Search Results (55)

This article presents the development and proof-of-concept testing of a vision-based safety monitoring tool for operators in simulated robotic cells in RoboDK. The proposed method uses a virtual camera placed above the cell and image processing techniques to analyze the relationship between the operator and the workspace swept by the robot. In an initial stage, the robot movement is recorded as a mask of the swept space, and areas irrelevant to the process can be excluded by user-defined polygons. In the monitoring stage, the operator is identified in the video stream by HSV segmentation, after which an adjustable clearance zone is generated around the detected contour. Based on the intersections between the operator, clearance, swept space mask and the mask of the current robot movement, the application provides four discrete states: SAFE, WARNING, DANGER and COLLISION. For the experimental validation in the virtual environment, the virtual contact moment is estimated separately, while the COLLISION state is defined as the intersection between the inflated operator contour and the current robot motion mask. Therefore, in this study, COLLISION does not indicate measured physical contact, but an image-based imminent-collision condition used for early warning. The test scenario was carried out in a virtual palletizing cell, which includes an articulated arm robot, conveyors, manipulated objects and a mobile dummy acting as an operator. The obtained results support the use of the method as an applicative simulation solution for the evaluation of the early detection of risk situations. The study is limited to the virtual environment and represents a basis for future research on the development of visual monitoring systems to increase safety in collaborative and industrial robotic cells. Full article

Amid growing global attention to corporate sustainability and responsible investment, the disclosure of Sustainable Development Goals (SDGs) has emerged as an important component of non-financial reporting. However, the extent to which SDG disclosure contributes to firm value remains underexplored, particularly in emerging markets. This study examines the association between SDG disclosure in corporate reports and firm value among 660 publicly listed companies across four Southeast Asian countries: Indonesia, Malaysia, Thailand, and Singapore. SDG disclosure is measured using 17 SDG indicators derived from the Refinitiv database and should be interpreted as a measure of disclosure breadth rather than disclosure quality or depth. The analysis begins with descriptive statistics to illustrate the distribution of key variables, followed by ANOVA to assess differences in SDG disclosure across countries and industries. Hypothesis testing is then conducted using multiple regression analysis with robust standard errors, with firm value proxied by price-to-book value (PBV). Several robustness checks are performed, including winsorised regression, year-by-year regressions, and regression models incorporating country and industry dummy variables. The results indicate that SDG disclosure is positively associated with firm value, although the relationship is interpreted as correlational rather than causal because of the short observation period and potential endogeneity. The findings also show that SDG disclosure is unevenly distributed across goals and countries, with SDG 8 and SDG 13 receiving the highest attention, while SDG 2 and SDG 14 remain among the least disclosed. These results highlight the importance of sustainability transparency in shaping market valuation and underscore the need for more balanced, comparable, and quality-oriented sustainability reporting frameworks across the region. Full article

Nowadays, Global Value Chains (GVCs) play a vital role in job creation, income generation, knowledge diffusion, and productivity growth. However, significant disparities exist across countries in terms of their integration into GVCs, and Tunisia is no exception to this pattern. In this regard, the question about factors that influence GVCs’ participation is yet to be discussed, to formulate and implement appropriate strategies and reforms. Thus, using firm-level data from the 2025 World Bank Enterprise Survey, this paper examines the role of female leadership and innovation in determining Tunisian firms’ participation in GVCs. Participation in GVCs is captured by a dummy variable indicating the firm’s export and import status. Estimation results from the logit model show that female representation in decision-making positions significantly increases the likelihood of firms’ participation in GVCs. The results also highlight the importance of process innovation in GVC participation, while product innovation appears to have no significant effect. Notably, when firms combine both types of innovation, their likelihood of joining GVCs increases further. Regarding control variables, firm size appears to be an important determinant, as larger firms display a greater tendency to participate in GVCs. The findings further indicate that firm certification and foreign equity participation significantly promote integration into GVCs, while corruption constitutes a major constraint on the integration of Tunisian firms. From a policy perspective, these findings highlight the need to rethink industrial policies, with a stronger focus on process innovation as a key lever of productive sector modernization. Achieving this transformation also requires the development of an inclusive policy ecosystem that supports meaningful and sustainable progress in female’s leadership representation. Full article

A holistic approach that prioritizes economic success and sustainable practices through Corporate Social Responsibility (CSR) is crucial for the long-term sustainability of organizations, including the tourism and hospitality industry, and the first step is CSR knowledge. The aim of this study is to identify the key factors influencing the level of Corporate Social Responsibility (CSR) knowledge in the hospitality industry, as a practical tool for the sustainability of the territories. For this purpose, the research was conducted using a quantitative methodological approach by applying a CSR questionnaire to hotel managers from a sample of 222 hotels in the Colombian Caribbean. Multivariate statistical techniques were applied, specifically Principal Component Analysis (PCA) and Multiple Linear Regression (MLR). The Principal Component Analysis determined two dependent variables (Basic CSR Knowledge and Advanced CSR Knowledge) and subsequently a Multiple Linear Regression was applied to each one, determining which independent variables (treated as dummy variables) have significant effects. The results have led to the conclusion that the CSR knowledge of the hotel sector in the Colombian Caribbean is positively influenced by hotel-related factors—such as age, management contract type, financial performance, and investment in innovation—as well as by managers’ gender and educational attainment. These results have important implications for the hotel sector and academia. Future research should consider more stakeholders and other geographical areas. Full article

In recent decades, Peru’s manufacturing sector has steadily declined in its share of gross domestic product, despite sustained economic growth and repeated improvements in the terms of trade. This study investigates whether this divergence between external bonanza and industrial stagnation reflects a manifestation of Dutch disease, with long-term implications for the structural sustainability of the country’s manufacturing base. A quantitative approach is applied through a multiple linear regression model estimated by Ordinary Least Squares, using quarterly data from 2012 to 2024. The analysis includes control variables such as real gross domestic product, private gross fixed investment, the real exchange rate, and a dummy for COVID-19. The results reveal a negative and statistically significant relationship between terms of trade and manufacturing performance, suggesting that favorable external shocks may undermine productive capacities by exacerbating structural vulnerabilities. Beyond quantifying this effect, the study offers a structural interpretation of how external shocks can erode industrial resilience in economies dependent on commodity exports. These findings underscore that structural sustainability depends not only on external conditions, but also on internal factors such as investment dynamics, institutional governance, and technological innovation capacity. In addressing a gap in the literature on Dutch disease and sectoral sustainability in the Peruvian context, the study concludes by calling for a strategic reorientation of industrial policy toward a more diversified, inclusive, and innovation-driven growth model, capable of absorbing external rents productively and ensuring the long-term resilience of the manufacturing sector amid persistent global volatility. Full article

This study investigates the impact of environmental, social, and governance (ESG) disclosure on value creation in a balanced panel of 100 non-financial Sharia-compliant firms listed on the Saudi Stock Exchange over the period 2014–2023. The analysis employs a combination of econometric techniques, including fixed effects models with Driscoll–Kraay standard errors, Pooled Ordinary Least Squares (POLS) with Driscoll–Kraay standard errors and industry and year dummies, and two-step system generalized method of moments (GMM) estimation to address potential endogeneity and omitted variable bias. Value creation is measured using Tobin’s Q (TBQ), Return on Assets (ROA), and Return on Equity (ROE). The models also control for firm-specific variables such as firm size, leverage, asset tangibility, firm age, growth opportunities, and market capitalization. The findings reveal that ESG disclosure has a positive and statistically significant effect on firm value across all three performance measures. Furthermore, firm size significantly moderates this relationship, with larger Sharia-compliant firms experiencing greater value gains from ESG practices. These results align with agency, stakeholder, and signaling theories, emphasizing the role of ESG in enhancing transparency, reducing information asymmetry, and strengthening stakeholder trust. The study provides empirical evidence relevant to policymakers, investors, and firms striving to achieve Saudi Arabia’s Vision 2030 sustainability goals. Full article

This study examines the critical role of institutional quality in driving corporate adaptation to climate change within the EU-27 member states from 2006 to 2023. It aims to investigate how governance factors—control of corruption, government effectiveness, rule of law, and regulatory quality—influence business strategies for environmental resilience and sustainability, focusing on environmental investments and industrial production. Employing fixed and random effects regression models on a balanced panel dataset, we analyze two dependent variables: environmental protection investment corporations (EPIC), measuring investments in pollution prevention and environmental degradation reduction, and industrial production (IP), reflecting output in mining, manufacturing, and utilities. A composite institutional quality index, derived through principal component analysis (PCA) from the four governance indicators, captures their collective impact, reducing multicollinearity and enhancing analytical robustness. Control variables, including final energy consumption, environmental tax revenues, expenditure on environmental protection, and a Paris Agreement dummy, are incorporated to test the institutional quality effect. Results demonstrate that higher institutional quality significantly enhances EPIC, particularly in countries with greater environmental tax revenues, indicating that robust governance and fiscal policies incentivize sustainable corporate investments. Conversely, the effect on IP is less consistent, with higher fossil energy consumption and lower environmental tax revenues driving production, suggesting a reliance on high-polluting industries. The Paris Agreement positively influences IP, reflecting stronger climate-focused industrial strategies post-2015. These findings underscore the pivotal interplay between institutional quality and environmental fiscal policies in fostering corporate adaptation to climate change. Over the long term, strong governance is essential for aligning business practices with sustainability goals, reducing environmental degradation, and mitigating climate risks across the EU. This study highlights the need for cohesive policies to support green investments and transition industries toward renewable energy sources, addressing disparities in environmental performance among EU member states. Full article

Conveyance tube manufacturing via a hot-finished, welded route is an energy-intensive process that promotes the rapid surface oxidation of curved surfaces. Previous studies have used computational and theoretical techniques to assess the oxidation of curved surfaces. However, experimental techniques for assessing the oxidation of curved surfaces, as well as for validating existing computational and analytical studies, have significant limitations that impact their ability to accurately recreate industrial processes. The challenges of thermogravimetric analysis (TGA) for in situ tests for the oxidation of cylindrical geometries were investigated, using an as-welded conveyance tube, and compared to an equivalent tube normalised in industry as well as computational predictions for the same geometry and thermal conditions. A core element of this work was the use of a refractory dummy sample to quantify thermal buoyancy and flow-induced vibration. There was a strong agreement between the oxide mass gain predicted by a computational model compared to that of the TGA sample, with only a 5% discrepancy. However, oxide thickness gain, measured using electron microscopy, showed poor agreement, particularly when comparing industrial and experimental results. This was attributed to the need for further work to account for transient heating, oxide porosity, atmospheric composition variation, and the effect of thermomechanical operations during conveyance tube manufacturing, e.g., hydraulic descaling. Full article

This research aimed to examine firm performance and its determinants in the textile and textile product (TPT) industry of Indonesia before and after the COVID-19 pandemic. The analysis used data from the manufacturing survey conducted by Indonesia’s Bureau of Central Statistics (BPS) for the period 2018–2021. It further incorporated the fixed-effect model on the subsectors by applying least-square dummy variables. The results show that firm performance declined during the COVID-19 pandemic while the price–cost margin was affected by firm size, export orientation, foreign ownership, and the pandemic. However, the Herfindahl–Hirschman index did not have a significant influence on firm performance. This research addresses the gaps identified in previous publications, which had limitations regarding sample data. It further contributed to the literature by applying price–cost margin (PCM) as a proxy for firm performance and investigating the determining factors in the TPT industry before and after the COVID-19 pandemic, particularly in Indonesia. Full article

Mixed land use has the advantages of promoting the economic and intensive utilization of land and improving the efficiency of land use, which can help alleviate the current urban problems and promote the sustainable development of cities. Existing studies have usually used quantitative indicators to reflect complex and diverse mixed land use situations, and the conclusions obtained usually cannot provide a basis for functional selection in mixed land use practices. Therefore, this study took Shenzhen as the study area to explore whether there are differences in the urban vibrancy enhancement among different mixed land use types. First, the block-scale mixed land use dataset of the study area was constructed. Second, the spatial distribution characteristics of the main functional types and urban vibrancy in the study area were explored. Finally, the impact of mixed land use types on urban vibrancy was explored by using a multiple linear regression model and setting land use type as the dummy variable. The results show that the number of mixed-function blocks in Shenzhen is relatively small, and the mixed land use degree still needs to be improved. Among the 12 main land use types in the study area, those containing industrial land are usually clustered in the northern industrial area of Shenzhen, those containing public or commercial service land are usually clustered in the city center, and those containing residential land are widely distributed in the study area. From the perspective of urban vibrancy, there is a phenomenon of “jobs–housing mismatch” in Shenzhen, as well as a problem of low urban vibrancy in the peripheral areas of the city. In addition, the urban vibrancy intensity of mixed land use types including residential or commercial land is higher, such as “administration+residential”, “residential+commercial”, “industrial+residential+commercial”, and “administration+residential+commercial” land, which includes residential or commercial land, is stronger, while. However, the urban vibrancy stability of mixed land use types including industrial land is higher, such as “industrial+residential” and “industrial+administration” land. The results of this study can provide a basis for future mixed land use practices in terms of land use type selection. For the urban central areas and subcenters in urban peripheral areas, mixed land use types such as “administration+residential”, “residential+commercial”, and “administration+residential+commercial” can be selected to enhance the urban vibrancy stability of the area. For industrial parks in urban peripheral areas, mixed land use types such as “industrial+residential”, “industrial+commercial”, “industrial+administration+residential”, and “administration+residential+commercial” can be selected to enhance the urban vibrancy intensity of the area. Full article

High-speed rail is a high-standard railway system, which allows trains to operate at high speed. The railway play a crucial role in connecting urban agglomerations, which represents the highest form of spatial organization in the mature stage of urban development, bringing together cities of various natures, types, and scales in specific regions. This paper explores the impacts of high-speed rail and its expansion on industrial concentration and macroeconomic conditions in the period of 2000 to 2019. We use a well-known transportation policy as a natural experiment, utilizing geographic distance data to study the effects of high-speed rail and its expansion on industrial concentration and macroeconomic conditions in urban agglomerations. The results show that high-speed rail increases industrial concentration but leads to a reduction in macroeconomic conditions. Unlike previous studies in this field, we use distance variables to analyze how the expansion of high-speed rail affects macroeconomic conditions and industrial concentration through location advantages. The impacts of high-speed rails vary across urban and non-urban agglomeration cities, resource-based and non-resource-based cities, large and small cities, and eastern, central, and western regions. Our results are robust to the shocks from the global financial crisis, time lags, different distance dummy variables, dependent variables, and endogeneity issues. This study regards the opening up of high-speed rail as both improving air quality and reducing carbon emissions through substituting for urban and aviation transport. Compared to traditional transport methods such as urban and air travel, the efficiency and environmental benefits of high-speed rail make it an important method for reducing greenhouse gas emissions. Consequently, the expansion of high-speed rail could support both economic development and environmental concerns, and it is playing a crucial role in transportation selection for advancing low-carbon economic goals. Full article

This paper examines how geography matters for the location of industries in East Asia, employing regression analyses on a novel and comprehensive regional GDP dataset. This study examines how geography affects industrial location patterns, particularly the role of infrastructure, such as ports and airports. This paper analyzes the current economic geography of East Asia using the novel dataset. The regression analyses utilize location quotients as the dependent variable and incorporate explanatory variables, such as domestic/foreign market access, per capita income, population density, and distance-based dummies for ports and airports. The findings reveal that the determinants of industrial location differ significantly across industries. The relative importance of domestic versus foreign market access and proximity to ports and airports varies across sectors. The results imply that countries/regions cannot easily host industries of their choice, as different industries require distinct locational characteristics. Full article

In industrial applications, local exhaust systems have been used extensively for capturing and confining contaminants at their source. The present study investigates the efficacy of these systems in mitigating the spread of exhaled pollutants by combining them with mixing and displacement ventilation. Experiments were conducted in a simulated meeting room with six closely situated workstations, featuring five exposed persons (simulated with heated dummies) and one infected person (simulated with a breathing manikin). Six overhead local exhaust units, merged with panels, corresponding to workstations, were installed using a lowered false ceiling. Additionally, a table plenum setting for air inlets was introduced to enhance displacement ventilation effectiveness along with local exhaust systems. Results from 16 experimental cases are presented, using the local air quality index and ventilation effectiveness in the breathing zone. The local exhaust system improved the local air quality at the measuring locations closest to the infector in almost all test scenarios. The improvement, particularly significant with displacement ventilation, marked a maximum 35% increase in the local air quality index adjacent to the infector and 25% in the entire breathing zone of the tested meeting room. Moreover, the table plenum settings, coupled with displacement ventilation, further enhanced conditions in the breathing zone. Under the specific conditions of this investigation, the number of operational local exhausts had a marginal impact on mixing ventilation but a significant one on displacement ventilation tests. The efficacy of local exhaust systems was also influenced by the levels of heat gains present in the room. Overall, the study aims to contribute to ongoing efforts to identify sustainable solutions to mitigate indoor airborne diseases with a combination of supply and local exhaust units. Full article

The purpose of this study was to examine the determinants of cash distribution options by critically considering the effects of earnings, dividends, firm size, and economic value added. The distribution of cash dividends to shareholders serves as a basic means by which shareholders receive returns on their investments, so it is essential to examine share repurchases alongside dividends to enhance management’s efforts in maximising shareholder value. This study utilised panel data from 52 companies listed on the Johannesburg Security Exchange (JSE) that engaged in open market share repurchases for at least 2 years between 2000 and 2019. The data were extracted from the IRESS database. The panel data regression model was fitted with the ordinary least squares (OLS), difference generalised moment method (Diff-GMM), system generalised moment method (Sys-GMM), and least-squares dummy variable correction estimator (LSDVC). The findings revealed that there was a positive and significant relationship between the earnings per share and the payoff flexibility, implying that there was an inherent flexibility of repurchases as a payout option in the sampled firms. Additionally, the study revealed a significant negative relationship between the firm size, economic value added, and payoff flexibility. This suggests that larger companies tend to distribute a lower proportion of their earnings as share repurchases and opt for higher cash dividends instead. The implications of these findings provide financial managers with valuable insights into the role of share repurchases as a cash distribution choice. By recognising share repurchases as a viable option, financial managers can enhance their efforts to create and maximise shareholder value, particularly in emerging market settings. This evidence should encourage financial managers to recognise share repurchases more as a distribution choice, diffusing the tension regarding share repurchases replacing the payment of cash dividends and some doubt that they may not possess attributes complimentary to cash dividends. The study recommended relevant academic, industry, and policy implications in the South African context. Full article

Fall accidents in industrial and construction environments require an immediate reaction, to provide first aid. Shortening the time between the fall and the relevant personnel being notified can significantly improve the safety and health of workers. Therefore, in this work, an IoT system for real-time fall detection is proposed, using the ASSIST-IoT reference architecture. Empowered with a machine learning model, the system can detect fall accidents and swiftly notify the occupational health and safety manager. To train the model, a novel multimodal fall detection dataset was collected from ten human participants and an anthropomorphic dummy, covering multiple types of fall, including falls from a height. The dataset includes absolute location and acceleration measurements from several IoT devices. Furthermore, a lightweight long short-term memory model is proposed for fall detection, capable of operating in an IoT environment with limited network bandwidth and hardware resources. The accuracy and F1-score of the model on the collected dataset were shown to exceed 0.95 and 0.9, respectively. The collected multimodal dataset was published under an open license, to facilitate future research on fall detection methods in occupational health and safety. Full article