Do Online Comments Affect Environmental Management? Identifying Factors Related to Environmental Management and Sustainability of Hotels

Saura, José Ramón; Reyes-Menéndez, Ana; Alvarez-Alonso, Cesar

doi:10.3390/su10093016

Cited by 62 publications

(75 citation statements)

References 72 publications

(109 reference statements)

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“…However, the majority of prior studies using the survey method were done a few years ago [12][13][14][15][16]. Nowadays researchers are using the text mining method for analyzing eWOM [4,8,[16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Investigating Key Attributes in Experience and Satisfaction of Hotel Customer Using Online Review Data

Ban

Choi

et al. 2019

Sustainability

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With the development of social media, customers are sharing their experiences, and it is rapidly spreading as a form of online review. That is why the online review has become a significant information source affecting customers' purchase intention and behavior. Therefore, it is important to understand the customer's experience shown in the online review in order to maintain sustainable customer satisfaction and loyalty. The purpose of this study is to investigate what are the key attributes and the structural relationship of those key attributes. To accomplish this purpose, a total of 6596 hotel reviews were collected from Google (google.com). A frequency analysis using text mining was performed to figure out the most frequently mentioned attributes. In addition, semantic network analysis, factor analysis, and regression analysis were applied to understand the experience and satisfaction of the hotel customer. As a result, the top 99 keywords were divided into four groups such as "Intangible Service", "Physical Environment", "Purpose", and "Location". The factor analysis reduced the dimension of the original 64 keywords to 22 keywords, and grouped them into five factors, which are "Access", "F&B (Food and Beverage)", "Purpose", "Tangibles", and "Empathy". Based on these results, theoretical and practical implications for sustainable hotel marketing strategies are suggested.

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Section: Introductionmentioning

confidence: 99%

Investigating Key Attributes in Experience and Satisfaction of Hotel Customer Using Online Review Data

Ban

Choi

et al. 2019

Sustainability

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“…Examples of possible policies include taxation systems favouring sustainable choices, science-based decision-making or leading by example. The results of the study could also be linked to the managerial use of sustainable factors [42] or collaborative economy analyses [43]. In the EU level, the potential savings are even higher.…”

Section: Electric Transportationmentioning

confidence: 95%

The Economic Potential to Support Sustainability through Household Consumption Choices

et al. 2018

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The amount of money that could potentially be saved by households by reducing unnecessary consumption and directed to sustainable investments without compromising the social needs in Finnish households was studied. The study was conducted by using statistical data and by creating short-and long-term scenarios to assess potential savings resulting from changes in household behaviour. According to the results, a Finnish household could save and subsequently allocate an average of €3400-€15,000 annually to invest in sustainability. The greatest potential for preventing unnecessary consumption is related to (1) food and drinks, and (2) transportation. In the long-term scenario, reducing expenditures in the category of housing also provides opportunities for high savings. A significant share of the saving created by sustainable patterns of consumption can be directed for example to investments in renewable energy.

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“…To determine the number of iterations required to train this algorithm so that it is ready to be used, we focus on the resulting KAV measurement [50]. This measure indicates what the level of significance is in terms of machine learning success [33,34]. Note that in applying the threshold levels of KAV, the results must be equal to or greater than 0.667 to have an average of success that is minimally reliable [50].…”

Section: Knowledge-based Methods To Extract Insights From Ugcmentioning

confidence: 99%

“…Specifically, this study develops a topic-modeling technique known as LDA (latent Dirichlet allocation) on which SA via machine-learning developed in Python, is applied. The results generated are then tested against Krippendorf's alpha value (KAV) which sets a meaningful threshold of 0.8 or better [33,34] to be considered as reliable on a sample of n = 9801 tweets [35]. The information analyzed is the text content of tweets that together with the indicators obtained from the applied methods, as well as the study of their groupings in communities, allow us to derive insights related to innovation in education [17,21].…”

Section: Introductionmentioning

confidence: 99%

How to Extract Meaningful Insights from UGC: A Knowledge-Based Method Applied to Education

2019

Self Cite

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New analysis and visualization techniques are required to glean useful insights from the vast amounts of data generated by new technologies and data sharing platforms. The aim of this article is to lay a foundation for such techniques so that the age of big data may also be the age of knowledge, visualization, and understanding. Education is the keystone area used in this study because it is deeply affected by digital platforms as an educational medium and also because it deals mostly with digital natives who use information and communication technology (ICT) for all manner of purposes. Students and teachers are therefore a rich source of user generated content (UGC) on social networks and digital platforms. This article shows how useful knowledge can be extracted and visualized from samples of readily available UGC, in this case the text published in tweets from the social network Twitter. The first stage employs topic-modeling using LDA (latent dirichlet allocation) to identify topics, which are then subjected to sentiment analysis (SA) using machine-learning (developed in Python). The results take on meaning through an application of data mining techniques and a data visualization algorithm for complex networks. The results obtained show insights related to innovative educational trends that practitioners can use to improve strategies and interventions in the education sector in a short-term future.

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Do Online Comments Affect Environmental Management? Identifying Factors Related to Environmental Management and Sustainability of Hotels

Cited by 62 publications

References 72 publications

Investigating Key Attributes in Experience and Satisfaction of Hotel Customer Using Online Review Data

Investigating Key Attributes in Experience and Satisfaction of Hotel Customer Using Online Review Data

The Economic Potential to Support Sustainability through Household Consumption Choices

How to Extract Meaningful Insights from UGC: A Knowledge-Based Method Applied to Education

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