Social media and environmentally sustainable tourism: insights from a systematic literature review of the tourist perspective

This study presents a systematic literature review at the intersection of social media and environmentally sustainable tourism from the tourist perspective. Drawing on a rigorous content analysis of 163 publications, we systematize and synthesize existing knowledge, identify key research gaps, and outline directions for future research. We demonstrate how user-generated social media data are employed to analyze and manage tourist flows at environmentally sustainable destinations. We further examine how contemporary research investigates the influence of social media on destination image and travelers’ behavioral intentions. In addition, we explore how social media are used to examine tourists’ perceptions, experiences, and values related to nature-based and sustainable destinations. Finally, we analyze how social media are utilized to shape tourists’ environmental mindsets. Building on these insights, we advance an integrated conceptual model illustrating how social media function as a socio-digital infrastructure shaping environmentally sustainable tourism. Our findings provide theoretical, methodological, and practical contributions while also demonstrating how social media can be leveraged by scholars and practitioners to promote environmentally sustainable tourism.

Authors

Institutions

Publication Details

Journal
Information Technology & Tourism
Published
2026-06-25
DOI
https://doi.org/10.1007/s40558-026-00387-x
Primary Topic
Diverse Aspects of Tourism Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Social media and environmentally sustainable tourism: insights from a systematic literature review of the tourist perspective

Adam Ryszko, Agnieszka Janik
Information Technology & Tourism
Diverse Aspects of Tourism Research
article

Social media and environmentally sustainable tourism: insights from a systematic literature review of the tourist perspective

Adam Ryszko, Agnieszka Janik
article en

Abstract

This study presents a systematic literature review at the intersection of social media and environmentally sustainable tourism from the tourist perspective. Drawing on a rigorous content analysis of 163 publications, we systematize and synthesize existing knowledge, identify key research gaps, and outline directions for future research. We demonstrate how user-generated social media data are employed to analyze and manage tourist flows at environmentally sustainable destinations. We further examine how contemporary research investigates the influence of social media on destination image and travelers’ behavioral intentions. In addition, we explore how social media are used to examine tourists’ perceptions, experiences, and values related to nature-based and sustainable destinations. Finally, we analyze how social media are utilized to shape tourists’ environmental mindsets. Building on these insights, we advance an integrated conceptual model illustrating how social media function as a socio-digital infrastructure shaping environmentally sustainable tourism. Our findings provide theoretical, methodological, and practical contributions while also demonstrating how social media can be leveraged by scholars and practitioners to promote environmentally sustainable tourism.

Information Technology & TourismVol. 28(2)
Silesian University of Technology (PL)
Decent work and economic growth, Responsible consumption and production
Openalex Percentile: Top 4%
Diverse Aspects of Tourism Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.