Environmental Performance Of Industry Research Articles

Effect of sound absorption on noise reduction in the automotive industry

Industrial noise is one of the most common physical factors that cause annoyance and damage workers' health in the long term. Precautions should be taken to reduce noise and improve acoustic performance in industrial working environments. This paper aims to analyze the acoustic performance of the automotive industry and contribute to the global outcomes of sustainability and the development of strategies to improve the quality of the working environment through improvement scenarios. For this purpose, the automotive industry in Türkiye was examined as a case study. In-situ acoustic measurements were made in the seat manufacturing unit of an automotive factory and the current situation was transferred to the simulation program. The effects of acoustic improvements on A-weighted sound pressure level and reverberation time at mid-frequencies (500, 1000, 2000 Hz) were investigated through three different scenarios. In the investigations, noise distributions were carried out through noise mapping. The A-weighted sound pressure levels in the automotive industry were reduced by approximately 15 dB. As a result of the study, suggestions for noise control precautions and their effects on the automotive industry seat manufacturing unit are presented.

Effect of Sound Absorption on Noise Reduction in the Automotive Industry

Industrial noise is one of the most common physical factors that cause annoyance and damage to workers' health in the long term. Precautions should be taken to reduce noise and to improve acoustic performance in industrial working environments. This paper aims to analyze the acoustic performance of the automotive industry contributes to the global outcomes of sustainability and develop strategies for improving the quality of the working environment through improvement scenarios. For this purpose, the automotive industry in Türkiye was examined as a case study. In-situ acoustic measurements were made in the seat manufacturing unit of an automotive factory, and the current situation was transferred to the simulation program. The effects of acoustic improvements on A-weighted sound pressure level and reverberation time at mid-frequencies (500, 1000, 2000 Hz) were investigated through three scenarios. In the investigations, noise distributions were carried out through noise mapping. The A-weighted sound pressure levels in the automotive industry were reduced by approximately 15 dB. As a result of the study, suggestions for noise control precautions and their effects on the automotive industry seat manufacturing unit are presented.

The Impact of Environmental Management Accounting Adoption on The Shipping Industry's Environmental Performance, Influenced by Green Shipping and Regulatory Pressure

The Impact of Environmental Management Accounting Adoption on The Shipping Industry's Environmental Performance, Influenced by Green Shipping and Regulatory Pressure

A Novel Energy-Efficient Routing Protocol for Industrial WSN Using Hybrid Coot-Ls Algorithm with LSTM-Based Dom Prediction

In industrial Wireless Sensor Networks (WSNs), energy efficiency and reliable data transmission are critical challenges that need to be addressed to ensure sustainable and robust network operations. This paper proposes a novel energy-efficient routing protocol that integrates a Hybrid COOT-LS (Coot- Levy Search) algorithm with Long Short-Term Memory (LSTM)-based Dominant Object Motion (DOM) prediction. The routing protocol leverages the strengths of Hybrid Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) to enhance routing efficiency and reduce energy consumption. The Hybrid PSO and ACO algorithms are employed to optimize routing paths by balancing exploration and exploitation, considering multiple factors such as energy levels, node distance, and reliability. The COOT-LS algorithm further refines these paths by incorporating a Levy flight mechanism to enhance the search process. Additionally, the LSTM-based DOM prediction provides accurate forecasts of network conditions, enabling dynamic adjustments to routing strategies in real time. Simulation results demonstrate that the proposed protocol significantly improves network lifetime, reduces energy consumption, and enhances data transmission reliability compared to traditional routing protocols. This approach provides a robust and scalable solution for industrial WSN applications, ensuring efficient and reliable network performance in dynamic and complex industrial environments.

The Influence of Green Innovations on the Environmental performance of the Hotel Industry in Ghana: Does the Moderating role of Green Transformational Leadership Matter

This study examined the effect of green innovations (GI) on the environmental performance (EP) of the hotel industry (HI) in Ghana, focusing on the moderating role of green transformational leadership (GTFL). Data from 500 hotel staff were analyzed using Structural Equation Modeling to analyze the data. The outcome showed that green innovation and transformational leadership positively and significantly influence the environmental performance of the hotel industry in Ghana. Furthermore, the finding indicated that green transformational leadership significantly moderated green innovation on the hotel industry's environmental performance, highlighting leadership's crucial role in promoting sustainability. This study explores the relatively unexplored interaction between green transformational leadership and green innovations within the context of the Ghanaian hotel industry. The unique combination of these factors adds a novel dimension to the existing literature on environmental performance in Ghana's hotel sector.

Sustainability in design: Sustainable fashion design practices and environmental impact using mixed‐method analysis

AbstractSustainable fashion design arises as a crucial reaction to the industry's fashion necessity for environmental influence reduction and addressing sustainability challenges effectively. This study examines the nuanced dimensions of this pursuit and its influence on the industry's environmental performance. Through a mixed‐method research approach involving 268 designers and 159 participants included in the interview process (fashion experts, entrepreneurs, and business strategists), the investigation explored the efficacy of eco‐friendly practices in enhancing overall sustainability. The findings underscore significant improvements in environmental performance metrics for fashion companies embracing sustainable design practices, revealing a direct correlation between such practices and a reduction in carbon footprint. The study identifies key drivers prompting fashion businesses to invest in innovative sustainable design solutions, particularly in response to sustainability challenges and consumer demand for eco‐friendly products. Collaboration with eco‐conscious suppliers and transparent supply chain practices is pivotal for effectively addressing sustainability challenges. Besides, the research underscores the significance of incorporating principles of circular economy, including recycling and upcycling, to augment environmental performance within the fashion sector. By offering practical insights and theoretical reflections, our research enriches the discourse on sustainable fashion (SF), guiding industry stakeholders, policymakers, and researchers aiming for a sustainable and ethical future.

Industry restructuring and environmental performance – Decomposing the drivers of water pollution reduction in the Swedish pulp and paper industry, 1969-1989

This paper analyses the reduction of biochemical oxygen demand (BOD) emissions in the Swedish pulp and paper industry between 1969-1989. To that end, I have constructed pollution records for a large sample of Swedish chemical pulp producers and decomposed the observed changes in BOD emissions into (i) scale, (ii) technique, (iii) composition, and (iv) plant entry and (v) plant exit effects. In contrast to previous decomposition analyses of industrial pollution reduction, which have mainly emphasised the technique effect and/or compositional changes across surviving plants, this study finds that the majority of the pollution reduction was due to the exit of numerous (predominantly emission-intensive sulfite) plants, in combination with a continuous reallocation of production from such plants towards the surviving (predominantly sulfate) plants. The divergence in results can be attributed to the industry’s market structure, which is an important factor to consider when assessing the potential for successful pollution reduction.

Development of Corrosion Resistant Welding Technology for Industrial Applications Study on the Impact of Material Variation and Welding Process

This article discusses the development of stainless welding technology aimed at improving corrosion resistance in industrial applications. The research focuses on the effect of material variation and welding process on the corrosion-resistant performance of welding joints. The research methodology includes the selection of materials with different compositions and the application of various welding techniques. Experiments were conducted to evaluate the microstructure, joint strength, and corrosion resistance properties of the weldments. The results show that material variation has a significant impact on the corrosion resistance of welding joints. The use of certain welding techniques can also affect the corrosion properties of the resulting material. Microstructure analysis provides an in-depth insight into the changes at the microscopic level that affect corrosion resistance. This study makes an important contribution in identifying critical parameters that need to be considered in the development of corrosion resistant welding technology to improve material performance in corrosive industrial environments. In conclusion, a better understanding of the relationship between material and welding process variations and corrosion resistance can help in designing more effective and durable welding technologies for industrial applications. This research has the potential to provide practical guidance for engineers and industry professionals in selecting optimal materials and welding techniques to address corrosion challenges in diverse work environments.

SiCw strengthened WC-Y2O3 composite and its electrochemical corrosion in aggressive medium

The mechanical properties and corrosion resistance of binderless tungsten carbide largely determine its performance and lifespan in complex industrial environments. Herein, WC-1Y2O3-xSiCw (x = 0, 0.5, 1, and 2 wt%) was prepared using the hot-press sintering. The mechanical properties of the composite, as well as the corrosion resistance of optimized mechanical properties in an aggressive medium (0.05 M H2SO4 and 1 M NaOH) were investigated. Results showed that SiCw could significantly increase mechanical properties of the composite, but excessive content (2 wt%) leads to whiskers aggregation and lower properties. The flexural strength and fracture toughness are all increased to varying degrees with whisker content. WC-1Y2O3-0.5SiCw possesses the optimal mechanical properties. The Vickers hardness, fracture toughness, and flexural strength are 2331.24 HV30, 8.59 MPa·m1/2, and 1727 MPa, respectively. Electrochemical tests show that the corrosion resistance of the WC-1Y2O3-0.5SiCw in H2SO4 is higher than that in NaOH solution, and its corrosion resistance in H2SO4 solution increases, but that of the NaOH solution decreases with exposure time. Detailed characterization demonstrated that a dense WO3 film forms in the H2SO4 solution, resulting in a flatter corrosion surface. In contrast, the WC phase in NaOH solution dissolves, thus leading to the accelerated corrosion rate.

Performance Evaluation of LoRa Communications in Harsh Industrial Environments

LoRa technology is being integrated into industrial applications as part of Industry 4.0 owing to its longer range and low power consumption. However, noise, interference, and the fading effect all have a negative impact on LoRa performance in an industrial environment, necessitating solutions to ensure reliable communication. This paper evaluates and compares LoRa’s performance in terms of packet error rate (PER) with and without forward error correction (FEC) in an industrial environment. The impact of integrating an infinite impulse response (IIR) or finite impulse response (FIR) filter into the LoRa architecture is also evaluated. Simulations are carried out in MATLAB at 868 MHz with a bandwidth of 125 kHz and two spreading factors of 7 and 12. Many-to-one and one-to-many communication modes are considered, as are line of sight (LOS) and non-line of Sight (NLOS) conditions. Simulation results show that, compared to an environment with additive white Gaussian noise (AWGN), LoRa technology suffers a significant degradation of its PER performance in industrial environments. Nevertheless, the use of forward error correction (FEC) contributes positively to offsetting this decline. Depending on the configuration and architecture examined, the gain in signal-to-noise ratio (SNR) using a 4/8 coding ratio ranges from 7 dB to 11 dB. Integrating IIR or FIR filters also boosts performance, with additional SNR gains ranging from 2 dB to 6 dB, depending on the simulation parameters.

The Influence of Noise Exposure at Different Loudness Levels on EEG Index and Types of Attention.

Noise is one of the most important harmful factors in the environment. There are limited studies on the effect of noise loudness on brain signals and attention. The main objective of this study was to investigate the relationship between exposure to different loudness levels with brain index, types of attention, and subjective evaluation. Four noises with different loudness levels were generated. Sixty-four male students participated in this study. Each subject performed the integrated visual and auditory continuous performance test (IVA-2) test before and during exposure to noise loudness signals while their electroencephalography was recorded. Finally, the alpha-to-gamma ratio (AGR), five types of attention, and the subjective evaluation results were examined. During exposure to loudness levels, the AGR and types of attention decreased while the NASA-Tax Load Index (NASA-TLX) scores increased. The noise exposure at lower loudness levels (65 and 75 phon) leads to greater attention dysfunction than at higher loudness. The AGR was significantly changed during exposure to 65 and 75 phon and audio stimuli. This significant change was observed in exposure at all loudness levels except 85 phon and visual stimuli. The divided and sustained attention changed significantly during exposure to all loudness levels and visual stimuli. The AGR had a significant inverse correlation with the total score of NASA-TLX during noise exposure. These results can lead to the design of methods to control the psychological effects of noise at specific frequencies (250 and 4000 Hz) and can prevent non-auditory damage to human cognitive performance in industrial and urban environments.

Green Human Resource Competency Mechanisms: Moderator Role Between Green Supply Chain and the Oil and Gas Industry Environmental Performance

The oil and gas (O&G) industry has been plagued by numerous green factors that have adversely affected supply chain management practices in recent years. This study aims to examine the impact of green human resource (GHR) competency mechanisms to strengthen the relationship between green supply chain management (GSCM) practices and environmental performance (EP). Using the proposed model, the present study developed a quantitative method for obtaining data from listed O&G companies in the UAE between December 2018 and May 2019. A total of 254 questionnaires were used for the analysis. There was a significant moderating effect between EP and GSCM, with GHR competency mechanisms decreasing the occurrence of negative environmental impacts associated with O&G operations. The findings will enable HR managers to align green skills with EP in UAE petroleum companies.

LoRa Performance in Industrial Environments: Analysis of Different ADR Algorithms

LoRaWAN (Long Range Wide Area Network) technology can be a good candidate for industrial applications in IoT and Adaptive Data Rate (ADR) algorithms help to improve LoRaWAN performance. These algorithms compute a link budget to define the data rate and the transmission power. However, the performance of these algorithms must be evaluated in industrial environments that pose challenging conditions to wireless communications due to obstacles, interference, and movement. Therefore, this article compares the performance of LoRaWAN with six different ADR algorithms using a realistic propagation model from an industrial environment. The research uses the FLoRa environment in Omnet++ to compare the packet delivery ratio and energy consumption with different gateway locations and data traffic. Results show that the algorithms that decrease the link budget in poor channel conditions have better performance in industrial scenarios. Furthermore, overestimating the channel behavior decreases packet delivery.

지역축제 브랜드자산과 축제성과의 관계에서 개최지역태도의 매개효과

The purpose of this study is to investigate the mediating effect of host region attitudes in the relationship between festival visitors' local festival brand equity and festival performance. The analysis results obtained in this study are as follows. First, among local festival brand equity, the higher the brand value and brand quality, the better the festival performance. Second, among the local festival brand equity, the higher the brand image, brand value, and brand quality, the better the attitude of the hosting region. Third, the host region attitude was found to have a positive effect on tourism industry performance, socio-cultural performance, environmental performance, political performance, and economic performance. Last, in the relationship between local festival brand equity and festival performance, it was confirmed that the host region attitude had a partial mediating effect.

Enhancing industrial environmental performance: interplay among environmental sustainability, green HRM, and green competitive advantage.

This study highlights the importance of green human resource management (HRM) practices, which investigates the connection between environmental sustainability and green competitive advantage. Using the CGM model and the generalized method of moments (GMM), this research investigates how green HRM may foster environmental sustainability by creating a competitive advantage for businesses. Research shows that green HRM may achieve green competitive advantage practices, crucial for environmental sustainability. By "green HRM practices," we mean incorporating environmental concerns into traditional HRM processes, including hiring, training, evaluating, and compensating employees. However, the importance of green HRM practices cannot be overstated due to their efficiency in creating a competitive advantage and advancing environmental sustainability. Specifically, the research shows that businesses that have adopted "green HRM practices" outperform their competitors in terms of environmental sustainability. The last section emphasizes the importance of green HRM as a key facilitator of environmental sustainability. Implications for businesses that want to improve their environmental performance are also provided.

The Effect of Industrial Type, Environmental Performance and Leverage on Carbon Emission Disclosure: Evidence from Indonesian LQ45 Companies

This study aims to examine and look for empirical evidence related to the determinants that influence the carbon emissions disclosure. The factors tested in this study include industrial type, environmental performance, leverage, and profitability. This research method uses a quantitative approach. The source of data in this study uses secondary data, namely data from sustainability reports and annual reports. The population used is all LQ45 index companies listed on the Indonesia Stock Exchange in 2016 – 2020 and this study uses purposive sampling technique. This study uses tests such as descriptive statistical analysis, classical assumption test, hypothesis testing and multiple linear regression analysis. The results of this study indicate that the industrial type and CEO tenure have no effect on carbon emission disclosures, while leverage, profitability, environmental performance, CEO gender and technology for disclosure have a negative effect on carbon emission disclosures.

Green Performance and Technological Competence of Human Resources Based on Industrial Revolution 4.0

Objective: The industrial revolution has changed the way humans work into automation/digitalization through innovations. Industry players play an active role as organizational entities that have a vision in achieving profits. The industrial revolution 4.0 which adopts the green concept has an impact on strategic transformation in the performance and technological competence of human resources. Green performance requires personal characteristics that are oriented towards the sustainability of the industrial environment and mastery of green technology. 
 Methodology: This research is qualitative research in the characteristic of library research, namely a series of activities related to library data collection methods, the research model uses an analytical descriptive method because this method is used to examine ongoing events and relate to current conditions. The initial article search returned as many as 90 articles. Furthermore, the selected articles were selected according to the research objectives by reading the title and abstract. The result is that the number of articles is 30 articles. The researcher chose again from 30 articles based on four focus research questions, and in the end, a total of 20 articles were reviewed.
 Results: The results indicate that the existence of an industrial revolution has advantages in developing competence and reducing consumption because, in this instance, there are prospects for e-commerce and the development of a digital green economy for industry players. Human resources and the industrial environment can both perform better when using green practices. To enable sustainable green innovation, green performance has to improve its technological proficiency. A rich society in development will result from the industrial revolution 4.0's synthesis, and people who live sustainably will be of the finest quality.
 Implication: The implications of this research provide valuable insights for green industry managers to formulate strategies and policies for transforming green technology competencies into green performance in industrial environments. This study is very useful for practitioners by identifying the benefits of linkage action between planned or realized green performance and green technology in the industry. This article provides a valuable reference for business players to consider implementing a green performance system that combines all communication, collaboration, critical thinking, creative, innovative skills in using resources and efficiency of natural resources.

Tracing green growth through industrial resource efficiency patterns: The role of competitiveness and clean technologies

AbstractThe European Green Deal entails benefits for industrial transition to cleaner production through resource efficiency, paving the way to green transition. We develop a conceptual framework to study the drivers of resource efficiency of European industries towards green growth via segments of the countries' competitiveness under technological heterogeneity. Data on 13 industries in 17 European countries over an 8‐year period is used. Evidence shows that isolated efforts to improve productive performance harms environmental efficiency in low competitiveness countries. Results show that industrial environmental performance is affected by country's competitiveness, contributing to the implementation of the New Industrial Strategy of Europe.

Examining the role of tourism industry in green economic and environmental performance: does structural change matter in Asia?

Tourism has become an increasingly significant contributor to economic growth in Asia. However, the rapid expansion of the tourism industry has also raised concerns about its impact on the environment and economic sustainability. Meanwhile, the structural transformation of economies in Asia has also been a major factor in shaping the region's environmental and economic performance. Thus, the present study aims to explore the impact of the tourism industry and structural change on green economic and environmental performance in Asia. Limited empirical evidence exists on the impact of tourism industry and structural change on CO2 emissions and green growth. The objective of this current study is to examine how tourism industry and structural change impact green economic and environmental performance over the period 1993 to 2020. For analyzing short- and long-run results across different quantiles, we have employed a nonlinear QARDL model that can provide estimates across different quantiles. The findings of the CO2 emissions model imply that long-term improvements in tourism and structural changes significantly reduce CO2 emissions. In contrast, the long-term negative changes in tourism and structural changes increase CO2 emissions. In the green growth model, long-term improvements in tourism and structural changes significantly improve green growth; however, the long-term decline in tourism and structural changes significantly reduce green growth. Moreover, the control variable of ICT reduces CO2 emissions and improves green growth, and energy consumption increases CO2 emissions and reduces green growth.

Can Digital Finance Improve Corporate Environmental Performance? Evidence from Heavy Polluting Listed Companies in China

ABSTRACT In the context of the digital transformation of China’s financial system and the synergistic growth of its economic environment, this research explores the impact of digital finance development on the environmental performance of enterprises. Through empirical analysis of data gathered from A-share heavy polluters from 2011 to 2020, our findings show that digital finance effectively improves the environmental performance of heavy polluters. The conclusions remain robust after controlling for endogeneity issues and running a series of robustness tests. The mechanism test reveals that the effects of financing and innovation are important channels through which digital finance influences industrial environmental performance. Furthermore, heterogeneity analysis shows that the beneficial influence of digital finance on the environmental performance of firms is enhanced when firms are smaller, have non-state ownership, are located in East China, and have a lower level of financial development. These findings expand upon the factors that influence corporate environmental performance and provide empirical evidence that heavy-polluting companies should fully grasp the opportunities of digital finance development and improve their environmental performance in order to achieve higher-quality development.