Search results

This research aims to contribute to the literature on sustainable hospitality and tourism by applying social network analysis to identify sustainable tourism business networks and untangle the role of cognitive and geographical proximity in their formation.

Data mining and machine learning techniques were applied to data collected from the websites of tourism companies located in northeastern Italy, namely, the Veneto region. Specifically, the authors used Web scraping to extract relevant information from the internet.

The results support the existence of geographical clusters of tourist accommodation providers that are linked by strong cognitive proximity based on sustainability principles that are well communicated via their websites. This does not appear to be greenwashing because companies that have agreed on sustainability principles have also implemented concrete actions and tend to signal these actions through a variety of sustainability certifications.

The results may guide tourism managers and policymakers in developing tourism initiatives directed at the creation of fruitful collaborations between similarly oriented organizations and methods to support clusters of sustainable tourism accommodation. Identifying sustainable tourism networks may assist in the identification of potential actors of change, fueling a widespread transition toward sustainability.

In this study, the authors adopted an innovative methodology to detect sustainability-oriented tourism business networks. Additionally, to the best of the authors’ knowledge, this study is one of the first to simultaneously explore the cognitive and geographical connections between tourism businesses.

The purpose of this study is to extend Bippus and Young’s (2005) study and examine the effectiveness of the “I-you,” “I,” “You,” “We,” “But” and Question-based “Why” statements from Winer’s (2021) verbal coding program of conflict management using Bandura’s (1977) social learning theory (SLT).

Mixed methods were used using 175 university students from Texas and New York. A cross-sectional convenience sampling approach was conducted. Survey data was collected using Qualtrics.

Descriptive results demonstrated that the “We” statement was the most passive, the “I-you” statement was the most assertive and the “But,” “I,” “You” and Question statements were perceived to be aggressive. In addition, assertive “I-You” statements were perceived to be more effective in resolving the conflict and maintaining a relationship, whereas aggressive statements were less likely to resolve the conflict and maintain the relationship. Qualitative themes also support the “I-You” statement as the most assertive, while the “But,” “You” and “I” statements were found to be the most aggressive statements.

Implications and applications are discussed to stimulate future research among researchers and practitioners when addressing conflict. Being aware of the verbal statements that de-escalate conflict may be helpful in solving conflict in interpersonal, family and professional relationships. Future trainings can adopt effective verbal statements to resolve conflict when experiencing anger issues. Future research can continue to investigate verbal communication statements using SLT to help practitioners and managers address conflict in interpersonal relationships.

This study examines verbal statements in relation to communication styles and conflict management.