Antecedentes da satisfação na rede hoteleira: Uma investigação através da modelagem de equações estruturais

Satisfaction studies have become crucial to improve the relationship between guests and hotels. With that in mind, this study analyzes the functional relations interfering in customer satisfaction in the hotel sector, based on the analysis of two elements: consumer background, related to previous experience and expectation; and consumer experience, related to the business’s physical aspects and social environment. Therefore, four hypotheses were formulated and tested with 260 guests in hotels located in the State of Rio Grande do Sul. The results support the hypotheses formulated, indicating that physical environment is the greatest satisfaction predictor for hotel customers, followed by the “previous experience,” “social environment” and, finally, “consumer expectation.”Los estudios de satisfacción se han vuelto fundamentales para aumentar la relación entre huéspedes y hoteles. En ese sentido, este estudio tiene como principal objetivo analizar las relaciones funcionales que interfieren en la satisfacción de los huéspedes del sector hotelero, tomando como base el análisis de dos componentes: antecedentes del consumidor, relacionado a las experiencias anteriores y a las expectativas del consumidor; y experiencias de consumo, relacionado a los aspectos físicos y al ambiente social de los establecimientos. En ese sentido, se plantearon cuatro hipótesis puestas a prueba con doscientos sesenta huéspedes de tres hoteles ubicados en el estado de Rio Grande do Sul. Los resultados confirmaron las hipótesis planteadas, indicando que el ambiente físico es el principal predictor en la satisfacción de los huéspedes de hoteles, seguido por las dimensiones experiencia anterior, ambiente social y, por último, expectativa de consumo.Os estudos da satisfação têm se tornado fundamentais para aumentar o relacionamento entre hóspedes e hotéis. Nesse sentido, este estudo tem como principal objetivo analisar as relações funcionais que interferem na satisfação dos hóspedes do setor hoteleiro, tendo como base a análise de dois componentes: antecedentes de consumo, relacionados às experiências anteriores e expectativas de consumidor; e experiências de consumo, relacionadas aos aspectos físicos e ao ambiente social dos estabelecimentos. Assim, foram levantadas quatro hipóteses testadas junto a duzentos e sessenta hóspedes de hotéis localizados no estado do Rio Grande do Sul. Os resultados apresentaram sustentação para as hipóteses levantadas, indicando que o “Ambiente físico” é o maior preditor na satisfação dos hóspedes de hotéis, seguido pela dimensão “Experiência anterior”, “Ambiente social” e, por fim, “Expectativa de consumo”

Antecedentes da satisfação na rede hoteleira: Uma investigação através da modelagem de equações estruturais

Satisfaction studies have become crucial to improve the relationship between guests and hotels. With that in mind, this study analyzes the functional relations interfering in customer satisfaction in the hotel sector, based on the analysis of two elements: consumer background, related to previous experience and expectation; and consumer experience, related to the business’s physical aspects and social environment. Therefore, four hypotheses were formulated and tested with 260 guests in hotels located in the State of Rio Grande do Sul. The results support the hypotheses formulated, indicating that physical environment is the greatest satisfaction predictor for hotel customers, followed by the “previous experience,” “social environment” and, finally, “consumer expectation.”Los estudios de satisfacción se han vuelto fundamentales para aumentar la relación entre huéspedes y hoteles. En ese sentido, este estudio tiene como principal objetivo analizar las relaciones funcionales que interfieren en la satisfacción de los huéspedes del sector hotelero, tomando como base el análisis de dos componentes: antecedentes del consumidor, relacionado a las experiencias anteriores y a las expectativas del consumidor; y experiencias de consumo, relacionado a los aspectos físicos y al ambiente social de los establecimientos. En ese sentido, se plantearon cuatro hipótesis puestas a prueba con doscientos sesenta huéspedes de tres hoteles ubicados en el estado de Rio Grande do Sul. Los resultados confirmaron las hipótesis planteadas, indicando que el ambiente físico es el principal predictor en la satisfacción de los huéspedes de hoteles, seguido por las dimensiones experiencia anterior, ambiente social y, por último, expectativa de consumo.Os estudos da satisfação têm se tornado fundamentais para aumentar o relacionamento entre hóspedes e hotéis. Nesse sentido, este estudo tem como principal objetivo analisar as relações funcionais que interferem na satisfação dos hóspedes do setor hoteleiro, tendo como base a análise de dois componentes: antecedentes de consumo, relacionados às experiências anteriores e expectativas de consumidor; e experiências de consumo, relacionadas aos aspectos físicos e ao ambiente social dos estabelecimentos. Assim, foram levantadas quatro hipóteses testadas junto a duzentos e sessenta hóspedes de hotéis localizados no estado do Rio Grande do Sul. Os resultados apresentaram sustentação para as hipóteses levantadas, indicando que o “Ambiente físico” é o maior preditor na satisfação dos hóspedes de hotéis, seguido pela dimensão “Experiência anterior”, “Ambiente social” e, por fim, “Expectativa de consumo”

Effectiveness of a 16-month multicomponent and environmental schoolbased intervention for recovery of poor income overweight/obese children and adolescents: study protocol of the health multipliers program

Background: Excess of weight is a serious public health concern in almost all countries, afflicting people of different ages and socioeconomic backgrounds. Studies have indicated the need for developing treatment strategies that intervene directly in the obesogenic environment. This study aims to evaluate the effectiveness of a multi-component and environmental school-based intervention, lasting 16 months, on the recovery of the nutritional status of lowincome children and adolescents with overweight/obesity. Methods/study design: The study was conducted by the Center for Recovery and Nutritional Education (CREN) in Sao Paulo, Brazil. Two schools located in poor neighborhoods were selected for the intervention, between March 2016 and June 2017. The participants were all students aged 8 to 12 years fromthe two participating schools. At the beginning of the intervention, anthropometric measurements were carried out to assess the nutritional status of the students. For convenience, students from one of the schools were considered as the control group, while those from the other school formed the experimental group. The intervention in the experimental group (n = 438) consists of the following weekly activities at school: psychological counseling in groups, theoretical/practical nutrition workshops, and supervised physical education classes. In addition, theoretical and practical educational activities are held regularly for parents, teachers, and cooks. Students with excess of weight (>= 1 body mass index [BMI] - for-age Z score, n = 138) received clinical and nutritional care periodically at the outpatient care at CREN. Students enrolled in the control group (n = 353) participated in psychological counseling groups and theoretical/practical nutrition workshops for 6 months held in the school environment to provide motivation to entire classrooms. In the following 10 months, students with excess of weight from the control group (n = 125) were invited to attend the routine outpatient care at CREN. Discussion: This study is the first to assess the effectiveness of a multi-component and environmental school-based intervention for the recovery of low-income, overweight/obese children and adolescents. If positive, the results demonstrate the feasibility for the recovery of excess of weight in populations of similar conditions and age.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Univ Fed Sao Paulo, UNIFESP, Dept Physiol, Rua Botucatu 862,2 Andar,Vila Clementino, BR-04023062 Sao Paulo, SP, BrazilUniv Fed Sao Paulo, UNIFESP, Hlth & Soc Inst, Dept Publ Hlth & Collect Hlth, Santos, SP, BrazilUniv Fed Sao Paulo, UNIFESP, Dept Pediat, Sao Paulo, SP, BrazilCREN, Sao Paulo, SP, BrazilUNIFESP, Hlth & Soc Inst, Dept Publ Hlth & Collect Hlth, Santos, SP, BrazilUNIFESP, Dept Human Movement Sci, Santos, SP, BrazilUniv Sao Paulo, Dept Comp Sci, Inst Math & Stat, Sao Paulo, SP, BrazilUniv Fed Sao Paulo, Paulista Sch Med, UNIFESP, Sao Paulo, SP, BrazilUniv Fed Sao Paulo, Dept Nephrol, UNIFESP, Sao Paulo, SP, BrazilUniv Fed Sao Paulo, UNIFESP, Dept Physiol, Rua Botucatu 862,2 Andar,Vila Clementino, BR-04023062 Sao Paulo, SP, BrazilUniv Fed Sao Paulo, UNIFESP, Hlth & Soc Inst, Dept Publ Hlth & Collect Hlth, Santos, SP, BrazilUniv Fed Sao Paulo, UNIFESP, Dept Pediat, Sao Paulo, SP, BrazilUNIFESP, Hlth & Soc Inst, Dept Publ Hlth & Collect Hlth, Santos, SP, BrazilUNIFESP, Dept Human Movement Sci, Santos, SP, BrazilUniv Fed Sao Paulo, Paulista Sch Med, UNIFESP, Sao Paulo, SP, BrazilUniv Fed Sao Paulo, Dept Nephrol, UNIFESP, Sao Paulo, SP, BrazilFAPESP: 2014/22351-2Web of Scienc

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio