Control Variables Research Articles

Corporate Sustainability Reporting and Financial Performance: An Empirical Analysis of Indian Listed Companies

This empirical analysis examines the relationship between corporate sustainability reporting and financial performance among Indian listed companies. In recent years, sustainability has gained prominence in corporate strategy due to increasing regulatory requirements, investor interest, and stakeholder expectations. The study explores how sustainability reporting, as disclosed through corporate sustainability reports (CSR), affects the financial performance of companies. Using a sample of Indian companies listed on major stock exchanges, the study analyzes data on sustainability disclosures, financial performance indicators (such as return on assets, return on equity, and market valuation), and various control variables. The analysis employs statistical methods, including regression models, to identify the correlation and potential causal linkages between sustainability reporting and financial performance. The findings suggest a positive relationship between comprehensive sustainability reporting and financial performance, indicating that companies with better sustainability practices tend to experience higher financial returns and market valuation. The results also highlight the role of regulatory frameworks, industry-specific factors, and company size in shaping the strength of this relationship. This study contributes to the growing body of literature on corporate sustainability by providing insights specific to the Indian context, where sustainability reporting practices are evolving. It suggests that companies engaging in transparent and detailed sustainability reporting may achieve not only environmental and social benefits but also financial gains, making sustainability a strategic priority for long-term value creation.

Examining the Nexus between Tourism Investment, Renewable Energy Consumption and CO2 Emissions in Indonesia

The tourism industry undoubtedly contributes positively to economic growth. However, numerous studies show that tourism can have diverse impacts on environmental quality. This study focuses on exploring the correlation between investment in the tourism sector, the renewable energy consumption, and the contribution of tourism-related sectors to CO2 emissions within the period 2000 – 2017 using a case study in Indonesia. By employing the distributed lag method with the Koyck approach, this study found that investment in the tourism sector in Indonesia has a statistically positive and significant correlation with CO2 emissions. Conversely, renewable energy consumption, as the control variable, exhibits a significant negative correlation with CO2 emissions. The findings suggest that the existing investment policies in Indonesia are not aligned with environmental sustainability, supporting the pollution haven hypothesis. To address this, the study underscores the need for stronger commitments to transitioning from fossil-based to renewable energy sources, ensuring that future tourism investments contribute to both economic growth and environmental preservation.

Transmission dynamics of fractional order SVEIR model for African swine fever virus with optimal control analysis

Understanding the dynamics of the African swine fever virus during periods of intense replication is critical for effective combatting of the rapid spread. In our research, we have developed a fractional-order SVEIR model using the Caputo derivatives to investigate this behaviour. We have established the existence and uniqueness of the solution through fixed point theory and determined the basic reproduction number using the next-generation matrix method. Our study also involves an examination of the local and global stability of disease-free equilibrium points. Additionally, we have conducted optimal control analysis with two control variables to increase the number of recovered pigs while reducing the number of those infected and exposed. We have supported our findings with numerical simulations to demonstrate the effectiveness of the control strategy.

Examining the impact of intellectual capital on underwriting risk of insurance companies in Pakistan: static and dynamic panel regression

Purpose This study aims to examine the impact of intellectual capital on the underwriting risk of insurance companies in Pakistan. Design/methodology/approach The study used a quantitative research approach and a longitudinal research design, gathering data from 23 insurance companies listed on the Pakistan stock exchange from 2010 to 2022. The value-added intellectual coefficient (VAIC) was used to measure intellectual capital (IC), and unbalanced panel data were analyzed using static and dynamic regression analyses. Findings The findings demonstrate a significant association between intellectual capital and underwriting risk in insurance companies in Pakistan. Specific components of intellectual capital, such as human capital efficiency (HCE), structural capital efficiency (SCE) and capital employed efficiency (CEE), have a strong negative impact on underwriting risk. Control variables like return on assets, insurer size and leverage also showed significant relationships with underwriting risk. Originality/value This research provides new insights into the theoretical understanding of the insurance industry by establishing a direct link between intellectual capital and underwriting risk in the context of Pakistan. It suggests that by improving aspects of intellectual capital, specifically HCE, SCE and CEE, policymakers and managers can reduce underwriting risk.

Association of neighborhood-level disadvantage beyond individual sociodemographic factors in patients with or at risk of knee osteoarthritis

ObjectiveLower socioeconomic status (SES) is a risk factor for poorer pain-related outcomes. Further, the neighborhood environments of disadvantaged communities can create a milieu of increased stress and deprivation that adversely affects pain-related and other health outcomes. Socioenvironmental variables such as the Area Deprivation Index, which ranks neighborhoods based on socioeconomic factors could be used to capture environmental aspects associated with poor pain outcomes. However, it is unclear whether the ADI could be used as a risk assessment tool in addition to individual-level SES.MethodsThe current study investigated whether neighborhood-level disadvantage impacts knee pain-related outcomes above sociodemographic measures. Participants were 188 community-dwelling adults who self-identified as non-Hispanic Black or non-Hispanic White and reported knee pain. Area Deprivation Index (ADI; measure of neighborhood-level disadvantage) state deciles were derived for each participant. Participants reported educational attainment and annual household income as measures of SES, and completed several measures of pain and function: Short-form McGill Pain Questionnaire, Western Ontario and McMaster Universities Osteoarthritis Index, and Graded Chronic Pain Scale were completed, and movement-evoked pain was assessed following the Short Physical Performance Battery. Hierarchical linear regression analyses were used to assess whether environmental and sociodemographic measures (i.e., ADI 80/20 [80% least disadvantaged and 20% most disadvantaged]; education/income, race) were associated with pain-related clinical outcomes.ResultsLiving in the most deprived neighborhood was associated with poorer clinical knee pain-related outcomes compared to living in less deprived neighborhoods (ps < 0.05). Study site, age, BMI, education, and income explained 11.3–28.5% of the variance across all of the individual pain-related outcomes. However, the ADI accounted for 2.5–4.2% additional variance across multiple pain-related outcomes.ConclusionThe ADI accounted for a significant amount of variance in pain-related outcomes beyond the control variables including education and income. Further, the effect of ADI was similar to or higher than the effect of age and BMI. While the effect of neighborhood environment was modest, a neighborhood-level socioenvironmental variable like ADI might be used by clinicians and researchers to improve the characterization of patients’ risk profile for chronic pain outcomes.

Psychosis Spectrum Symptoms Before and After Adolescent Cannabis Use Initiation

Adolescent cannabis use has been consistently posited to contribute to the onset and progression of psychosis. However, alternative causal models may account for observed associations between cannabis use and psychosis risk, including shared vulnerability for both cannabis use and psychosis or efforts to self-medicate distress from psychosis spectrum symptomology. To test 3 hypotheses that may explain cannabis-psychosis risk associations by modeling psychosis spectrum symptom trajectories prior to and after cannabis initiation across adolescent development (approximately 10-15 years of age). This cohort study used data from 5 waves across 4 years of follow-up from the Adolescent Brain Cognitive Development (ABCD) Study. The ABCD study is an ongoing large-scale, longitudinal study of brain development and mental and physical health of children in the US launched in June 2016. Data are collected from 21 research sites. The study included data from 11 868 adolescents aged 9 to 10 years at baseline. Three participants were excluded from the present analysis owing to missing data. Data analysis was performed from September 2023 to July 2024. Discontinuous growth curve modeling was used to assess trajectories of psychosis spectrum symptoms before and after cannabis initiation. Control variables considered for this investigation were age, sex, internalizing and externalizing symptoms, socioeconomic status, parental mental health, and other substance use. Among the 11 858 participants at wave 1, the mean (SD) age was 9.5 (0.5) years; 6182 (52%) participants were male. Consistent with a shared vulnerability hypothesis, adolescents who used cannabis at any point during the study period reported a greater number of psychosis spectrum symptoms (B, 0.86; 95% CI, 0.68-1.04) and more distress (B, 1.17; 95% CI, 0.96-1.39) from psychosis spectrum symptoms relative to those who never used cannabis. Additionally, consistent with a self-medication hypothesis, the number of psychosis spectrum symptoms (B, 0.16; 95% CI, 0.12-0.20) and distress (B, 0.23; 95% CI, 0.21-0.26) from psychosis spectrum symptoms increased in the time leading up to cannabis initiation. We observed mixed evidence for an increase in psychosis symptoms after cannabis initiation (ie, contributing risk hypothesis). The findings underscore the importance of accounting for shared vulnerability and self-medication effects when modeling cannabis-psychosis risk associations.

Emergence of global value chains as key driver behind industrial development: evidence from participating African countries

Purpose The purpose of this paper is to examine the role of global value chains (GVC) in industrial development of emerging economies, with particular focus on participating African countries. The findings of this study are expected to provide insight on the need for more developing countries to participate in GVC. Design/methodology/approach This study is built upon the neoclassical and endogenous growth theories, which postulate that savings, physical capital and human capital are the fundamental drivers of development in productive sectors of the economy. The investigation, covering the period 1980–2021, is carried out by using the unrestricted error correction model and dynamic ordinary least squares model. Findings The results of this study reveal that GVC stands as the dominant factor driving industrial development, compared to savings, physical capital and human capital. The findings, therefore, seem to contradict the postulation of conventional theories. The policy implications of the findings are not far-fetched. First, industrial development in the participating African countries has benefited largely from GVC; hence, it is necessary to encourage more participation. Second, industrial development also benefited from the control variables (savings, physical capital and human capital), hence the need to sustain their complementary role. Thirdly, only three African countries are actively participating in GVC, which suggests that more countries need to join, to facilitate industrial development. Originality/value Previous studies have not given adequate attention to African countries that participate in GVC, thus creating a void that needs to be filled. This study, therefore, produced results that are relevant to policy-making on industrial development in African countries.

Effect of a Sensorimotor Training Program for Aerial Maneuvers in Junior Surfers

The purpose of this study was to examine the impact of a sensorimotor training program on maximum ankle dorsiflexion (ankle DF), coordination, dynamic balance and postural control, and lower-limb muscle power, in competitive junior surfers, and its relation to parameters of sensorimotor control required to perform aerial maneuvers. Twelve junior competitive surfers followed a 7-week sensorimotor training program, being assessed pre- and post-program with the knee-to-wall test (KW), Y-Balance test—lower quarter (YBT-LQ), and the countermovement jump test (CMJ). Post-training assessment revealed positive effects on the KW (ankle DF) distance, which increased approximately 2 cm (p &lt; 0.001) for both ankles, and all scores for the YTB-LQ (coordination, dynamic balance, and postural control) variables increased, being significant (p &lt; 0.005) for some reach distances (YBT-LQ—Anterior Left, YBT-LQ—Postero-medial Left, and YTB-LQ Anterior Right). YBT-LQ Anterior Reach Asymmetry also improved by decreasing 1.62 cm (p &lt; 0.001) and the CMJ height (lower limb muscle power) increased 2.89 cm (p &lt; 0.001). The training program proved to effectively enhance parameters of physical performance for this sample, including ankle DF, coordination, dynamic balance, postural control, and lower limb muscle power. This tailored-made task approach can help to optimize surfing performance capabilities and contribute to reducing the risk of injuries while performing aerials.

Perceived social support and symptoms of depression and anxiety in emerging adulthood: A Swedish prospective cohort study.

The transition from adolescence to young adulthood, often referred to as 'emerging adulthood', is a challenging period in life, and mental health problems are common. Although a large number of studies have shown that social support is linked with fewer mental health problems, few longitudinal studies have examined these associations during this life phase. The aim of the current study was to examine the associations between perceived social support from different sources - family, friends and significant other - at age 17-18 and symptoms of depression and anxiety at age 20-21. Data were obtained from the cohort study Futura01 based on a Swedish national sample of adolescents attending grade 9 in 2016/2017. We used survey information from 2019 (age 17-18) and 2022 (age 20-21) and linked registry information (N=2722). Symptoms of depression and anxiety were measured by the Patient Health Questionnaire-4 (PHQ-4) at age 20-21. Perceived social support was measured by the Multidimensional Scale of Perceived Social Support (MSPSS) at age 17-18. Control variables included sociodemographic characteristics and indicators of mental health problems at age 17-18. Binary logistic regressions were performed. When mutually adjusting for all sources of perceived social support, family support at age 17-18 had inverse associations with symptoms of both depression and anxiety at age 20-21. Perceived support from friends was associated with subsequent symptoms of anxiety only. Perceived social support can be a protective factor against mental health problems in emerging adulthood. The family serves a particularly important source of social support.

Study on the Impact of Entrepreneurship on Enterprise Performance in the Manufacturing Industry

Purpose: The study aims to explore the impact of entrepreneurship on the performance of manufacturing enterprises in China, focusing on specific traits of entrepreneurship such as innovation, risk-taking, and competitiveness. Additionally, it examines the relationship between entrepreneurship and regional economic growth, with an emphasis on how entrepreneurship drives enterprise performance, particularly in economically underdeveloped regions. Approach/Methodology/Design: The research uses empirical analysis based on sample data from listed manufacturing companies on China’s Shanghai and Shenzhen A-share markets. It employs regression models to assess the impact of entrepreneurship on enterprise performance. Indicators such as R&amp;D investment, market share, and firm size serve as proxies for entrepreneurship traits, while principal component analysis is used to calculate scores for both entrepreneurship and enterprise performance. Control variables include regional economy and leadership structure. Sub-regional analysis is conducted to compare the impact of entrepreneurship across different economic regions. Findings: The results show that entrepreneurship, innovation spirit, risk-taking spirit, and competitive spirit all have significant positive impacts on enterprise performance. Additionally, in different economic regions, entrepreneurship generally has a positive impact on enterprise performance, with a greater effect observed in areas with lower economic development. Practical Implications: The study provides valuable insights for enterprises and policymakers. It suggests that enterprises can enhance their competitiveness by fostering entrepreneurial traits, increasing R&amp;D investment, and efficiently managing financial leverage. Furthermore, governments should support entrepreneurship in underdeveloped regions through training and policy measures to stimulate regional economic growth. Originality/value: This study constructs a unique evaluation system for entrepreneurship from a micro perspective and verifies its positive impact on enterprise performance. This study innovatively explores the differential impact of entrepreneurship across various economic regions, providing new perspectives for future research on the relationship between regional economies and entrepreneurship.

Democracy and Crime in Latin America

Abstract Do firm stances against crime, up to a level at which they disregard Human Rights, overflow the sphere of crime control and associate with a preference against democracy? This study determines whether victimization of crime encourages support for the death penalty, the desire to own a firearm, and broader authoritarian political attitudes. The hypothesis is tested in Latin America using the LAPOP (2018/2019) database in 17 countries. Three sets of indicators are observed in the logistic models: a) dependent variables (desire to own a firearm, support for the death penalty, perception of democracy as the best form of government, support for a coup in the case of high crime, satisfaction with democracy, and trust in institutions); b) independent variables (victimization by crime); and c) control variables (waiting time for police response, and sociodemographic factors). Although no significant effects were found on democracy as the best form of government, victimization increases the likelihood of wanting a firearm, favoring the death penalty, and supporting coups, while it reduces the satisfaction with democracy and trust in institutions. Therefore, the results confirm that crime not only favors public support for harsh measures to control it but also weakens democracy and its institutions.

Impact of natural resource rents on global trade dynamics in RCEP: Economic and geopolitical interdependencies

This research analyzes the impact of natural resource revenues on global economic trends in the RCEP countries, emphasizing the importance of resource exploitation in the financial development process. The work explores complex interdependencies between resource extraction, geopolitical risk, economic environment, and trade relationships. Energy efficiency, geopolitical risk, and GDP are the control variables. These findings highlight the importance of natural resource rents, GDP, geopolitical risk, and energy conservation on the trade structure of the RCEP trading partners. Quantile regression studies show the negative effect of oil revenues on world trade, thus providing evidence of the multifaceted link between natural resource earnings and trade outcomes. The findings underscore the significance of policymakers and businesses understanding these interrelated links and their implications for global trade relations. The report offers policy directions for RCEP countries to foster sustainable economic development and enhance export competitiveness. These recommendations aim to further the resource sector's growth, financial infrastructure, and managing geopolitical risks.

Vegetation Restoration Enhanced Canopy Interception and Soil Evaporation but Constrained Transpiration in Hekou–Longmen Section During 2000–2018

The quantitative assessment of the impact of vegetation restoration on evapotranspiration and its components is of great significance in developing sustainable ecological restoration strategies for water resources in a given region. In this study, we used the Priestley-Taylor Jet Pro-pulsion Laboratory (PT-JPL) to simulate the ET components in the Helong section (HLS) of the Yellow River basin. The effects of vegetation restoration on ET and its components, vegetation transpiration (Et), soil evaporation (Es), and canopy interception evaporation (Ei) were separated by manipulating model variables. Our findings are as follows: (1) The simulation results are compared with the ET calculated by water balance and the annual average ET of MODIS products. The R2 of the validation results are 0.61 and 0.78, respectively. The results show that the PT-JPL model tracks the change in ET in the HLS well. During 2000–2018, the ET, Ei, and Es increased at a rate of 1.33, 0.87, and 2.99 mm/a, respectively, while the Et decreased at a rate of 2.52 mm/a. (2) Vegetation restoration increased the annual ET in the region from 331.26 mm (vegetation-unchanged scenario) to 338.85 mm (vegetation change scenario) during the study period, an increase of 2.3%. (3) TMP (temperature) and VPD (vapor pressure deficit) were the dominant factors affecting ET changes in most areas of the HLS. In more than 37.2% of the HLS, TMP dominated the change affecting ET, and vapor pressure difference (VPD) dominated the area affecting ET in 30.5% of the HLS. Overall, the precipitation (PRE) and VPD were the main factors affecting ET changes. Compared with previous studies that directly explore the relationship between many influencing factors and ET results through correlation research methods, our study uses control variables to obtain results under two different scenarios and then performs difference analysis. This method can reduce the excessive interference of influencing factors other than vegetation changes on the research results. Our findings can provide strategic support for future water resource management and sustainable vegetation restoration in the HLS region.

The effect of crop insurance on the financial risk of smallholder rice farmers in Cameroon

This study examined the effect of crop insurance on the financial risk of smallholder rice farmers in the grass field of Cameroon. Panel data from 76 Smallholder rice farming groups from 2019-2022 was used, while the Panel-corrected standard error technique was used for estimation. The results revealed that crop insurance captured using inputs (fertilizers, herbicides, and treated seeds) and land preparation had a positive and statistically significant effect on financial risk. These results validate the risk balancing hypothesis for smallholder rice farmers. Control variables like Farm size and labour had a positive and statistically significant effect, while training cost and buying price had a negative and statistically significant effect on financial risk. The results therefore, indicate that smallholder rice farmers need to adopt crop insurance practices such as use of quality farm inputs and better land preparation techniques in order to manage financial risk.

Unwrapping the Intricate Interplay Between Energy Dependency and Macroeconomic Volatility in OECD Countries

While research has explored the connection between oil prices and macroeconomic performance, there is limited understanding of the interaction between overseas energy imports dependency and macroeconomic fluctuations. This work addresses the foregoing study using the augmented mean group (AMG) econometrics technique on panel data of 29 OECD net energy‐importing countries from 2001 to 2021. The long‐run finding unearthed that energy dependency intensifies macroeconomic instability, confirming that relying on overseas energy imports will hamper the smooth functioning of domestic economic machinery in the form of energy supply interruption. Besides energy dependency, this study uses government consumption spending, regulatory quality, and globalisation as control variables in macroeconomic instability function. The long‐run outcomes further depict that government consumption spending and globalisation aggravate macroeconomic instability while regulatory quality reduces it. These findings are further checked by applying the pooled mean group‐autoregressive distributed lag (PMG‐ARDL) method. In conclusion, this study provides policy implications to prioritise domestically produced energy use and diversify energy sources by increasing the share of clean energy in the total energy mix.

Analysis of heating performance of transverse magnetic inductor at different operating frequencies

Abstract Traditional induction heating technology has problems such as uneven temperature distribution and the need to improve heating efficiency and accuracy. Horizontal magnetic flux induction heating technology is a new type of induction heating technology with the advantages of energy efficiency, environmental friendliness, and suitability for local workpiece heating. It is widely used in metallurgy, mechanical manufacturing, light chemical industry, and other fields, holding important economic value. This article studies the heating performance of transverse magnetic inductors at different operating frequencies, simplifies the heating process calculation using finite element analysis, selects stainless steel 405 as the heating material, and sets commonly used parameters such as conductivity and magnetic permeability as fixed values, with frequency as the control variable. Using SolidWorks software to establish a model and COMSOL Multiphysics for simulation, simulated three frequencies: 500Hz, 1kHz, and 5kHz. Analyzed the section temperature, current density distribution, and heating efficiency.

Grain Size Prediction in SCR420HB Hot Forging: Combining Phenomenological and JMAK Models with Experimental and Numerical Analysis

This study presents the enhancement of a phenomenological model for predicting grain size evolution during the hot deformation of SCR420HB bearing steel. The model now incorporates strain rate and temperature as controllable variables, thereby improving prediction accuracy for various combinations of these factors. Material’s microstructural constants, including initial grain size exponent, strain exponent, strain rate exponent, and dynamic recrystallization activation energy, were determined through FEM-coupled optimization techniques. Accurate flow stress data, crucial for determining the onset of dynamic recrystallization, was integrated to enhance the model's precision. The accuracy of the optimized model was validated by comparing predicted and experimental grain sizes across different stages of the hot forging process, demonstrating improved model performance. Additionally, the study provides insights into the sensitivity of the grain size to different deformation conditions, offering valuable guidance for industrial forging applications. This comprehensive approach ensures the model's robustness and practical applicability in real-world scenarios.

Velocity prediction program for windsurfing: A hierarchical approach integrating biomechanical insights

Windsurfing sails have three degrees of controllable angular freedoms and rely heavily on the sailor’s gravity to balance the heeling moments. The position of the sailor’s centre of gravity that affect the moment generation is greatly influenced by the posture. These factors result in the complexity of predicting windsurfing velocity during steady sailing, which is shown to be an under-defined problem. To address the challenges, this study proposes a hierarchical approach. At the lower levels of the hierarchy, a mechanical model of windsurfing is constructed by incorporating a tailor-made biomechanical model of the sailor, as well as the aero- and hydrodynamic properties of the sail, board, and sailor. The mechanical model allows the investigation of control variables that lead to different steady states, including sail roll, yaw and hydrofoil roll. At a higher level, these variables are optimized to maximize sailing speed. The proposed approach provides intermediate results that explore factors affecting sailing velocity, such as sail and board orientation angles, the sailor’s center of gravity, and wind conditions. Furthermore, the approach generates a velocity polar chart that illustrates the maximum sailing speed for different travel directions. The chart indicates the maximum VMG and optimal sailing angle for achieving an upwind or downwind mark. This study contributes to a deeper understanding of the critical variables influencing windsurfing velocity and provide insights for improving sailing performance.

Numerical Treatment for the Distributed Order Fractional Optimal Control Coronavirus (2019-nCov) Mathematical Model

In this paper, we presented the distributed order fractional optimal control of the Coronavirus (2019-nCov) mathematical model. The distributed order fractional operator is defined in the Caputo sense. Control variables are considered to reduce the transmission of infection to healthy people. The discretization of the composite Simpson's rule and Grünwald-Letnikov nonstandard finite difference method is constructed to solve the obtained optimality system numerically. The stability analysis of the proposed method is studied. Numerical examples and comparative studies for testing the applicability of the utilized method and to show the simplicity of this approximation approach are presented. Moreover, by using the proposed method we can conclude that the model given in this paper describes well the confirmed real data given in Spain and Wuhan.

몽골인의 사회계층이 관광 목적지 숙식 및 체험활동 선택에 미치는 영향 : 홉스골 국립공원 지역 관광자를 대상으로 한 이항 로지스틱 회귀분석

Looking at Mongolian tourists to the Khuvsgul National Park area, this study examines the impacts of tourists’ social stratification on their accommodation, dining, and experiential activity choices. The survey was conducted both online and offline at five different accommodations in the Khuvsgul National Park area between January 2024 and March 2024, and 288 valid questionnaires were used for the binary logistic regression analysis. The results showed that tourists’ occupation, average monthly household income, and subjective social class significantly influenced their choice of either luxury (e.g., hotels and resorts) or inexpensive accommodation (e.g., traditional Mongolian ger camps). Specifically, office workers were about 4.24 times more likely to stay in hotels or resorts than unskilled laborers, and the probability of staying at a hotel or resort increased by 1.45 times with each increment in subjective social stratification. In regard to tourists' dining choices (i.e., eating at hotel or resort restaurants vs. bringing their own food or eating at regular restaurants), average monthly household income and subjective social class had significant effects. However, education level influenced neither accommodation nor dining choices. Finally, tourists’ choices of some experiential activities (e.g., Tsaatan experience and Sukhbaatar ship travels) were influenced by their occupation and other control variables such as gender and age. The study findings and their implications were further discussed at the conclusion of this article.