Today, wellness tourism has become a thriving industry. In wellness tourism, the tourists travel to relieve the pressures of ordinary life and become refreshed with no medicinal intervention. In wellness tourism, tourists seldom have any specific physical illnesses; rather, they are interested in enjoying the healing properties of certain regions. In this non-experimental research, a structural equation model was used to analyze the data to explore various aspects of well-being and identify the variables that influence wellness tourism. The statistical population included 237,415 tourists who visited the tourist attractions of Sarab County in Iran. The sample size was determined 384 subjects. The results showed that destination location in terms of climate, positive image of the region, excellent food, as well as physical, traditional, and historical appeals of the region, were the factors that had the highest effect on determining the destination of wellness tourism. In general, this study contributed to the development of wellness tourism in the world including Iran. The practical steps were taken based on the strategies, and approaches presented to reduce stress which enhances well-being during the COVID-19 outbreak.

The present research aimed to identify and analyze the factors influencing water conservation behaviors (WCBs) and determine the most important ones. The research adopted a causal-relational method with a questionnaire compiled for data collection. The validity and reliability of the questionnaire based on the calculation of Cronbach’s alpha for different sections were between 0.71 and 0.95. The statistical population included 5473 wheat farmers in Bukan Township, Iran. Krejcie and Morgan tables were used to calculate the sample size of 357 people. All these farmers have key information about the effects of climate change (e.g., drought) and are pioneers in using adaptation and water conservation strategies in wheat production. In this study, the sample size was determined using stratified sampling method with proportional assignment. The questionnaire validity was approved by the validity expert board. According to the findings of the exploratory factor analysis, the most important factors influencing WCBs of wheat producers included “institutional”, “economic”, “natural”, “extensional”, “social”, “attitudinal”, and “self-identity” ones. These seven factors together accounted for 47.498% of the variance in WCBs of wheat producers. The relationship between independent variables and wheat growers’ WCBs was determined by Pearson correlation coefficients. According to the results, economic, institutional, natural, attitudinal, social, and self-identity factors had a significant relationship with WBC at 1% error level. The regression results also showed that among the studied variables, economic and extensional factors had the greatest impact on wheat growers’ WCBs. The results can help managers and planners determine policies that focus more on economic and extensional factors that have been neglected in previous studies.

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