring the threshold effect.

The goal of this paper is to investigate the antecedent of employee performance (EP) through perceived organizational support (POS), as well as the moderating role of job satisfaction (JS) on the connection between POS and EP among employees of small and medium enterprises (SMEs) in Northwest Nigeria, using social exchange theory (SET) and organizational support theory (OST).

This research employed a survey design, using SMEs employees in Northwest Nigeria as the research unit of analysis. Purposive sampling was used in this research, with standardized questionnaires used to obtain data from 1750 employees of the targeted SMEs within the region. This study’s hypotheses were tested using partial least square–structural equation modeling (PLS-SEM).

The findings of this research stated that POS has a substantial effect on EP, while JS moderates the association between POS and EP.

The study offers practical insights for SMEs in Northwest Nigeria, aiding in resolving employee issues and providing actionable strategies for management. Understanding the dynamics of perceived organizational support, job satisfaction and employee performance enables proactive measures to improve organizational effectiveness, fostering a positive work environment and enhancing competitive edge.

This study innovates existing literature by exploring how perceived organizational support affects employee performance in small and medium-sized enterprises in an emerging economy. It introduces PLS-SEM, emphasizing job satisfaction’s pivotal role as a moderator. This provides valuable guidance for SMEs to boost employee performance and formulate effective HR strategies, advancing organizational behavior and management research.

This study aims to examine whether energy poverty impacts gender inequality and CO₂ emissions in African countries with the biggest economies by gross domestic product (GDP) per capita from 1996 to 2020. Additionally, this study examines the existence of the gender Kuznets curve (GKC) and the environmental Kuznets curve (EKC) theories. Furthermore, it evaluates the connection between economic development and carbon emissions, on the one hand, and economic development and gender inequality on the other.

This study uses the augmented Dickey–Fuller and Phillip–Perron unit root tests to determine the degree of integration between the variables. It also uses the Pedroni and Fisher–Combine Johansen cointegration tests to assess a long-run relationship between the variables. The authors adopted the pooled mean group (PMG)-autoregressive distributed lag model and used the E-Views 12 software to run the analysis.

The empirical analysis approves the long-run correlation among the variables used in this study. Increased energy poverty and GDP increase CO₂ emissions, whereas income square hurts CO₂ emissions. These results are consistent with the EKC hypothesis, which proposes a non-linear relationship between CO₂ emissions and economic growth in the studied areas (similar to an inverted U shape). Long-term foreign direct investment (FDI) has a negative correlation with CO₂ emissions. On the contrary, energy poverty, GDPsq and FDI find a positive relationship with gender inequality, whereas GDP finds a negative association with gender inequality. The negative relationship between GDPsq and gender inequality establishes a “U”-shaped connection between income and gender inequality. Thus, it supports the hypothesis of the GKC. Therefore, this study proposes that decreasing energy poverty is vital for promoting a clean environment and mitigating gender inequality.

This study supports the hypothesis of the GKC. Therefore, this study proposes that decreasing energy poverty is vital for promoting a clean environment and mitigating gender inequality.