Green manufacturing is increasingly becoming popular, especially in lubricant manufacturing, as more environmentally friendly substitutes for mineral base oil and synthetic additives are being found among plant extracts and progress in methodologies for extraction and synthesis is being made. It has been observed that some of the important performance characteristics need enhancement, of which nanoparticle addition has been noted as one of the effective solutions. However, the concentration of the addictive that would optimised the performance characteristics of interest remains a contending area of research. The research was out to find how the concentration of green synthesized aluminum oxide nanoparticles in nano lubricants formed from selected vegetable oils influences friction and wear. A bottom-up green synthesis approach was adopted to synthesize aluminum oxide (Al2O3) from aluminum nitrate (Al(NO3)3) precursor in the presence of a plant-based reducing agent—Ipomoea pes-caprae. The synthesized Al2O3 nanoparticles were characterized using TEM and XRD and found to be mostly of spherical shape of sizes 44.73 nm. Al2O3 nanoparticles at different concentrations—0.1 wt%, 0.3 wt%, 0.5 wt%, 0.7 wt%, and 1.0 wt%—were used as additives to castor, jatropha, and palm kernel oils to formulate nano lubricants and tested alternately on a ball-on-aluminum (SAE 332) and low-carbon steel Disc Tribometer. All the vegetable-based oil nano lubricants showed a significant decrease in the coefficient of friction (CoF) and wear rate with Ball-on-(aluminum SAE 332) disc tribometer up to 0.5wt% of the nanoparticle: the best performances (eCOF = 92.29; eWR = 79.53) came from Al2O3-castor oil nano lubricant and Al2O3-palm kernel oil; afterwards, they started to increase. However, the performance indices displayed irregular behaviour for both COF and Wear Rate (WR) when tested on a ball-on-low-carbon steel Disc Tribometer.
The purpose of this research was to investigate the influence of innovative organizational culture on innovativeness through human resource management and the innovative skills of personnel. The population of this study comprised small and medium enterprises (SMEs) in Thailand from both the manufacturing and service sectors. Purposive sampling was employed to gather information from entrepreneurs, executives, or department managers of SMEs through an online questionnaire distributed via email, obtaining a total of 440 responses. Data were analyzed using descriptive statistics and structural equation models (SEM) for hypothesis testing. The results indicated that SMEs in this context had a moderate level of innovative organizational culture, human resource management, innovative skills, and innovativeness. Moreover, the structural equation model was consistent with the empirical data, revealing that innovative organizational culture has a direct influence on innovativeness. Furthermore, human resource management and the innovative skills of personnel were found to be partial mediators in the relationship between innovative organizational culture and innovativeness. The indirect effect through these two variables was greater than the direct effect. These findings confirmed the relationship between innovative organizational culture, human resource management, innovative skills, and innovativeness among SMEs in Thailand, leading to guidelines for businesses to improve their innovativeness.
This study delves into the evolving landscape of smart city development in Kazakhstan, a domain gaining increasing relevance in the context of urban modernization and digital transformation. The research is anchored in the quest to understand how specific technological factors influence the formation of smart cities within the region. To this end, the study adopts a Spatial Autoregressive Model (SAR) as its core analytical tool, leveraging data on server density, cloud service usage, and electronic invoicing practices across various Kazakhstani cities. The crux of the research revolves around assessing the impact of these selected technological variables on the smart city development process. The SAR model’s application facilitates a nuanced understanding of the spatial dynamics at play, offering insights into how these factors vary in influence across different urban areas. A key finding of this investigation is the significant positive correlation between the adoption of electronic invoicing and smart city development, a result that stands in contrast to the relatively insignificant impact of server density and cloud service usage. The conclusion drawn from these findings underscores the pivotal role of digital administrative processes, particularly electronic invoicing, in driving the smart city agenda in Kazakhstan. This insight not only contributes to the academic discourse on smart cities but also holds practical implications for policymakers and urban planners. It suggests a strategic shift towards prioritizing digital administrative innovations over mere infrastructural or technological upgrades. The study’s outcomes are poised to guide future smart city initiatives in Kazakhstan and offer a reference point for similar emerging economies embarking on their smart city journeys.
This research paper aims to examine the association between financial development and environmental quality in 31 European Union (EU) countries from 2001 to 2020. This study proposed an estimation model for the study by combining regression models. The regression model has a dependent variable, carbon emissions, and five independent variables, including Urbanization (URB), Total population (POP), Gross domestic product (GDP), Credit to the private sector (FDB), and Foreign direct investment (FDI). This research used regression methods such as the Fixed Effects Model, Random Effects Model, and Feasible generalized least squaresThe findings reveal that URB, POP, and GDP positively impact carbon emissions in EU countries, whereas the FDB variable exhibits a contrary effect. The remaining variable, FDI, is not statistically significant. In response to these findings, we advocate for adopting transformative green solutions that aim to enhance the quality of health, society, and the environment, offering comprehensive strategies to address Europe’s environmental challenges and pave the way for a sustainable future.
The objective of this paper is to analyze the impact of infrastructure financing on economic growth in emerging markets through the application of both quantitative and qualitative research methodologies. In this study, the research will employ both primary and secondary data to investigate the impact of different structures of infrastructure financing on the performance of the economy through interviews with the stakeholders and policy documents alongside quantitative data from the World Bank and the IMF. The quantitative analysis employs the econometric models to establish the effect of infrastructure investment on the GDP growth of the selected countries, India, China, Brazil, and Nigeria. Additional secondary qualitative data obtained from interviews with policymakers and financial specialists from Brazil, India, and South Africa offer more practical information regarding the efficiency of the discussed financing approaches. This paper is therefore able to conclude that appropriate management of infrastructure investments, particularly those that involve the PPP, are central to the development of the economy. However, certain drawbacks such as the lack of regularity of data and the disparity in the effectiveness of financing instruments by the regions are pointed out. The research provides policy implications to policymakers and investors who wish to finance infrastructure in the emerging economy to enhance economic growth in the long run.
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