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Submission Deadline: 30 September 2024
Guest Editors: Andrea Ghermandi (University of Haifa); David Katz (University of Haifa); Maria L. Loureiro (University of Santiago de Compostela)
Environment and Development Economics seeks to publish a special issue on digital media data in environment and development economics. The issue will be guest edited by Andrea Ghermandi, David Katz and Maria L. Loureiro.
A new field of research has been developing in the environmental sciences over the past decade that relies on user-generated content as a source of insights into how humans interact with the natural environment (Ghermandi and Sinclair, 2019). Such a broad term encompasses digital data from a variety of sources. These notably include social media such as social networking sites (e.g., Facebook, WeChat, Reddit), (micro-)blogging platforms (e.g., Twitter, Weibo), online rating and reviews (e.g., TripAdvisor, Google Reviews), and media sharing services (e.g., Instagram, YouTube, Flickr). A growing interest is also gathering around user-generated content from other sources, such as sports and outdoor recreation apps (e.g., Strava, Wikiloc), cell phone network data, and other cell phone apps.
While much of the “big data” users upload and share on such platforms is not directly related to environmental research, the analysis of spatial movements (e.g., GPS locations) and of media such as texts, photographs, videos may offer a unique and unmediated window into people’s experiences and perceptions of the natural environment, as well as some of the ecological processes taking place within it (Ghermandi et al., 2023).
Within this context, user-generated content has still received only limited attention in the field of environmental and development economics. Applications have mainly focused on the potential of integrating user-generated content within established non-market valuation techniques, including stated preference methods (Kolstoe et al., 2022; Loureiro et al., 2022), and the travel cost method (Sinclair et al., 2020; Lingua et al., 2022; Kubo et al., 2020; Jaung and Carrasco, 2020). Applications in lower-income countries are especially lacking (Sinclair et al., 2018). Such limited uptake stands in stark contrast to the potential of these new data sources to provide high-volume, relatively easily accessible and scalable user-generated information, which is not mediated by researchers and facilitators, like in conventional surveys.
This special issue aims to extend the understanding of the potential applications and new insights that can be generated through the analysis of user-generated content in economic assessments. This call is open to both theoretical and applied empirical contributions which provide novel insights into all aspects related to the uptake of user-generated content within environmental and development economics, with an emphasis on applications in low-income countries. These include, but are not limited to: (1) the integration into non-market valuation techniques; (2) improving understanding of consumer preferences and behavior; (3) the exploration of potential limitations of these new data sources (e.g., from lack of representativeness of the sampled users or data scarcity for specific areas and populations as a consequence of digital divides); and (4) the investigation of the ethical aspects (e.g., privacy protection) related to the analysis of user-generated content in economic studies.
Submission Guidelines: Papers should be submitted by 30 September 2024 at the latest. Early submissions are encouraged and will be processed immediately. Papers will undergo the normal refereeing process. The quality of the paper and the extent to which it fits the focus of the special issue are the criteria for acceptance.
Submissions should be made online at: https://mc.manuscriptcentral.com/ede. During the first step of the submission process, in the “Special Issue” field, authors should select “Digital media”. Authors should also indicate in their cover letter that the manuscript is for the “Digital media data in environment and development economics” Special Issue.
Instructions for contributors can be found here.
For further information, authors should contact the Guest Editors at the emails below.
| Andrea Ghermandi | University of Haifa, Israel | |
| David Katz | University of Haifa, Israel | |
| Maria L. Loureiro | University of Santiago de Compostela, Spain |
References
Ghermandi A and Sinclair M (2019) Passive Crowdsourcing of Social Media in Environmental Research: A Systematic Map. Global Environmental Change 55: 36–47. https://doi.org/10.1016/j.gloenvcha.2019.02.003.
Jaung W and Carrasco LR (2020) Travel Cost Analysis of an Urban Protected Area and Parks in Singapore: A Mobile Phone Data Application. Journal of Environmental Management 261 (May): 110238. https://doi.org/10.1016/j.jenvman.2020.110238
Kolstoe S, Vander Naald B and Cohan A (2022) A Tale of Two Samples: Understanding WTP Differences in the Age of Social Media. Ecosystem Services 55 (June): 101420. https://doi.org/10.1016/j.ecoser.2022.101420
Kubo T, Uryu S, Yamano H, Tsuge T, Yamakita T and Shirayama Y (2020) Mobile Phone Network Data Reveal Nationwide Economic Value of Coastal Tourism under Climate Change. Tourism Management 77 (April): 104010. https://doi.org/10.1016/j.tourman.2019.104010
Lingua F, Coops NC and Griess VC (2022) Valuing Cultural Ecosystem Services Combining Deep Learning and Benefit Transfer Approach. Ecosystem Services 58 (December): 101487. https://doi.org/10.1016/j.ecoser.2022.101487
Loureiro ML, Alló M and Coello P (2022) Hot in Twitter: Assessing the Emotional Impacts of Wildfires with Sentiment Analysis. Ecological Economics 200 (October): 107502. https://doi.org/10.1016/j.ecolecon.2022.107502
Sinclair M, Ghermandi A and Sheela AM (2018) A Crowdsourced Valuation of Recreational Ecosystem Services Using Social Media Data: An Application to a Tropical Wetland in India. Science of the Total Environment 642: 356–65. https://doi.org/10.1016/j.scitotenv.2018.06.056
Sinclair M, Mayer M, Woltering M and Ghermandi A (2020) Valuing Nature-Based Recreation Using a Crowdsourced Travel Cost Method: A Comparison to Onsite Survey Data and Value Transfer. Ecosystem Services 45 (October): 101165. https://doi.org/10.1016/j.ecoser.2020.101165
Ghermandi A, Langemeyer J, Van Berkel D, Calcagni F, Depietri Y, Egarter Vigl L, Fox N, Havinga I, Jaeger H, Kaiser N, Karaxov O, McPhearson T, Podschun S, Ruiz-Frau A, Sinclair M, Venohr M and Wood SA (2023) Social media data for environmental sustainability: a critical review of opportunities, threats and ethical use. One Earth (in press).