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This study aims to examine the technical efficiency of the chemical-free farming system in India using a hybrid combination of data envelopment analysis (DEA) and machine learning (ML) approaches.

The study used a two-stage approach. In the first stage, the efficiency scores of decision-making units’ efficiency (DMUs) are obtained using an input-oriented DEA model under the assumption of a variable return to scale. Based on these scores, the DMUs are classified into efficient and inefficient categories. The 2nd stage of analysis involves the identification of the most important predictors of efficiency using a random forest model and a generalized logistic regression model.

The results show that by using their resources efficiently, growers can reduce their inputs by 34 percent without affecting the output. Orchard's size, the proportion of land, grower's age, orchard's age and family labor are the most important determinants of efficiency. Besides, growers' main occupation and footfall of intermediaries at the farm gate also demonstrate significant influence on efficiency.

The study used only one output and a limited set of input variables. Incorporating additional variables or dimensions like fertility of the land, climatic conditions, altitude of the land, output quality (size/taste/appearance) and per acre profitability could yield more robust results. Although pineapple is cultivated in all eight northeastern states, the data for the study has been collected from only two states. The production and marketing practices followed by the growers in the remaining six northeastern states and other parts of the country might be different. As the growers do not maintain farm records, their data might suffer from selective retrieval bias.

Given the rising demand for organic food, improving the efficiency of chemical-free growers will be a win-win situation for both growers and consumers. The results will aid policymakers in bringing necessary interventions to make chemical-free farming more remunerative for the growers. The business managers can act as a bridge to connect these remote growers with the market by sharing customer feedback and global best practices.

Although many developments have happened to the DEA technique, the present study used a traditional form of DEA. Therefore, future research should combine ML techniques with more advanced versions like bootstrap and fuzzy DEA. Upcoming research should include more input and output variables to predict the efficiency of the chemical-free farming system. For instance, environmental variables, like climatic conditions, degree of competition, government support and consumers' attitude towards chemical-free food, can be examined along with farm and grower-specific variables. Future studies should also incorporate chemical-free growers from a wider geographic area. Lastly, future studies can also undertake a longitudinal estimation of efficiency and its determinants for the chemical-free farming system.

No prior study has used a hybrid framework to examine the performance of a chemical-free farming system.

Brazil’s regional inequality is an important topic due to the large and persistent differences in development between states and the high levels of inequality in the country. These variations in development can potentially render survey data inaccurate since the significance of capital income varies across the states. Besides, previous studies incorporating tax and national accounts data globally have mainly focused on measuring the income distribution at the country-level. This approach can limit the understanding of inequality, especially when considering large countries such as Brazil.

The methodology used to construct these estimates follows the guidelines of the Distributional National Accounts, whose core goal is to provide income distribution measures consistent with macroeconomic aggregates and harmonized across countries and time. The procedure has three main steps: first, it corrects the survey’s underrepresentation of top incomes using tax data. Then, it accounts for national income items not included in the survey or tax data, such as imputed rents and undistributed profits. Finally, it ensures that all components match the national income.

Compared to survey-based estimations, the results reveal a new angle on the state-level inequality. This study indicates that Amazonas, Rio de Janeiro and São Paulo have a more concentrated income distribution. The top 1\% of earners in these states receives around 28\% of total pre-tax income, while the top 10\% receive nearly 60\%. On the other end, Amapá (AP), Acre (AC), Rondônia (RO) and Santa Catarina (SC) are the states where the income distribution is less concentrated. There were no significant changes in the income distribution across the states during the period analyzed.

This study combines survey, tax and national accounts data to construct new estimates of Brazil’s state-level income distribution from 2006 to 2019. Previous results only considered income captured in surveys, which usually misses a significant part of capital incomes. This limitation may bias comparisons as capital income has different importance across the states. The new estimates represent the income of top groups more accurately, account for the entire national income and enable to compare regional inequality levels consistently with other countries.

The impacts of institutional quality on entrepreneurship are well established. However, the effects of an external factor, such as the shadow economy, that moderates this relationship have largely been neglected in existing literature. As such, this paper investigates how the shadow economy moderates the effects of institutional quality on entrepreneurship in a global sample of 79 economies from 2006 to 2018, when the latest required data are available.

This paper utilizes the fixed-effect and generalized method of moments (GMM) estimation techniques. Various scenarios have been considered for the robustness of the analysis, including different estimation techniques, different estimates of the shadow economy and various subsamples of countries with different income levels.

Empirical findings indicate that improved institutional quality boosts entrepreneurship activities, while the extended shadow economy is associated with reduced entrepreneurship activities. Interestingly, the positive impacts of institutional quality on entrepreneurship will be lessened with a larger shadow economy. These findings have remained largely unchanged across samples of countries and different proxies and estimation techniques.

Findings from this paper offer policymakers the relationships between institutional quality, shadow economy and entrepreneurship and the moderating effects of shadow economy on the institutional quality–entrepreneurship nexus. The implication is that institutional quality should be strengthened while the shadow economy should be controlled to promote entrepreneurship initiatives.

To the best of the author's knowledge, this is the first empirical study to explore the moderating effects of the shadow economy on the institutional quality–entrepreneurship nexus.

This study motivated by humanistic care aims to identify hospitality frontline employees’ alienation in Taiwan during the COVID-19 pandemic, and based on the job demands-resources (JD-R) model, the mediating role of alienation between job characteristics and organizational citizenship behavior (OCB) is discussed.

The authors drew on the JD-R model to delineate the mechanisms by which job demands (including emotional dissonance and work–home conflict) and job resources (including job support, training and possibility for career development) affect OCB through employees’ alienation. This study adopted snowball sampling and purposive sampling to conduct a questionnaire survey aimed at Taiwanese hospitality frontline employees. A total of 373 valid questionnaires were retained, and structural equation model was used to test the research hypotheses.

The results revealed that job demands of emotional dissonance and work–family conflict positively affect alienation; job resources of job support, training and possibility for career development negatively affect alienation; alienation negatively affects OCB; and alienation mediates the relationship between job characteristics and OCB fully.

Considering that alienation plays a full mediating role between job characteristics and organizational outcomes, this study put forward specific suggestions on how to increase job resources and reduce job demands to weaken alienation and further improve organizational performance in management practices. And practical implications were provided to help hospitality human resource management deal with the issue of talents retention. In addition, “work authenticity” should be introduced as a mediator in the future research. “Work authenticity” reflects employees’ positive working life state and is the opposite of “alienation.” The effectiveness of employees’ positive and negative working life state in communicating job characteristics and organizational outcomes can be compared.

The specific alienation experience of hospitality frontline employees is defined. Moreover, by introducing the alienation theory, this study demonstrates the health impairment path of JD-R model and suggests that job characteristics affect OCB through the full mediation of alienation.

本研究以人文关怀为动机, 明确了COVID-19疫情期间台湾酒店一线员工的异化状态, 并基于工作需求-资源理论模型, 探讨了异化在工作特性与组织公民行为之间发挥的中介作用。

笔者运用工作需求-资源模型以阐释工作需求（包括情绪失调和工作-家庭冲突）和工作资源（包括工作支持、培训和职业发展潜能）透过员工的异化影响组织公民行为的机制。本研究采用滚雪球抽样和目的性抽样的抽样方式, 对台湾酒店一线员工开展问卷调查; 留存有效问卷373份, 并采用结构方程模型对研究假设进行检验。

本研究揭示了情绪失调和工作-家庭冲突的工作需求正向影响异化; 工作支持、培训和职业发展潜能的工作资源对异化产生负面影响; 异化对组织公民行为产生负面影响; 异化在工作特性与组织公民行为的关系中起完全中介作用。

综合异化在工作特性与组织成果之间起着完全的中介作用, 本研究就管理实践中如何增加工作资源和减少工作需求以减弱异化并进一步提高组织绩效提出了具体建议, 以此帮助酒店人力资源管理部门处理留住人才的问题。此外, 应引入反映员工积极工作状态的“工作真实性”（即“异化”的对立面）作为中介, 比较员工积极和消极工作状态在沟通工作特性和组织成果上的有效性。

本研究明确了酒店一线员工具体的异化体验。此外, 透过引入异化理论, 本研究实证了工作需求-资源模型的健康损害路径, 并揭示了工作特性通过异化的完全中介作用影响组织公民行为。

Este estudio motivado por la atención humanística identificó la alienación de los empleados de primera línea de la hostelería en Taiwán durante la pandemia de COVID-19 y, basándose en el modelo de exigencias laborales-recursos (JD-R), se analizó el papel mediador de la alienación entre las características laborales y el comportamiento de ciudadanía organizacional fue discutido.

Nos basamos en el modelo JD-R para delinear los mecanismos por los que las exigencias del puesto de trabajo (incluida la disonancia emocional y el conflicto entre el trabajo y el hogar) y los recursos del puesto de trabajo (incluido el apoyo laboral, la formación y la posibilidad de desarrollo profesional) afectan a la organización. Del comportamiento ciudadano (OCB) a través de la alienación de los empleados. Este estudio adoptó el muestreo de bola de nieve y el muestreo intencional para realizar una encuesta por cuestionario dirigida a los empleados de primera línea de la hostelería taiwanesa. Se obtuvieron 373 cuestionarios válidos y se utilizó un modelo de ecuaciones estructurales para probar las hipótesis de la investigación.

Los resultados revelaron que las demandas laborales de disonancia emocional y conflicto trabajo-familia afectan positivamente a la alienación; los recursos laborales de apoyo al trabajo, formación y posibilidad de desarrollo profesional afectan negativamente a la alienación; la alienación afecta negativamente al comportamiento de ciudadanía organizacional; la alienación media totalmente la relación entre las características laborales y el comportamiento de ciudadanía organizacional.

Teniendo en cuenta que la alienación desempeña un papel mediador total entre las características del puesto de trabajo y los resultados organizativos, este estudio presentó sugerencias específicas sobre cómo aumentar los recursos del puesto de trabajo y reducir las exigencias del mismo para debilitar la alienación y mejorar aún más el desempeño organizacional en las prácticas de gestión. Y se aportaron implicaciones prácticas para ayudar a abordar la cuestión de retención de talentos en la gestión de los recursos humanos en la hostelería. Además, la “autenticidad del trabajo” debería introducirse como mediador en la investigación futura. La “autenticidad laboral” refleja el estado de vida laboral positivo de los empleados y es lo contrario de la “alienación”. Se puede comparar la eficacia del estado de vida laboral positivo y negativo de los empleados en la comunicación de las características del trabajo y los resultados organizacionales.

Se define la experiencia específica de alienación de los empleados de primera línea de la hostelería. Además, mediante la introducción de la teoría de la alienación, este estudio demuestra la trayectoria de deterioro de la salud del modelo JD-R, y sugiere que las características del puesto de trabajo afectan al comportamiento de ciudadanía organizacional a través de la mediación total de la alienación.

The integration of digital technologies into education has brought about a profound transformation, fundamentally reshaping the learning landscape. The purpose of this study is to underscore the importance of investigating the factors influencing students’ engagement (SE) in this evolving digital era, particularly within formal digital learning environments. To address this need, the study is grounded in self-determination theory (SDT) and presents a comprehensive model comprising interconnected elements: digital competence (DC), smartphone use (SPU), perceived autonomy (PA), digital formal learning (DFL) and SE.

The research conducted an investigation within Saudi Arabian universities, collecting a robust data set of 392 cases. This data set underwent rigorous analysis to validate the proposed model. To untangle the intricate relationships within the framework, the study used partial least squares structural equation modelling. Given the distinct dimensions of the two constructs under study, the researcher used a disjoint two-stage approach to establish reflective-formative higher-order constructs (HOC).

The findings revealed that digital literacy and digital skills (DS) constitute the foundational constituents of DC. Simultaneously, the study identified facilitation, distraction and connectedness as integral components of SPU. Importantly, the study established that DC, SPU, PA and DFL significantly influence SE. Furthermore, the research illuminated the mediating roles played by SPU, PA and DFL in the complex relationship between DC and SE.

This study advances the literature by delineating the dynamic interplay between DC, SPU and SE in digital learning. It extends SDT within educational contexts, emphasizing the role of internal motivations and DS. Methodologically, it innovates through reflective-formative HOCs, deepening the analysis of complex educational constructs. Managerially, it guides institutions in enhancing DC and integrating smartphones effectively into learning, advocating for tailored strategies to foster engaging and autonomous digital learning environments, thereby enriching both theoretical understanding and practical application in education.

The purpose of this study is to examine the determinants of the level of indebtedness in the health sector in Portugal, taking into account the effects of the COVID-19 pandemic. At the same time, an attempt is made to understand whether the effect of a pandemic crisis is similar to that of a financial crisis.

To achieve this aim, two subperiods were analyzed: a global period between 2011 and 2020 that includes the pandemic crisis and the period between 2011 and 2014, designated as the financial assistance period by the “Troika” in Portugal. For a sample of 514 companies belonging to the NACE code: 86100 – activities of the health sector with hospitalization, the panel data methodology was applied, specifically, the generalized method of moments system proposed by Arellano and Bover (1995) and Blundell and Bond (1998).

The results of the study are in line with the Pecking-order explanatory theory, demonstrating that companies in this sector follow a financing hierarchy, preferentially resorting to internally generated funds and external debt. Additionally, the results reveal that the capital structure of companies has changed due to the COVID-19 pandemic. As for the period of financial assistance, there are no major differences in evidence when the total debt ratio is considered. The results suggest different impacts when it comes to a bear market period caused by a health crisis or a period of growing economic slowdowns.

As far as we know, this is the first study that analyses the debt levels in the context of the health sector in a country with a financial system based on the bank sector, using short- and long-term debt ratios, taking into account the particularities of two different moments considered to be bear market that may eventually be useful for comparison with other bear market moments in other macroeconomic environments.

El objetivo principal de este estudio es examinar los determinantes del nivel de endeudamiento en el sector de la salud en Portugal, teniendo en cuenta los efectos de la pandemia de COVID-19. Al mismo tiempo, se intenta comprender si el efecto de una crisis pandémica es similar al de una crisis financiera.

Para lograr este objetivo, se analizaron dos subperíodos: un período global entre 2011 y 2020 que incluye la crisis pandémica y el período entre 2011 y 2014, designado como el período de asistencia financiera por la “Troika” en Portugal. Para una muestra de 514 empresas pertenecientes al código NACE: 86100 – actividades del sector de la salud con hospitalización, se aplicó la metodología de datos de panel, específicamente, el método generalizado de momentos (GMM)-sistema propuesto por Arellano y Bover (1995) y Blundell y Bond (1998).

Los resultados del estudio están en línea con la teoría explicativa del “Pecking-order”, demostrando que las empresas en este sector siguen una jerarquía de financiamiento, recurriendo preferentemente a fondos generados internamente y deuda externa. Además, los resultados revelan que la estructura de capital de las empresas ha cambiado debido a la pandemia de COVID-19. En cuanto al período de asistencia financiera, no hay diferencias significativas en la evidencia cuando se considera la proporción total de deuda. Los resultados sugieren impactos diferentes cuando se trata de un período de mercado bajista causado por una crisis de salud o un período de crecimiento económico más lento.

Hasta donde sabemos, este es el primer estudio que analiza los niveles de deuda en el contexto del sector de la salud en un país con un sistema financiero basado en el sector bancario, utilizando ratios de deuda a corto y largo plazo, teniendo en cuenta las particularidades de dos momentos diferentes considerados como momentos de mercado bajista que eventualmente pueden ser útiles para comparar con otros momentos de mercado bajista en otros entornos macroeconómicos.

O principal objetivo deste estudo é examinar os determinantes do nível de endividamento no setor de saúde em Portugal, levando em consideração os efeitos da pandemia de COVID-19. Ao mesmo tempo, tenta-se compreender se o efeito de uma crise pandêmica é semelhante ao de uma crise financeira.

Para atingir esse objetivo, foram analisados dois subperíodos: um período global entre 2011 e 2020, que inclui a crise pandêmica, e o período entre 2011 e 2014, designado como o período de assistência financeira pela “Troika” em Portugal. Para uma amostra de 514 empresas pertencentes ao código NACE: 86100 – atividades do setor de saúde com hospitalização, foi aplicada a metodologia de dados em painel, especificamente o método generalizado de momentos (GMM)-sistema proposto por Arellano e Bover (1995) e Blundell e Bond (1998).

Os resultados do estudo estão de acordo com a teoria explicativa da ordem de preferência (“Pecking-order”), demonstrando que as empresas neste setor seguem uma hierarquia de financiamento, recorrendo preferencialmente a fundos gerados internamente e dívida externa. Além disso, os resultados revelam que a estrutura de capital das empresas mudou devido à pandemia de COVID-19. No que diz respeito ao período de assistência financeira, não há diferenças significativas na evidência quando se considera a proporção total de dívida. Os resultados sugerem impactos diferentes quando se trata de um período de mercado em baixa causado por uma crise de saúde ou um período de desaceleração econômica.

Até onde sabemos, este é o primeiro estudo que analisa os níveis de dívida no contexto do setor de saúde em um país com um sistema financeiro baseado no setor bancário, utilizando índices de dívida de curto e longo prazo, levando em consideração as particularidades de dois momentos diferentes considerados como momentos de mercado em baixa que eventualmente podem ser úteis para comparação com outros momentos de mercado em baixa em outros ambientes macroeconômicos.

The safety management of construction machines is of primary importance. Considering that traditional construction machine safety monitoring and evaluation methods cannot adapt to the complex construction environment, and the monitoring methods based on sensor equipment cost too much. This paper aims to introduce computer vision and deep learning technologies to propose the YOLOv5-FastPose (YFP) model to realize the pose estimation of construction machines by improving the AlphaPose human pose model.

This model introduced the object detection module YOLOv5m to improve the recognition accuracy for detecting construction machines. Meanwhile, to better capture the pose characteristics, the FastPose network optimized feature extraction was introduced into the Single-Machine Pose Estimation Module (SMPE) of AlphaPose. This study used Alberta Construction Image Dataset (ACID) and Construction Equipment Poses Dataset (CEPD) to establish the dataset of object detection and pose estimation of construction machines through data augmentation technology and Labelme image annotation software for training and testing the YFP model.

The experimental results show that the improved model YFP achieves an average normalization error (NE) of 12.94 × 10^–3, an average Percentage of Correct Keypoints (PCK) of 98.48% and an average Area Under the PCK Curve (AUC) of 37.50 × 10^–3. Compared with existing methods, this model has higher accuracy in the pose estimation of the construction machine.

This study extends and optimizes the human pose estimation model AlphaPose to make it suitable for construction machines, improving the performance of pose estimation for construction machines.

This study aims to examine the relationship between the environment and tourism flows, as well as the economic variables of the 32 states of Mexico for the period 1999–2019 based on data availability. The related literature studying tourism and environmental impacts is scarce at a national level, with most of them being local case studies. Some international studies find that if the relationship exists, it is weak or nonexistent, using CO₂ as a proxy in most cases.

The present study uses panel data and cointegration panel methodologies, while also using geographic information systems to observe the distribution of variables at a state level between tourism and environmental variables.

The findings of the study are as follows: state gross domestic product, the inertia of environmental variables (i.e. volume of water treatment and solid waste), occupied rooms (proxy variable for tourism activity) and average temperature have an impact on the contemporary evolution of environmental variables; national and international tourist variables have no impact on the environment; the panels are integrated in such a way that there is a long-term equilibrium between states and some environmental care variables; and no conclusive evidence is found regarding the impact of tourism activity on the considered environmental variables.

The main limitations and areas of opportunity of the work refer to the amount of data available over time and the precision of the measurement of the variables. The availability, temporality and frequency of the data are also limitations of the research. An example of this is the nonexistence of CO₂ emissions at the state level. Additionally, studying other countries and regions for which there are limitations of data and applied studies is also a challenge.

The results are important for economies (in growth) and societies whose economic growth depends on tourism flows and have done little to reverse the damage that tourism has on the environment.

The models can contribute to study the relation between tourism and environmental variables and could be extended to regions, states and provinces for decision-making on actions to be taken for the present and future.

The originality of the research is innovative for the region: Mexico, Central and Latin America. There are no works that have studied these problems with this methodology and these variables. In terms of originality, the classic models of panel data and cointegration of panel data are useful and easily replicable for others to use for different countries. The results are relevant because there is apparently no relationship between tourism and some environmental variables in the short run, but there exists a weak and strong long-run relation between some of them.

本研究采用面板数据和协整面板模型方法, 同时利用地理信息系统(gis)观察州一级层面旅游和环境方面的变量分布。

本研究根据数据可用性, 研究了墨西哥32个州1999–2019年期间环境与旅游流量及经济变量之间的关系。在国家层面上研究旅游与环境影响的相关文献很少, 而且大多是地方的个案研究。一些国际研究发现, 即使有这种关系, 大多数案例中使用二氧化碳作为替代变量, 这种关系也是很弱或不存在。

i)国家国内生产总值, 环境变量的惯性(即水处理量和固体废物量), 占用的房间(旅游活动的代理变量)和平均温度对环境变量的现有演化有影响。ii)国内和国际旅游变量对环境没有影响。iii)面板数据以这样一种方式集成, 即国家和一些环境变量之间存在一种长期平衡。iv)关于旅游活动对所考虑的环境变量的影响没有确凿的证据。

这项工作的主要局限和机会领域是指随着时间的推移可获得的数据量和变量测量的精度。数据的可用性、时效性和频率也是本研究的局限性。这方面的一个例子是在州一级不存在二氧化碳排放。此外, 由于数据和应用研究的局限, 研究其他国家和地区也是一个挑战。

研究结果对经济增长依赖旅游业流量的经济体和社会具有重要意义, 这些经济体和社会对扭转旅游业对环境的破坏方面做得还不够。

这些模型有助于研究旅游业与环境变量之间的关系, 并可推广到地区、州和省, 以制定当前和未来的行动决策。

这项研究的原创性对该地区(墨西哥、中美洲和拉丁美洲)来说是具有创新性的。没有人用这种方法和这些变量研究过这些问题。就原创性而言, 面板数据和面板数据协整的经典模型是有用的且易于复制, 可供其他国家使用。 研究结果具有一定的相关性, 因为旅游业与部分环境变量在短期内不存在明显的相关性, 但在它们中的一些变量在长期内存在着或强或弱的相关性。

Se examina la relación entre medio ambiente y flujos turísticos, así como variables económicas de los 32 estados de México para el período 1999-2019 basado en la disponibilidad de datos. La literatura relacionada que estudia el turismo y los impactos ambientales es escasa a nivel nacional, siendo la mayoría de ellos estudios de casos locales. Estudios internacionales encuentran que, si la relación existe, es débil o inexistente, utilizando el CO2 como un indicador en la mayoría de los casos.

Se utilizaron metodologías de datos de panel y cointegración de panel, además sistemas de información geográfica para observar la distribución de variables a nivel estatal.

i) El Producto Interno Bruto Estatal, la inercia de las variables ambientales (es decir, volumen de tratamiento de agua y residuos sólidos), habitaciones ocupadas (proxy de la actividad turística) y temperatura promedio tienen un impacto en la evolución contemporánea de las variables ambientales, ii) las variables turísticas nacionales e internacionales no tienen un impacto en el medio ambiente, iii) los paneles están integrados de tal manera que existe un equilibrio a largo plazo entre turismo, crecimiento económico y algunas variables ambientales, y iv) no se encuentra evidencia concluyente con respecto al impacto de la actividad turística en las variables ambientales consideradas.

Las principales limitaciones y áreas de oportunidad del trabajo se refieren a la cantidad de datos disponibles en el tiempo y a la precisión de la medición de las variables. La disponibilidad, temporalidad y frecuencia de los datos también son limitaciones de la investigación. Un ejemplo de ello es la inexistencia de emisiones de CO2 a nivel estatal. Además, el estudio de otros países y regiones para los que existen limitaciones de datos y estudios aplicados también es un reto.

Los resultados son importantes para las economías (en crecimiento) y las sociedades cuyo crecimiento económico depende de los flujos turísticos y que han hecho poco por invertir los daños que el turismo produce en el medio ambiente.

Los modelos pueden contribuir a estudiar la relación entre el turismo y las variables medioambientales y podrían extenderse a regiones, estados y provincias para la toma de decisiones sobre las acciones a emprender para el presente y el futuro.

El artículo proporciona un análisis innovador y exploratorio hacia una perspectiva futura que agrega valor al turismo y la planificación para la sostenibilidad. La relación entre turismo y medio ambiente se ha estudiado durante varios años. La UNTWO ha abordado las consecuencias del turismo en el medio ambiente, particularmente, más basura, mayor consumo de agua, emisiones de CO2 y otros aspectos. Pocos trabajos estudian la relación entre estas variables.

La originalidad de la investigación es innovadora para la región: México, América Central y América Latina. No existen trabajos que hayan estudiado estos problemas con esta metodología y estas variables.

En términos de originalidad, los modelos clásicos de datos de panel y cointegración de datos de panel son útiles y fácilmente replicables para que otros los utilicen en diferentes países.

Los resultados son relevantes porque aparentemente no hay una relación entre el turismo y algunas variables ambientales a corto plazo, existe una relación débil y fuerte a largo plazo entre algunas de ellas.

The aim of this paper is to provide a narrative review of previous research on tourism demand modelling and forecasting and potential future developments.

A narrative approach is taken in this review of the current body of knowledge.

Significant methodological advancements in tourism demand modelling and forecasting over the past two decades are identified.

The distinct characteristics of the various methods applied in the field are summarised and a research agenda for future investigations is proposed.

本文旨在对先前关于旅游需求建模和预测的研究进行叙述性回顾并对未来潜在发展进行展望。

本文采用叙述性回顾方法对当前知识体系进行了评论。

本文确认了过去二十年旅游需求建模和预测方法论方面的重要进展。

本文总结了该领域应用的各种方法的独特特征, 并对未来研究提出了建议。

El objetivo de este documento es ofrecer una revisión narrativa de la investigación previa sobre modelización y previsión de la demanda turística y los posibles desarrollos futuros.

En esta revisión del marco actual de conocimientos sobre modelización y previsión de la demanda turística y los posibles desarrollos futuros,se adopta un enfoque narrativo.

Se identifican avances metodológicos significativos en la modelización y previsión de la demanda turística en las dos últimas décadas.

Se resumen las características propias de los diversos métodos aplicados en este campo y se propone una agenda de investigación para futuros trabajos.

Many environmental problems are due to the unfavorable environmental intentions and cultural–behavioral weaknesses in the relationship between man and nature. This study aims to adopt an environmental psychological perspective to green intention (GI) and green behavior (GB) of agricultural students; to this end, protection motivation theory (PMT) was used as the core of the theoretical base.

This research method was based on descriptive–correlational and causal–relational analyses. The statistical population included agricultural students of Iranian universities with green university standards (N = 5,582). Out of the total population, 384 students were selected as the study sample. The research instrument was a questionnaire whose validity was confirmed using a panel of experts and the average variance extracted. Also, its reliability was verified by Cronbach’s alpha coefficients (0.61 ≤ α ≤ 0.92), principal component analysis and composite reliability index.

The results of structural equation modeling showed that the obtained model is able to explain 36.3% and 5.56% of GB and GI variance changes, respectively. In addition, the results revealed that GI has the greatest effect on GB (β = 0.362).

It is worth to mention that according to the results, most of the independent variables, besides the direct effects they have on students’ GB, also indirectly affect this variable. This effect was performed through the key variable – GI. In other words, it can be concluded that the GI variable successfully mediates the effects of variables such as response efficacy (RE), self-efficacy (SE) and environmental norms (EN). Therefore, it is suggested that in the behavioral changes interventions in GB of agricultural studies, it should be considered that the presence or absence of GI can affect the actual behavior of individuals. In other words, it is recommended that to accelerate actual behavioral changes, behavioral interventionists should first focus on encouraging people’s GI.

It can be said that the conclusion of this research can provide a basis for the successful encouragement of students to GB. First, GI, as a key element, can mediate the impacts of variables such as RE, SE and EN on students’ GB. Second, PS only directly affects students’ GB. Third, RE has no significant impact on GB, but its effect on GI is significant. Fourth, RC affects students’ GI directly, without mediation. Fifth, SE and EN constructs affect students both directly and indirectly GB of students through GI. Knowing the location of the effect of these variables on each other and the role they have in explaining GI and GB of agricultural students presented some suggestions that can prepare the ground for further development of GB. Hence, managers, students, agricultural educators and other users can use these results to accelerate GB changes.

The conclusion of this research might provide a basis for the successful encouragement of students to GB. In interventions to change GB, it would be essential to pay enough attention to the fact that the presence or absence of GI might affect the actual behavior. It is suggested that behavioral interventionists focus on encouraging people’s GI so as to be able to accelerate the actual behavioral changes.