The success of each enterprise is finding, working on it, promoting, and obviously offering what the consumers really love and enjoy. Albania is very useful if you have this mission： Reconciling all the nature compon...The success of each enterprise is finding, working on it, promoting, and obviously offering what the consumers really love and enjoy. Albania is very useful if you have this mission： Reconciling all the nature components with favorable weather conditions, we can really offer an adventure business, where everyone can discover the beauty of Albania through an unforgettable trip. The key word that summarizes all the elements mentioned is without a doubt “Rafting”. Introducing rafting both as a sport and as a touristic outdoor activity, in that way we develop a new touristic market and a strong promoter of sustainable adventure tourism in Albania. When a person takes pleasure but in an unhealthy extent, how does this affect his personality？ The adrenaline as happiness, meaning and pleasure…The topics that this study is about, are two key terms that will guarantee the success of this “adventure project”： The first is the satisfaction of consumers, which gives us a feedback about the product/service and the second part deals with the term adrenaline （pleasure supreme customer）; hedonic consumer features, part of their character, the main approaches and a study conducted with customers who have attended at least once rafting, customers attending characteristic of emotions, adrenaline, and adventure to take the pleasure of life. A company should always try and please its consumers. Usually, pleased consumers will always come back for more; they will also spread the word and bring new potential consumers into your business that will pay a fair amount of money for a new upcoming product that set company offers. The measurement of consumer satisfaction is a pure indicator of the consumers repurchases intentions, an indicator of the actual performance and differentiation from the current competition. The consumers mind will always remember the name of the company that they had a bad experience rather than the onethey have been satisfied with. Often when we receive a fixed service, our mind tends to create a very close emotional connection to set service. Often we find that the smallest things bring the greatest joy, regardless of the price. For the majority part, following the adrenaline passion is more than just a need. Lately, the traditional notion of purchasing is left behind and everyone is focusing on providing themselves with pleasure and emotions. The definition of the word “hedonic” comes from Ancient Greece, meaning “taking the maximal pleasure from life” being our primary goal.展开更多
The nonlinearity of hedonic datasets demands flexible automated valuation models to appraise housing prices accurately,and artificial intelligence models have been employed in mass appraisal to this end.However,they h...The nonlinearity of hedonic datasets demands flexible automated valuation models to appraise housing prices accurately,and artificial intelligence models have been employed in mass appraisal to this end.However,they have been referred to as“blackbox”models owing to difficulties associated with interpretation.In this study,we compared the results of traditional hedonic pricing models with those of machine learning algorithms,e.g.,random forest and deep neural network models.Commonly implemented measures,e.g.,Gini importance and permutation importance,provide only the magnitude of each explanatory variable’s importance,which results in ambiguous interpretability.To address this issue,we employed the SHapley Additive exPlanation(SHAP)method and explored its effectiveness through comparisons with traditionally explainable measures in hedonic pricing models.The results demonstrated that(1)the random forest model with the SHAP method could be a reliable instrument for appraising housing prices with high accuracy and sufficient interpretability,(2)the interpretable results retrieved from the SHAP method can be consolidated by the support of statistical evidence,and(3)housing characteristics and local amenities are primary contributors in property valuation,which is consistent with the findings of previous studies.Thus,our novel methodological framework and robust findings provide informative insights into the use of machine learning methods in property valuation based on the comparative analysis.展开更多
文摘The success of each enterprise is finding, working on it, promoting, and obviously offering what the consumers really love and enjoy. Albania is very useful if you have this mission： Reconciling all the nature components with favorable weather conditions, we can really offer an adventure business, where everyone can discover the beauty of Albania through an unforgettable trip. The key word that summarizes all the elements mentioned is without a doubt “Rafting”. Introducing rafting both as a sport and as a touristic outdoor activity, in that way we develop a new touristic market and a strong promoter of sustainable adventure tourism in Albania. When a person takes pleasure but in an unhealthy extent, how does this affect his personality？ The adrenaline as happiness, meaning and pleasure…The topics that this study is about, are two key terms that will guarantee the success of this “adventure project”： The first is the satisfaction of consumers, which gives us a feedback about the product/service and the second part deals with the term adrenaline （pleasure supreme customer）; hedonic consumer features, part of their character, the main approaches and a study conducted with customers who have attended at least once rafting, customers attending characteristic of emotions, adrenaline, and adventure to take the pleasure of life. A company should always try and please its consumers. Usually, pleased consumers will always come back for more; they will also spread the word and bring new potential consumers into your business that will pay a fair amount of money for a new upcoming product that set company offers. The measurement of consumer satisfaction is a pure indicator of the consumers repurchases intentions, an indicator of the actual performance and differentiation from the current competition. The consumers mind will always remember the name of the company that they had a bad experience rather than the onethey have been satisfied with. Often when we receive a fixed service, our mind tends to create a very close emotional connection to set service. Often we find that the smallest things bring the greatest joy, regardless of the price. For the majority part, following the adrenaline passion is more than just a need. Lately, the traditional notion of purchasing is left behind and everyone is focusing on providing themselves with pleasure and emotions. The definition of the word “hedonic” comes from Ancient Greece, meaning “taking the maximal pleasure from life” being our primary goal.
基金supported by the National Research Foundation of Korea grant funded by the Korea government(MSIT)(RS-2025-16067531:Kwangwon Ahn)Hankuk University of Foreign Studies Research Fund(0f 2025:Sihyun An).
文摘The nonlinearity of hedonic datasets demands flexible automated valuation models to appraise housing prices accurately,and artificial intelligence models have been employed in mass appraisal to this end.However,they have been referred to as“blackbox”models owing to difficulties associated with interpretation.In this study,we compared the results of traditional hedonic pricing models with those of machine learning algorithms,e.g.,random forest and deep neural network models.Commonly implemented measures,e.g.,Gini importance and permutation importance,provide only the magnitude of each explanatory variable’s importance,which results in ambiguous interpretability.To address this issue,we employed the SHapley Additive exPlanation(SHAP)method and explored its effectiveness through comparisons with traditionally explainable measures in hedonic pricing models.The results demonstrated that(1)the random forest model with the SHAP method could be a reliable instrument for appraising housing prices with high accuracy and sufficient interpretability,(2)the interpretable results retrieved from the SHAP method can be consolidated by the support of statistical evidence,and(3)housing characteristics and local amenities are primary contributors in property valuation,which is consistent with the findings of previous studies.Thus,our novel methodological framework and robust findings provide informative insights into the use of machine learning methods in property valuation based on the comparative analysis.
