Search results

The study aims to apply catastrophe theory to the analysis of accidental dwelling fire injuries in terms of age band, gender and contributory factors in order to inform fire prevention activities.

The study employed a case study in a UK Fire and Rescue service concerning analysis of the circumstances of accidental dwelling fire injuries, and the characteristics and behaviours associated with utilising frequency analysis, percentages, ratios and catastrophe theory modelling.

Overall, males were more likely to be injured in an accidental dwelling fire compared to females by a ratio of 1.68 to 1, and those in the age band 50–64 appeared to be at maximum risk. A total of 15.4% of the accidental dwelling fire injuries involved consumption of alcohol or drugs, and 5.9% involved falling asleep.

The circumstances of accidental dwelling fire injury can be analysed to identify patterns concerning when a catastrophic change relating to ordinary use of domestic objects results in an accidental dwelling fire injury.

A catastrophe theory view can aid the understanding of how ordinary use of domestic objects results in an accidental dwelling fire injury.

Since fire injuries have both a social and economic cost, understanding how such fire injuries occur can aid fire prevention through appropriately targeted fire prevention activities.

The study made use of a catastrophe theory view to analyse the circumstances under which accidental dwelling fire injuries occurred using fire injury data from a UK fire and rescue service.

Nowadays, there is a strong public interest in promoting transparency to be informed about the actions of the public sector. At the same time, there has been a significant change in society’s perceptions and concerns about sustainable development, with a marked increase in attention to this area. In this context, our main objective is to investigate the impact of transparency practices in local government on the implementation of the Sustainable Development Goals (SDGs) in Spanish municipalities.

We will analyse a sample of 84 municipalities, using the Dynamic Transparency Index published by Dyntra to measure transparency. For the level of implementation of the SDGs, we will use an index specifically created using data from the report “The SDGs in 100 Spanish Cities”, published by the Spanish Network for Sustainable Development in 2020.

Municipalities with a larger dependent population tend to achieve higher SDG levels. Municipalities with lower financial surpluses and more self-generated resources show better SDG implementation. Progressive political parties lean more towards sustainability, and coalition governments show higher SDG implementation than majority governments. Gender appears to play a minor role in SDG implementation, but male leadership is associated with higher levels. Factors such as population density and government transfers do not have a significant impact on SDG implementation levels.

This study seeks to address the lack of empirical research on the potential impact of transparency on the achievement of the SDGs, while also taking into account other socio-economic, financial and political aspects of the municipality. In doing so, it also contributes to the limited empirical literature on the determinants of the level of SDG implementation in local governments.

The construction industry is frequently scrutinised by the public for a variety of issues, including waste, inefficiency, narrow profit margins, scheduling setbacks, budget overruns, quality concerns, trust deficits, transparency issues, coordination challenges, communication issues and fraud. The purpose of this paper is to assess the effect of blockchain technology adoption on the construction supply chain.

This study used a quantitative research approach through a questionnaire survey that was conducted among professionals in the Nigerian construction industry using the snowball sampling method, which resulted in a selection of 155 respondents. The collected data were analysed using partial least squares structural equation modelling, enabling a thorough assessment of the proposed relationships and offering valuable insights specific to the construction industry.

The study’s findings validated the conceptual framework established. The results indicated that implementing blockchain across all stages of the construction supply chain has the potential to improve the construction process. The study also revealed that blockchain technology will significantly affect the construction supply chain in a positive manner.

This research was carried out in the South-western region which is one of the six geo-political zones in Nigeria using a cross-sectional survey method. The study holds implications not only for local construction practices but will also contribute to the broader discourse on national construction sector challenges and possible solutions.

The findings of this study will be immensely beneficial to both professionals, practitioners and stakeholders in the Nigerian construction industry in learning about the potential of blockchain technology application in improving the construction supply chain.

The study in this paper constructed and evaluated a conceptual framework by exploring the connections between the variables. The results have significant implications for the construction sector, as they provide avenues for enhancing the construction process and the overall supply chain. These findings are valuable for researchers examining the potential effects of blockchain technology on the construction supply chain.

An effective business model (BM) is essential for the success of any company, with sustainable innovation being a critical component of this model. This entails finding creative ways to meet present needs without compromising future generations. In this regard, cooperation can be crucial in developing sustainable innovation. This paper investigates how different types of cooperation impact the development of small and medium-sized enterprises (SMEs) innovation for environmental sustainability. In this sense, it intends to compare the effects of cooperation acquired nationally or at a European level.

The methods used are logistic regression for the sample of 87,374 observations from 14 countries of the Eurostat Community Innovation Survey (CIS) database.

The results confirm that cooperation with national or European agents significantly impacts the innovation for environmental sustainability of SMEs; however, not all cooperations have the same significance level. At a national level, cooperation with the suppliers of equipment, materials, components or software, clients or customers and universities or other higher education institutes impacts the innovations for environmental sustainability developed by SMEs. At a European level, cooperation established with other enterprises within your enterprise group, equipment, materials, components or software suppliers, clients or customers and government, public or private research institutes significantly impacts innovations for environmental sustainability.

This study also provides substantial theoretical contributions on the subject and more information about the importance of cooperation by SMEs in developing innovation for environmental sustainability.

The purpose of this paper is to examine the effect of unemployment during the COVID-19 pandemic on mental health, quality of life and the labour market outcome across North and Southern Nigeria.

Data was obtained from staff laid off in selected tertiary institutions in North East and South West Nigeria using a self-administered questionnaire with a total sample size of 185. Findings are shown using the heteroscedastic linear regression and descriptive statistics.

The results showed a significant negative effect of unemployment during the pandemic on mental health and quality of life. Less than half of those laid off are reabsorbed into the labour market with the majority in the South than the Northern region and most are in self-employment.

The coronavirus pandemic negatively affected the human race, with a huge socio-economic impact linked to health and well-being. This reality calls for attention to the role it played on mental health and the quality of life as well as how it has influenced the labour market. Labour empowerment during a pandemic is key to cushion the effect of pandemics on health and the labour market. This can be in the form of skill empowerment and increased access to funds for business start-ups to enable self-employment that typifies the labour market after a pandemic. This in turn will reduce mental health challenges and low quality of life associated with pandemics.

To the best of the authors’ knowledge, this research is the first in the literature that provides empirical evidence of the effect of unemployment during the pandemic on well-being captured using mental health and the quality of life in Nigeria. Findings on labour market outcomes due to the pandemic and across regions in Nigeria are also scarce in the literature.

Although technologies such as blockchain (BCT) hold great potential to improve global food supply chains (GFSCs), our understanding of BCT use in GFSCs remains limited. The purpose of this study is to broaden BCT discussions by exploring its benefits and challenges across the entire GFSC.

Qualitative interviews with 23 industry experts were used to identify and comprehend the nuanced issues with BCT application in GFSCs.

The study identifies 21 perceived benefits and challenges with BCT use in GFSCs, including the benefit of broader data incentives beyond BCT use and the challenge of reluctance to assume dominant roles among the GFSC actors.

While prior studies mostly focused on BCT use for traceability and food safety in the GFSC midstream, this study extends the scope to include upstream and midstream actors. It highlights socio-economic benefits for traditionally disadvantaged farmers in the upstream and normative challenges to its adoption in the GFSC midstream and downstream. It also identifies three paradoxes emerging with BCT use in the GFSCs including the paradoxes of food technology, transparency and de-centralization.

Supply chains need to be made viable in this volatile and competitive market, which could be possible through digitalization. This study is an attempt to explore the role of Industry 4.0, smart supply chain, supply chain agility and supply chain resilience on sustainable business performance from the lens of natural resource-based view.

The study tests the proposed model using a covariance-based structural equation modelling and further investigates the ranking of each construct using the artificial neural networks approach in AMOS and SPSS respectively. A total of 234 respondents selected using purposive sampling aided in capturing the industry practices across supply chains in the UK. The full collinearity test was carried out to study the common method bias and the content validity was carried out using the item content validity index and scale content validity index. The convergent and discriminant validity of the constructs and mediation study was carried out in SPSS and AMOS V.23.

The results are overtly inferring the significant impact of Industry 4.0 practices on creating smart and ultimately sustainable supply chains. A partial relationship is established between Industry 4.0 and supply chain agility through a smart supply chain. This work empirically reinstates the combined significance of green practices, Industry 4.0, smart supply chain, supply chain agility and supply chain resilience on sustainable business value. The study also uses the ANN approach to determine the relative importance of each significant variable found in SEM analysis. ANN determines the ranking among the significant variables, i.e. supply chain resilience > green practices > Industry 4.0> smart supply chain > supply chain agility presented in descending order.

This study is a novel attempt to establish the role of digitalization in SCs for attaining sustainable business value, providing empirical support to the mediating role of supply chain agility, supply chain resilience and smart supply chain and manifests a significant integrated framework. This work reinforces the integrated model that combines all the constructs dealt with in silos so far in prior literature.

The global population has been experiencing an unprecedentedly rapid demographic transition as the populations have been growing older in many countries during the current decades. The purpose of this study is to introduce a Grey Exponential Smoothing model (GESM)-based mechanism for analyzing population aging.

To analyze the aging population of Sri Lanka, initially, three major indicators were considered, i.e. total population, aged population and proportion of the aged population to reflect the aging status of a country. Based on the latest development of computational intelligence with Grey techniques, this study aims to develop a new analytical model for the analysis of the challenge of disabled and frail older people in an aging society.

The results suggested that a well-defined exponential trend has been seen for the population ages 65 and above, a total of a million) during 1960–2022; especially, the aging population ages 65 and above has been rising rapidly since 2008. This will increase to 24.8% in 2040 and represents the third highest percentage of elderly citizens living in an Asian country. By 2041, one in every four Sri Lankans is expected to be elderly.

The study proposed a GESM-based mechanism for analyzing the population aging in Sri Lanka based on the data from 1960 to 2022 and forecast the aging demands in the next five years from 2024 to 2028.

A major obstacle regarding the measurement of an organization's sustainability and accountability in the space economy is defining the context and boundaries of commercial activity in outer space. Here, we introduce an ecosystem framework to address this obstacle. We utilize this framework to analyze the space mining sector. Our ecosystem framework sets the space mining sector's boundaries and helps a firm identify key stakeholders, activities, policies, norms and common pool resources in that sector and the interactions between them; a significant step in structuring how to measure space sustainability and accountability.

Borrowing theories and perspectives from a wide range of academic fields, this paper conducts a comprehensive context analysis of the space mining ecosystem.

Using our ecosystem framework to define the context and set boundaries for the space mining sector allowed us to identify sustainability-related issues in the sector and offer roadmaps to develop sustainability measures and standards.

To the best of the authors’ knowledge, this is one of the first papers to introduce a framework to define boundaries in the global space economy and provides a tool to understand, measure and evaluate the space mining sector's environmental, social and economic issues.

By studying the green development efficiency (GDE) of 33 cities in the provinces of Jiangsu, Zhejiang, and Fujian in China, this study strives to conduct an analysis of the sustainable practices implemented in these developed regions, and derive valuable insights that can foster the promotion of green transformation.

First, the urban green development system (GDS) was decomposed into the economic benefit subsystem (EBS), social benefit subsystem (SBS), and pollution control subsystem (PCS). Then, a mixed network SBM model was proposed to evaluate the GDE during 20152020, with Moran’s I and Bootstrap truncated regression model subsequently applied to measure the spatial characteristics and driving factors of efficiency.

Subsystem efficiency presents a distribution trend of PCS > EBS > SBS. There is a particular spatial aggregation effect in EBS efficiency, whereas SBS and PCS efficiencies have no significant spatial autocorrelation. Furthermore, urbanization level contributes significantly to the efficiency of all subsystems; industrial structure, energy consumption, and technological innovation play a crucial role in EBS and SBS; external openness is a pivotal factor in SBS; and environmental regulation has a significant effect on PCS.

This study further decomposes the black box of GDS into subsystems including the economy, society, and environment. Additionally, by employing a mixed network SBM model and Bootstrap truncated regression model to investigate efficiency and its driving factors from the subsystem perspective, it endeavors to derive more detailed research conclusions and policy implications.