Purpose
Through the application of the theory of planned behavior (TPB), this study aims to explore the main determinants of higher education students’ pro-environmental behavior.
Design/methodology/approach
An online survey was conducted among the students of a public higher education institution (HEI) in Portugal, from March to May of 2020. The data were analyzed with the structural equation modeling technique, considering environmental attitude, knowledge, subjective norm and perceived behavioral control as exogenous latent variables, and pro-environmental intention and behavior as endogenous latent variables.
Findings
The results show that the students’ environmental attitude and knowledge have no significant impact on their pro-environmental intention, while the students’ subjective norm and perceived behavioral control have a positive impact on their pro-environmental intention. The results also reveal that the students’ perceived behavioral control and pro-environmental intention have a strong and positive impact on their pro-environmental behavior.
Research limitations/implications
This study focuses on the students from a single public HEI, in accounting and administration area, and deepens environmental behavior in relation to resources’ consumption.
Practical implications
This study provides findings that can be useful for HEIs to be more effective in their policies, strategies and practices to improve students’ environmental behavior.
Originality/value
The paper contributes to the literature by exploring the main determinants of higher education students’ pro-environmental behavior in a Portuguese HEI and extending the TPB considering the additional variable environmental knowledge.
In this paper we consider the modified Shewhart control chart for ARCH processes and introduce it for threshold ARCH (TARCH) ones. For both charts, we determine bounds for the distribution of the in-control run length (RL) and, consequently, for its average (ARL), both depending only on the distribution of the generating white noise, the model parameters and the critical value. For the ARCH model, we compare our bounds with others available in literature and show how they improve the existing ones. We present a simulation study to assess the quality of the bounds calculated for the ARL.
Resumo -A auditoria financeira foca-se na obtenção e avaliação de prova, tendo por base certas asserções. Baseia-se no escrutínio dos dados das empresas, com o objetivo de obter evidência, apropriada e suficiente, que forneça um grau de segurança razoável de que as demonstrações financeiras estão isentas de fraude e/ou de erros materiais, comunicando posteriormente os resultados aos stakeholders. Porém, a dimensão e complexidade crescente das organizações, bem representada pelo volume de dados que atualmente geram e armazenam, aumentaram muito a exigência do trabalho do auditor, que deve ser eficaz e eficiente. Os procedimentos clássicos de auditoria, extremamente dependentes de amostragem e procedimentos manuais, têm-se revelado insuficientes. Devido à quantidade massiva de dados, surgimento de novas tecnologias e ferramentas informáticas a um nível frenético, a auditoria está hoje a ser repensada, com o debate a estender-se das organizações profissionais ao meio académico. Este artigo reúne as lacunas e insuficiências reveladas recentemente no pensamento da auditoria dita tradicional, e os desafios que esta enfrenta atualmente. Apresenta as novas tecnologias, concretamente de Automatização Robótica de Processos e a Inteligência Artificial, como já tendo expressão na auditoria de hoje, e que, numa visão de futuro, são potenciadas pela sua combinação em Automação Inteligente de Processos.
In this paper we establish bounds for the finite dimensional laws of a threshold GARCH process, X, with generating process Z. In this class of models the conditional standard deviation has different reactions according to the sign of past values of the process. So, we firstly find lower and upper bounds for the law of
PurposeThis paper aims to better understand if speculative activity is a factor or even the main factor in the run-up of oil prices in the spot market, particularly in the recent price bubble that occurred in the period from mid-2003 to 2008.Design/methodology/approachThe methodology used is based on an existing vector autoregressive model proposed by Kilian and Murphy (2014), which is a structural model of the global market for crude oil that accounts for flow demand and flow supply shocks and speculative demand oil shocks.FindingsFrom the output of the authors’ structural model, the authors ruled out speculation as a factor of rising oil prices. The authors have found instead that the rapid oil demand caused by an unexpected increase in the global business cycle is the most accurate culprit. Despite the change of perspective in the speculative component, the authors’ conclusions concur with the findings of Kilian and Murphy (2014) and others.Originality/valueAs far as the authors are aware, this is the first time that a study has used as a spread oil variable, a speculative component of the real price, replacing the oil inventories considered by Kilian and Murphy (2014). Another contribution is that the model used allows estimating traditional oil demand elasticity in production and oil supply elasticity in spread movements, casting doubt on existing models with perfect price-inelastic output for crude oil.
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