A scientometric review of global research on sustainability and project management dataset

There are few works that have attempted to map the global research on sustainability and project management. This research utilizes scientometric review of global sustainability and project management research in 2006–2018, through co-word analysis, co-author analysis, journal analysis, institution analysis, and country analysis. A total of 400 bibliographic records from the Web of Science and Scopus core collection databases were selected and analyzed. The findings reveal an evolution of the research field based on the concepts in the Brundtland Commission report to considering sustainability Triple Bottom Line in project management activities. The purpose of this data article is to provide an understanding of the status quo and the trend for research on sustainability and project management in the world.


a b s t r a c t
There are few works that have attempted to map the global research on sustainability and project management. This research utilizes scientometric review of global sustainability and project management research in 2006e2018, through co-word analysis, co-author analysis, journal analysis, institution analysis, and country analysis. A total of 400 bibliographic records from the Web of Science and Scopus core collection databases were selected and analyzed. The findings reveal an evolution of the research field based on the concepts in the Brundtland Commission report to considering sustainability Triple Bottom Line in project management activities. The purpose of this data article is to provide an understanding of the status quo and the trend for research on sustainability and project management in the world.

Data
The data is presented as a bibliometric dataset originated from 400 bibliographic records extracted, selected and refined from the Web of Science and Scopus core collection databases.
The data presents the evolution of the research field based on the concepts from the Brundtland Commission report to considering sustainability Triple Bottom Line in project management activities.
The scientometric data is presented trough combined information as tables, graphs and figures as networks and density maps, presenting a map of global research on sustainability and project management, and the key players on this subject area in 2006e2018: Fig. 1. Presents data on the evolution of the publication of research articles. Table 1. Searches executed on SCOPUS and WOS data bases; Fig. 2. Database refinement; Table 2. 17 most frequent words; Fig. 3. Most frequent words. Table 3. 17 most frequent co-occurring keywords; Fig. 4. Network of co-occurring keywords; Fig. 5. Item Density Visualization of co-occurring keywords; Table 4. The top 21 most productive authors; Table 5. The top 15 most productive co-authors; Fig. 6. Network Visualization of co-authorship; Table 6. The top 10 source journals; Table 7. The top more active institutions x country; Table 8. List of authors/articles x number of times the keyword codes (Green Project or Sustainable Project), were referenced; Table 9. List of authors/articles x number of times the keyword codes (Sustainable Project, Green Project, Project Management Methodology and Project Success), were referenced; Table 10. List of authors/ articles x number of times the keyword codes (Lean Six Sigma, Project Management Methodology, Project Success and Sustainability), were referenced.

Data collection
The majority of databases search realized, return a huge number of publications, in this work we've followed a methodology proposed by Treinta et al. [1]. After evaluating basic concepts related to sustainability and project management, the following retrieval codes were used on both database collections (Table 1.) to identify only document type articles written in English: 1-("project management" and ("methodology" or "lean six sigma" or "success" or "green project") and 2-("sustainability" and ("green project" or "triple bottom line" or "carbon footprint" or "global reporting initiative" or "integrated reporting"). Were excluded from the data, articles from the following subject areas considered irrelevant to sustainability and project management: 1-SCOPUS ("medicine", "agriculture", "chemical engineering", "arts and humanities", "psychology", "biochemical", "physics", "chemistry", "nursing", "health", "pharmacology", "immunology", "veterinary", "neuroscience", and 2-WOS (industrial relations labor, instruments instrumentation, ergonomics, mathematical, computational Specifications Value of the data The set of scientometric data presented in the article allows researchers and other interested parties, to reach easily articles, authors and journals, as well as to present the views and tendencies of the main researchers working with sustainability and project management. The dataset integrates recent and updated information with knowledge on sustainability and project management subject, adding more context to the data, providing support for future researches.
The dataset also provides information that will help to analyze the evolution of sustainability and project management research data in terms of co-word analysis, co-author analysis, journal analysis, institution analysis, and country analysis. The dataset highlights the articles addressing sustainable project and project management methodology.
biology, nursing, meteorology atmospheric sciences, engineering chemical, pharmacology pharmacy, hospitality leisure sport tourism, psychiatry, psychology experimental, statistics probability, surgery, thermodynamics, food science technology, agricultural economics policy, biochemical research methods, chemistry multidisciplinary, psychology social, immunology, international relations, agriculture multidisciplinary, linguistics, biodiversity conservation, mineralogy, oncology, forestry, physics applied, geosciences multidisciplinary, psychology applied, radiology nuclear medicine medical imaging, social issues, psychology multidisciplinary, social sciences biomedical, social sciences mathematical methods, social work, health care sciences services, sociology, health policy services, agronomy, veterinary sciences, art, virology, biotechnology applied microbiology, anesthesiology, medical informatics, archaeology, chemistry analytical, biochemistry molecular biology, chemistry applied, humanities multidisciplinary, criminology penology). A total of 7055 articles were extracted and were exported and uploaded on EndNote® software, where we followed the following steps described on Fig. 2. in order to refine this database collection.
The Figures: 4-Network of co-occurring keywords; 5-Item Density Visualization of co-occurring keywords and 6-Network Visualization of co-authorship, and Table 3-17 most frequent cooccurring keywords were generated using VOSviewer®.
At the end of this refinement process, a total of 400 bibliographic records were selected as the final database collection for considering in our analysis.
The EndNote software permits that a database collection be exported in different output styles. We've executed a complete database export in.xml form and imported it on Microsoft Excel. Microsoft Excel was used to support the data totalization and information formatting for articles x year, most productive authors, co-authors and top source journals. To support our bibliometric analysis, we've also selected NVivo -the most used qualitative and mixed-methods data analysis software tool and VOSviewer -a software tool for constructing and visualizing bibliometric networks. These networks may for instance include journals, researchers, or individual publications, and they can be constructed based on citation, bibliographic coupling, co-citation, or co-authorship relations.
With NVivo we executed the functions: a e "Word frequency", to identify the most frequent words with minimum length of 7 letters, thus generating a "word cloud"; b e "Text search" for the same keywords used as retrieval codes for the databases, saving the data as codes for these keywords; c e  SCOPUS "project management" AND ("methodology" OR "lean six sigma" OR "success" OR "green project") /Document type: article /Language: English MEDI" OR "AGRI" OR "CENG" OR "ARTS" OR "PSYC" OR "BIOC" OR "PHYS" OR "CHEM" OR "NURS" OR "HEAL" OR "PHAR" OR "IMMU" OR "VETE" OR "NEUR" 3929 2nd WOS "project management" AND ("methodology" OR "lean six sigma" OR "success" OR "green project") SCOPUS "sustainability" AND ("green project" OR "triple bottom line" OR "carbon foot print" OR "global reporting initiative" OR "integrated reporting") /Document type: article /Language: English "AGRI" OR "ARTS" OR "BIOC" OR "CENG" OR "MEDI" OR "CHEM" OR "PSYC" OR "IMMU" OR "MULT" OR "HEAL" OR "NURS" OR "NEUR" OR "PHAR" OR "PHYS" 924 4th WOS "sustainability" AND ("green project" OR "triple bottom line" OR "carbon foot print" OR "global reporting initiative" OR "integrated reporting")

Words and keywords frequency
This dataset took into account the words and keywords frequency in order to allow the comparison between terms used inside the full text with the authors keywords included on titles and abstracts.
For word frequency analysis, we've chosen NVivo software function "word frequency query", selecting words with minimum length of 7 letters and restricting to display only the 1000 most frequent. The decision of choosing words with minimum length of 7 letters was taken, in order to avoid the inclusion of adverbs and pronouns on the data retrieved, prioritizing substantives and adjectives that are more representative of the data content. This function lists the most frequently occurring words or concepts, in our research we've applied over all articles PDF files. We can see this data on Table 2., it displays a list of the 17 most frequent words and the number of occurrences, and on Fig. 3. "Word cloud view", it displays up to 100 words in varying font sizes, where frequently occurring words are in larger fonts. For keywords frequency analysis, we've chosen VOSviewer software function "create a map based on bibliographic data", þ type of analysis; "co-occurrence" þ unit of analysis: "keywords", þ counting method: "full counting", þ minimum number of occurrences of a keyword: "2", and number of keywords to be selected: 500. The keywords are extracted from the titles and abstracts of each article. We can see this data on Table 3., 17 top keywords and number of occurrences and on Fig. 4. "Network of cooccurring keywords". In co-occurrence analysis of keywords, the relatedness of items is determined based on the number of documents in which they occur together. The higher the number of cooccurrence of two terms, closed they will be located close to each other on the map.
In the network visualization, items are represented by their label and by default also by a circle. The size of the label and the circle of an item is determined by the weight of the item, this indicates the number of publications that have the corresponding term in their title or abstract. The higher the weight of an item, the larger the label and the circle of the item. For some items the label may not be  displayed. This is done in order to avoid overlapping labels. The color of an item is determined by the cluster to which the item belongs. Van Eck NJ and Waltman L [2]. VOSviewer has grouped the terms into ten clusters, of which three are of significant size. The red cluster consists of sustainability terms. The yellow cluster covers terms related to sustainable development, the blue cluster consist of terms related to project management. The green cluster presents the keywords that appear less frequently.
On Fig. 5. We have "Item Density Visualization of co-occurring keywords". In this visualization, colors indicate how nodes are distributed in the two-dimensional space underlying the visualization. The density visualization allows one to immediately identify dense areas in which many nodes are located close to each other. Van Eck NJ and Waltman L [4].
The larger the number of items in the neighborhood of a point and the higher the weights of the neighboring items, the closer the color of the point is to yellow. On the opposite, the smaller the number of items in the neighborhood of a point and the lower the weights of the neighboring items, the closer the color of the point is to blue. Van Eck NJ and Waltman L [4].
The keywords in red color area that appear more frequently: 1-sustainability, 2-project management and 3-sustainable development, each one pertains to the three higher clusters. These keywords are part of the core keywords in our research, we can also observe that sustainability is closer to sustainability reporting, integrated reporting and triple bottom line and project management is closer to construction projects and construction industry, but green buildings that pertains to the same cluster, has a lower weight. Table 4  A co-authorship network was generated using VOSviewer, for authors with a minimum of 2 articles, is presented in Fig. 6., where we could identify 72 authors, divided in 41 clusters or a research community. Each circle/node represents a researcher, large circles represent researchers that have many publications. Small circles represent researchers with only a few publications. In general, the closer two Table 9 List of authors/articles x number of times the keyword codes (Sustainable Project, Green Project, Project Management Methodology and Project Success), were referenced.

Table 10
List of authors/articles x number of times the keyword codes (Lean Six Sigma, Project Management Methodology, Project Success and Sustainability), were referenced.
researchers are located to each other in the visualization, the more strongly they are related to each other based on bibliographic coupling. Van Eck NJ and Waltman L [3]. The colors indicate the strong collaboration stablished between the researchers as the circuit of Erikssom D., Ferro C., Hogevold N. M., Padin C., Svensson G., Valera J. C. S. and Wagner B., that is the largest community presented. The second largest community includes the researchers Chan E. H. W., Chau C. K., Lam P. T. I. and Pon C. S.. Table 6 presents the top 10 source journals for sustainability and project management. Journal of Cleaner Production, published in Netherlands occupied the top position and published 38 articles (9,5%), followed by International Journal of Project Management (13 articles), published in United Kingdom and Business Strategy and the Environment (12 articles), published in United States. Out of the 10 journals, five journals are published in United States. Table 7 presents the contribution of Institutions and country from the 10 Top more productive authors and co-authors on sustainability and project management. Table 8, presents a total of 57 the records of authors/articles that referenced keywords code (Green Project or Sustainable Project). Table 9, presents the authors/articles that referenced keywords code (Sustainable Project, Green Project, Project Management Methodology and Project Success), the only authors x articles that referenced all of these keywords together are: Kivila, J., Martinsuo M., Vuorinen, L. "Sustainable project management through project control in infrastructure projects" e 2017; Silvius G. "Sustainability as a new school of thought in project management" e 2017; Verba Y. S., Ivanov I. N. "Sustainable Development and Project Management: Objectives and Integration Results" e 2015 and Schipper R., Silvius G. "The sustainable project management canvas" e 2017. Table 10, presents the authors/articles that referenced keywords code (Lean Six Sigma, Project Management Methodology, Project Success and Sustainability).