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This study aims to evaluate how the criteria of sustainability standards (SS) ensure the social dimension of corporate sustainability (CS) in rural entrepreneurships using the case of banana agribusinesses in Magdalena (Colombia).

The methodological design was quantitative, explanatory and cross-sectional, where a sample of banana producers from Magdalena (Colombia) was selected. A structural equation model (SEM) was developed to evaluate the hypotheses. The SEM goodness-of-fit and fit indices were all acceptable.

There is a strong and statistically significant correlation between SS criteria and the social dimension of CS. In particular, local development is the most influential factor in shaping CS in the context of banana agribusinesses in Magdalena, Colombia, operating as rural entrepreneurship. Meanwhile, working conditions and human rights show moderate effects, while labor rights do not have a perceptible impact.

Only the SS criteria that ensure the social dimension of CS in the banana agribusinesses of Magdalena (Colombia) were considered. It is important to note that other variables may be involved in ensuring CS. Future research to identify these possible variables is recommended.

This investigation explores an understudied issue within the CS sphere, explicitly focusing on rural entrepreneurship in developing countries, notably Colombia. The study scrutinizes the impact of SS on the social dimension of CS in rural environments, using banana cooperatives as a case study and highlighting the value of developing strategies to help improve the CS performance of this type of organization.

El objetivo de esta investigación es evaluar cómo los criterios de los Estándares de Sostenibilidad (SS) aseguran la dimensión social de la Sostenibilidad Corporativa (CS) en los emprendimientos rurales utilizando el caso de los agronegocios bananeros en Magdalena (Colombia).

El diseño metodológico fue cuantitativo, explicativo y transversal, donde se seleccionó una muestra de productores bananeros del Magdalena (Colombia). Se desarrolló un modelo de ecuaciones estructurales (SEM) para evaluar las hipótesis. Los índices de bondad de ajuste y ajuste del SEM fueron aceptables.

existe una correlación fuerte y estadísticamente significativa entre los criterios de SS y la dimensión social de la SC. En particular, el desarrollo local aparece como el factor más influyente en la conformación de la SC en el contexto de las agroempresas bananeras de Magdalena, Colombia, que operan como empresas rurales. Mientras tanto, las condiciones de trabajo y los derechos humanos muestran efectos moderados, mientras que los derechos laborales no parecen tener un impacto perceptible.

sólo se consideraron los criterios de SS que aseguran la dimensión social de la SC en los agronegocios bananeros de Magdalena (Colombia). Es importante señalar que otras variables pueden estar involucradas en el aseguramiento de la CS. Se recomiendan futuras investigaciones para identificar estas posibles variables.

Esta investigación explora un tema poco estudiado dentro de la esfera de la Sostenibilidad Corporativa (SC), centrándose explícitamente en el empresariado rural en los países en desarrollo, en particular Colombia. El estudio analiza el impacto de los Estándares de Sostenibilidad (SS) en la dimensión social de la SC en entornos rurales, utilizando las cooperativas bananeras como caso de estudio y resaltando el valor de desarrollar estrategias que ayuden a mejorar el desempeño en SC de este tipo de organizaciones.

O objetivo desta pesquisa é avaliar como os critérios dos Padrões de Sustentabilidade (SS) garantem a dimensão social da Sustentabilidade Corporativa (SC) em empreendimentos rurais usando o caso das agroindústrias de banana em Magdalena (Colômbia).

O desenho metodológico foi quantitativo, explicativo e transversal, onde foi selecionada uma amostra de produtores de banana de Magdalena (Colômbia). Foi desenvolvido um modelo de equação estrutural (SEM) para avaliar as hipóteses. Os índices de adequação e de ajuste do SEM foram todos aceitáveis.

existe uma correlação forte e estatisticamente significativa entre os critérios de SS e a dimensão social da SC. Em particular, o desenvolvimento local aparece como o fator mais influente na formação da SC no contexto dos agronegócios da banana em Magdalena, Colômbia, que operam como empresas rurais. Entretanto, as condições de trabalho e os direitos humanos apresentam efeitos moderados, enquanto os direitos laborais não parecem ter um impacto percetível.

apenas foram considerados os critérios de SS que garantem a dimensão social da SC nas agroindústrias da banana de Magdalena (Colômbia). É importante notar que outras variáveis podem estar envolvidas na garantia da SC. Recomenda-se a realização de investigação futura para identificar estas possíveis variáveis.

Esta investigação explora uma questão pouco estudada no âmbito da Sustentabilidade Empresarial (SC), focando explicitamente o empreendedorismo rural nos países em desenvolvimento, nomeadamente na Colômbia. O estudo examina o impacto dos Padrões de Sustentabilidade (SS) na dimensão social da SC em ambientes rurais, utilizando cooperativas de banana como estudo de caso e destacando o valor do desenvolvimento de estratégias para ajudar a melhorar o desempenho da SC deste tipo de organização.

The purpose of this paper aims to investigate the adaptive impedance control and its optimized PSO algorithm for force tracking of a dual-arm cooperative robot. Because the dual-arm robot is directly in contact with external environment, controlling the mutual force between robot and external environment is of great importance. Besides, a high compliance of the robot should be guaranteed.

An impedance control based on Particle Swarm Optimization (PSO) algorithm is designed to track the mutual force and achieve compliance control of the robot end.

The experimental results show that the impedance control coefficients can be automatically tuned converged by PSO algorithm.

The system can reach a steady state within 0.03 s with overshoot convergence, and the force fluctuation range at the steady state decreases to about ±0.08 N even under the force mutation condition.

The swivel construction method is a specially designed process used to build bridges that cross rivers, valleys, railroads and other obstacles. To carry out this construction method safely, real-time monitoring of the bridge rotation process is required to ensure a smooth swivel operation without collisions. However, the traditional means of monitoring using Electronic Total Station tools cannot realize real-time monitoring, and monitoring using motion sensors or GPS is cumbersome to use.

This study proposes a monitoring method based on a series of computer vision (CV) technologies, which can monitor the rotation angle, velocity and inclination angle of the swivel construction in real-time. First, three proposed CV algorithms was developed in a laboratory environment. The experimental tests were carried out on a bridge scale model to select the outperformed algorithms for rotation, velocity and inclination monitor, respectively, as the final monitoring method in proposed method. Then, the selected method was implemented to monitor an actual bridge during its swivel construction to verify the applicability.

In the laboratory study, the monitoring data measured with the selected monitoring algorithms was compared with those measured by an Electronic Total Station and the errors in terms of rotation angle, velocity and inclination angle, were 0.040%, 0.040%, and −0.454%, respectively, thus validating the accuracy of the proposed method. In the pilot actual application, the method was shown to be feasible in a real construction application.

In a well-controlled laboratory the optimal algorithms for bridge swivel construction are identified and in an actual project the proposed method is verified. The proposed CV method is complementary to the use of Electronic Total Station tools, motion sensors, and GPS for safety monitoring of swivel construction of bridges. It also contributes to being a possible approach without data-driven model training. Its principal advantages are that it both provides real-time monitoring and is easy to deploy in real construction applications.

Construction enterprises are achieving the goal of production safety by increasingly focusing on the critical factor of “human” and the impact of individual characteristics on safety performance. Emotional intelligence is categorized into three models: skill-based, trait-based and emotional learning systems. However, the mechanism of action and the internal relationship between emotional intelligence and safety performance must be further studied. This study intends to examine the internal mechanism of emotional intelligence on safety performance in construction projects, which would contribute to the safety management of construction enterprises.

A structural equation model exploring the relationship between emotional intelligence and safety performance is developed, with political skill introduced as an independent dimension, situational awareness presented as a mediator, and management safety commitment introduced as a moderator. Data were collected by a random questionnaire and analyzed by SPSS 24.0 and AMOS 26.0. The structural equation model tested the mediation hypothesis, and the PROCESS macro program tested the moderated mediation hypothesis.

The results showed that construction workers' emotional intelligence directly correlates with safety performance, and situational awareness plays a mediating role in the relationship between emotional intelligence and the safety performance of construction workers. Management safety commitment weakens the positive predictive relationships between emotional intelligence and situational awareness and between emotional intelligence and safety performance.

This research reveals a possible impact of emotional intelligence on safety performance. Adding political skills to the skill-based model of emotional intelligence received a test pass. Political skill measures the sincere and cooperative skills of construction workers. Using people as a critical element plays a role in the benign mechanism of “Emotional Intelligence – Situational Awareness – Safety Performance.” Improving emotional intelligence skills through training, enhancing situational awareness, understanding, anticipation and coordination and activating management environment factors can improve safety performance. Construction enterprises should evaluate and train workers' emotional intelligence to improve workers' situational awareness and safety performance.

Today’s world is struggling with the hardship of climate change that has drastically disturbed human life, wildlife and the earth’s biological system. This study aims to show how implementing climate change mitigation strategies and environmental protection measures can ensure sustainable development through collaborative efforts between governmental authorities and the nation’s populace.

An extensive literature review of studies is conducted from across the world concentrating on holistic, sustainable development, enabling a showcase of various conferences, action plans initiated and resolutions passed. VOSviewer software is used to quantify the results of bibliometric analysis and cluster analysis. A total of 260 research studies released between 1993 and 2022 on the Scopus platform are quantified in terms of topmost publications, collaborations among authors, citations index and year-wise publication. The search string has keywords including “climate change,” “sustainable development” and “environment protection.”

The study results revealed a steep increase in research publications in the last three years, from 2017 to 2021, which serves as the basis of the emergence of high-impact articles. The most cited document in this context throws light on assessing vulnerability to climatic risk and building adaptive capacity. It also draws attention to voluntary carbon markets’ rationale while condemning emission trading systems for climate change due to structural flaws, negative consequences and questionable emission-cutting effectiveness. Low energy demand, zero energy buildings and shared socioeconomic pathways should be implemented as strategies for sustainable development.

This study provides a significant opportunity to construct a valuable addition to mitigate climate change. Also, it shows a positive and significant correlation between mitigation and adaptation policies by analyzing publication efforts worldwide considering local climate risks and national adaptation mandates.

The originality of this study lies in its comprehensive approach, combining literature review, bibliometric analysis and cluster analysis to provide insights into current research trends, challenges and potential strategies for addressing climate change and promoting sustainable development. The study’s emphasis on the correlation between mitigation and adaptation policies adds practical significance to its findings.

This study analyzes the impact of COVID-19 on agricultural production in South India by evaluating the influence of market channels and socioeconomic conditions on the production decisions of farmers during two key cropping seasons. We base our analysis on primary data from 200 marginal, small and medium farmers, primarily focusing on the key seasonal crops, namely paddy and black gram.

We studied the downstream supply chains of paddy and black gram crops in the district of Villupuram, situated in the South Indian state of Tamil Nadu. Using a Bi-Probit model, we analyzed the production decisions of marginal, small and medium farmers engaged in paddy and black gram cultivation. Various factors are considered, including farmers’ socioeconomic characteristics, gender, market channels accessed and the coping strategies employed.

After the easing of lockdown measures in June 2020, our research revealed substantial disruptions in agricultural production during the critical Kharif and Rabi seasons. Most farmers refrained from returning to their fields during the Kharif season; those who did produced millet as the main crop. Factors such as choice of market channels in previous seasons, economic status, access to all-weather roads, labor availability, gender and coping strategies played an important role in the return to production in the subsequent Kharif and Rabi seasons.

Our data revealed several interesting threads related to price volatility, irrigation and access to markets and their impact on food security. The role of intermediaries and market channels in providing liquidity emerges as an important aspect of farmers' choice of markets. The pandemic impacted all these factors, but a detailed analysis was beyond the scope of this study.

We also find that resilience to economic shocks varies not only by economic status but also by gender and social groups. Farmers with female members are more likely to be resilient, and marginal and small farmers primarily belong to social groups that are economically less developed.

This study contributes to the literature on factors influencing farmer choice and decision-making and provides nuances to discussions by analyzing crop-specific supply chains, highlighting the critical role of socioeconomic factors. It also highlights the role of demographics and infrastructural factors like access to all-weather roads and access to markets that influence farmers’ production decisions.

Forecasting population movement trends is crucial for implementing effective policies to regulate labor force growth and understand demographic changes. Combining migration theory expertise and neural network technology can bring a fresh perspective to international migration forecasting research.

This study proposes a conditional generative adversarial neural network model incorporating the migration knowledge – conditional generative adversarial network (MK-CGAN). By using the migration knowledge to design the parameters, MK-CGAN can effectively address the limited data problem, thereby enhancing the accuracy of migration forecasts.

The model was tested by forecasting migration flows between different countries and had good generalizability and validity. The results are robust as the proposed solutions can achieve lesser mean absolute error, mean squared error, root mean square error, mean absolute percentage error and R² values, reaching 0.9855 compared to long short-term memory (LSTM), gated recurrent unit, generative adversarial network (GAN) and the traditional gravity model.

This study is significant because it demonstrates a highly effective technique for predicting international migration using conditional GANs. By incorporating migration knowledge into our models, we can achieve prediction accuracy, gaining valuable insights into the differences between various model characteristics. We used SHapley Additive exPlanations to enhance our understanding of these differences and provide clear and concise explanations for our model predictions. The results demonstrated the theoretical significance and practical value of the MK-CGAN model in predicting international migration.

Financial mathematics is one of the most rapidly evolving fields in today’s banking and cooperative industries. In the current study, a new fractional differentiation operator with a nonsingular kernel based on the Robotnov fractional exponential function (RFEF) is considered for the Black–Scholes model, which is the most important model in finance. For simulations, homotopy perturbation and the Laplace transform are used and the obtained solutions are expressed in terms of the generalized Mittag-Leffler function (MLF).

The homotopy perturbation method (HPM) with the help of the Laplace transform is presented here to check the behaviours of the solutions of the Black–Scholes model. HPM is well known for its accuracy and simplicity.

In this attempt, the exact solutions to a famous financial market problem, namely, the BS option pricing model, are obtained using homotopy perturbation and the LT method, where the fractional derivative is taken in a new YAC sense. We obtained solutions for each financial market problem in terms of the generalized Mittag-Leffler function.

The Black–Scholes model is presented using a new kind of operator, the Yang-Abdel-Aty-Cattani (YAC) operator. That is a new concept. The revised model is solved using a well-known semi-analytic technique, the homotopy perturbation method (HPM), with the help of the Laplace transform. Also, the obtained solutions are compared with the exact solutions to prove the effectiveness of the proposed work. The different characteristics of the solutions are investigated for different values of fractional-order derivatives.

This study aims to investigate the landscape of family-based organic farm businesses in the Kashmir Valley, India, analyzing the factors that either facilitate or hinder their adoption. The research also intends to uncover sources of information seeking. The primary purpose is to provide qualitative evidence to address existing knowledge gaps and offer insights for promoting sustainable farm practices in the region.

The research employs a qualitative approach, drawing on focus group interviews. The study thoroughly explores the background and relevant literature, utilizing a comprehensive research framework. Data is collected from family based farmers engaged in organic farming practices in the Kashmir Valley. The data is analyzed using content analysis ensuring a robust and thorough exploration of the subject matter.

This study reveals a notable transition in the agricultural landscape of the Kashmir Valley, showcasing a widespread adoption of organic farming on considerable land. The study reveals that key facilitators for organic farming among family-based farms are farm productivity, entrepreneurial intention, governance, environmental consciousness, and health concerns. The exchange of information, both through formal and informal channels, is found to be a crucial factor influencing the adoption of organic farming. The study also unveiled significant inhibitors that hinder the adoption of organic farming on commercial scales, including on-farm challenges such as difficulties in acquiring inputs and facing reduced yields, market-related concerns, and a lack of support and assistance from government agencies.

This research contributes significantly to the existing literature by advancing the understanding of organic farm business and agri-entrepreneurship. It unveils key factors that either support or hinder family-based organic farms, identifying crucial information sources and presenting valuable insights for policymakers. Furthermore, this study provides practical guidance for overcoming obstacles, enhancing infrastructure, and translating identified facilitators into successful agri-ventures in the Kashmir region.

The primary objective of the current study is to unveil this relatively new phenomenon in the context of travel and tourism. In line with this purpose, the study provides a comprehensive overview of the concept of digital nomadism through a tourism perspective, discusses the relationship between digital nomadism, travel and tourism, examines the opportunities and threats of digital nomadism, and finally uncovers its transformative impact.

This conceptual study examined secondary data, i.e. existing literature. In this data, the focus has been on the tourism aspect of the digital nomad phenomenon.

The results suggest that digital nomadism introduces a novel perspective on the nature of travel and tourism mobility, along with a distinct tourist typology characterized by unique traits. Moreover, the results indicate that, while digital nomadism contributes to the local economy and cultural change on the one hand, it poses challenges in terms of regulations and taxation on the other. In this context, one can conclude that legislators should establish regulations for the employment of digital nomads, while managers should engage in activities that attract potential digital nomads on an international scale.

The study comprehensively reviews relevant literature in various ways, conducts a conceptualization of digital nomad tourists and makes a noteworthy theoretical contribution within the context of tourism. It addresses the gaps in the existing literature, particularly in specific contexts such as the legal status of digital nomads, taxation, prevention of gentrification, cultural exchanges, identity transformation and the impact on travel and tourism.