Navigating Sustainability: A Bibliometric Exploration of Environmental Decision-Making and Behavioral Shifts

Abstract

In recent years, the research area around environmental decision-making has drawn more and more interest, driven by a really big global push to achieve net-zero emissions. Significant investments in areas such as electric vehicles and renewable energy, coupled with increasingly limited access to natural resources, have intensified research efforts in this field. New and emerging research is aimed at shifting consumer behavior to make more sustainable decisions. Building on this context, the purpose of this paper is to explore academic publications related to decision-making and behavioral shifts in the context of sustainability. Using an advanced bibliometric tool such as Biblioshiny, the authors analyze an Institute for Scientific Information Web of Science dataset to identify the main authors and affiliated journals and map the academic and thematic evolution of this interdisciplinary field, including the key topics and countries involved. The analysis reveals a 6.68% annual growth rate. Through thematic maps, three field plots, word clouds, and a review of the top 10 most cited papers, this study provides a comprehensive overview of the evolving domain of environmental decision-making.

1. Introduction

Recent academic research has highlighted that navigating sustainability in environmental decision-making and behavioral shifts is a complex and evolving field. Integrating corporate sustainability strategies with organizational management is a significant challenge for decision-makers as they strive to align sustainable development with business strategies. Kitsios et al. [1] consider this alignment crucial for implementing effective corporate sustainability strategies, yet empirical research in this area remains limited, indicating a need for further exploration.

Consumer behavior plays a key role in sustainability, with frameworks such as nudge models defined by Thaler and Sunstein [2] providing insights into the drivers of eco-friendly purchasing behaviors and sustainable consumption. These frameworks emphasize the importance of social influences, individual habits, and emotions in shaping consumer decisions, highlighting the complexity of fostering sustainable consumer behaviors, as White et al. [3] explained in their paper.

Pro-environmental behavior research has evolved significantly over the past three decades, with emerging themes such as ecotourism, sustainable consumption, and corporate social responsibility gaining popularity. Zhang and Chabay [4] focus on this evolution, which reflects a broader societal shift toward recognizing the importance of individual and collective actions in mitigating environmental challenges.

Sustainable behavior can be observed in industries such as finance, another critical area, with research indicating a shift from social to environmental and climate change considerations in financial decision-making. According to Bennett et al., this shift encourages the growing importance of aligning financial strategies with sustainability goals, particularly in the context of green finance and renewable energy [5]. In addition, understanding cognitive biases in decision-making is essential, as these biases can significantly impact individual and group sustainability behaviors. Engler et al. [6] addressed these biases that can help mitigate unsustainable practices and promote more informed decision-making.

Incorporating corporate values into sustainability decision-making is another critical aspect, as it involves balancing empirical data with normative considerations to address complex environmental challenges. The approach discussed by Martin [7] requires transparent methods to integrate diverse stakeholder values, which is key for corporate social responsibility practices. Furthermore, the evolution of environmental sustainability practices highlights the importance of multidisciplinary collaboration, data-driven decision-making, and agile management strategies. Technological advancements and international agreements have played a significant role in shaping these practices, offering valuable insights for future policy decisions and research, as Tennakoon et al. [8] presented.

The field of behavioral economics plays another significant role in encouraging consumers to adopt more sustainable practices. It can help leverage insights into human behavior to design effective, sustainable interventions with a clear outcome in mind. Thaler and Sunstein’s nudge theory highlights how minor changes in existing behaviors can guide consumers toward more sustainable choices without limiting their preferences [9].

A particularly good example of how behavioral insights can influence environmental decision-making comes from the research and experiment conducted by Allcott and Mullainathan [10]. The authors introduced a simple nudge strategy in the form of feedback to households about their energy consumption relative to their neighbors. The results of this empirical study were overwhelming, showing that households that received comparative feedback significantly reduced their energy consumption compared to the control group. This suggests that social comparisons can strongly incentivize individual consumers to adopt sustainable practices.

More recent studies have shown that various approaches using nudge theory can be a practical pathway for achieving carbon neutrality goals in G20 countries, as Xu et al. [11] discovered. While green nudges can impact human behavior, their effects are context-dependent and should be considered as a simple tool amongst many in crafting environmental policies, as Carlsson et al. [12] explained in their research. A systematic review of choice architecture interventions revealed that most studies focus on exploring effectiveness in a specific context, with limited assessment of underlying processes, according to Szaszi et al. [13]. Most importantly, empirical evidence suggests that existing carbon pricing schemes have had little to no effect on increasing zero-carbon behavior and promoting technological change, despite theoretical arguments supporting their effectiveness, as Liliestam et al. [14] found. These findings, coupled with an increasing body of research in the field of sustainable behavioral changes, highlight the need for diverse and complementary approaches in order to achieve net-zero emissions.

Also, recent studies have discussed the complexity and interdisciplinary nature of sustainability and environmental decision-making [15]. For example, Zhang et al. [15] explored the relationship between corporate social responsibility (CSR) and risk spillovers for the particular case of carbon emission trading and stock markets. The authors have highlighted CSR’s potential to influence market dynamics [15]. Furthermore, in their research, Salim et al. [16] have addressed the role of renewable and non-renewable energy in economic activities in the case of the OECD countries and have underlined the importance of a balanced energy strategy for sustainable development [16]. Moreover, Hassan and Salim [17] have addressed the population aging in OECD countries and have connected this variable with income growth and CO₂. This approach provides important insights into demographic transitions and sustainability [17].

The purpose of this study is to assess the area of academic research around using behavioral insights to promote eco-conscious behavior and influence environmental decision-making. By using a bibliometric method, the main frameworks used to promote these environmental behavior shifts will be identified, investigating the collaboration among authors, which contributed the most, which are the most relevant affiliations and journals, and how the domain developed during the timespan Block and Fisch [18] presented in their research. The bibliometric approach aims to explore the structural elements of the investigated domains by offering a perspective regarding the entire timespan, showing how an area developed [19,20,21,22,23]. However, while extensive data collection and visually engaging representations and frameworks have advanced the field, a gap remains in the analytical integration of these findings with broader policy and behavioral insights. This bibliometric analysis aims to transform descriptive trends into actionable insights by addressing four key research questions. First, this paper examines how the publication of academic papers has evolved over the analyzed time scale (SQ1), therefore clarifying the dynamic landscape of research output. Second, it identifies the countries that have contributed most significantly to the literature (SQ2), offering a geographic perspective on existing research. Third, this study determines the authors with the most significant impact, as measured by citation metrics and influential papers (SQ3), to identify key contributors in the field. Finally, this research analyzes which journals have published the most articles on environmental decision-making (SQ4), highlighting the publications that have shaped the academic discourse. By linking these research questions with the overarching objective of transforming research trends into actionable insights, this study synthesizes findings into clear recommendations for future research. This paper and its objective target policymakers, academic researchers, and environmental professionals in the private sector.

To strengthen the purpose of this study, these are the research questions as described:

SQ1: How did the publication of academic papers evolve during the analyzed time scale?

SQ2: What are the countries with the most research published?

SQ3: Who are the authors with the most significant impact, taking into consideration the most cited papers in this domain?

SQ4: Which are the journals with the most articles published in the field of environmental decision-making?

The scope of the present paper is to use a bibliometric approach to answer the above scientific questions. By answering these questions in this study, researchers can cite this work when discussing trends in publication output or the impact of key authors and journals. In addition, policymakers and environmental managers may reference these findings and insights to understand how academic focus areas have evolved over time (e.g., the quantitative evolution of the field—represented by the overall number of papers per year or the overall number of citations—is depicted through the analysis of various indicators such as the annual scientific production, or the annual average article citations per year, while the topic’s evolution can be observed through the use of the thematic map—by observing which are the emerging or declining themes, the motor themes—namely the themes that have “fueled” the area over time, or the basic themes—the themes which have captured the attention of the researchers for a long period of time, or by the analysis of thematic map’s evolution—focusing on specific time periods), identifying the leading contributors shaping the academic field (through presenting the most prolific authors, countries, sources, or universities). In this way, this study not only positively contributes to the scholarly mapping of ecosystem service research but also provides a foundation for future studies aiming to bridge the gap between the academic literature and practical, policy-relevant insights.

To offer a detailed perspective of the field, this study incorporates a review of the 10 most cited documents in the investigated domains, extracting patterns, the most important contributors, and key terms used, combining qualitative and quantitative analyses. The H-index and collaboration index have been applied as quantitative methods to identify the impact of the authors and journals.

To meet the goals above, the first step was to show the most suitable papers in the research domain [5,8]. The analysis was undertaken using an R library called Biblioshiny, a data science tool used for bibliometric analysis, offering data visualization techniques and insights on the imported databases. This, in turn, facilitated the analysis of the data, extracting the most relevant authors, countries, and journals or visualizing the temporal evolution of academic research with ease.

To reinforce the analysis, the authors conducted a comprehensive review of the most highly cited papers within this emerging academic field.

This manuscript’s structure is organized as follows: The subsequent section presents the methodological framework for literature identification, detailing the search parameters and exclusion criteria employed in curating the existing academic research. Section 3 presents a comprehensive bibliometric analysis. The analysis begins with a broad characterization of the identified literature, examining keyword distributions, citation metrics across temporal scales, authorship patterns, and publication venues. This is followed by an in-depth review of the most cited articles. The authors conclude by addressing methodological constraints and offering concluding perspectives.

2. Materials and Methods

The focus of the research was to analyze the Web of Science (WoS) or Clarivate Analytics’ Web of Science Core Collection papers based on existing articles that have been published [24]. Bakir et al. [25] detailed why WoS is the most used and suitable database for a bibliometric analysis, as it has a higher coverability and has indexed numerous articles from reputable journals within the literature [26], even if the inclusivity is smaller compared with other databases. The majority of ISI Web of Science papers are published in English, with exclusive journal coverage compared to Scopus or Dimensions databases, with more than 74.8 million scholarly datasets and 1.5 billion cited references, grouping a variety of multidisciplinary academic papers [27]. WoS has a higher coverage for the papers that have been published before 1990 [28]. Furthermore, it has been observed that a series of papers dealing with similar topics in the research field have opted for the use of ISI Web of Sciences. For example, Gora [29] evaluated the connection between decision-making processes and performance by applying a bibliometric approach, extracting a WoS dataset between 2000 and 2018, and obtaining relevant outcomes for future directions and for researchers to delve further into the topic. Maier et al. [30] explored the correlation between sustainability and innovation using a dataset extracted from WoS dataset. The results that have been extracted from the bibliometric investigations showed that there is a similarity between innovation and sustainability, combining common elements that can be assimilated as “sustainable innovation”.

The methodology employed in this study was a structured mixed-method approach leveraging bibliometric analysis with the use of systematic literature review principles and literature review to ensure rigor and comprehensiveness. The methodology is broken down as follows:

• Systematic search strategy: This study followed a systematic process for literature identification, as described below, including predefined search terms, inclusion and exclusion criteria as described further in the paper, and multiple rounds of screening across the Web of Science database. This approach aligns with systematic review principles for reproducibility and transparency;
• Bibliometric analysis framework: The analysis leveraged Biblioshiny, an R-based bibliometric tool, to map publication trends, authorship networks, keyword evolution, and thematic clusters. Bibliometric methods inherently require systematic data extraction and normalization to ensure analytical consistency, as reflected in the empirical analysis of this paper;
• Literature review of the top cited papers: To contextualize findings, this paper offers a qualitative review of top ten most cited papers in the dataset. This involved thematic analysis of their contributions, methodological frameworks, and implications for behavioral shifts in sustainability.

Thanks to the scientific literature that has been described above [1,5,6], a detailed overview of the domain has been defined, but the dataset extraction from Clarivate Analytics’ Web of Science Core Collection could be affected based on the available indexes and WoS offering multiple paid subscriptions. According to Liu [31,32], it is crucial for researchers who are performing a bibliometric analysis to detail the indexes that are available for them through WoS database since the number of indexes could lead to a different number of articles extracted, generating diverse outcomes. In our case, the indexes that are included in the subscription for the mentioned period are the following:

• Social Sciences Citation Index (SSCI)—1975–present;
• Index Chemicus (IC)–2010–present;
• Book Citation Index–Science (BKCI-S)—2010–present;
• Book Citation Index–Social Sciences and Humanities (BKCI-SSH)—2010–present;
• Science Citation Index Expanded (SCIE)—1900–present;
• Emerging Sources Citations Index (ESCI)—2005–present;
• Arts and Humanities Citation Index (A&HCI)—1975–present;
• Conference Proceedings Citation Index–Science (CPCI-S)—1990–present;
• Current Chemical Reactions (CCR-Expanded)—2010–present;
• Conference Proceedings Citation Index–Social Sciences and Humanities (CPCI-SSH)—1990–present.

The main steps that were applied during the research are detailed in Figure 1, describing the extraction process, together with investigation, discussions, limitations, and conclusions.

Having in mind the scope of the research, the initial step was to extract the dataset from WoS database, and the main steps are detailed in

Table 1. Data selection steps.

Exploration Steps	Questions on Web of Science	Description	Query	Query Number	Count
1	Title	Contains the specific keyword related to sustainability, environmental decision-making, and behavioral shifts	((((TI = (eco-conscious_behavio*)) OR TI = (environmental_decision_making)) OR TI = (behavio*_ change_for_sustainability)) OR TI = (climate_action*_ nudge*)) OR TI = (sustainability_preference*)	#1	404
2	Abstract	Contains the specific keyword related to sustainability, environmental decision-making, and behavioral shifts	((((AB = (eco-conscious_behavio*)) OR AB = (environmental_decision_making)) OR AB = (behavio*_ change_for_sustainability)) OR AB = (climate_action*_ nudge*)) OR AB = (sustainability_preference*)	#2	1258
3	Keywords	Contains the specific keyword related to sustainability, environmental decision-making, and behavioral shifts	((((AK = (eco-conscious_behavio*)) OR AK = (environmental_decision_making)) OR AK = (behavio*_ change_for_sustainability)) OR AK = (climate_action*_ nudge*)) OR AK = (sustainability_preference*)	#3	247
4	Title/Abstract/Keywords	Contains the specific keyword related to sustainability, environmental decision-making, and behavioral shifts	#1 OR #2 OR #3	#4	1691
5	Language	Limit to English	(#4) AND LA = (English)	#5	1674
6	Document Type	Limit to article	(#5) AND DT = (Article)	#6	1322

. The initial step was to filter the titles by using one of the keywords related to sustainability, environmental decision-making, and behavioral shifts: “conscious_behavior*”, “environmental_decision_making”, “behavior*_change_for_sustainability”, “climate_action*_nudge”, and “sustainability_preference”. In this case, the “*” replaces zero or more letters, which eases the inclusion in the research for both the singular and the plural forms of the words [33]. Furthermore, the use of “_” ensures that the words included in the group of keywords used for searching the papers in the database are located near one another and are not separated by other words. Using the previous keywords, a total of 404 documents have been extracted. The key terms that have been used in order to filter the titles, abstracts, and keywords are similar to other bibliometric analyses in the areas of sustainability, environmental decision-making, and behavioral shifts. The evolution of sustainable development has been investigated, together with the environmental attitude and behavior of green consumers [34,35,36].

For the second step, the same keywords have been used to filter the abstract, resulting in a total of 1258 papers. In the third step, the focus was on keywords, and using the same terms, 247 articles were obtained. In the fourth step, the authors only kept documents that contained the keywords either in titles, abstracts, or keywords in the analysis, resulting in a total of 1691 documents. In the fifth step, a language filter was performed, keeping only articles published in English and reducing the number of papers from 1691 to 1674.

The English language has been selected as a filter since it is the most used language in academic research [37,38,39]. Inclusion of multiple languages could have led to false results while investigating the n-grams; most importantly, bigrams, trigrams, and themes are of utter importance in bibliometric analysis [40,41,42].

The last step removed the documents that were published in 2025, resulting in a total of 1322 papers that will be further investigated from multiple perspectives. The year 2025 was removed because it could affect the indicators related to citations and growth rate, as Moreno-Guerrero et al. [43] tested. Thangavel and Chandra [44] observed that the usage of English articles exclusively in bibliometric research is a critical criterion for maintaining the approachability and regularity of the paper.

Regarding the usage of the metrics, the outcomes take into consideration most of the metrics, such as the mean years from publication, the total number of documents, collaboration index, Hirsch index (h-index) for authors and sources, the average references per article, the number of co-authors per paper, the number of author’s keywords, and the most important universities, by taking into account the number of published documents, the total number of documents for each corresponding researcher’s country, etc. [36,45,46,47,48]. Based on the existing dataset, the maximum number of indicators have been extracted.

Apart from the indicators presented above, there are other indicators that are more complex, such as the keywords plus, fractionalized articles, or normalized total citations.

The keywords plus represent a type of words that are extracted by default from WoS database, which takes into consideration the words from titles and cited references with the highest number of frequencies from the articles included in the analysis.

The fractionalized article metric quantifies the individual contribution of the researchers based on the number of published papers, according to Bibliometrix webpage [49]. Wei and Jiang [50] investigated international studies by applying a bibliometric analysis, also defining the fractionalized articles as the individual contribution of the researchers by supposing same shares for each co-author of the article.

The Hirsch index defines the total number of papers that have been cited as no fewer than the number of citations of the source, as Hirsch [51] presented in his paper.

The normalized total citations (NTC) explain the performance of a document by focusing on the number of citations that are obtained and dividing the number of total citations for each article by the mean citations received by all documents. The calculation is performed only if the publication year is the same as the analyzed paper. For instance, if the NTC value is 2 for an article, it shows that the document overstepped twice the mean number of citations that were obtained by all articles in the dataset that have been released in the same year [20,52].

3. Dataset Analysis

The third section explores the dataset from multiple perspectives: initially, an overview of the papers is the focus, followed by sources, authors, countries, most cited documents, keywords, and collaboration networks.

3.1. Dataset Overview

This section explores the dataset, describing the total number of documents, sources, and references, together with the types of papers, number of keywords plus, or author’s keywords.

Table 2. Main information about the data.

Indicator	Value
Timespan	1975–2024
Sources	608
Documents	1321
Average years from publication	11
Average citations per document	32.86
Average citations per year per document	2.99
References	61,320

details the main information of the dataset. The extracted papers are from between 1975 and 2024, with a total of 1321 articles and 608 sources, which shows the interest of the researchers with an annual growth rate of 6.68%, as the Biblioshiny library presented [53].

The average number of citations per document is very high, 32.86, while the average number of citations per year per document is 2.99, with an average year from publication of 11.

Figure 2 displays the evolution of scientific production in the area of sustainability, decision-making, and behavioral shifts between 1975 and 2024, showing the positive trend regarding the interest of the researchers. The first four papers were published in 1975, while the next papers were released in 1977. Until 1992, production was reduced, with values between 0 and 4. Starting with 1992, the number of articles grew to 9, and in 1993, it was 12. The trend is positive but with spikes in some periods of time when production decreased, such as in 2005 or 2014, when 24 and 42 articles were released. In 2024, the peak was achieved with a total of 95 articles published.

Figure 3 details the yearly average citations. Contrary to the previous figure, the trend is not positive, with numerous spikes that show a high volatility, which could be correlated with the first steps of the research in behavior shifts, sustainability, and decision-making.

The papers published in 1975 have an average citation per year of only 0.1, and until 1983, the value was 0. The second most significant spike appeared in 1991, with an average citation per year of 7.8, when Lubchenco et al. [54] published their paper, which is also described in Figure 3 as one of the most cited papers. In the following years, the citations dropped significantly, with a small spike in 1995 and an average value of 3.2 citations.

Until 2009, when the most important spike appeared, the citation values were between 1 and 3, but in 2009, the value was 9.1, the highest of all time, which can be explained by the publication of three of the most cited papers, which were published by Fisher et al. [55], Prell et al. [56], and Sachdeva et al. [57].

Between 2009 and 2013, a strong decrease can be observed, followed by a positive trend until 2016. Starting with 2016, the trend became negative, with the minimum in 2024 having a value of one citation.

Table 3. Document contents.

Indicator	Value
Keywords plus	2435
Author’s keywords	3785

includes the total number of keywords plus and the author’s keywords that were used by the researchers. In total, there are more author’s keywords (3785) than keywords plus (2435). As Zhang et al. [58] explained, keywords plus and the author’s keywords are very similar, but keywords plus describes the domain in a broad way, while the author’s keywords are more specific.

Table 4. Authors.

Indicator	Value
Authors	3941
Authors of single-authored documents	330
Authors of multi-authored documents	3611
Single-authored documents	356
Multi-authored documents	965

contains information related to authors, such as the number of authors and the number of single-authored documents and multi-authored documents. In total, there are 3941 authors, and 330 worked on single-authored documents, while 3611 worked on multi-authored documents. The metrics presented in Table 4 define the nature of the collaboration, and similar papers that evaluated sustainability topics have been investigated, extracting the single-authored documents and multiple-authored documents, together with the number of authors’ keywords and keywords plus sources [39,59]. Gorski et al. [39] extracted a total of 2827 documents from the ISI Web of Science database that are related to education for sustainable development and education for sustainability topics. A bibliometric analysis was conducted, and one of the main steps represented the author’s exploration. On the extracted dataset, a total of 551 authors of single-authored papers, 694 single-authored documents, and 5765 authors highlighting relevant information about researchers on the investigated topics were found. Sing [59] analyzed sustainable agriculture in the QUAD countries, extracting the papers related to the topic from the Scopus database and using VOSViewer and Biblioshiny as tools. Among the datasets that contain information between 2002 and 2021, some of the main metrics that have been presented are the authors of single-authored documents for each country, authors of multi-authored documents, documents per author, keywords plus, and number of authors.

Table 5. Author collaboration.

Indicator	Value
Authors per document	2.98
Co-authors per documents	3.31
International co-authorship	24.07%

details the authors’ collaboration information, presenting the number of authors per document, which is 2.98, while the co-authors per document are 3.31, and the collaboration index is 3.74. According to Aria and Cuccurullo [53], the collaboration index is calculated as the division between total authors of multi-authored academic articles (3611 in our case) and total multi-authored documents (965 in our case), resulting in a value of 3.74. Similar papers have been assessed to compare the results. Wang et al. [45] explored the sustainability transition using a bibliometric approach, obtaining a database with 757 documents, 1514 authors, 2115 author’s keywords, and 1507 keywords plus, with two authors per document and a collaboration network of 2.31. Comparing the results, our dataset has higher collaboration, number of authors, author’s keywords, keywords, and authors per document, most likely due to the dataset size. This is smaller (757) than the one used for this paper (1321).

The collaboration index (3.74), authors per document (2.98), and co-authors per document (3.31) collectively illustrate the interdisciplinary and collaborative nature of sustainability research. These metrics align with broader trends in environmental scholarship, where complex challenges like behavioral shifts and policy design increasingly require cross-disciplinary teams. For instance, Wang et al. [45] reported a collaboration index of 2.31 in their bibliometric analysis of sustainability transitions, while the higher value presented in this paper reflects intensified integration of behavioral economics, environmental science, and policy expertise in this domain. By quantifying collaboration patterns, Table 5 enables comparative analysis with prior bibliometric studies.

Table 6. Document types.

Indicator	Value
Article	1225
Book chapter	27
Early-access article	21
Proceedings paper	48

contains the distribution of the articles based on their type. Most of the papers are articles, 1225, while 48 are proceedings papers, 27 are book chapters, and only 21 are early-access articles.

3.2. Sources

The second section of the third chapter explores the most important sources extracted from the WoS database.

According to Figure 4, the most important journal is Environmental Management, which published a total of 31 papers, which is followed by the Journal of Environmental Management with 26 articles and Environmental Science & Policy with 25 documents. The Journal of Cleaner Production and Sustainability each have 23 articles, while Ecological Economics and Environmental Modelling & Software each have 22 papers. The last three journals are Science of The Total Environment, Society & Natural Resources, and Ecological Modelling, with 18, 18, and 15 documents.

Figure 5 contains a graphical representation of Bradford’s law method, which clusters the articles into three groups by taking into account the number of papers. The method was developed by Samuel Bradford in 1934 to order the number of papers in a specific domain in descending order [60]. In our case, the most important journals are Environmental Management (31 articles), the Journal of Environmental Management (26 articles), Environmental Science & Policy (25 articles), the Journal of Cleaner Production (23 articles), Sustainability (23 articles), Ecological Economics (22 articles), Environmental Modelling & Software (22 articles), Science of Total Environment (18 articles), Society & Natural Resources (18 articles), and Ecological Modelling (15 articles).

Figure 6 describes the impact of journals based on the H-index or Hirsch index. The Hirsch index was defined in 2005, and it totals the number of articles that have at least the same number of citations as the source [51,61]. The most relevant sources based on the H-index are Environmental Management and Journal of Cleaner Production, with a value of 18 for each, followed by the Journal of Environmental Management with a Hirsch-value of 17, while Ecological Economics and Environmental Modelling & Software have a value of 16 each. Environmental Science & Policy has an H-index of 14, Science of the Total Environment has an H-index of 13, and Ecosystem Services has an H-index of 12, while the last two, Ecological Modelling and Society & Natural Resources, have an H-index of 11 each.

3.3. Authors

The third section focuses on the most relevant authors for the analyzed domains, also presenting the yearly production of the authors, together with the most important affiliations and countries.

Figure 7 presents the most important authors on the sustainability, behavioral shifts, and environmental decision-making areas. The first two are Han H. and Huang GH. With eight articles, each one having a fractionalized article value of 2.40 and 2.78, Han and Huang are the most representative authors for the analyzed domains. The fractionalized article value explains the contribution of each author by considering the equal implication of each researcher of the paper [50]. In third place, there are two authors, Newig J and Yeomans JS, with seven articles published, but with a significant difference in fractionalized articles, 1.73 for Newig J, while Yeomans JS has 4.25. Jager NW and Sadiq R each have six articles, with 1.53 and 1.98 fractionalized articles. The last four authors, Challies E., Dietz T., Satterfield T., and Seager TP., have five articles, while the articles’ fractionalized values are 1.20, 2.17, 1.12, and 1.40.

Figure 8 includes the production of the most important 10 authors during the timespan. Han H is the most prolific author based on the number of published papers, with the first article published in 2015 and the total citations per year being 13.1. In 2017, the author published the most papers, three, with the total citations per year being 36.5. Huang GH published his first document in 2001, with the total citations per year being only 3.38, while the second paper was released in 2003, with the total citations per year being 7.45. The peak was in 2012, when two documents were published, with four citations per year. Newig J published the first article in 2017, with the total citations per year being 2.62, while in 2020, he published two papers, with the citations per year being 23.4. Yeomans JS released the first paper in 2008, with the number of citations per year being just 1.29, while in 2012, the author published two papers, with the total citations per year being 1.69. Sadiq R published a total of six articles between 2006 and 2018, with one in each year (2006, 2009, 2012, 2013, 2015, 2018) and the total citations per year being between 0.83 in 2013 and 9.56 in 2009. Challies E released five papers between 2018 and 2023, except 2021, with the total citations per year being between 1.33 and 15.8. Dietz T released five papers, the first one in 2004, with the total citations per year being 0.33, while the peak was in 2017 with two papers and the total citations per year being 29.88. Satterfield T released five documents, with the highest citations per year in 2013 and a total of 15.75. The last author in the top 10 is Seager TP, with five papers, with two documents in 2007, and the total citations per year being 3.39.

Similar to Figure 6, the Hirsch index was used in order to identify the most relevant locally cited authors in Figure 9. In first place, Turner BK has an H-index value of 16, followed by Gregory R and Marttunen M, with each one having an H-index value of 14. The next two authors are Fisher B and Morling P, with an H-index value of 13, while Rea AW and Webler T have an H-index value of 12. The last three authors are Hamalainen RP, Satterfield T, and Tuler S, with an H-index of 11.

Figure 10 explores the most relevant affiliations in the domains of sustainability, environmental decision-making, and behavioral shifts. In first place is the United States Environmental Protection Agency (United States of America) with 70 publications, followed by the University of California System (United States of America) with 64 documents. The rest of the affiliations have a smaller number of articles. For instance, in third place is the University of British Columbia (Canada) with 38 articles, while Michigan State University (United States of America) has 35 documents, and the University of Queensland (Australia) has 30. The State University System of Florida (United States of America) published 26 papers, while the last four affiliations, the University of Washington (United States of America), Commonwealth Scientific and Industrial Research Organization (Australia), Carnegie Mellon University (United States of America), and Swiss Federal Institutes of Technology Domain (Switzerland), have 22, 21, 20, and 19 articles. In total, there are six universities from the United States of America, two from Australia, one from Canada, and one from Switzerland, showing the significant implications of the USA in the investigated areas.

Figure 11 presents the countries with the highest number of publications, dividing the papers into two different categories: single-country publications (SCP) and multiple-country publications (MCP). In first place is the United States of America (USA) with 408 articles, where 349 (85.5%) are SCP and 59 are MCP (14.5%), representing 30.9% of all papers published in the analyzed domains. In second place is the United Kingdom (UK) with only 145 papers, which represents 11% of total papers, 110 SCP (75.9%) and 35 MCP (24.1%), followed by Australia with 111 papers, 81 SCP (73.0%) and 30 MCP (27.0%), with a total contribution of 8.4% in total published documents. Canada released 104 documents, with a contribution of 7.9%, with a total of 88 SCP (84.6%) papers and 16 MCP (15.4%). The rest of the countries have a smaller impact but are worthy to be mentioned: China published 70 documents, with a contribution of 5.3%, with 44 SCP (62.9%) papers and 26 MCP (37.1%); Germany has 33 articles, 19 SCP (57.6%), 14 MCP (42.4%), with a contribution of 2.5%; the Netherlands released 31 documents (2.3%), 15 SCP (48.4%) and 16 MCP (51.6%); Spain released 26 papers (2.0%), 15 SCP (57.7%) and 11 MCP (42.3%); and New Zealand published 25 articles (1.9%), 18 SCP (72.0%) and 7 MCP (28.0%). The last country in the top 10 is Finland, with 23 documents (1.7%), 14 SCP (60.9%) and 9 MCP (39.1%). The USA is the country with the highest impact and also the smallest percentage of MCP publications, showing the interest of local authors, while the Netherlands is the country with the highest number of MCP articles, which expresses the intention of authors to integrate into areas by collaborating with international researchers.

Figure 12 presents the number of scientific publications of each country by various shades of blue, with light blue signifying the countries with the lowest contribution and dark blue signifying the countries with the highest contribution. Furthermore, the countries marked in grey do not have any contribution to the selected field in terms of published papers.

As can be observed, in first place is the USA with a frequency of 1080 appearances, followed by the UK with 321 appearances, Canada with 285 appearances, and Australia with 256 appearances. China is fifth with 164 appearances, while Spain and Germany have 93 and 85 appearances, and the Netherlands, New Zealand, and Finland published a total of 80, 64, and 62 appearances.

Furthermore, by considering the country of the corresponding author and the top 5 greatest contributing countries, the evolution of the number of papers presented in Figure 13 has been obtained.

Besides the overall contribution provided to the field by each country, it can also be observed that the first four contributors—namely the USA, UK, Canada, and Australia—have had a steady increase over the years and for a longer period of time than China, which presents a rapid growth in the number of papers, in a more limited period of time. Given the rapid ascent of China, particularly emphasized in recent years (as shown in Figure 13E) and the decline recorded for the USA (Figure 13A) and Australia (Figure 13D), it shall be mentioned that there might be a potential shift in the leaders in the near future when considering the number of papers published in this area.

As the change in the number of published papers can have multiple sources, in the following section, the influence of the funding on the number of published papers in the case of the top 5 most prolific countries based on the number of published papers associated with the corresponding author has been analyzed. Figure 14 highlights this evolution for each of the five countries. As noted in Figure 14, the fluctuations in the number of papers funded in the case of the USA (Figure 14A) and China (Figure 14E) seem very similar, with a peak around the year 2020, marked by the COVID-19 pandemic. On the other hand, the UK’s (Figure 14B) and Canada’s (Figure 14C) funded research papers seem to follow a similar path in the evolution of the number of funded papers included in the dataset, following a stable trajectory with a moderate growth in the number of funded research papers. An irregular pattern can be encountered in the case of Australia (Figure 14D), which might have various causes, such as a competitive funding system or targeted funding for specific areas at various periods of time.

To support these statements, according to a report undertaken by Ernest and Young [62], the US government allocated significant resources for health and environmental research as part of its COVID-19 response. The report highlights that the Infrastructure Investment and Jobs Act provided USD 1 trillion for sustainability-focused investments, which indirectly could impact environmental decision-making research [62]. Another paper, titled “Analyzing and visualizing global research trends on COVID-19 linked to sustainable development goals” [63], observes a plateau in US publications. This may be reflecting broader trends in funding allocation, where priorities shifted more toward pandemic-related studies during 2020.

Similarly, UK-funded research on climate change has shown consistent investment, according to a UK Collaborative and Development Research (UKCDR) report undertaken between 2015 and 2020 [64]. The report shows progress in initiatives like the UK Official Development Assistance (UK ODA) and Welcome-funded projects. Between this period, 2015 and 2020, GBP 564.2 million was allocated to over 6901 projects with a focus on sustainability and sustainable development goals (SDGs). This aligns well with the trajectory seen in Figure 13 [64].

The trajectory in Canada could be explained through a new strategy employed by the Canadian government, which is backing USD 4 billion to support a transition to clean energy and sustainable development [65].

Similarly, the irregular change in Australia could be linked to the overall spending on research and development declining as a percentage of GDP. It reached a historic low of 1.68% in 2021–2022. This reduction not only created challenges, but it could directly impact any funded research work focused on environmental decision-making [66].

Moving further and analyzing the sources of funding, it has been observed that in the case of the USA, the National Science Foundation (NSF) is the main funder of the papers included in the dataset (with 46 papers), followed by the NSF Directorate for Social Behavioral Economic Sciences (SBE) (with 16 papers), the National Aeronautics Space Administration (NASA) with 7 papers, and the United States Department of Energy (DOE) (with 7 papers). The remainder of the funders, in the case of the USA, have funded less than five papers.

For the UK, the main funders were the UK Research Innovation (UKRI—with 31 papers), the Economic Social Research Council (ESRC—with 15 papers), and the Natural Environment Research Council (NERC—with 14 papers).

Two main funders can be identified in the case of Canada: the Natural Sciences and Engineering Research Council of Canada (NSERC—with 22 papers) and the Social Sciences Humanities Research Council of Canada (SSHRC—with 11 papers).

Similarly, in the case of Australia, two main funders have been observed, namely the Australian Research Council—with 12 papers—and the Australian government—with 7 papers.

Analyzing the funding in the case of China, it has been noticed that the National Natural Science Foundation of China (NSFC) has been the most important funder (with 22 papers), which stands as the top funder as the remainder of the funding agencies have had less than 4 papers funded.

Thus, in terms of funders, it can be observed that, in general, the selected countries have two or three main funders, except for the USA, which has had a vaster variety of funders, and China, where a single funder emerged.

In Figure 15, the gap between the evolution of the number of papers belonging to the five selected countries and the evolution of the number of funded papers is represented. In the case of the USA (Figure 15A), one can note the highest overall gap between the two situations, suggesting that a great portion of published papers in the selected area and indexed in ISI WoS are self-founded or supported by alternative sources.

A relatively smaller gap can be encountered in the case of the United Kingdom (Figure 15B) and Canada (Figure 15C), suggesting that the funding system supports a moderate part of the total publications of the countries in the selected field.

Australia (Figure 15D) faces a more pronounced gap starting from 2017 to 2021, while in recent years, the gap has dramatically reduced.

Lastly, China (Figure 15E) stands out with a high percentage of funded papers in the total number of published papers and a trend that suggests an increase in the interest of the researchers in the selected area.

Figure 16 details the most cited countries in the investigated areas. In first place is the USA, with a total citation of 17,260 and an average article citation of 42.30, followed by the UK, with 7002 citations, with over 10,000 differences between first place and second place. The average article citations for the UK are 48.30. In third place is Canada, with 3348 citations, with an average article citation of 32.20, while Australia has 2980 citations, with an average article citation of 26.80, followed by Italy, with 1411 citations and an average article citation of 67.20. China is in sixth place, with a total of 1309 citations, with an average article citation of 18.70, followed by Spain and the Netherlands, with 1032 citations and 841 citations, with an average article citation of 39.70 and 27.10. The last two countries are Korea and Germany, with 793 citations and 777 citations and an average article citation of 41.70 and 23.50.

Figure 17 details the collaboration among countries on sustainability, environmental decision-making, and behavioral shifts. The significance of different shades of blue is the same as in Figure 12, while the width of red lines represents the intensity of the collaboration within a pair of two countries located at each end of the line.

The most fruitful collaboration is between the USA and Canada, with a total of 31 articles, followed by the USA–UK with 26 articles and the USA–Australia with 18 documents. The UK–Australia is the fourth most important collaboration, publishing 17 articles altogether, while the USA–China, the UK–Canada, and the USA–Netherlands published 16, 15, and 15 papers. The last three collaborations are between the USA and Germany (13 documents), the UK and the Netherlands (11 documents), and Canada and Australia (10 documents).

Figure 18 clustered the most important 50 authors in nine clusters. The number of edges is two in this case, with a repulsion force of 0.2. To better represent this cluster, the analysis uses a visualization generated by Biblioshiny, an R package, as a primary method of data visualization [53]. The identified clusters are discussed below.

• The cluster with the highest contribution to the field is formed by four authors, colored in turquoise, containing the following researchers: Challies E., Kochskamper E., Newig J., and Jager NW. The focus of the authors was to explain the applicability of environmental governance decision-making methods, their impact, and their findings using surveys and meta-analysis [67,68,69,70];
• The second cluster, colored in yellow, is formed by two authors, Garcia-Llorente M. and Martin-Lopez B., who detail the importance of integrated valuation and biodiversity conservation in Europe, exploring the collaboration among ecosystem domain in order to define a profile for the stakeholders [71,72,73,74];
• The third cluster, represented using brown, contains two authors, Hwang J. and Han H., who explore the possibility of integrating a goal for behavior and norm activation strategies into a framework and investigating the behavior of customers using value-belief–emotion–norm model [75,76,77];
• The fourth cluster, illustrated using purple, is formed by two researchers, Ulgiati S. and Brown MT., who describe the geobiosphere energy (available energy), investigating the patterns for a sustainable ecosystem and electricity production [78,79,80];
• The fifth cluster, colored in green, contains two authors, Yeomans JS. and Kozlova M., who explored the decision-making for carbon footprint by simulating decomposition and the impact for environmental sustainability, together with the investigation of technical evolution in aviation, the investments in simulation decomposition and the effects of sustainable decision-making [81,82,83];
• The sixth cluster, illustrated using red, has only two authors, Tuler S. and Webler T., who focused on public participation by using focus groups, Q method, or surveys and local governmental expectations from experts’ perspectives [84,85,86,87];
• The seventh cluster, colored in blue, is formed by three researchers, Gregory R., Satterfield T., and Failing I., who provided an overview of the metrics in environmental management, discussing policies, cultural values, and environmental decision-making [88,89];
• The eighth cluster, represented using gray, is formed by two authors, Gupta H. and Liu YQ., who explored the hydrologic implementation by integrating a data framework, connecting environmental decision-making with science in order to provide sustainable water resources or to develop a framework for environmental decision-making [90,91,92];
• The last cluster, illustrated using pink, contains two researchers, Marttunen M. and Hamalainen RP., who focused on multicriteria decision analysis using interview datasets, measuring the potential impact of the measures and creating a web decision support for participation in decision-making processes on environmental area [93,94,95].

3.4. Analysis of Literature

In this section, the authors have selected the top ten most cited papers and analyzed their content through a full paper review and through reviewing the information accompanying the paper.

3.4.1. Top 10 Most Cited Papers—Overview

Table 7. The top 10 most cited documents globally.

No.	Paper (First Author, Year, Journal, Reference)	Number of Authors	Region	Total Citations (TC)	Total Citations Per Year (TCY)	Normalized TC (NTC)
1	Fisher B., 2009, Ecological Economics [55]	3	UK	1920	120	13.21
2	Liu YQ, 2007, Water Resources Research [90]	2	USA	595	33.06	8.47
3	Prell C., 2009, Society & Natural Resources [56]	3	UK	583	36.44	4.01
4	Bagstad KJ., 2013, Ecosystem Services [96]	4	USA	533	44.42	10.55
5	Sachdeva S., 2009, Psychological Science [57]	3	USA	525	32.81	3.61
6	Lubchenco J., 1991, Ecology [54]	16	USA	512	15.06	1.94
7	Villamagna AM., 2013, Ecological Complexity [97]	3	USA, Canada	501	41.75	9.91
8	Hoyos D., 2010, Ecological Economics [98]	1	Spain	501	33.40	9.12
9	Bonney R., 2016, Public Understanding of Science [99]	4	USA	480	53.33	11.83
10	Agrawal A., 2001, Politics & Society [100]	2	USA	469	19.54	5.78

lists the top 10 most cited papers in environmental decision-making, providing information on the number of authors, total citations, regions, total citations per year, and normalized total citations. The normalized total citations (NTC) are determined by dividing the number of citations a paper has received by the average number of citations received by the other academic papers included in the dataset and published in the same year as the paper analyzed [20].

The reviewed literature represents a large body of research spanning four decades, with particular emphasis on ecosystem services analysis, environmental valuation methodologies, and behavioral dimensions of environmental decision-making. In the domain of ecosystem service analysis and valuation, which makes up the primary thematic focus, several groundbreaking methodological frameworks emerge. Bagstad et al. [96] offer a comprehensive comparative assessment of 17 decision support tools, analyzing their applicability, computational requirements, and practical limitations across different environmental decision contexts. This work builds upon Fisher et al. [55] foundational framework for ecosystem service classification, which established critical taxonomic principles that continue to influence contemporary valuation approaches. The methodological rigor is further examined and enhanced by Prell et al.’s [56] integration of social network analysis into natural resource management, introducing novel stakeholder engagement metrics and communication pattern analyses. Building on these methodological advances, the literature addresses environmental survey design and implementation, with multiple papers examining technical aspects of discrete choice experiments, including dimensionality considerations, statistical design principles, and data collection methodologies. The behavioral research dimension, particularly exemplified and supported by Sachdeva et al.’s [57] investigation of moral self-regulation and prosocial behavior, adds crucial psychological insights to environmental valuation frameworks. This literature collectively shows a methodological progression from theoretical frameworks to practical operational frameworks and implementation guidance. This evolution is characterized by increasingly robust quantitative methodologies, systematic incorporation of multi-stakeholder perspectives, and the application of advanced statistical techniques for empirical validation.

3.4.2. Top 10 Most Cited Papers—Review

Recent research in environmental valuation and ecosystem services assessment confirms significant advances in both theoretical frameworks and practical methodologies. The recent relevant literature has indicated an understanding of how to value and assess environmental services while incorporating stakeholder perspectives and behavioral insights.

Fisher et al. [55] conducted research on the fundamental work of ecosystem service classification, offering essential definitions and frameworks that help structure the field. Their paper addresses the crucial need for standardized approaches to categorizing ecosystem services, particularly distinguishing between intermediate and final services. This work has proven influential in shaping researchers’ and practitioners’ thinking of environmental valuation.

Liu and Gupta [90] provide an important contribution to the ongoing discourse on uncertainty in hydrologic modeling through their comprehensive exploration of data assimilation frameworks. Despite significant advancements in computational power, observational capabilities, and distributed hydrologic modeling, the authors highlight the constant challenge of properly addressing uncertainties in hydrologic predictions. This challenge, they argue, is key for improving the reliability and practical applicability of hydrologic models, especially in environmental decision-making contexts. The paper consistently categorizes uncertainties into three main types: model structural errors, parameter uncertainties, and data inaccuracies [90]. Structural errors come from inherent simplifications and assumptions in model design, while parameter uncertainties stem from the use of non-measurable or aggregate parameters that inadequately capture spatial and temporal heterogeneity. Data inaccuracies, including measurement and representativeness errors, further complicate modeling reliability. Recognizing the interconnected nature of these uncertainties, Liu and Gupta [90] advocate for a cohesive and integrated approach to their identification, quantification, and reduction.

Prell et al. [16] made a significant methodological contribution by investigating the intersection of stakeholder dynamics and environmental valuation through social network analysis frameworks. Their empirical study highlights the complex interrelationships among stakeholders and demonstrates the analytical utility of network-based methodologies in natural resource governance. Their work acknowledges the evolving sophistication of interdisciplinary approaches in environmental management scholarship [16].

Behavioral aspects of environmental decision-making are observed through Sachdeva et al.’s [57] examination of moral self-regulation and prosocial behavior. Their findings consistently support the hypothesis that moral self-regulation involves additional behaviors based on shifting self-perception. When humans perceive themselves as “too moral”, they may limit further moral actions to balance their own self-concept. By contrast, when their moral identity is threatened, they engage in behaviors that restore a sense of moral adequacy. This dynamic underscores the costs associated with altruistic behavior and the balancing act individuals must perform in order to maintain a comfortable moral self-image [57]. This study also puts forward the understanding of moral licensing, showing that it may lead to non-collaborative or self-serving behavior when humans perceive their moral obligations as fulfilled. This phenomenon has societal challenges, particularly in contexts where altruism is needed [57].

Building on this theoretical foundation, Bagstad et al. [96] sought to examine decision support tools for ecosystem service assessment. Their comparison of 17 different tools offers practical insights into the strengths and limitations of various approaches. The authors pointed out that while many tools show promise, challenges remain in terms of data requirements, technical and computational needs, as well as ease of implementation. Their contribution highlights the gap between theoretical frameworks and practical application, suggesting areas where further development is needed. The findings consistently support the hypothesis that moral self-regulation involves additional behaviors based on shifts in self-perception [96]. When humans perceive themselves as “too moral”, they may limit further moral actions to balance their self-concept. By contrast, when their moral identity is threatened, they engage in behaviors that restore a sense of moral adequacy. This dynamic underscores the costs associated with altruistic behavior and the inherent balancing act individuals must perform to maintain a comfortable moral self-image. The study also puts forward the understanding of moral licensing, demonstrating that it may lead to non-cooperative or self-serving behavior when individuals perceive their moral obligations as fulfilled [96]. This phenomenon has societal challenges, particularly in contexts requiring sustained altruism. Their experimental work reveals interesting and emerging patterns in how moral self-worth influences environmental choices, suggesting that psychological factors play a key role in environmental decision-making [96].

The Sustainable Biosphere Initiative (SBI) by Lubchenco et al. [54] is a leading framework designed to address pressing ecological challenges through a more structured research agenda. The study has been commissioned by the Ecological Society of America, and it emphasizes the need to prioritize ecological research. In turn, this will inform policy and sustainable practices, balancing fundamental ecosystem science with applied science and targeting human–environment interactions and decision-making. The SBI identified three primary objectives: understanding ecosystem functioning, assessing human impacts, and developing strategies for sustainable resource use. The core of the initiative was its support for interdisciplinary approaches, integrating ecology with social sciences and economics to address complex environmental issues in a more comprehensive way [54]. Its focus on ecosystem services and biodiversity conservation has since influenced major frameworks like the Millennium Ecosystem Assessment. The initiative significantly contributed to environmental decision-making, providing a foundation for policies in biodiversity conservation, climate change, and sustainable development. Its promotion of ecosystem services helped embed this concept in research and policy. Furthermore, the SBI fostered collaboration among scientists, policymakers, and communities, enhancing the practical application of ecological science [54].

In a similarly important and highly cited paper, Villamagna et al. [97] introduce a comprehensive framework for analyzing ecosystem service delivery. The authors proposed this to be performed through four interrelated components: capacity, pressure, demand, and flow. Their seminal work addresses the persistent inconsistency in how ecosystem services are conceptualized, measured, and integrated into environmental decision-making. By differentiating these components, the study provides a systematic approach to assess the developing ecosystem services while bridging gaps in existing methodologies. The framework reveals the dynamics between ecological properties, societal demand, and external pressures, emphasizing their impact on service delivery across provisioning and regulating. The paper also highlights the crucial need for consistency in ecosystem services terminology and methodology, especially for regulating services that are often undervalued due to complexities in measurement. Villamagna et al. [97] propose using ecological work—a metric of the effort ecosystems spend to mitigate pressures—as an innovative measure for assessing regulating service flow.

An important paper for the field of environmental decision-making comes from Hoyos [98], who reviewed the current state of environmental valuation using discrete choice experiments, also known as DCEs. The author examines the entire discrete choice experiment process, from survey and experimental design to econometric analysis and welfare estimations. The findings highlight several challenges in DCE methodology, including choice–task complexity, experimental design, and preference heterogeneity. The study also explores frontiers in discrete choice analysis, such as non-linear utility functions, advanced experimental designs, and model estimation techniques for obtaining willingness-to-pay measures [98].

In their academic paper, Bonney et al. [99] aim to review the effectiveness of citizen science projects in enhancing public understanding of science. The authors assess four categories of projects—data collection, data processing, curriculum-based, and community science—assessing their impact on participants’ scientific knowledge, attitudes, and behaviors. While citizen science demonstrably adds valuable scientific data, the evidence regarding its effect on public understanding is mixed, with stronger results observed in knowledge gain than in attitude or behavior change [99]. The authors find that improving project design, implementing robust evaluation methods, and expanding outreach to diverse audiences are crucial for realizing citizen science’s full potential in promoting public engagement with science. This would be particularly important in shifting communities’ behavior as often these types of projects seek to influence policy or local decision-making. In turn, these can also empower communities and individuals to improve their behavior toward the environment [99].

Agrawal’s [100] seminal work on “Environmentality” provides important insights into the relationship between environmental governance and community behavior. Through a detailed study of forest councils in Kumaon, India, Agrawal demonstrates how regulatory practices influence environmental subjects’ formation and behavior. This longitudinal study has been particularly influential in understanding how institutional arrangements shape environmental attitudes and practices over time. The empirical data showed an evolution of community-based forest management, the formation of environmental subjects through regulatory practices, and the long-term effects of decentralized governments [100].

Together, these papers confirm the notion that the field’s evolution toward more integrated approaches that combine theoretical rigor with practical applicability. The literature suggests a growing interest in the complex interplay between social, behavioral, and environmental factors in ecosystem service assessment. While significant progress has been made, opportunities remain for further development, particularly in integrating behavioral insights and improving computational tools for practical application.

This body of research maintains substantial influence on contemporary environmental valuation paradigms, establishing both theoretical frameworks and methodological protocols that inform current research trajectories and practitioner implementations.

Table 8. Brief summary of the content of the top 10 most cited documents globally.

No.	Paper (First Author, Year, Journal, Reference)	Title	Data	Purpose
1	Fisher B., 2009, Ecological Economics [55]	Defining and classifying ecosystem services for decision making	Theoretical data based on existing case studies	The paper explores how integrating stakeholder analysis with social network analysis can improve decision-making and conflict management in natural resource management.
2	Liu YQ, 2007, Water Resources Research [90]	Uncertainty in hydrologic modeling: towards an integrated data assimilation framework	Data modeling through assimilation techniques	This paper advocates for an integrated approach to hydrologic data assimilation, emphasizing the reduction of uncertainty as a dynamic and ongoing process.
3	Prell C., 2009, Society & Natural Resources [56]	Stakeholder analysis and social network analysis in natural resource management	Surveys and social network data case studies	The aim of the paper is to offer a method that practitioners and policymakers can use to measure stakeholder interactions and plan strategies for participatory and sustainable management of natural resources.
4	Bagstad KJ., 2013, Ecosystem Services [96]	A comparative assessment of decision-support tools for ecosystem services quantification and valuation	Descriptive, evaluative, and application-based data	The paper’s aim is to evaluate and compare 17 decision support tools designed for ecosystem service quantification and valuation, helping practitioners choose the most right tool for their specific needs.
5	Sachdeva S., 2009, Psychological Science [57]	Sinning saints and saintly sinners: The paradox of moral self-regulation	Quantitative data based on three experiments	The paper aims to show how moral identity and self-regulation affect behavior, providing insights into designing interventions for fostering cooperative and prosocial actions.
6	Lubchenco J., 1991, Ecology [54]	The sustainable biosphere initiative: An ecological research agenda	Synthetic review of interdisciplinary research challenges	The paper aims to set up research priorities for ecological science, focusing on sustainable approaches to address global environmental challenges and improve human well-being.
7	Villamagna AM., 2013, Ecological Complexity [97]	Capacity, pressure, demand, and flow: A conceptual framework for analyzing ecosystem service provision and delivery	Literature review and component analysis	The paper looks to develop a conceptual framework for systematically analyzing the provision and delivery of ecosystem services, addressing gaps in existing approaches.
8	Hoyos D., 2010, Ecological Economics [98]	The state of the art of environmental valuation with discrete choice experiments	Survey and experimental designWelfare analysis	The paper aims to review the methodologies and applications of discrete choice experiments (DCEs) in environmental valuation. It highlights the growing relevance of DCEs in environmental decision-making and highlights areas for future research.
9	Bonney R., 2016, Public Understanding of Science [99]	Can citizen science enhance public understanding of science?	Synthetic analysis of findings from various studies	The paper is looking to highlight science’s potential to improve public awareness, influence environmental decision-making, and foster science–society relationships.
10	Agrawal A., 2001, Politics & Society [100]	Environmentality: Community, intimate government, and the making of environmental subjects in Kumaon, India	Historical archival analysisField interviewsSurvey dataTemporal analysis	This paper’s aim is to examine how environmental subjectivities (people’s thoughts, beliefs, and actions regarding the environment) are developed and transformed through institutional practices and regulatory mechanisms in Kumaon, India

summarizes the main elements and purpose of the top 10 most cited papers in this field.

3.4.3. Words Analysis

Table 9. The top 10 most frequent words in keywords plus and author’s keywords.

Keywords Plus	Occurrences	Author’s Keywords	Occurrences
Management	157	Environmental decision-making	100
Science	74	Public participation	65
Conservation	71	Ecosystem services	44
Policy	70	Sustainability	41
Framework	66	Decision-making	37
Values	66	Uncertainty	34
Model	64	Climate change	33
Climate-change	59	Environmental justice	31
Biodiversity	37	Sustainable development	31
Public participation	36	Risk assessment	23

contains the most used keywords plus and the author’s keywords, together with their frequency. The difference between keywords plus and author’s keywords has been explained in Table 3. On the left part of the table are detailed the keywords plus, while on the right part are the author’s keywords. In both cases, the terms refer to environmental elements, sustainability, decision-making, or solutions that should be adopted. The most used keyword plus is “management”, which appeared 157 times, followed by “science” (74 occurrences), “conservation” (71 occurrences), “policy” (70 occurrences), “framework” (66 appearances), “values” (66 appearances), “model” (64 appearances), “climate-change” (59 appearances), “biodiversity” (37 appearances), and “public participation” (36 appearances). The terms also explore the conservation process that should be considered to have an environment cleaner, adopting various policies that could be tested using multiple frameworks or models. The management term is correlated with the decision-making process. The most frequently used author keyword is “environmental decision-making”, which appeared 100 times, followed by “public participation” with 65 occurrences, “ecosystem services” with 44 occurrences, “sustainability” with 41 occurrences, and “decision-making” with 37 occurrences. The last five terms have a reduced frequency but are still worthy to be mentioned: “uncertainty” (34 appearances), “climate change” (33 appearances), “environmental justice” (31 appearances), “sustainable development” (31 appearances), and “risk assessment” (23 appearances). The keywords defining the environmental importance currently are decision-making process, sustainability, existing risks, and uncertainty.

Figure 19 contains the word clouds, a graphical representation of the most used terms, which was created using the Bibliohsiny library, which is part of the R programming language [53]. A list of synonyms has been used since similar terms have been used. The term “environmental decision-making” incorporates “environmental decision-making” and “environmental decision making”, while “decision-making” contains “decision-making” and “decision making”. On the left side is the word cloud for the most used 50 keywords plus, which has “management” as the most frequently used term with 157 appearances, followed by “science” with 74 occurrences, “conservation” with 71 appearances, “policy” (70 occurrences), “framework” (66 occurrences), “values” (66 occurrences), “model” (64 occurrences), “climate-change” (59 occurrences), “knowledge” (58 occurrences), and “impact” (48 occurrences). On the right side, the 50 most used author’s keywords are detailed. The most representative is “environmental decision-making”, with a total of 181 appearances, followed by “decision-making” (75 appearances), “public participation” (65 appearances), “ecosystem services” (44 appearances), “sustainability” (41 appearances), “environment” (35 appearances), “environmental management” (34 appearances), “uncertainty” (34 appearances), “climate change” (33 appearances), and “environmental justice” (31 appearances).

In terms of the occurrence of keywords, “management” and “environmental decision making” are the most encountered ones in the word cloud. Following that, the words “public participation” and “conservation” came next. Therefore, there is a strong presence of these words in article publications, showing that this area of research is of strong interest to the academic community. Furthermore, it can also be inferred that public participation is strongly explored, indicating that a study of behavioral shifts is as important as studying the external impact on the environment.

Similar academic papers have been analyzed, and the outcome was comparable with the outcome of this paper. Delesposte et al. [101] explored the multi-criteria decision in sustainable innovations. The most used keywords in the paper are related to decision-making, namely “decision-making”, “decision support”, “sustainability”, “environmental impact”, and “climate change”.

Table 10. The top 10 most frequent bigrams in abstracts and titles.

Bigrams in Abstracts	Occurrences	Bigrams in Titles	Occurrences
Environmental decision-making	698	Environmental decision-making	149
Ecosystem services	222	Ecosystem services	55
Public participation	192	Public participation	48
Climate change	164	Life cycle	27
Impact assessment	103	Impact assessment	23
Decision-making processes	101	Risk assessment	22
Sustainable development	100	Environmental governance	20
Life cycle	99	Climate change	19
Environmental policy	98	Decision analysis	14
Risk assessment	98	Sustainable development	13

includes the most used group of two words (bigrams) in the abstracts and titles. On the left part of the table are detailed the bigrams in abstracts. The most used bigram is “environmental decision-making” with 698 appearances, followed by “ecosystem services” (222 occurrences), “public participation” (192 occurrences), “climate change” (occurrences), “impact assessment” (103 occurrences), “decision-making processes” (101 occurrences), “sustainable development” (100 occurrences), “life cycle” (99 occurrences), “environmental policy” (98 occurrences), and “risk assessment” (98 occurrences). The bigrams can be clustered into two categories, one being related to environment and ecology (“environmental decision-making”, “ecosystem services”, “climate change”, “decision-making processes”, “life cycle”, “environmental policy”,) and the second one to sustainability (“public participation”, “impact assessment”, “sustainable development”, “risk assessment”). On the right part are the most important bigrams in titles. The most used bigram is “environmental decision-making”, which has 149 appearances, while “ecosystem services” appeared 55 times, followed by “public participation” (48 appearances), “life cycle” (27 appearances), “impact assessment” (23 appearances), “risk assessment” (22 appearances), “environmental governance” (20 appearances), “climate change” (19 appearances), “decision analysis” (14 appearances), and “sustainable development” (13 appearances). The bigrams can be clustered into two groups, one referring to the environment and ecology (“environmental decision-making”, “ecosystem services”, “public participation”, “life cycle”, “environmental governance”, “climate change”, “sustainable development”), and the second one presents the technological development and the assessments (“impact assessment”, “risk assessment”, “decision analysis”).

These bigrams reveal a discussion and comparison between ecological and sustainability-focused themes, with a strong emphasis on both environmental processes and assessment tools. Terms like “environmental decision-making”, “ecosystem services”, and “climate change” dominate, reflecting the importance of ecological concerns in the academic discourse, particularly around decision-making frameworks and environmental policies. The frequent appearance of terms such as “public participation”, “impact assessment”, and “sustainable development” indicates a growing recognition of the need to integrate social and behavioral dimensions in addressing environmental challenges. This trend is further enhanced by the presence of “risk assessment” and “decision analysis” in both abstracts and titles, signaling an increasing reliance on analytical tools and data-driven approaches to inform decisions. Together, these bigrams underscore the evolution of environmental research, where a balance between ecological concerns, sustainability, and quantitative assessments is becoming increasingly essential for shaping effective, informed policies and practices.

Table 11. The top 10 most frequent trigrams in abstracts and titles.

Trigrams in Abstracts	Occurrences	Trigrams in Titles	Occurrences
Environmental decision-making processes	48	Life cycle assessment	20
Environmental impact assessment	45	Environmental impact assessment	11
Life cycle assessment	41	Ecological risk assessment	7
Natural resource management	27	Cultural ecosystem services	6
Greenhouse gas emissions	17	Natural resource management	5
Ecological risk assessment	16	Decision support system	4
Analytic hierarchy process	13	Multi-criteria decision analysis	4
Cultural ecosystem services	11	Corporate social responsibility	3
International environmental law	11	Global environmental governance	3
Decision support systems	10	International environmental law	3

incorporates the most used group of three words (trigrams) for abstracts and titles, together with their occurrences. On the left part are the most used abstracts. In first place is “environmental decision-making processes”, which appeared 48 times, while “environmental impact assessment” has 45 appearances, and ”life cycle assessment” has 41 appearances, followed by “natural resource management” (27 occurrences), “greenhouse gas emissions” (17 occurrences), “ecological risk assessment” (16 occurrences), “analytic hierarchy process” (13 occurrences), “cultural ecosystem services” (11 occurrences), “international environmental law” (11 occurrences), and “decision support systems” (10 occurrences). Considering the topic of the trigrams, they can be grouped into two categories, with one related to the environment and ecology, including all trigrams apart from “decision support systems”, which represents the technology and models category.

On the right part, the trigrams in titles with the number of appearances are detailed. The most frequently used trigram is ”life cycle assessment” with 20 occurrences, followed by “environmental impact assessment” (11 appearances), “ecological risk assessment” (7 appearances), “cultural ecosystem services” (6 appearances), “natural resource management” (5 appearances), “decision support system” (4 appearances), “multi-criteria decision analysis” (4 appearances), “corporate social responsibility” (3 appearances), “global environmental governance” (3 appearances), and “international environmental law” (3 appearances). The trigrams can be grouped into three categories. The first category focuses on environmental and ecological areas, including “life cycle assessment”, environmental impact assessment”, “ecological risk assessment”, ”natural resource management”, ”global environmental governance”, and ”international environmental law”. The second category groups the technology and models that can be applied, such as “decision support system” and “multi-criteria decision analysis”. The last category explores the cultural and social responsibility “cultural ecosystem services”, “global environmental governance”.

These trigrams predominantly highlight environmental and sustainability concerns, with an impact on processes such as environmental decision-making and resource management. In turn, this reflects the interdisciplinary nature of research in this domain, underscoring its focus on addressing the underlying causes and challenges. Titles, as observed in this analysis, further diversify the thematic scope of the research by including additional perspectives, such as technology-driven approaches and multi-criteria decision analysis, as well as cultural and social dimensions, such as corporate social responsibility.

The overlap between abstract and title trigrams highlights the importance of impact assessment as a foundational tool alongside behavioral-focused frameworks, signaling a growing global recognition of the role of consumers and society in harnessing pro-environment behavior.

It shall be stated that the selection of bigrams and trigrams follows established bibliometric analyses, optimizing for the trade-off between term specificity and analytical breadth. The use of higher-order n-grams (>4 words) occurs too infrequently for meaningful pattern detection. This approach aligns with methodological precedents in sustainability science, enabling precise identification of interdisciplinary connections between behavioral, technical, and policy-oriented research strands, as observed in other papers. Wang et al. [45] and Delesposte et al. [101] similarly prioritized bigrams/trigrams like “sustainability transition governance” to map interdisciplinary research trajectories, while Bonney et al. [99] employed bigrams to analyze public engagement trends.

3.5. Mixed Analysis

This section explores how the keywords are grouped based on their topics and what is the correlation between universities, authors, countries, journals, and keywords.

Figure 20 grouped the most used 250 keywords plus in different topics, with a label size of 0.3, a minimum cluster frequency per thousand documents of 15, and 3 for the number of labels. The most representative cluster is colored in red and focuses on developing a framework that is designed to include the impact, biodiversity, conservation, and management of environmental areas. The most important terms are “management” (157 occurrences), “conservation” (71 occurrences), “framework” (66 occurrences), “systems” (40 occurrences), “sustainability” (38 occurrences), “biodiversity” (37 occurrences), “uncertainty” (36 occurrences), “challenges” (34 occurrences), “design” (27 occurrences), and “impacts” (27 occurrences). The second cluster, represented by blue, explores the policies, politics, and governance of science and public participation. The most frequently used keyword is “science” (74 appearances), followed by “policy” (70 appearances), “knowledge” (58 appearances), “participation” (45 appearances), “governance” (42 appearances), “public-participation” (36 appearances), “community” (23 appearances), “politics” (23 appearances), “information” (20 appearances), and “power” (19 appearances). On the top left part of the graph is the third most relevant cluster, colored light blue, explaining the attitudes, behavior, perceptions, and values of the green environmental and ecological methods. The most used keywords are “values” (56 occurrences), “behavior” (35 occurrences), “attitudes” (26 occurrences), “perceptions” (21 occurrences), and “green” (19 occurrences). In the bottom part of the graphical representation is the fourth cluster, colored in green, which includes terms related to the impact, performance, and risks of the used models. The terms existing in the green cluster are “model” (64 appearances), “impact” (48 appearances), “risk” (48 appearances), and “performance” (38 appearances). The last two clusters, light brown and pink clusters, each contain two terms and explore the terms “climate-change” (59 occurrences) and “climate-change” (37 occurrences), respectively, and “energy” (31 appearances) and “indicators” (20 appearances).

Based on this analysis, the authors can observe different values for centrality and density. The centrality metric highlights the relevance of keywords in the aforementioned analyzed themes. The density metric calculates the degree to which the research has developed by exploring internal associations of the keywords with the actual topics of the paper. This clustering of the 250 most frequently used keywords provides valuable insights into the focus areas of the academic literature. The findings reveal six different clusters, each defined by a specific keyword, thematic focus, and various levels of centrality and density. These clusters also signal an interconnection between these subfields of research.

The red cluster reflects the importance of developing frameworks for environmental management, the conservation of biodiversity, as well as sustainability. In turn, this also suggests the need to create a more structural approach to address environmental challenges. The blue cluster focuses on policies, governance, and public participation, reflecting keywords such as “science”, “policy”, and “participation”. This signals a reliance on stakeholder engagement and public participation at a policy level.

The light blue cluster focuses on attitudes, behaviors, perceptions, and consumer values. Words such as “values”, “behavior”, and “attitudes” emphasize the psychological aspect of driving an environmental change. Its low centrality but high density suggests that this is a specialized area with well-developed internal associations but limited external connections to the other terms.

The green cluster explores models, performance, and risks, underscoring the technical and analytical aspects of environmental research. Keywords such as “model”, “impact”, and risk point to academic research assessing the effectiveness of various frameworks and methodologies. This cluster has a medium centrality, which signals a moderate relevance across themes and a much less developed internal structure.

The light brown and pink clusters address climate change and energy indicators. The repetition of “climate change” as a term in both clusters shows its critical importance in research, while “energy” and “indicators” signal more specialized academic studies focused on sustainability metrics.

In conclusion, the distribution of centrality and density across these clusters provides a more nuanced understanding of the current state of research. Clusters with high centrality, such as red and blue, are guiding toward broad and impactful themes that connect multiple areas of academic research. In turn, clusters with high density but low centrality, like blue and pink, reflect more specialized yet really well-established subfields.

Figure 21 represents a factorial analysis of the 100 most used authors’ keywords using the multiple correspondence analysis method. The terms were grouped into three different clusters. The most representative is the red one, containing terms referring to “governance”, “resilience”, “decision-making”, “environment”, and “ecosystems”. The second cluster is colored in blue and focuses on the “responsibility”, “intentions”, “planned behavior”, “norms”, and “attitudes” of each member of the society, while the last cluster, represented using green, explores the “lessons”, “experiences”, and “services” of the “economics” area.

From this factorial analysis, the authors can observe that the red cluster is the most representative, focusing on terms such as “governance”, “resilience”, “decision making”, “environment”, and “ecosystems”. This demonstrates the integration of policy frameworks and decision-making processes and methodologies in managing environmental systems as well as building resilience within ecosystems.

The blue cluster focuses on societal and behavioral aspects, noticeable from keywords such as “responsibility”, “intentions”, “planned behaviors”, and “norms”. This reflects research that explores individual as well as collective behavior, values, and norms that can influence environmental and sustainability outcomes. From this, it can be inferred that behavioral and psychological theories, such as the nudge theory mentioned in the Introduction, play a big role in understanding how individuals shape sustainable practices and decision-making processes.

The green cluster addresses the economic dimensions of environmental research with keywords such as “experiences”, “services”, and “economics”. This suggests a focus on economic emulation, cost–benefit analysis, and the application of economic principles to environmental challenges. This cluster also points to an emphasis on using economic insights to guide decision-making and policy development in environmental management.

The thematic evolution, visualized in Figure 22, highlights the trajectory of research themes related to environmental decision-making in three different periods through the use of unigrams extracted from the titles of the papers included in the database.

The 1975–1991 period captures foundational themes, especially in the field of decision-making. During this period, as seen in the graph, the research predominantly revolved around foundational concepts, such as “decision making”, “environmental”, “management”, and “approach”. These thematic titles are reflective of the efforts of integrating decision-making into environment-related fields. Behavioral economics was emerging as a research field, and so its core principles—such as bounded rationality and cognitive biases—were beginning to influence how decisions were conceptualized [102].

The second period, 1992–2011, saw a thematic expansion of the titles in areas such as “assessment”, “ecosystem”, “social”, and “participation”. This shift can be indirectly related to the growth of behavioral economics research, including the recognition of the social and ecological dimensions of environmental decision-making. The field of behavioral economics contributed a large amount to this by examining how cognitive biases, such as optimism bias and present bias, influenced environmental policy design. Some key insights from behavioral economics in this phase are social norms, which play a role in social influences in driving eco-conscious behavior, such as participation in conservation efforts or adopting sustainable practices [103].

In the third period, from 2012 onwards, title themes such as “sustainability”, “decisions”, “conservation”, and “water” also appeared. This could reflect a more integrated approach that combines both behavioral insights with sustainability goals. In line with the evolution of behavioral economics, nudges, and defaults emerged as a framework to shape decision-making. This perspective has been key in designing policies that are in line with behavior and drive conservation efforts [104].

In order to have a more faceted analysis of the selected domain and due to the fact that the selected keywords for extracting the dataset are mainly related to Sustainable Development Goal (SDG) 13: Climate Action, the number of papers connected to this SDG has been extracted from ISI WoS, and a comparative evolution between the overall number of papers and the papers associated with SDG 13 has been conducted. Figure 23 presents the evolution of the two-mentioned indicators. From Figure 23, a particularly significant increase in the number of papers can be observed after 2015, when the Paris Agreement raised the overall awareness of climate change and sustainability. This was also the year in which international policy efforts started to be seen at a global level. As previously noted, the number of publications has continued to increase in the period analyzed. Interestingly, it can be observed that the number of papers associated with SDG 13 has followed the same trajectory, with a significant number of papers being related to this SDG from the total number of papers, highlighting once more the interest of the academic community toward the SDGs remaining strong.

Figure 24 combines the countries, authors, and sources to provide an overview of all three elements. The most important countries from the perspective of the number of publications are the USA, Germany, and Canada. At the same time, Satterfield T., Newig J., and Jager NW. are the primary authors who published in Environmental Management, Society & Natural Resources, and Sustainability.

Figure 25 defines the combination of universities, authors, and keywords. The most representative affiliations are Michigan State University, the University of British Columbia, and the University of Washington. At the same time, the most significant authors who contributed to the analyzed areas are Dietz T., Satterfield T., and Huang GH, who explored decision-making, sustainability, and public participation.

4. Discussion and Limitations

This section provides a summative discussion related to the bibliometric analysis conducted in this paper, an analysis of some of the leading research topics that can be encountered in the selected documents, and this study’s limitations.

4.1. Discussions on the Bibliometric Analysis

Bibliometric analysis provides a rich assessment of the evolution of eco-conscious behavior and environmental decision-making. The analysis begins in 1975, the year of the first publication relevant to ecological decision-making. However, driven by behavioral science and technological advancements, the field has grown exponentially since the 2000s.

There has been a positive trend during the analyzed time, showing the continuous interest in growth in sustainability, environmental decision-making, and behavioral shifts. The peak in the number of papers was achieved in 2024, with 95 articles in total.

Several journals have been key in sustainable behavior and environmental decision-making. Environmental Management, the Journal of Environmental Management, and Environmental Science & Policy are among the most important.

The research area of environmental decision-making and eco-conscious behavior has increasingly attracted interest, especially in the last ten years, following a big focus on net-zero and carbon neutrality, predominantly in the US and the UK.

While the U.S and U.K. dominate research output as presented in this study, this pattern correlates but does not causally derive from their net-zero policy agendas. The prominence of English-speaking nations and China likely reflects systematic factors, including linguistic dominance in academic publishing (85.5% of analyzed papers are single-country publications from Anglophone nations), historical research infrastructure, and funding allocation (for example, the U.S National Science Foundation grants for sustainability science) and database indexing biases favoring English-language journals. China also appears prominent due to its inclusion in the top five, aligning with its strategic investments in sustainability R&D—though this is not directly measurable through bibliometric data.

The most representative countries based on the number of publications are the USA, the UK, Australia, Canada, and China, with various articles published using either local authors or international collaboration.

The existing body of research provided essential details about eco-conscious behavior and environmental decision-making, offering a good perspective on the evolution of this field. However, it is necessary to recognize and discuss the limitations that impacted the research and the findings.

4.2. Research Directions

This section discusses some of the leading research directions identified in the papers included in the dataset.

4.2.1. Organizational and Consumer Decision-Making

The sustainability and environmental decision-making sectors have developed in the last few years, partially thanks to technological advancements, which help implement new and sustainable solutions for various industry sectors. This study has looked at several seminal papers to support this claim, as detailed in the following section.

For example, fast-food chains have developed significantly in the last few years, with social media representing one of the main communication methods with clients. Liu and Jiang [105] explored the conversation about sustainability and green values in sustainable actions. The data that were collected in the study were from a fast-food company established in Malaysia. The outcome of the research confirms that the sustainability discussion of fast-food restaurants contributes to the increase in the eco-conscious behavior of clients, thanks to the psychological factors, one of the most representative being responsibilities, which is part of green values. In addition, it shows how social media contributes decisively, promoting the sustainability values of the fast-food chain much more quickly [105].

Social, governance, and environmental metrics are used as methods for quantifying organizational sustainability performance. Luque-Vilchez et al. [106] focus on European food companies’ social and ecological aspects, governance, and how to achieve sustainability goals. The study’s analysis shows numerous differences in the organization depending on the employee’s job, but the outcome confirms that improving communication and transparency with stakeholders is mandatory.

For example, based on consumer behavior in more cultural organizations, Han et al. [107] have investigated the customer approach and intentions for eco-friendly products available in the museum from social, environmental, and ecological perspectives. The nature of the product is strongly correlated with a feeling of quality and pride, which is the main factor leading to visits, payments, and word-of-mouth. At the same time, social pressure plays a crucial role in relationship quality. The model that has been defined was tested, resulting in high accuracy [107].

On a different spectrum, the engagement between investment behavior and sustainability priorities of mutual contributions have been investigated by Lofgren and Nordblom [108], exploring the survey data of Swedish investors. Most respondents tend to minimize the returns for a sustainable investment, which describes the differences among behavior and preferences. The best examples that confirm the discrepancies occur when financial decision-making should be taken. In general, investors who are more interested in sustainability are less aware of the potential investment, leading to biases between preferences and behavior [108].

The financial, environmental, and normative information in organizations that are active in the energy sector has been investigated by Hafner et al. [109], with a focus on decision-making behavior. A case study focused on 599 non-student participants from the United Kingdom who had to choose between an efficient energy solution, such as a heat pump, or a standard heating system, such as a gas boiler, without providing any other information. Surprisingly, only 32.5% of the participants preferred the heat pump, but the percentage would have increased if more information had been given. The normative information that was offered could have a significant impact on people’s behavior [109].

In the next section, leading research will be discussed around risk in environmental and business contexts.

4.2.2. Risk in Environmental and Organizational Context

In a leading paper, Grumann et al. [110] proposed a case study for renewable energy investments, which is sometimes considered a high-risk technology. The scope of the research is to determine the potential risks of investors in the green finance sector; define multiple case studies for renewable energy sources and possible risks to reduce the gap in the literature; and evaluate press articles, financial reports, and any online information. The outcome confirms the growth of the green finance risk by companies’ risks, operational risks, financial instrument risks, or renewable energy projects, representing potential alerts for future investors. The authors also provided methods to mitigate the risks, promoting multiple development methods.

Furthermore, due to the population increase expected to reach approximately 9.6 billion around 2050, Krimi and Al-Aomar [111] pointed out that companies should achieve sustainability and resilience to implement the latest, most effective technologies and expand capacity. The decisions could play a decisive role in the market, leading to a competitive advantage. A deep delft into the primary industries has been carried out, defining the sustainable and resilient impediments and how to mitigate them. The main objective was to define a framework focusing on the chemical industry, presenting multiple scenarios and explaining the leading solutions to achieve sustainability and resilience goals [111].

As this area of research grew, more frameworks emerged. In their study, Alriksson and Filipsson [112] have implemented and considered green marketing a competitive advantage. The paper focused on the Swedish steel sector, which has evolved significantly, implementing various environmental solutions such as energy efficiency or recyclability, reducing the impact on the ecosystem. To better understand the risks and personal problems in daily work, the employees in the Swedish steel industry were interviewed. The 38 employees suggest that carbon dioxide, dioxin, and non-renewable energy represent the main worries [112].

The petrochemical sector has been investigated by Verbeek [113], exploring the risks and the level of acceptance, considering the environmental and economic concerns. The study focused on the Antwerp petrochemical complex, which is the largest in Europe. The residents participated in multiple interviews and surveys regarding the environmental and public health risks. Most of the participants are aware of the potential consequences of the petrochemical complex. Still, at the same time, the population accepts the factory because it provides socio-economic advantages, which is the main factor of the community. In the end, the research is presented as a quantitative exploration of the communities that live around an industrialized area and highlights the acceptance of industrial risk for the academic community [113].

4.2.3. Pollution and Challenges in Sustainability Management

In their paper, Murdock and Sexton [114] have examined pollution prevention, focusing on a project called Good Neighbor Dialogue. In this project, the communities and local factories are from Minnesota. The authors provided multiple cases of successful and unsuccessful examples with different companies, where companies were open to discussing and negotiating with the community or not, and on the opposite side, not engaging. The companies understood the importance of the environment and the community’s needs and welcomed solutions for pollution prevention and methods to control emissions values. In a similar research area, a detailed analysis of the wastewater industry sector has been performed by Beavis and Lundie [115], expressing the need for a decision-making tool that can assist the non-financial cases, exploring the plant-specific methods, effluent quality, and supporting steps of a plant. The authors defined two case studies on wastewater treatment. The results showed that life cycle assessment significantly influences the decision-making and treatment process, and the non-financial drivers behind this were analyzed. In another paper, Wakefield and Elliott [116] evaluated the effects of landfills on Ontario communities from an environmental perspective, highlighting the main risks. The researchers confirmed that communities’ and individuals’ well-being can be influenced in the same manner as the decision-making process or the outcome of the choice. A case study in Ontario, Canada, has been performed, exploring two landfill sites. A total of 36 interviews have been conducted to understand the individuals’ experience with a local landfill plan and the behavioral effects of the individuals regarding the community, implementing risk society theory. The results express the necessity of a sensitive balance between decision-making processes and communities, the risks of mistrust, the lack of ontological security, and the loss of control.

Ruparathna et al. [117] explored the environmental impact of the buildings, considering the actual decision-making processes as inefficient in combining future technological development and ecological demands. The authors defined a multi-period asset management solution that minimizes the life cycle costs by climate change objectives. The risks have been prioritized, and the risk value has been calculated to identify the risk capital strategy. The approach has been tested successfully on a British Columbian central building. The outcome shows that the scenario of great transitions (the future technologies will reduce the energy demand between 10% and 25%) will provide the most minor financial risk [117].

4.2.4. Sustainability in Supply Chain

Another sector that has been influenced by behavioral shifts is the supply chain and logistics industry. Cruz and Matsypura [118] have evaluated the companies’ responsibilities in the environmental decision-making processes by implementing a framework for modeling supply chain networks. Sustainability in the supply chain is an important area, and it was included to obtain the optimal conditions for maximizing the net returns and minimizing the emissions based on the supplier’s behavior (manufacturers, retailers, or consumers). It has been observed that social responsibility increases when transaction costs, risks, and waste are reduced. The equilibrium state has been defined for the supply chain network to achieve the research goal, which can be further implemented in real case studies [118].

The supply chain network has a high volatility that has been investigated from investment in sustainability, consumers’ willingness to pay, and external cost perspectives by Li and Cruz [119]. Due to the constraints in the supply chain area, the authors developed an optimization method that evaluates decision-makers’ interactions and defines the equilibrium for prices, inventory, transactions, productions, and sustainability levels. During the implementation phase, numerous simulations were conducted to better understand the metrics (production capacity, net present value, externality cost, and others) [119].

In their paper, Boutkhoum et al. [120] defined a multi-criteria decision-making framework to implement green supply chain management methods sustainably. The authors have described multiple papers published in green supply chain management, promoting new manufacturing methods and environmental strategies. The researchers have also created a multi-criteria decision-making model that combines fuzzy and TOPSIS. The outcome was tested in the chemical sector for a Morocco-based company, showing its practical applicability [120].

4.2.5. Methodologies and Decision-Making Frameworks in Sustainability Research

Throughout the analysis of the papers in the dataset, methodologies and decision-making frameworks have emerged. For example, the management of sustainable development, together with the impact of stakeholders in hydropower, has been explored by Watkin et al. [121], focusing on the potential challenges that could appear for a small hydropower evolution from the stakeholder perspective and how it can influence the decision-making. The stakeholders generally focus on economic elements rather than environmental and social aspects, where the costs are more important than the profit, introducing a level of bias in the analysis. The authors concluded that there needs to be a mandatory equilibrium between social, economic, and environmental aspects [121].

Yeh and Xu [122] implemented fuzzy multicriteria to present sustainable e-waste recycling processes and evaluate alternative methods, considering sustainability performance and economic, social, and environmental metrics. The authors conducted several simulations to identify the optimum weights for each feature, describing the methodology for planning decisions. At the end of these simulations, the defined model was applied to a case study [122].

Pellegrini et al. [123] have described the relationship between the intention to implement sustainable behavior and the employee’s perception of resource practices. The authors have included an equation model that combines the employee’s perception with the company’s sustainability objectives, reward systems, training, and support for sustainable behavior. If the line managers promote the idea, the employees will consider sustainability more relevant, resulting in a higher desire to implement sustainable behavior. Cox and Ricci [124] evaluated environmental decision-making in health-risk assessment. The research explored the mathematics and statistical case studies of human health risks and how to mitigate them. The outcome confirmed that the approach should combine the latest technologies and probabilistic theory. In some situations, probabilistic techniques are no longer suitable and generate errors mainly because of the uncertainty level and the lack of information [124].

Multi-criteria decision-making (MCDM) methods are increasingly used to address complex challenges, with sensitivity analysis gaining importance for assessing robustness, as Demir et al. [125] detailed. The analytic hierarchy process is identified as the most widely used decision model in uncertainty, according to Paula et al. [126]. China leads in article publications and scientific collaborations [125,126]. Key themes include decision models and frameworks for sustainable logistics, with carbon footprinting as a prominent issue, as Qaiser et al. [127] explored in their article. Future research opportunities lie in developing more effective solutions using various MCDM methods and DSS configurations while considering all aspects of sustainability [1,127].

4.3. Analysis Overview

While many bibliometric studies have provided descriptive overviews of publication trends—such as citation counts, journal impact, and geographic distribution—these analyses often stop at summarizing data without an overview of the underlying drivers or putting the information in a specific context. In the case of the present paper, we have tried to bring evidence from similar papers, when available, to provide a better understanding, and a discussion has been provided, when possible, regarding the identified trends and their specific factors.

Furthermore, this research offers a different perspective than traditional bibliometric analyses by considering how various factors could shape the production of the research papers associated with the field. For example, a spike in publications from a particular country might coincide with government initiatives aimed at sustainability or recent private sector investments in renewable energy, as seen in the examples provided in Figure 22. This framework enables future directions of research and hypotheses, such as linking the emergence of innovative methodologies such as “behavioral interventions” to shifts in public perceptions and policy framework.

This paper focused on understanding the evolution and growth of behavioral shifts and decision-making trends through existing research by connecting various elements provided by the bibliometric analysis. The combination of graphical data visualization has been used to explain the topic of the evolution of the fields, evolving from a limited domain to a popular research field. This conclusion has been drawn as the evolution of the papers shows a positive trend from 1990 to 2025. At the same time, due to the high timespan, several limitations have occurred and might affect the results, in general referring to the papers published before 1990.

In addition to the bibliometric analysis, this manuscript also reviewed the ten most cited documents, delving deeper into the seminal studies, and has provided a series of research directions—identified based on the papers included in the dataset—through which a better understanding of the field has been aimed.

4.4. Limitations

A significant limitation of this paper is rooted in dataset comprehensiveness. Firstly, the choice and reliance on a single dataset introduces constraints and can lead to incomplete coverage of the literature. While WoS is one of the most significant and reliable academic tools, excluding the other databases may impact the size and diversity of the selected dataset. The selection of keywords such as “eco-conscious behavior” and “environmental decision-making” may have unintentionally excluded studies that follow alternative terminologies or focus on themes relevant to sustainable decision-making. Furthermore, the predefined search criteria applied during extracting and selecting papers from WoS present another set of limitations. Only papers marked and indexed as “journal article” in the Web of Science (WoS) databases were reviewed and analyzed, including both journal and conference papers. This choice introduces a potential bias due to differences between Scopus and WoS databases, as highlighted by Singh et al. [27]. Web of Science coverage has consistently improved since 1990, featuring papers written in English and indexing 13,610 journals with just over 13 million publications as of June 2020. This comprehensive coverage typically results in a higher impact on WoS articles.

In contrast, Scopus indexes a broader array of journals and articles, with around 40,835 journals and 18 million papers as of June 2020. Still, the impact of Scopus-indexed journals is generally low compared to WoS. The decision to exclude Scopus-indexed journals from this bibliometric analysis may have impacted the results, potentially overlooking significant contributions from a bigger pool of sources. The temporal scope of the dataset excludes publications from 2023 due to incomplete indexing at the time of analysis. In turn, this may have limited the capture of emerging trends or recent advancements in sustainability research, particularly the advancements in renewable energy. Methodologically, reviewing only the top ten most highly cited articles might have overlooked less popular but innovative studies in similar areas like behavioral interventions for climate action and environmental cognitive biases.

Grouping documents from multiple databases is possible, but it is essential to mention that various disadvantages affect the results. First, the investigation of keywords plus a unique indicator provided exclusively by the WoS database, such as the factorial analysis, thematic map, or word clouds, could not have been carried out. Second, there is a high chance of errors in the database since the same article might be included in multiple databases, resulting in various citations, as Chemali et al. [128] discovered in their paper.

5. Conclusions

The scope of the analysis was to obtain the most important contributions regarding sustainability, environmental decision-making, and behavioral shift domains using scientific questions from existing academic papers. Numerous graphs and tables were presented and explained during this research, extracting relevant metrics that helped us achieve a clear perspective on the behavioral shifts and decision-making process. Thanks to the bibliometric approach used on the extracted papers from the WoS database, the most important authors, countries, and affiliations have been discovered, together with the collaboration between researchers, providing an overview of how the domain evolved from 1975 up to 2024. This research aims to respond to the scientific questions that have been included in the first section of this document regarding the paper submissions and the most relevant countries, authors, and journals.

Considering the findings that have been detailed in the research, we determined the following:

• The first article was published in 1975, and up to 1992, productivity was reduced, publishing a maximum of four papers. The trend increased starting in 1993 when 13 documents were released, and there were two periods when production decreased, such as 2005 or 2014, with 24 and 42 papers published. The peak was achieved in 2024 when 95 articles were published, showing the continuous interest of the researchers in sustainability, environmental decision-making, and behavioral shifts;
• The most important country, based on the number of publications and citations, is the USA, which has 1080 documents and 17,260 citations. The UK follows by a significant margin with 321 articles and 7002 citations, while Canada is third with 285 papers and 3348 citations;
• Taking into consideration the number of publications, the most important researchers are Han H (total citations per year of 13.1 and a fractionalized article value of 2.40) and Huang GH (total citations per year of 3.38 and a fractionalized article value of 2.78), each with eight papers, followed by Newig J. (total citations per year of 2.62 and a fractionalized article value of 1.73) and Yeomans JS (total citations per year of 1.29 and a fractionalized article value of 4.25), with seven documents each;
• The most productive journal that has published papers in the area of environmental decision-making—from the point of view of the number of published papers—is Environmental Management, with 31 papers. In second place is the Journal of Environmental Management, which has 26 documents, followed by Environmental Science & Policy, which has 25 articles. The fourth place is occupied by the Journal of Cleaner Production and Sustainability, with 23 publications each;
• Furthermore, it has been observed from the analysis made through the use of thematic map evolution in titles that the progress of themes is in line with the growth from foundational concepts to a more integrated approach, partially driven by the evolution of understanding behavioral economics and decision-making.

Moving beyond the summary of the empirical data presented in this study, the findings indicate that, although seminal papers have played a foundational role in shaping the conceptual development of ecosystem service assessment, many of their methods and theoretical contributions have not been widely adopted in subsequent research. This discrepancy may be partially explained by evolving social norms, shifting policy priorities, and regional economic changes that alter both the focus and reception of environmental research. From a behavioral economics perspective, these changes highlight the importance of understanding stakeholder behaviors and policy impact as integral components of the evolution of research. Following from this bibliometric analysis, future research should focus on the following:

• Integrating disciplinary methods, particularly drawing from behavioral economics, to capture the nuanced ways in which consumer behavior and policy framework influence research trends in environmental decision-making;
• Exploring regional or topical shifts in the literature as reflections of broader social and economic changes and examining why certain topics or regions that were once prominent have decreased over time.

By addressing these areas, future research can offer more precise guidance for environmental decision-making and contribute to a more coherent, theoretically grounded framework for ecosystem service delivery. This approach not only enriches the understanding of past and present research trends but also lays the groundwork for more impactful papers.

Future research will integrate multiple databases, including non-English papers that have been utilized in this paper, and investigate the impact of policies on sustainability and behavioral shifts.