# Knowledge Mapping of Green Technology Visualization with Bibliometric Tools

Authors: Shiliang Xia; Kaiyang Zhong
Journal: Scientific Programming
 (2021)

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## Abstract

An increasing number of research literature studies about green technology have been accepted by journals of different disciplines due to the rapid technical progress and innovation in all types of industry. This study uses bibliometric tools of CiteSpace and VOSviewer to analyse the key authors’ co-citation network, institution cooperation, the keyword clusters of green technology, and the evolution trend of green technology. We find that since 1960s, the number of research papers with green technology theme has been growing. These papers are mainly involved in fields of economics and business, engineering, and chemistry, in which there exist 13 highest cited papers from 2009 to 2020 based on the Web of Science database. In this study, we find the top 20 journals of green technology with the parameter of literature count and centrality. We find that the cooperation of authors is quite weak with the co-authorship analysis, and we obtain the top 12 institutions in 15 countries dominantly in green technology research through country and institution analysis. We conduct a cluster analysis of keywords related to green technology, and we obtain 10 clusters, with three economical clusters, five engineering clusters, and two chemical clusters. Finally, we summarise green technology with the aid of the timeline view function of CiteSpace system.


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## Body

## 1. Introduction

The concept of green technology was put forward in the 1960s due to the social appeal of saving resources and energy consumption, less pollutive output, and less damage to the ecological circle [1]. With the sustainable and ecological revolution of the modern industry, similar concepts of environmental sound technology and ecological technology have been created to conform with technical civilisation. Nowadays, green technology has been widely accepted in different disciplines of philosophy, natural science, economics, and management; however, green technology research has focused quite differently in several disciplines. Some economic researchers have discussed the efficiency improvement of green technology applied on electric charging behaviour and different sizes of farm [2–5]; some chemical papers of green technology dealt with molecular imprinting technology [6] and wastewater treatment [7]; some engineering issues put green technology into textile processing [8], green building practice [9, 10], and surface engineering [11]; and even Internet of Things (IoT) technology has been applied in waste water treatment [12]. Moreover, multidisciplinary integrated green technologies are utilised in agriculture, biology, medical, and some other research areas.The current literature amount with “green technology” in titles in the Web of Science (WoS) database was 1516 by December 31, 2020, with 12 types including common articles, reviews, editorial materials, meeting abstracts, book reviews, and proceeding papers. Of the review papers, 140 literature records reviewed a certain method or technical application [13–15]. Unfortunately, no paper has addressed the present research situation and future trend of green technology with bibliometric tools. Bibliometric tools can provide a clear knowledge map of a specific theme. In this study, we use two bibliometric tools, CiteSpace and VOSviewer, to examine the present research status and hot papers, the cooperation network of authors and main institution, and the cluster attribute of green technology [16]. This study attempts to solve three important questions. First, we will show the green technology literature research status according to the publishing and citing trend with three stages. Second, we will use knowledge mapping systems to show the core journals, highly cited papers, and categories of different fields of green technology. Third, cluster and co-word analysis will clarify the green technology development themes and the implications of each cluster are provided.


## 2. Materials and Methods

According to the knowledge mapping theory, we can use co-word, institution, timeline, and cluster analyses to obtain the research front and the evolutionary trend of a certain theme. In this study, we use the former three analyses with CiteSpace tool and the cluster analysis with VOSviewer software. The analysis data units are collected from the WoS database.


### 2.1. Data Collection and Literature Search Strategy

WoS is equipped with the global academic literature of different disciplines, and it can provide the citation record of each literature that meets the functional requirements of co-word analysis. We choose the WoS core collection database with the timespan from 1900 to 2020, with citation indexes of Science Citation Index Expanded, Social Science Citation Index, Arts and Humanities Citation Index, and Emerging Sources Citation Index. With the consideration of the accuracy of citation results and some literature references [17, 18], we set the retrieval strategy as follows: “TITLE: (green technology) OR TITLE: (Environmental Sound Technology) OR TITLE: (Ecological Technology)”. We obtain a total of 1516 relevant papers, and we refine the document types. Then, we obtain 996 “ARTICLE” and 140 “REVIEW” papers, and a total of 1136 papers are the input text files. The data were last updated on December 31, 2020.


### 2.2. Bibliometric Tools of CiteSpace and VOSviewer

CiteSpace is an information visualisation system developed by Chen (2006) based on Java language; it can give the knowledge map of a specific research domain with co-citation analysis and pathfinder network scaling to seek the key evolutionary path and intellectual turning points [19]. CiteSpace can realise several important functions: it can identify the milestone paper, appraise the innovative extent, and reveal the research front evolution of the knowledge unit. VOSviewer software was developed by the two Netherland scholars van Eck and Waltman. Their paper Software Survey: VOSviewer, a Computer Program for Bibliometric Mapping is a hot paper of the Journal of Informetrics. VOSviewer provides five types of function, including co-authorship analysis, co-occurrence analysis, citation analysis, bibliographic coupling, and co-citation analysis, and the units of analysis can include authors, organisation (institution), and countries. In comparison with CiteSpace, VOSviewer can provide a clearer clustering result due to its parameter set of clustering resolution. The following knowledge mapping analysis of green technology includes four steps (Figure 1): the first step is to select data from the WoS database; the second step is the co-citation analysis to acquire the key literature; the third step is the co-occurrence network analysis; and the fourth step is cluster view analysis to obtain the cluster results of green technology literature.Figure 1
Four steps of knowledge mapping analysis.In VOSviewer, the basic colour view of a theme depends on the ordinary density rule. The colour of a point in the map is determined based on the item density of the point. Letd¯ denote the average distance between two items, that is,(1)d¯=2nn−1∑i≤jxi−xj.The item density D(x) of a point x  = (x1, x2) is then defined as(2)Dx=∑i=1nwiKx−xihd¯,where k: [0, ∞) ⟶ [0, ∞) denotes a kernel function; h > 0 denotes a parameter called the kernel width; and wi denotes the weight of item i, that is, the total number of occurrences or co-occurrences of item i. The kernel function k must be nonincreasing. VOSviewer uses a Gaussian kernel function given by(3)Kt=exp−t2.It follows from (2) that the item density of a point in a map depends on the number of neighbouring items and on the weights of these items. The larger the number of neighbouring items and the smaller the distances between these items and the point of interest is, the higher the item density will be. In addition, the higher the weights of the neighbouring items is, the higher the item density will be.


## 2.1. Data Collection and Literature Search Strategy

WoS is equipped with the global academic literature of different disciplines, and it can provide the citation record of each literature that meets the functional requirements of co-word analysis. We choose the WoS core collection database with the timespan from 1900 to 2020, with citation indexes of Science Citation Index Expanded, Social Science Citation Index, Arts and Humanities Citation Index, and Emerging Sources Citation Index. With the consideration of the accuracy of citation results and some literature references [17, 18], we set the retrieval strategy as follows: “TITLE: (green technology) OR TITLE: (Environmental Sound Technology) OR TITLE: (Ecological Technology)”. We obtain a total of 1516 relevant papers, and we refine the document types. Then, we obtain 996 “ARTICLE” and 140 “REVIEW” papers, and a total of 1136 papers are the input text files. The data were last updated on December 31, 2020.


## 2.2. Bibliometric Tools of CiteSpace and VOSviewer

CiteSpace is an information visualisation system developed by Chen (2006) based on Java language; it can give the knowledge map of a specific research domain with co-citation analysis and pathfinder network scaling to seek the key evolutionary path and intellectual turning points [19]. CiteSpace can realise several important functions: it can identify the milestone paper, appraise the innovative extent, and reveal the research front evolution of the knowledge unit. VOSviewer software was developed by the two Netherland scholars van Eck and Waltman. Their paper Software Survey: VOSviewer, a Computer Program for Bibliometric Mapping is a hot paper of the Journal of Informetrics. VOSviewer provides five types of function, including co-authorship analysis, co-occurrence analysis, citation analysis, bibliographic coupling, and co-citation analysis, and the units of analysis can include authors, organisation (institution), and countries. In comparison with CiteSpace, VOSviewer can provide a clearer clustering result due to its parameter set of clustering resolution. The following knowledge mapping analysis of green technology includes four steps (Figure 1): the first step is to select data from the WoS database; the second step is the co-citation analysis to acquire the key literature; the third step is the co-occurrence network analysis; and the fourth step is cluster view analysis to obtain the cluster results of green technology literature.Figure 1
Four steps of knowledge mapping analysis.In VOSviewer, the basic colour view of a theme depends on the ordinary density rule. The colour of a point in the map is determined based on the item density of the point. Letd¯ denote the average distance between two items, that is,(1)d¯=2nn−1∑i≤jxi−xj.The item density D(x) of a point x  = (x1, x2) is then defined as(2)Dx=∑i=1nwiKx−xihd¯,where k: [0, ∞) ⟶ [0, ∞) denotes a kernel function; h > 0 denotes a parameter called the kernel width; and wi denotes the weight of item i, that is, the total number of occurrences or co-occurrences of item i. The kernel function k must be nonincreasing. VOSviewer uses a Gaussian kernel function given by(3)Kt=exp−t2.It follows from (2) that the item density of a point in a map depends on the number of neighbouring items and on the weights of these items. The larger the number of neighbouring items and the smaller the distances between these items and the point of interest is, the higher the item density will be. In addition, the higher the weights of the neighbouring items is, the higher the item density will be.


## 3. Results

### 3.1. Yearly Distribution of Green Technology Papers and Highly Cited Paper Analysis

#### 3.1.1. Yearly Distribution of Green Technology Papers

We search for the green technology papers from the WoS Core Collection. Then, we obtain the number of published articles annually (PN) from 1968 to 2020. The published papers can be divided into three stages: the primary stage (1968–1990), in which the maximum number is below 10; the booming stage (1991–2007), in which the maximum number is below 30; and the prosperous stage (2008–2020), in which the slope ratio of trendline is obviously increasing. For the citation situation analysis, we collect the citation number (CN) of all the green technology papers. The h-index of green technology source is 77, and the average citation per item is 20.16. The sum of times cited is 30567, and that without self-citations is 30066 (Figure2). As indicated in Figure 2, green technology theme has attracted increasing academic interest since 1968.Figure 2
Annual PN and CN distribution of green technology.The 1136 green technology papers involve 149 types of research area, the top ten of which are environmental sciences, green sustainable science technology, engineering environmental, engineering chemical, environmental studies, energy fuels, chemistry multidisciplinary, economics, food science technology, and biotechnology applied microbiology. As shown in Table1, green technology records of environmental sciences exist, which accounts to 24.47% of the total records; the last research fields are agriculture and biotechnology applied microbiology, with 49 records of 4.31% of the total. Surprisingly, management and business categories take up the 11th and the 12th positions of all the research areas.Table 1
Research area of green technology records.
Research areasRecord countPercentage of the total recordsEnvironmental sciences27824.47Green sustainable science technology16814.79Engineering environmental11710.30Engineering chemical11410.03Environmental studies958.36Energy fuels887.75Chemistry multidisciplinary786.87Economics726.34Food science technology595.19Biotechnology applied microbiology494.31


#### 3.1.2. Cited Journal Analysis

In VOSviewer software, we select 1968–2020 with one year per slice as the time slice. To obtain the core journals of green technology, we set the types of citation and “sources” as the unit of analysis. We obtain 716 sources; the total strength of each of the citation links with other sources are calculated. The sources with the greatest total link strength are selected. We find that some of the 716 items in the network are not connected to each other. The largest set of connected items consists of 91 items (in Figure3).Figure 3
Cited journal mapping of green technology.We choose the top 20 journals of green technology by the centrality value (Table2). From Table 2, we can find that the Journal of Cleaner Production has 184 green technology records, whereas the Journal of Agricultural and Food Chemistry has the least 7 records. From the centrality parameter, the value of Journal of Cleaner Production in 2010 is 0.26, which is the largest, whereas the value of Journal of Agricultural and Food Chemistry in 2005, Journal of the American Chemical Society in 2012, Angewandte Chemie in 2012, and Pure and Applied Chemistry in 2007 is 0.06, which is the least.Table 2
Parameters of green technology cited journals.
CountCentralityYearCited journals11840.262010Journal of Cleaner Production2390.242011Resources Conservation and Recycling3450.162006Environmental Science and Technology41050.132002Science51010.131980Journal of Hazardous Materials6660.132010Industrial and Engineering Chemistry Research7820.122006Bioresource Technology8650.122005Journal of Chemical Technology and Biotechnology9810.112009Chemical Review10400.112005MIS Quarterly11350.102007Renewable and Sustainable Energy Reviews12480.092010Energy Policy131280.082011American Economic Review141200.072011Energy Economics15590.072004Journal of Organic Chemistry16290.072012Research Policy1770.062005Journal of Agricultural and Food Chemistry18670.062012Journal of the American Chemical Society19510.062012Angewandte Chemie20380.062007Pure and Applied Chemistry


#### 3.1.3. Highly Cited Paper Analysis

From the green technology citation results, we can refine papers by highly cited type in the field with data from the Essential Science Indicator (ESI) automatically. Now, ESI ranking is becoming increasingly popular, and the highly cited paper has received sufficient citations to place it in the top of 1% of different academic fields based on a highly cited threshold for the field and publication year. After we comb the 13 papers of green technology, four papers related to the field of chemistry remain published onSeparation and Purification Technology, Journal of Supercritical Fluids, Analytica Chimica Acta, and Fuel Processing Technology Journal. These papers deal with electrocoagulation technique [20], supercritical fluid extraction [21], eutectic solvents [22], and biodiesel focusing on green catalytic techniques [23], which introduce certain new applicable techniques or methods for reducing pollutive outputs or promote production efficiency.There are four papers related to the field of engineering published on theInternational Journal of Production Economics, Chemical Engineering Journal, Solar Energy, and Production and Operations Management Journal. These four papers examine carbon emission reductions under market mechanism [24], membrane bioreactor technology in waste water treatment [25], green roofs technology to mitigate the heat island phenomenon [26], and environmental taxes and subsidies motivating the consumer’s choice of green emission technology [27].Four papers are related to the field of economics and business published onManagement Decision, Management Science, R&D Management, and Journal Of Environmental Economics and Management. These papers discuss the productive technical progress and green technical innovation in China [28], the potential effects of governmental subsidies for green technology adoption in view of the manufacturing industry’s response [29], the current overview of green innovation management [30], and American consumer adoption of hybrid-electric vehicles [31]. One paper is related to the field of geosciences, which is about metals for green technology application and published on Ore Geology Reviews [32].As shown in Table3, the highest citation count is the “Natural deep eutectic solvents as new potential media for green technology” by Dai et al. (2013), with a total number of 587; and the lowest citation count is “Electrocoagulation as a green technology for phosphate removal from river water” by Hashim et al. (2019).Table 3
Highly cited papers of green technology.
AuthorPaper titleJournal titleFieldCitation countsPublished year1Hashim > et al.Electrocoagulation as a green technology for phosphate removal from river waterSeparation and Purification TechnologyChemistry2120192Song and WangMarket competition, green technology progress and comparative advantages in ChinaManagement DecisionEconomics and business3620183Xu, He, and XuSupply chain coordination with green technology under cap-and-trade regulationInternational Journal of Production EconomicsEngineering6020174Cohen, Lobel, and ParakisThe impact of demand uncertainty on consumer subsidies for green technology adoptionManagement ScienceEconomics and business5020165Neoh, Noor, and MutamimGreen technology in wastewater treatment technologies: Integration of membrane bioreactor with various wastewater treatment systemsChemical Engineering JournalEngineering9220166De Melo, Silcestre, and SilvaSupercritical fluid extraction of vegetable matrices: Applications, trends and future perspectives of a convincing green technologyJournal of Supercritical FluidsChemistry17020147SantamourisCooling the cities - a review of reflective and green roof mitigation technologies to fight heat island and improve comfort in urban environmentsSolar EnergyEngineering51120148Krass, Nedorezov and OvchinnikovEnvironmental taxes and the choice of green technologyProduction and Operations ManagementEngineering14920139Hein, Mizell, and KoschinskyDeep-ocean mineral deposits as a source of critical metals for high- and green technology applications: Comparison with land-based resourcesOre Geology ReviewsGeosciences202201310Dai, van Spronsen, and WitkampNatural deep eutectic solvents as new potential media for green technologyAnalytica Chimica ActaChemistry587201311Schiederig, Tietze, and HerstattGreen innovation in technology and innovation management - an exploratory literature reviewR&D ManagementEconomics and business169201212Gallagher and MuehleggerGiving green to get green? Incentives and consumer adoption of hybrid vehicle technologyJournal of Environmental Economics and ManagementEconomics and business260201113Helwani, Othman, and AzizTechnologies for production of biodiesel focusing on green catalytic techniques: A reviewFuel Processing TechnologyChemistry3442009


### 3.2. Co-Authorship Analysis of Green Technology Research

We use the VOSviewer co-authorship function to create a map of co-authorship of green technology. We click the type of analysis item and choose the “Authors” unit of analysis; for the counting method, we choose “Full counting.” We set the minimum number of documents of an author default threshold value as 3, and of all the 4158 authors, 54 authors meet the thresholds (Figure4). For each of the 54 authors, the total strength of the co-authorship links with each other author is calculated automatically. The authors with the greatest total link strength is selected. The result can be adjusted with documents, citations, and total link strength parameter.Figure 4
Co-authorship analysis of green technology.As shown in Figure4, the co-author distribution of green technology is quite scattered. Moreover, we obtain three small co-authorship networks. The first network, indicated by red colour, includes three authors belonging to the economic field; they mainly contribute to the strategies, barriers, and critical drivers of green building technology adoption in developing countries, with the cases of Ghana and developed countries, such as the USA [10, 33, 34]. The second network, indicated by blue colour, includes five authors belonging to the bio-engineering field; these authors investigate the adoption of green fertilizer technology (GFT) among Malaysian farmers in the paddy industry, which may be a possible solution for Malaysian food security [35, 36]. The third network, indicated by green colour, includes eight authors belonging to the chemistry field; they suggest green methods for the production of high fatty acid starch esters without the use of solvent and additives [37].


### 3.3. Country and Institution Analysis

Country and institution analysis in knowledge mapping can reflect the number distribution of research papers and the cooperation of different institutions and countries. The node size reflects the number, and the link value between nodes reflects the strength of co-authorship. Figure5 shows the top three countries, USA, China, and England, which have co-authorship with one another to some extent.Figure 5
Co-authorship mapping of different countries.From Table4, we can obtain the top 15 countries or regions of green technology, namely, the USA, China, England, Australia, Canada, France, Italy, Spain, Germany, Malaysia, Japan, South Korea, Taiwan, Finland, and the Netherlands. From the Documents column, 301 green technology records in the USA rank first among all the countries, followed by China with 205 documents and England with 72 documents, and the last country is Finland with 16 documents. From the Citations column, the USA still ranks first with 5877 citations, followed by Canada with 1763 and China with 1703, and the lowest country is Finland, with 335 citations. From the Total link strength column, the top three countries are the USA, China and England with total link strength of 108, 99, and 65, respectively, and the last two countries are Finland and the Netherlands, with the same value of total link strength of 21.Table 4
Green technology co-authorship of different countries or regions.
CountryDocumentsCitationsTotal link strength1USA30158771082China2051703993England721632654Australia501157415Canada531763346France29420347Italy60571338Spain49684329Germany4910052910Malaysia518662911Japan395262712South Korea417722413Taiwan403952414Finland163352115Netherlands2186221For institution analysis, there exist 1575 research organisations all over the world with publishing papers with green technology issues. We set the minimum number of documents of an organisation threshold value as 7, and 12 research institutions meet the threshold, of which three institutions are in Malaysia (Univ Sains Malaysia, Univ Malaya, and Univ Teknol Malaysia), two institutions are in China (Chinese Acad Sci and Hongkong Polytec Univ), two institutions are in Canada (Mcgill Univ and Queens Univ), one institution is in South Korea (Seoul Natl Univ), one institution is in Jordan (Jordan Univ Sci and Technol), one institution is in the USA (Texas A&M Univ), one institution is in the UK (Univ Nottingham), and one institution is in Italy (Univ Turin). As shown in Table5, Chinese Acad Sci, which is the top institution, has 19 documents of green technology. Mcgill Univ has 549 most citations of green technology. The total link strength value indicates that the correlation between institutions is quite weak, and individual organisation has limited academic influence.Table 5
Green technology co-authorship of different institutions.
InstitutionDocumentsCitationsTotal link strength1Univ Sains Malaysia948122Chinese Acad Sci1912713Seoul Natl Univ1012414Univ Malaya714615Univ Teknol Malaysia79216Hongkong Polytec Univ1019507Jordan Univ Sci and Technol911208Mcgill Univ854909Queens Univ7191010Texas A&M Univ7139011Univ Nottingham9436012Univ Turin8730


### 3.4. Keyword Cluster Analysis

#### 3.4.1. Green Technology Cluster Analysis

Keyword cluster analysis can reveal the specific theme’s present situation and research front. Cluster analysis can detect homogeneous units using an algorithm method [38]. In contrast to other meta-analysis methods, cluster calculation has been proved to have less subjective bias, and strong connections of units reflect the specific theme in the same field [39]. The co-word matrix is commonly constructed from the samples, and statistical variables are used to measure the degree of similarity of indicators. According to different similarities, closely related objects are gathered automatically, which denote the direct connections among keywords or titles in knowledge mapping software. The CiteSpace system provides five types of visualisation style, namely, cluster view, timeline view, timezone view, geographic overlay, and dual-map overlay. The cluster and timeline views are the most popular. The cluster view can reflect the distribution of research area in different dimensions, and the timeline view can tell us the yearly evolution and interaction of each cluster. Two important parameters indicate the quality of cluster mapping, namely, modularity and silhouette values. Generally, if the modularity value is greater than 0.3, then the cluster is significant; if the mean silhouette value is greater than 0.5, then the cluster view is reasonable and acceptable. First, we perform the cluster view operation. The results indicate that the merged network of keywords related to green technology consists of 352 nodes and 1684 links. The parameter modularity value is 0.5225, and the mean silhouette value is 0.6082 (Figure 6).Figure 6
Keyword cluster of green technology.From the statistical results of the keywords from the yearly slice (Table6), we choose the top 10 keywords of the green technology cluster. The top 10 keywords are emission, green technology, performance, energy, design, optimisation, system, behaviour, environment, and product. The maximum value of centrality is 0.15, and the minimum value is 0.07. From the year distribution, we find that the significant nodes range from 2008 to 2015.Table 6
Top 10 keywords in the green technology cluster.
CountCentralityYearKeywords240.152009Emission890.142010Green technology710.112013Performance320.102012Energy200.092011Design600.092013Optimisation150.082008System180.082011Behaviour90.072010Environment150.072015Product


#### 3.4.2. Timeline View Evolutionary Analysis of Green Technology

The timeline view in the CiteSpace system can reflect the relationship between clusters and historic duration of the literature. In the timeline view, the horizontal axis is the year distribution and the vertical axis is the labelling of the clusters. Keywords belonging to the same cluster are set in a line according to the date of the published literature. In the timeline view, we can obtain the beginning year of a cluster, the numerical trend of a cluster, and the important literature with high betweenness centrality value. From the timeline view of green technology (Figure7), 10 clusters are labelled with #0–#9 and the distribution of clusters mainly focuses from 1998 to 2020.Figure 7
Timeline view of green technology.In the CiteSpace system, the cluster labelling comes from the citing articles based on three types of algorithms: TF∗IDF, log-likelihood rate, and mutual information. Given that the consciousness of mapping and log-likelihood ratio value can provide quantifying information automatically, we choose log-likelihood rate algorithm. The labelling results and log-likelihood ratio value of green technology clusters are as follows (Table 7). The first cluster labelling is resource-based view, with a total size of 61 keywords, and the mean year is 2014. Under the line, we can see that the first cluster keywords include adoption, green technology impact, sustainability, renewable energy, environmental policy, green cleaner production, and empirical evidence. The second cluster labelling is green technology progress, with a total size of 55 keywords, and the mean year is 2015; it includes keywords of information technology, remote sensing, energy efficiency, green growth, environmental strategy, and environmental regulation. The third cluster is labelled with BR, with a total of 50 keywords and the mean year of 2016; keywords include life cycle assessment, emission, fuel cell, heavy metal, electric vehicle, catalyst, and eco-design. The fourth cluster is labelled with molecular weight, with a total size of 40 keywords and the mean year of 2015; keywords include degradation, green kinetics, fermentation, biodegradation mechanism, polymer, fabrication, and health. The fifth cluster is labelled with ultrasound-assisted extraction, with a total size of 37 keywords and the mean year of 2016; it includes keywords of polymerisation, carbon dioxide, superficial, subcritical water, plant, and assisted extraction. The sixth cluster is labelled with green revolution, with a total size of 31 keywords and the mean year of 2015; it includes keywords of green technology, rice production, social responsibility, supply chain, and environmental prevention. The seventh cluster is labelled with green building technologies, with a total size of 31 keywords and the mean year of 2015; it includes keywords of environment management, design, investment policy, green economy, sustainable development, green building, critical success factor, and barrier. The eighth cluster is labelled with paper mill waste, with a total size of 19 keywords and the mean year of 2012; keywords of this cluster include water, biosorption waste, ironic liquid, acid extraction, recycling, and aqueous solution. The ninth cluster is labelled with organic peroxide, with a total size of 5 keywords and the mean year of 2012; keywords include SADT, organic peroxide, and accelerating decomposition temperature. The tenth cluster is labelled with alginate, with a total size of 3 keywords and the mean year of 2014; it includes keywords of bacteria, Escherichia coli, and temperature.Table 7
10 keyword clusters of green technology.
Cluster IDSizeMean yearTop 10 terms (log-likelihood ratio value)0612014Resource-based view (9.35); geothermal energy (6.22); employment (6.22); institutional theory (6.22); ecological modernisation (6.22); climate change (6.22); innovation (5.32); sustainability (4.1); evaluation (3.11); manufacturing (3.11)1552015Green technology progress (15.31); adoption (7.63); TPB (7.63); big data (7.63); GFT (7.63); pollutant discharge (3.8); software-defined networks (3.8); IoT (3.8); adoption decision (3.8); Bayesian learning (3.8)2502016BR (7.92); CL (7.92); leaching (7.92); BIM technology (7.92); fuel cells (7.92); application (7.92); nanocrystal (7.92); diode (7.92); detoxification (7.92); CsPbX3 (7.92)3402015Molecular weight (9.62); branched structure (9.62); biodegradation (9.62); membrane separations (4.8); chromatography (4.8); fly ash geopolymer (4.8); mesophase (4.8); chain degradation (4.8); saccharification (4.8); criteria weighting (4.8)4372016Ultrasound-assisted extraction (12.99); antioxidant (8.64); supercritical fluid extraction (8.64); polycaprolactone (4.31); supercritical extraction (4.31); antioxidant activity (4.31); ellagitannins (4.31); tough external peels (4.31); green extraction technologies (4.31)5312015Green revolution (15.23); sawah (10.12); chemical properties (5.04); cap-and-trade (5.04); smartphones (5.04); information technology managers (5.04); mealtime (5.04); exchangeable cations (5.04); rice production (5.04); total carbon (5.04)6312015Green building technologies (30.75); promotion strategies (20.37); construction industry (20.37); barriers (20.374); sustainable development (20.3); drivers (15.23); Ghana (10.9); developing countries (10.9); construction market (10.125); new economy (10.12)7192012Paper mill waste (5.29); botanical (5.29); herbal preparation (5.29); quality control (5.29); environmental assessment tool (eat) (5.29); ozonation (5.29); biopolymers (5.29); green chemistry (5.29); recycled paper (5.29); municipal solid waste (5.29);852012Organic peroxide (15.17); vent sizing package (7.53); thermal hazard (7.53); differential scanning calorimetry (7.53); thermokinetic parameters (7.53); consumption energy (7.53); safety parameter (7.53); diffusion (7.53); kinetic (7.53)932014Alginate (6.77); bacterial inactivation (6.77); silica gel (6.77); catalyst (6.77); immobilisation (6.77); energy sustainability (6.77); antimicrobial activity (6.77); bacteria (6.77); organic Rankine cycle (6.77)


#### 3.4.3. Brief Summary of the 10 Clusters

From Table8, all the papers about green technology can be divided as follows: three clusters are in the economics and business field, five clusters are in the engineering field, and two clusters are in the chemistry field.Table 8
Summary of research subjects of 10 green technology clusters.
Cluster labellingFieldResearch subjects#0Resource-based viewEconomics and business(1) Sustainability; (2) supply chain; (3) human resources management; (4) carbon dioxide emission#1Green technology progressEconomics and business(1) Green technology progress; (2) paddy farmer; (3) energy efficiency; (4) green growth#2BREngineering(1) Green engineering construction; (2) energy conservation; (3) emerging vehicle technology; (4) coal utilisation; (5) biotechnology#3Molecular weightChemistry(1) Bioremediation; (2) biodegradation; (3) membrane separations; (4) chromatography#4Ultrasound-assisted extractionEngineering(1) Clean extraction; (2) green solvents#5Green revolutionEconomics and business(1) Rice production; (2) information technology; (3) financial services industry; (4) environmental sustainability#6Green building technologiesEngineering(1) Promotion strategies; (2) construction market; (3) driving force; (4) technologies adoption#7Paper mill wasteEngineering(1) Green chemistry; (2) environmental assessment; (3) paper mill waste; (4) municipal solid waste#8Organic peroxideChemistry(1) Organic peroxide; (2) scanning calorimetry; (3) incompatible material; (4) thermal hazard#9AlginateEngineering(1) Alginate; (2) bacterial inactivation; (3) silica gel; (4) catalystThe #0 cluster deals with sustainability, with research subjects mainly about sustainability, supply chain, human resources management, and carbon dioxide emission. Resource-based view theory, which was proposed by Birger Wernerfelt, is an important source of modern core competitive compacity of firms [40]. Each market entity should pay attention to allocate human resources, currency capital, and technology to achieve a more desirable output. Green information technologies and systems refer to initiatives and programs that directly or indirectly address environmental sustainability in organisations [41]. In this cluster, environmental technologies are used in supply chain management to check the collaboration effect between suppliers and customers [42] and corporate sustainable capability may be integrated with information technology and supply chain [43].The #1 cluster concentrates on the green technology progress and innovations in different industries. It includes research subjects of green technology progress, adoption decision, Bayesian learning, energy efficiency, and green growth. Topics include energy strategy should be transformed, hydrogen economy as a greener choice as a carbon-free carrier [44], green building technologies adoption [33], green technology progress measurement of thermoelectric enterprises [45], green technology progress influencing factors [46], and technological progress in green cement industry [47].The #2 cluster explores types of new green technology applicable in chemical and biological engineering. The research subjects are mainly about green engineering construction, energy conservation, emerging vehicle technology, coal utilisation, and biotechnology. The hot topics of this cluster include network energy-saving technologies in mobile industry [48], future wireline networks’ potential economic and environmental consequences [49], smart cities and green growth based on universal infrastructure and green technologies [50], and electric vehicle routing designing and technology to recharge [51].The #3 cluster offers a series of microstructural practices and inner material structure exploratory research. It includes research subjects of bioremediation, biodegradation, membrane separations, and chromatography. These green technologies include phytoremediation technology using diverse plants to remediate contaminated environments [52], polysaccharides modification [53], ferrate as an efficient agent for the abatement of pollutants in water [54], and sorption membrane for water purification and liquid separation [55, 56].The #4 cluster reveals environmentally friendly extraction mechanism of green extraction kinetics and polymerisation processing technologies. The research subjects are mainly about ultrasound-assisted extraction, supercritical fluid extraction, extraction kinetics, clean extraction, polymer blends, and biomedical polymers. Topics include cleaner production purposes embracing supercritical fluid extraction [21], enhancing aqueous extraction processes without using solvents with ultrasound-assisted extraction technology [57], developing green solvents for oil extraction [58], promoting innovation of more environmentally friendly and tuneable solvents [59], and exploring green catalytic techniques of homogeneous liquids and heterogeneous solids in biodiesel production [23].The #5 cluster manifests the social information learning of green revolution in agricultural technology adoption and environmental performance, especially with the cap-and-trade carbon dioxide emission constraint. It includes research subjects of rice production, information technology, financial services industry, and environmental sustainability. It includes discussions on the proper farm size related to effective new technology adoption and credit constraint [60], information flows in social learning of Indian rice and wheat technology revolution [61], technology policy function [62], impact assessment of technology intervention [63], and effects of improved agricultural technologies [64].The #6 cluster presents the driving force of green building technologies adoption and existing barriers in the construction industry. The research subjects are mainly about designers’ adoption behaviours [65], driving force [10], and barriers of green building [66]. New engineering applications of green water technologies [67], green roof technology [68], green wall technology [69], and “green concrete” concept [70] are discussed in this cluster.The #7 cluster focuses on environmental negative impact control, such as water pollution and solid waste disposal and recycling problems. This cluster includes research subjects of green chemistry, environmental assessment, environmental compatibility, paper mill waste, and municipal solid waste. Modern industrial production inevitably comes up with undesirable output, even some pollutive and poisonous substance. Poliakoff (2007) contributed with unsustainable chemical manufacturing and 12 modern principles of green chemistry [71]. Green technologies are developed to realise removal of heavy metals, cyanobacteria, and other hazardous material in water [72, 73]. Some novel processing and methods have also been presented to deal with solid waste, such as industrial and municipal solid waste [74].The #8 cluster reflects the functional materials with unique characterisation and thermal hazard evaluation. The research subjects are mainly about organic peroxide, scanning calorimetry, incompatible material, and thermal hazard. Newly found material characteristics, effective processing adjustment, and novel monitoring tools have been presented. Topics include ionic liquids with unique advantages showing higher selectivity, fast rates, and greater enzyme stability [75]; organic synthesis using microreactor technology having better thermal stability than traditional batch synthesis [76]; polylactide, as packaging material, being suitable for industrial usage, as well as its environmental implications [77]; and for thermal hazard, some novel calorimetric tests and simulation evaluating methods have been presented [78, 79].The #9 cluster concentrates on biological materials and engineering applications. It includes research subjects of alginate, bacterial inactivation, silica gel, catalyst, and immobilisation. Several highly cited papers are about microalgae encapsulation technology [80], green biocides [81], encapsulation in chitosan-based nanomatrix [82], and polyphenol recovery from pomegranate peels [83].


## 3.1. Yearly Distribution of Green Technology Papers and Highly Cited Paper Analysis

### 3.1.1. Yearly Distribution of Green Technology Papers

We search for the green technology papers from the WoS Core Collection. Then, we obtain the number of published articles annually (PN) from 1968 to 2020. The published papers can be divided into three stages: the primary stage (1968–1990), in which the maximum number is below 10; the booming stage (1991–2007), in which the maximum number is below 30; and the prosperous stage (2008–2020), in which the slope ratio of trendline is obviously increasing. For the citation situation analysis, we collect the citation number (CN) of all the green technology papers. The h-index of green technology source is 77, and the average citation per item is 20.16. The sum of times cited is 30567, and that without self-citations is 30066 (Figure2). As indicated in Figure 2, green technology theme has attracted increasing academic interest since 1968.Figure 2
Annual PN and CN distribution of green technology.The 1136 green technology papers involve 149 types of research area, the top ten of which are environmental sciences, green sustainable science technology, engineering environmental, engineering chemical, environmental studies, energy fuels, chemistry multidisciplinary, economics, food science technology, and biotechnology applied microbiology. As shown in Table1, green technology records of environmental sciences exist, which accounts to 24.47% of the total records; the last research fields are agriculture and biotechnology applied microbiology, with 49 records of 4.31% of the total. Surprisingly, management and business categories take up the 11th and the 12th positions of all the research areas.Table 1
Research area of green technology records.
Research areasRecord countPercentage of the total recordsEnvironmental sciences27824.47Green sustainable science technology16814.79Engineering environmental11710.30Engineering chemical11410.03Environmental studies958.36Energy fuels887.75Chemistry multidisciplinary786.87Economics726.34Food science technology595.19Biotechnology applied microbiology494.31


### 3.1.2. Cited Journal Analysis

In VOSviewer software, we select 1968–2020 with one year per slice as the time slice. To obtain the core journals of green technology, we set the types of citation and “sources” as the unit of analysis. We obtain 716 sources; the total strength of each of the citation links with other sources are calculated. The sources with the greatest total link strength are selected. We find that some of the 716 items in the network are not connected to each other. The largest set of connected items consists of 91 items (in Figure3).Figure 3
Cited journal mapping of green technology.We choose the top 20 journals of green technology by the centrality value (Table2). From Table 2, we can find that the Journal of Cleaner Production has 184 green technology records, whereas the Journal of Agricultural and Food Chemistry has the least 7 records. From the centrality parameter, the value of Journal of Cleaner Production in 2010 is 0.26, which is the largest, whereas the value of Journal of Agricultural and Food Chemistry in 2005, Journal of the American Chemical Society in 2012, Angewandte Chemie in 2012, and Pure and Applied Chemistry in 2007 is 0.06, which is the least.Table 2
Parameters of green technology cited journals.
CountCentralityYearCited journals11840.262010Journal of Cleaner Production2390.242011Resources Conservation and Recycling3450.162006Environmental Science and Technology41050.132002Science51010.131980Journal of Hazardous Materials6660.132010Industrial and Engineering Chemistry Research7820.122006Bioresource Technology8650.122005Journal of Chemical Technology and Biotechnology9810.112009Chemical Review10400.112005MIS Quarterly11350.102007Renewable and Sustainable Energy Reviews12480.092010Energy Policy131280.082011American Economic Review141200.072011Energy Economics15590.072004Journal of Organic Chemistry16290.072012Research Policy1770.062005Journal of Agricultural and Food Chemistry18670.062012Journal of the American Chemical Society19510.062012Angewandte Chemie20380.062007Pure and Applied Chemistry


### 3.1.3. Highly Cited Paper Analysis

From the green technology citation results, we can refine papers by highly cited type in the field with data from the Essential Science Indicator (ESI) automatically. Now, ESI ranking is becoming increasingly popular, and the highly cited paper has received sufficient citations to place it in the top of 1% of different academic fields based on a highly cited threshold for the field and publication year. After we comb the 13 papers of green technology, four papers related to the field of chemistry remain published onSeparation and Purification Technology, Journal of Supercritical Fluids, Analytica Chimica Acta, and Fuel Processing Technology Journal. These papers deal with electrocoagulation technique [20], supercritical fluid extraction [21], eutectic solvents [22], and biodiesel focusing on green catalytic techniques [23], which introduce certain new applicable techniques or methods for reducing pollutive outputs or promote production efficiency.There are four papers related to the field of engineering published on theInternational Journal of Production Economics, Chemical Engineering Journal, Solar Energy, and Production and Operations Management Journal. These four papers examine carbon emission reductions under market mechanism [24], membrane bioreactor technology in waste water treatment [25], green roofs technology to mitigate the heat island phenomenon [26], and environmental taxes and subsidies motivating the consumer’s choice of green emission technology [27].Four papers are related to the field of economics and business published onManagement Decision, Management Science, R&D Management, and Journal Of Environmental Economics and Management. These papers discuss the productive technical progress and green technical innovation in China [28], the potential effects of governmental subsidies for green technology adoption in view of the manufacturing industry’s response [29], the current overview of green innovation management [30], and American consumer adoption of hybrid-electric vehicles [31]. One paper is related to the field of geosciences, which is about metals for green technology application and published on Ore Geology Reviews [32].As shown in Table3, the highest citation count is the “Natural deep eutectic solvents as new potential media for green technology” by Dai et al. (2013), with a total number of 587; and the lowest citation count is “Electrocoagulation as a green technology for phosphate removal from river water” by Hashim et al. (2019).Table 3
Highly cited papers of green technology.
AuthorPaper titleJournal titleFieldCitation countsPublished year1Hashim > et al.Electrocoagulation as a green technology for phosphate removal from river waterSeparation and Purification TechnologyChemistry2120192Song and WangMarket competition, green technology progress and comparative advantages in ChinaManagement DecisionEconomics and business3620183Xu, He, and XuSupply chain coordination with green technology under cap-and-trade regulationInternational Journal of Production EconomicsEngineering6020174Cohen, Lobel, and ParakisThe impact of demand uncertainty on consumer subsidies for green technology adoptionManagement ScienceEconomics and business5020165Neoh, Noor, and MutamimGreen technology in wastewater treatment technologies: Integration of membrane bioreactor with various wastewater treatment systemsChemical Engineering JournalEngineering9220166De Melo, Silcestre, and SilvaSupercritical fluid extraction of vegetable matrices: Applications, trends and future perspectives of a convincing green technologyJournal of Supercritical FluidsChemistry17020147SantamourisCooling the cities - a review of reflective and green roof mitigation technologies to fight heat island and improve comfort in urban environmentsSolar EnergyEngineering51120148Krass, Nedorezov and OvchinnikovEnvironmental taxes and the choice of green technologyProduction and Operations ManagementEngineering14920139Hein, Mizell, and KoschinskyDeep-ocean mineral deposits as a source of critical metals for high- and green technology applications: Comparison with land-based resourcesOre Geology ReviewsGeosciences202201310Dai, van Spronsen, and WitkampNatural deep eutectic solvents as new potential media for green technologyAnalytica Chimica ActaChemistry587201311Schiederig, Tietze, and HerstattGreen innovation in technology and innovation management - an exploratory literature reviewR&D ManagementEconomics and business169201212Gallagher and MuehleggerGiving green to get green? Incentives and consumer adoption of hybrid vehicle technologyJournal of Environmental Economics and ManagementEconomics and business260201113Helwani, Othman, and AzizTechnologies for production of biodiesel focusing on green catalytic techniques: A reviewFuel Processing TechnologyChemistry3442009


## 3.1.1. Yearly Distribution of Green Technology Papers

We search for the green technology papers from the WoS Core Collection. Then, we obtain the number of published articles annually (PN) from 1968 to 2020. The published papers can be divided into three stages: the primary stage (1968–1990), in which the maximum number is below 10; the booming stage (1991–2007), in which the maximum number is below 30; and the prosperous stage (2008–2020), in which the slope ratio of trendline is obviously increasing. For the citation situation analysis, we collect the citation number (CN) of all the green technology papers. The h-index of green technology source is 77, and the average citation per item is 20.16. The sum of times cited is 30567, and that without self-citations is 30066 (Figure2). As indicated in Figure 2, green technology theme has attracted increasing academic interest since 1968.Figure 2
Annual PN and CN distribution of green technology.The 1136 green technology papers involve 149 types of research area, the top ten of which are environmental sciences, green sustainable science technology, engineering environmental, engineering chemical, environmental studies, energy fuels, chemistry multidisciplinary, economics, food science technology, and biotechnology applied microbiology. As shown in Table1, green technology records of environmental sciences exist, which accounts to 24.47% of the total records; the last research fields are agriculture and biotechnology applied microbiology, with 49 records of 4.31% of the total. Surprisingly, management and business categories take up the 11th and the 12th positions of all the research areas.Table 1
Research area of green technology records.
Research areasRecord countPercentage of the total recordsEnvironmental sciences27824.47Green sustainable science technology16814.79Engineering environmental11710.30Engineering chemical11410.03Environmental studies958.36Energy fuels887.75Chemistry multidisciplinary786.87Economics726.34Food science technology595.19Biotechnology applied microbiology494.31


## 3.1.2. Cited Journal Analysis

In VOSviewer software, we select 1968–2020 with one year per slice as the time slice. To obtain the core journals of green technology, we set the types of citation and “sources” as the unit of analysis. We obtain 716 sources; the total strength of each of the citation links with other sources are calculated. The sources with the greatest total link strength are selected. We find that some of the 716 items in the network are not connected to each other. The largest set of connected items consists of 91 items (in Figure3).Figure 3
Cited journal mapping of green technology.We choose the top 20 journals of green technology by the centrality value (Table2). From Table 2, we can find that the Journal of Cleaner Production has 184 green technology records, whereas the Journal of Agricultural and Food Chemistry has the least 7 records. From the centrality parameter, the value of Journal of Cleaner Production in 2010 is 0.26, which is the largest, whereas the value of Journal of Agricultural and Food Chemistry in 2005, Journal of the American Chemical Society in 2012, Angewandte Chemie in 2012, and Pure and Applied Chemistry in 2007 is 0.06, which is the least.Table 2
Parameters of green technology cited journals.
CountCentralityYearCited journals11840.262010Journal of Cleaner Production2390.242011Resources Conservation and Recycling3450.162006Environmental Science and Technology41050.132002Science51010.131980Journal of Hazardous Materials6660.132010Industrial and Engineering Chemistry Research7820.122006Bioresource Technology8650.122005Journal of Chemical Technology and Biotechnology9810.112009Chemical Review10400.112005MIS Quarterly11350.102007Renewable and Sustainable Energy Reviews12480.092010Energy Policy131280.082011American Economic Review141200.072011Energy Economics15590.072004Journal of Organic Chemistry16290.072012Research Policy1770.062005Journal of Agricultural and Food Chemistry18670.062012Journal of the American Chemical Society19510.062012Angewandte Chemie20380.062007Pure and Applied Chemistry


## 3.1.3. Highly Cited Paper Analysis

From the green technology citation results, we can refine papers by highly cited type in the field with data from the Essential Science Indicator (ESI) automatically. Now, ESI ranking is becoming increasingly popular, and the highly cited paper has received sufficient citations to place it in the top of 1% of different academic fields based on a highly cited threshold for the field and publication year. After we comb the 13 papers of green technology, four papers related to the field of chemistry remain published onSeparation and Purification Technology, Journal of Supercritical Fluids, Analytica Chimica Acta, and Fuel Processing Technology Journal. These papers deal with electrocoagulation technique [20], supercritical fluid extraction [21], eutectic solvents [22], and biodiesel focusing on green catalytic techniques [23], which introduce certain new applicable techniques or methods for reducing pollutive outputs or promote production efficiency.There are four papers related to the field of engineering published on theInternational Journal of Production Economics, Chemical Engineering Journal, Solar Energy, and Production and Operations Management Journal. These four papers examine carbon emission reductions under market mechanism [24], membrane bioreactor technology in waste water treatment [25], green roofs technology to mitigate the heat island phenomenon [26], and environmental taxes and subsidies motivating the consumer’s choice of green emission technology [27].Four papers are related to the field of economics and business published onManagement Decision, Management Science, R&D Management, and Journal Of Environmental Economics and Management. These papers discuss the productive technical progress and green technical innovation in China [28], the potential effects of governmental subsidies for green technology adoption in view of the manufacturing industry’s response [29], the current overview of green innovation management [30], and American consumer adoption of hybrid-electric vehicles [31]. One paper is related to the field of geosciences, which is about metals for green technology application and published on Ore Geology Reviews [32].As shown in Table3, the highest citation count is the “Natural deep eutectic solvents as new potential media for green technology” by Dai et al. (2013), with a total number of 587; and the lowest citation count is “Electrocoagulation as a green technology for phosphate removal from river water” by Hashim et al. (2019).Table 3
Highly cited papers of green technology.
AuthorPaper titleJournal titleFieldCitation countsPublished year1Hashim > et al.Electrocoagulation as a green technology for phosphate removal from river waterSeparation and Purification TechnologyChemistry2120192Song and WangMarket competition, green technology progress and comparative advantages in ChinaManagement DecisionEconomics and business3620183Xu, He, and XuSupply chain coordination with green technology under cap-and-trade regulationInternational Journal of Production EconomicsEngineering6020174Cohen, Lobel, and ParakisThe impact of demand uncertainty on consumer subsidies for green technology adoptionManagement ScienceEconomics and business5020165Neoh, Noor, and MutamimGreen technology in wastewater treatment technologies: Integration of membrane bioreactor with various wastewater treatment systemsChemical Engineering JournalEngineering9220166De Melo, Silcestre, and SilvaSupercritical fluid extraction of vegetable matrices: Applications, trends and future perspectives of a convincing green technologyJournal of Supercritical FluidsChemistry17020147SantamourisCooling the cities - a review of reflective and green roof mitigation technologies to fight heat island and improve comfort in urban environmentsSolar EnergyEngineering51120148Krass, Nedorezov and OvchinnikovEnvironmental taxes and the choice of green technologyProduction and Operations ManagementEngineering14920139Hein, Mizell, and KoschinskyDeep-ocean mineral deposits as a source of critical metals for high- and green technology applications: Comparison with land-based resourcesOre Geology ReviewsGeosciences202201310Dai, van Spronsen, and WitkampNatural deep eutectic solvents as new potential media for green technologyAnalytica Chimica ActaChemistry587201311Schiederig, Tietze, and HerstattGreen innovation in technology and innovation management - an exploratory literature reviewR&D ManagementEconomics and business169201212Gallagher and MuehleggerGiving green to get green? Incentives and consumer adoption of hybrid vehicle technologyJournal of Environmental Economics and ManagementEconomics and business260201113Helwani, Othman, and AzizTechnologies for production of biodiesel focusing on green catalytic techniques: A reviewFuel Processing TechnologyChemistry3442009


## 3.2. Co-Authorship Analysis of Green Technology Research

We use the VOSviewer co-authorship function to create a map of co-authorship of green technology. We click the type of analysis item and choose the “Authors” unit of analysis; for the counting method, we choose “Full counting.” We set the minimum number of documents of an author default threshold value as 3, and of all the 4158 authors, 54 authors meet the thresholds (Figure4). For each of the 54 authors, the total strength of the co-authorship links with each other author is calculated automatically. The authors with the greatest total link strength is selected. The result can be adjusted with documents, citations, and total link strength parameter.Figure 4
Co-authorship analysis of green technology.As shown in Figure4, the co-author distribution of green technology is quite scattered. Moreover, we obtain three small co-authorship networks. The first network, indicated by red colour, includes three authors belonging to the economic field; they mainly contribute to the strategies, barriers, and critical drivers of green building technology adoption in developing countries, with the cases of Ghana and developed countries, such as the USA [10, 33, 34]. The second network, indicated by blue colour, includes five authors belonging to the bio-engineering field; these authors investigate the adoption of green fertilizer technology (GFT) among Malaysian farmers in the paddy industry, which may be a possible solution for Malaysian food security [35, 36]. The third network, indicated by green colour, includes eight authors belonging to the chemistry field; they suggest green methods for the production of high fatty acid starch esters without the use of solvent and additives [37].


## 3.3. Country and Institution Analysis

Country and institution analysis in knowledge mapping can reflect the number distribution of research papers and the cooperation of different institutions and countries. The node size reflects the number, and the link value between nodes reflects the strength of co-authorship. Figure5 shows the top three countries, USA, China, and England, which have co-authorship with one another to some extent.Figure 5
Co-authorship mapping of different countries.From Table4, we can obtain the top 15 countries or regions of green technology, namely, the USA, China, England, Australia, Canada, France, Italy, Spain, Germany, Malaysia, Japan, South Korea, Taiwan, Finland, and the Netherlands. From the Documents column, 301 green technology records in the USA rank first among all the countries, followed by China with 205 documents and England with 72 documents, and the last country is Finland with 16 documents. From the Citations column, the USA still ranks first with 5877 citations, followed by Canada with 1763 and China with 1703, and the lowest country is Finland, with 335 citations. From the Total link strength column, the top three countries are the USA, China and England with total link strength of 108, 99, and 65, respectively, and the last two countries are Finland and the Netherlands, with the same value of total link strength of 21.Table 4
Green technology co-authorship of different countries or regions.
CountryDocumentsCitationsTotal link strength1USA30158771082China2051703993England721632654Australia501157415Canada531763346France29420347Italy60571338Spain49684329Germany4910052910Malaysia518662911Japan395262712South Korea417722413Taiwan403952414Finland163352115Netherlands2186221For institution analysis, there exist 1575 research organisations all over the world with publishing papers with green technology issues. We set the minimum number of documents of an organisation threshold value as 7, and 12 research institutions meet the threshold, of which three institutions are in Malaysia (Univ Sains Malaysia, Univ Malaya, and Univ Teknol Malaysia), two institutions are in China (Chinese Acad Sci and Hongkong Polytec Univ), two institutions are in Canada (Mcgill Univ and Queens Univ), one institution is in South Korea (Seoul Natl Univ), one institution is in Jordan (Jordan Univ Sci and Technol), one institution is in the USA (Texas A&M Univ), one institution is in the UK (Univ Nottingham), and one institution is in Italy (Univ Turin). As shown in Table5, Chinese Acad Sci, which is the top institution, has 19 documents of green technology. Mcgill Univ has 549 most citations of green technology. The total link strength value indicates that the correlation between institutions is quite weak, and individual organisation has limited academic influence.Table 5
Green technology co-authorship of different institutions.
InstitutionDocumentsCitationsTotal link strength1Univ Sains Malaysia948122Chinese Acad Sci1912713Seoul Natl Univ1012414Univ Malaya714615Univ Teknol Malaysia79216Hongkong Polytec Univ1019507Jordan Univ Sci and Technol911208Mcgill Univ854909Queens Univ7191010Texas A&M Univ7139011Univ Nottingham9436012Univ Turin8730


## 3.4. Keyword Cluster Analysis

### 3.4.1. Green Technology Cluster Analysis

Keyword cluster analysis can reveal the specific theme’s present situation and research front. Cluster analysis can detect homogeneous units using an algorithm method [38]. In contrast to other meta-analysis methods, cluster calculation has been proved to have less subjective bias, and strong connections of units reflect the specific theme in the same field [39]. The co-word matrix is commonly constructed from the samples, and statistical variables are used to measure the degree of similarity of indicators. According to different similarities, closely related objects are gathered automatically, which denote the direct connections among keywords or titles in knowledge mapping software. The CiteSpace system provides five types of visualisation style, namely, cluster view, timeline view, timezone view, geographic overlay, and dual-map overlay. The cluster and timeline views are the most popular. The cluster view can reflect the distribution of research area in different dimensions, and the timeline view can tell us the yearly evolution and interaction of each cluster. Two important parameters indicate the quality of cluster mapping, namely, modularity and silhouette values. Generally, if the modularity value is greater than 0.3, then the cluster is significant; if the mean silhouette value is greater than 0.5, then the cluster view is reasonable and acceptable. First, we perform the cluster view operation. The results indicate that the merged network of keywords related to green technology consists of 352 nodes and 1684 links. The parameter modularity value is 0.5225, and the mean silhouette value is 0.6082 (Figure 6).Figure 6
Keyword cluster of green technology.From the statistical results of the keywords from the yearly slice (Table6), we choose the top 10 keywords of the green technology cluster. The top 10 keywords are emission, green technology, performance, energy, design, optimisation, system, behaviour, environment, and product. The maximum value of centrality is 0.15, and the minimum value is 0.07. From the year distribution, we find that the significant nodes range from 2008 to 2015.Table 6
Top 10 keywords in the green technology cluster.
CountCentralityYearKeywords240.152009Emission890.142010Green technology710.112013Performance320.102012Energy200.092011Design600.092013Optimisation150.082008System180.082011Behaviour90.072010Environment150.072015Product


### 3.4.2. Timeline View Evolutionary Analysis of Green Technology

The timeline view in the CiteSpace system can reflect the relationship between clusters and historic duration of the literature. In the timeline view, the horizontal axis is the year distribution and the vertical axis is the labelling of the clusters. Keywords belonging to the same cluster are set in a line according to the date of the published literature. In the timeline view, we can obtain the beginning year of a cluster, the numerical trend of a cluster, and the important literature with high betweenness centrality value. From the timeline view of green technology (Figure7), 10 clusters are labelled with #0–#9 and the distribution of clusters mainly focuses from 1998 to 2020.Figure 7
Timeline view of green technology.In the CiteSpace system, the cluster labelling comes from the citing articles based on three types of algorithms: TF∗IDF, log-likelihood rate, and mutual information. Given that the consciousness of mapping and log-likelihood ratio value can provide quantifying information automatically, we choose log-likelihood rate algorithm. The labelling results and log-likelihood ratio value of green technology clusters are as follows (Table 7). The first cluster labelling is resource-based view, with a total size of 61 keywords, and the mean year is 2014. Under the line, we can see that the first cluster keywords include adoption, green technology impact, sustainability, renewable energy, environmental policy, green cleaner production, and empirical evidence. The second cluster labelling is green technology progress, with a total size of 55 keywords, and the mean year is 2015; it includes keywords of information technology, remote sensing, energy efficiency, green growth, environmental strategy, and environmental regulation. The third cluster is labelled with BR, with a total of 50 keywords and the mean year of 2016; keywords include life cycle assessment, emission, fuel cell, heavy metal, electric vehicle, catalyst, and eco-design. The fourth cluster is labelled with molecular weight, with a total size of 40 keywords and the mean year of 2015; keywords include degradation, green kinetics, fermentation, biodegradation mechanism, polymer, fabrication, and health. The fifth cluster is labelled with ultrasound-assisted extraction, with a total size of 37 keywords and the mean year of 2016; it includes keywords of polymerisation, carbon dioxide, superficial, subcritical water, plant, and assisted extraction. The sixth cluster is labelled with green revolution, with a total size of 31 keywords and the mean year of 2015; it includes keywords of green technology, rice production, social responsibility, supply chain, and environmental prevention. The seventh cluster is labelled with green building technologies, with a total size of 31 keywords and the mean year of 2015; it includes keywords of environment management, design, investment policy, green economy, sustainable development, green building, critical success factor, and barrier. The eighth cluster is labelled with paper mill waste, with a total size of 19 keywords and the mean year of 2012; keywords of this cluster include water, biosorption waste, ironic liquid, acid extraction, recycling, and aqueous solution. The ninth cluster is labelled with organic peroxide, with a total size of 5 keywords and the mean year of 2012; keywords include SADT, organic peroxide, and accelerating decomposition temperature. The tenth cluster is labelled with alginate, with a total size of 3 keywords and the mean year of 2014; it includes keywords of bacteria, Escherichia coli, and temperature.Table 7
10 keyword clusters of green technology.
Cluster IDSizeMean yearTop 10 terms (log-likelihood ratio value)0612014Resource-based view (9.35); geothermal energy (6.22); employment (6.22); institutional theory (6.22); ecological modernisation (6.22); climate change (6.22); innovation (5.32); sustainability (4.1); evaluation (3.11); manufacturing (3.11)1552015Green technology progress (15.31); adoption (7.63); TPB (7.63); big data (7.63); GFT (7.63); pollutant discharge (3.8); software-defined networks (3.8); IoT (3.8); adoption decision (3.8); Bayesian learning (3.8)2502016BR (7.92); CL (7.92); leaching (7.92); BIM technology (7.92); fuel cells (7.92); application (7.92); nanocrystal (7.92); diode (7.92); detoxification (7.92); CsPbX3 (7.92)3402015Molecular weight (9.62); branched structure (9.62); biodegradation (9.62); membrane separations (4.8); chromatography (4.8); fly ash geopolymer (4.8); mesophase (4.8); chain degradation (4.8); saccharification (4.8); criteria weighting (4.8)4372016Ultrasound-assisted extraction (12.99); antioxidant (8.64); supercritical fluid extraction (8.64); polycaprolactone (4.31); supercritical extraction (4.31); antioxidant activity (4.31); ellagitannins (4.31); tough external peels (4.31); green extraction technologies (4.31)5312015Green revolution (15.23); sawah (10.12); chemical properties (5.04); cap-and-trade (5.04); smartphones (5.04); information technology managers (5.04); mealtime (5.04); exchangeable cations (5.04); rice production (5.04); total carbon (5.04)6312015Green building technologies (30.75); promotion strategies (20.37); construction industry (20.37); barriers (20.374); sustainable development (20.3); drivers (15.23); Ghana (10.9); developing countries (10.9); construction market (10.125); new economy (10.12)7192012Paper mill waste (5.29); botanical (5.29); herbal preparation (5.29); quality control (5.29); environmental assessment tool (eat) (5.29); ozonation (5.29); biopolymers (5.29); green chemistry (5.29); recycled paper (5.29); municipal solid waste (5.29);852012Organic peroxide (15.17); vent sizing package (7.53); thermal hazard (7.53); differential scanning calorimetry (7.53); thermokinetic parameters (7.53); consumption energy (7.53); safety parameter (7.53); diffusion (7.53); kinetic (7.53)932014Alginate (6.77); bacterial inactivation (6.77); silica gel (6.77); catalyst (6.77); immobilisation (6.77); energy sustainability (6.77); antimicrobial activity (6.77); bacteria (6.77); organic Rankine cycle (6.77)


### 3.4.3. Brief Summary of the 10 Clusters

From Table8, all the papers about green technology can be divided as follows: three clusters are in the economics and business field, five clusters are in the engineering field, and two clusters are in the chemistry field.Table 8
Summary of research subjects of 10 green technology clusters.
Cluster labellingFieldResearch subjects#0Resource-based viewEconomics and business(1) Sustainability; (2) supply chain; (3) human resources management; (4) carbon dioxide emission#1Green technology progressEconomics and business(1) Green technology progress; (2) paddy farmer; (3) energy efficiency; (4) green growth#2BREngineering(1) Green engineering construction; (2) energy conservation; (3) emerging vehicle technology; (4) coal utilisation; (5) biotechnology#3Molecular weightChemistry(1) Bioremediation; (2) biodegradation; (3) membrane separations; (4) chromatography#4Ultrasound-assisted extractionEngineering(1) Clean extraction; (2) green solvents#5Green revolutionEconomics and business(1) Rice production; (2) information technology; (3) financial services industry; (4) environmental sustainability#6Green building technologiesEngineering(1) Promotion strategies; (2) construction market; (3) driving force; (4) technologies adoption#7Paper mill wasteEngineering(1) Green chemistry; (2) environmental assessment; (3) paper mill waste; (4) municipal solid waste#8Organic peroxideChemistry(1) Organic peroxide; (2) scanning calorimetry; (3) incompatible material; (4) thermal hazard#9AlginateEngineering(1) Alginate; (2) bacterial inactivation; (3) silica gel; (4) catalystThe #0 cluster deals with sustainability, with research subjects mainly about sustainability, supply chain, human resources management, and carbon dioxide emission. Resource-based view theory, which was proposed by Birger Wernerfelt, is an important source of modern core competitive compacity of firms [40]. Each market entity should pay attention to allocate human resources, currency capital, and technology to achieve a more desirable output. Green information technologies and systems refer to initiatives and programs that directly or indirectly address environmental sustainability in organisations [41]. In this cluster, environmental technologies are used in supply chain management to check the collaboration effect between suppliers and customers [42] and corporate sustainable capability may be integrated with information technology and supply chain [43].The #1 cluster concentrates on the green technology progress and innovations in different industries. It includes research subjects of green technology progress, adoption decision, Bayesian learning, energy efficiency, and green growth. Topics include energy strategy should be transformed, hydrogen economy as a greener choice as a carbon-free carrier [44], green building technologies adoption [33], green technology progress measurement of thermoelectric enterprises [45], green technology progress influencing factors [46], and technological progress in green cement industry [47].The #2 cluster explores types of new green technology applicable in chemical and biological engineering. The research subjects are mainly about green engineering construction, energy conservation, emerging vehicle technology, coal utilisation, and biotechnology. The hot topics of this cluster include network energy-saving technologies in mobile industry [48], future wireline networks’ potential economic and environmental consequences [49], smart cities and green growth based on universal infrastructure and green technologies [50], and electric vehicle routing designing and technology to recharge [51].The #3 cluster offers a series of microstructural practices and inner material structure exploratory research. It includes research subjects of bioremediation, biodegradation, membrane separations, and chromatography. These green technologies include phytoremediation technology using diverse plants to remediate contaminated environments [52], polysaccharides modification [53], ferrate as an efficient agent for the abatement of pollutants in water [54], and sorption membrane for water purification and liquid separation [55, 56].The #4 cluster reveals environmentally friendly extraction mechanism of green extraction kinetics and polymerisation processing technologies. The research subjects are mainly about ultrasound-assisted extraction, supercritical fluid extraction, extraction kinetics, clean extraction, polymer blends, and biomedical polymers. Topics include cleaner production purposes embracing supercritical fluid extraction [21], enhancing aqueous extraction processes without using solvents with ultrasound-assisted extraction technology [57], developing green solvents for oil extraction [58], promoting innovation of more environmentally friendly and tuneable solvents [59], and exploring green catalytic techniques of homogeneous liquids and heterogeneous solids in biodiesel production [23].The #5 cluster manifests the social information learning of green revolution in agricultural technology adoption and environmental performance, especially with the cap-and-trade carbon dioxide emission constraint. It includes research subjects of rice production, information technology, financial services industry, and environmental sustainability. It includes discussions on the proper farm size related to effective new technology adoption and credit constraint [60], information flows in social learning of Indian rice and wheat technology revolution [61], technology policy function [62], impact assessment of technology intervention [63], and effects of improved agricultural technologies [64].The #6 cluster presents the driving force of green building technologies adoption and existing barriers in the construction industry. The research subjects are mainly about designers’ adoption behaviours [65], driving force [10], and barriers of green building [66]. New engineering applications of green water technologies [67], green roof technology [68], green wall technology [69], and “green concrete” concept [70] are discussed in this cluster.The #7 cluster focuses on environmental negative impact control, such as water pollution and solid waste disposal and recycling problems. This cluster includes research subjects of green chemistry, environmental assessment, environmental compatibility, paper mill waste, and municipal solid waste. Modern industrial production inevitably comes up with undesirable output, even some pollutive and poisonous substance. Poliakoff (2007) contributed with unsustainable chemical manufacturing and 12 modern principles of green chemistry [71]. Green technologies are developed to realise removal of heavy metals, cyanobacteria, and other hazardous material in water [72, 73]. Some novel processing and methods have also been presented to deal with solid waste, such as industrial and municipal solid waste [74].The #8 cluster reflects the functional materials with unique characterisation and thermal hazard evaluation. The research subjects are mainly about organic peroxide, scanning calorimetry, incompatible material, and thermal hazard. Newly found material characteristics, effective processing adjustment, and novel monitoring tools have been presented. Topics include ionic liquids with unique advantages showing higher selectivity, fast rates, and greater enzyme stability [75]; organic synthesis using microreactor technology having better thermal stability than traditional batch synthesis [76]; polylactide, as packaging material, being suitable for industrial usage, as well as its environmental implications [77]; and for thermal hazard, some novel calorimetric tests and simulation evaluating methods have been presented [78, 79].The #9 cluster concentrates on biological materials and engineering applications. It includes research subjects of alginate, bacterial inactivation, silica gel, catalyst, and immobilisation. Several highly cited papers are about microalgae encapsulation technology [80], green biocides [81], encapsulation in chitosan-based nanomatrix [82], and polyphenol recovery from pomegranate peels [83].


## 3.4.1. Green Technology Cluster Analysis

Keyword cluster analysis can reveal the specific theme’s present situation and research front. Cluster analysis can detect homogeneous units using an algorithm method [38]. In contrast to other meta-analysis methods, cluster calculation has been proved to have less subjective bias, and strong connections of units reflect the specific theme in the same field [39]. The co-word matrix is commonly constructed from the samples, and statistical variables are used to measure the degree of similarity of indicators. According to different similarities, closely related objects are gathered automatically, which denote the direct connections among keywords or titles in knowledge mapping software. The CiteSpace system provides five types of visualisation style, namely, cluster view, timeline view, timezone view, geographic overlay, and dual-map overlay. The cluster and timeline views are the most popular. The cluster view can reflect the distribution of research area in different dimensions, and the timeline view can tell us the yearly evolution and interaction of each cluster. Two important parameters indicate the quality of cluster mapping, namely, modularity and silhouette values. Generally, if the modularity value is greater than 0.3, then the cluster is significant; if the mean silhouette value is greater than 0.5, then the cluster view is reasonable and acceptable. First, we perform the cluster view operation. The results indicate that the merged network of keywords related to green technology consists of 352 nodes and 1684 links. The parameter modularity value is 0.5225, and the mean silhouette value is 0.6082 (Figure 6).Figure 6
Keyword cluster of green technology.From the statistical results of the keywords from the yearly slice (Table6), we choose the top 10 keywords of the green technology cluster. The top 10 keywords are emission, green technology, performance, energy, design, optimisation, system, behaviour, environment, and product. The maximum value of centrality is 0.15, and the minimum value is 0.07. From the year distribution, we find that the significant nodes range from 2008 to 2015.Table 6
Top 10 keywords in the green technology cluster.
CountCentralityYearKeywords240.152009Emission890.142010Green technology710.112013Performance320.102012Energy200.092011Design600.092013Optimisation150.082008System180.082011Behaviour90.072010Environment150.072015Product


## 3.4.2. Timeline View Evolutionary Analysis of Green Technology

The timeline view in the CiteSpace system can reflect the relationship between clusters and historic duration of the literature. In the timeline view, the horizontal axis is the year distribution and the vertical axis is the labelling of the clusters. Keywords belonging to the same cluster are set in a line according to the date of the published literature. In the timeline view, we can obtain the beginning year of a cluster, the numerical trend of a cluster, and the important literature with high betweenness centrality value. From the timeline view of green technology (Figure7), 10 clusters are labelled with #0–#9 and the distribution of clusters mainly focuses from 1998 to 2020.Figure 7
Timeline view of green technology.In the CiteSpace system, the cluster labelling comes from the citing articles based on three types of algorithms: TF∗IDF, log-likelihood rate, and mutual information. Given that the consciousness of mapping and log-likelihood ratio value can provide quantifying information automatically, we choose log-likelihood rate algorithm. The labelling results and log-likelihood ratio value of green technology clusters are as follows (Table 7). The first cluster labelling is resource-based view, with a total size of 61 keywords, and the mean year is 2014. Under the line, we can see that the first cluster keywords include adoption, green technology impact, sustainability, renewable energy, environmental policy, green cleaner production, and empirical evidence. The second cluster labelling is green technology progress, with a total size of 55 keywords, and the mean year is 2015; it includes keywords of information technology, remote sensing, energy efficiency, green growth, environmental strategy, and environmental regulation. The third cluster is labelled with BR, with a total of 50 keywords and the mean year of 2016; keywords include life cycle assessment, emission, fuel cell, heavy metal, electric vehicle, catalyst, and eco-design. The fourth cluster is labelled with molecular weight, with a total size of 40 keywords and the mean year of 2015; keywords include degradation, green kinetics, fermentation, biodegradation mechanism, polymer, fabrication, and health. The fifth cluster is labelled with ultrasound-assisted extraction, with a total size of 37 keywords and the mean year of 2016; it includes keywords of polymerisation, carbon dioxide, superficial, subcritical water, plant, and assisted extraction. The sixth cluster is labelled with green revolution, with a total size of 31 keywords and the mean year of 2015; it includes keywords of green technology, rice production, social responsibility, supply chain, and environmental prevention. The seventh cluster is labelled with green building technologies, with a total size of 31 keywords and the mean year of 2015; it includes keywords of environment management, design, investment policy, green economy, sustainable development, green building, critical success factor, and barrier. The eighth cluster is labelled with paper mill waste, with a total size of 19 keywords and the mean year of 2012; keywords of this cluster include water, biosorption waste, ironic liquid, acid extraction, recycling, and aqueous solution. The ninth cluster is labelled with organic peroxide, with a total size of 5 keywords and the mean year of 2012; keywords include SADT, organic peroxide, and accelerating decomposition temperature. The tenth cluster is labelled with alginate, with a total size of 3 keywords and the mean year of 2014; it includes keywords of bacteria, Escherichia coli, and temperature.Table 7
10 keyword clusters of green technology.
Cluster IDSizeMean yearTop 10 terms (log-likelihood ratio value)0612014Resource-based view (9.35); geothermal energy (6.22); employment (6.22); institutional theory (6.22); ecological modernisation (6.22); climate change (6.22); innovation (5.32); sustainability (4.1); evaluation (3.11); manufacturing (3.11)1552015Green technology progress (15.31); adoption (7.63); TPB (7.63); big data (7.63); GFT (7.63); pollutant discharge (3.8); software-defined networks (3.8); IoT (3.8); adoption decision (3.8); Bayesian learning (3.8)2502016BR (7.92); CL (7.92); leaching (7.92); BIM technology (7.92); fuel cells (7.92); application (7.92); nanocrystal (7.92); diode (7.92); detoxification (7.92); CsPbX3 (7.92)3402015Molecular weight (9.62); branched structure (9.62); biodegradation (9.62); membrane separations (4.8); chromatography (4.8); fly ash geopolymer (4.8); mesophase (4.8); chain degradation (4.8); saccharification (4.8); criteria weighting (4.8)4372016Ultrasound-assisted extraction (12.99); antioxidant (8.64); supercritical fluid extraction (8.64); polycaprolactone (4.31); supercritical extraction (4.31); antioxidant activity (4.31); ellagitannins (4.31); tough external peels (4.31); green extraction technologies (4.31)5312015Green revolution (15.23); sawah (10.12); chemical properties (5.04); cap-and-trade (5.04); smartphones (5.04); information technology managers (5.04); mealtime (5.04); exchangeable cations (5.04); rice production (5.04); total carbon (5.04)6312015Green building technologies (30.75); promotion strategies (20.37); construction industry (20.37); barriers (20.374); sustainable development (20.3); drivers (15.23); Ghana (10.9); developing countries (10.9); construction market (10.125); new economy (10.12)7192012Paper mill waste (5.29); botanical (5.29); herbal preparation (5.29); quality control (5.29); environmental assessment tool (eat) (5.29); ozonation (5.29); biopolymers (5.29); green chemistry (5.29); recycled paper (5.29); municipal solid waste (5.29);852012Organic peroxide (15.17); vent sizing package (7.53); thermal hazard (7.53); differential scanning calorimetry (7.53); thermokinetic parameters (7.53); consumption energy (7.53); safety parameter (7.53); diffusion (7.53); kinetic (7.53)932014Alginate (6.77); bacterial inactivation (6.77); silica gel (6.77); catalyst (6.77); immobilisation (6.77); energy sustainability (6.77); antimicrobial activity (6.77); bacteria (6.77); organic Rankine cycle (6.77)


## 3.4.3. Brief Summary of the 10 Clusters

From Table8, all the papers about green technology can be divided as follows: three clusters are in the economics and business field, five clusters are in the engineering field, and two clusters are in the chemistry field.Table 8
Summary of research subjects of 10 green technology clusters.
Cluster labellingFieldResearch subjects#0Resource-based viewEconomics and business(1) Sustainability; (2) supply chain; (3) human resources management; (4) carbon dioxide emission#1Green technology progressEconomics and business(1) Green technology progress; (2) paddy farmer; (3) energy efficiency; (4) green growth#2BREngineering(1) Green engineering construction; (2) energy conservation; (3) emerging vehicle technology; (4) coal utilisation; (5) biotechnology#3Molecular weightChemistry(1) Bioremediation; (2) biodegradation; (3) membrane separations; (4) chromatography#4Ultrasound-assisted extractionEngineering(1) Clean extraction; (2) green solvents#5Green revolutionEconomics and business(1) Rice production; (2) information technology; (3) financial services industry; (4) environmental sustainability#6Green building technologiesEngineering(1) Promotion strategies; (2) construction market; (3) driving force; (4) technologies adoption#7Paper mill wasteEngineering(1) Green chemistry; (2) environmental assessment; (3) paper mill waste; (4) municipal solid waste#8Organic peroxideChemistry(1) Organic peroxide; (2) scanning calorimetry; (3) incompatible material; (4) thermal hazard#9AlginateEngineering(1) Alginate; (2) bacterial inactivation; (3) silica gel; (4) catalystThe #0 cluster deals with sustainability, with research subjects mainly about sustainability, supply chain, human resources management, and carbon dioxide emission. Resource-based view theory, which was proposed by Birger Wernerfelt, is an important source of modern core competitive compacity of firms [40]. Each market entity should pay attention to allocate human resources, currency capital, and technology to achieve a more desirable output. Green information technologies and systems refer to initiatives and programs that directly or indirectly address environmental sustainability in organisations [41]. In this cluster, environmental technologies are used in supply chain management to check the collaboration effect between suppliers and customers [42] and corporate sustainable capability may be integrated with information technology and supply chain [43].The #1 cluster concentrates on the green technology progress and innovations in different industries. It includes research subjects of green technology progress, adoption decision, Bayesian learning, energy efficiency, and green growth. Topics include energy strategy should be transformed, hydrogen economy as a greener choice as a carbon-free carrier [44], green building technologies adoption [33], green technology progress measurement of thermoelectric enterprises [45], green technology progress influencing factors [46], and technological progress in green cement industry [47].The #2 cluster explores types of new green technology applicable in chemical and biological engineering. The research subjects are mainly about green engineering construction, energy conservation, emerging vehicle technology, coal utilisation, and biotechnology. The hot topics of this cluster include network energy-saving technologies in mobile industry [48], future wireline networks’ potential economic and environmental consequences [49], smart cities and green growth based on universal infrastructure and green technologies [50], and electric vehicle routing designing and technology to recharge [51].The #3 cluster offers a series of microstructural practices and inner material structure exploratory research. It includes research subjects of bioremediation, biodegradation, membrane separations, and chromatography. These green technologies include phytoremediation technology using diverse plants to remediate contaminated environments [52], polysaccharides modification [53], ferrate as an efficient agent for the abatement of pollutants in water [54], and sorption membrane for water purification and liquid separation [55, 56].The #4 cluster reveals environmentally friendly extraction mechanism of green extraction kinetics and polymerisation processing technologies. The research subjects are mainly about ultrasound-assisted extraction, supercritical fluid extraction, extraction kinetics, clean extraction, polymer blends, and biomedical polymers. Topics include cleaner production purposes embracing supercritical fluid extraction [21], enhancing aqueous extraction processes without using solvents with ultrasound-assisted extraction technology [57], developing green solvents for oil extraction [58], promoting innovation of more environmentally friendly and tuneable solvents [59], and exploring green catalytic techniques of homogeneous liquids and heterogeneous solids in biodiesel production [23].The #5 cluster manifests the social information learning of green revolution in agricultural technology adoption and environmental performance, especially with the cap-and-trade carbon dioxide emission constraint. It includes research subjects of rice production, information technology, financial services industry, and environmental sustainability. It includes discussions on the proper farm size related to effective new technology adoption and credit constraint [60], information flows in social learning of Indian rice and wheat technology revolution [61], technology policy function [62], impact assessment of technology intervention [63], and effects of improved agricultural technologies [64].The #6 cluster presents the driving force of green building technologies adoption and existing barriers in the construction industry. The research subjects are mainly about designers’ adoption behaviours [65], driving force [10], and barriers of green building [66]. New engineering applications of green water technologies [67], green roof technology [68], green wall technology [69], and “green concrete” concept [70] are discussed in this cluster.The #7 cluster focuses on environmental negative impact control, such as water pollution and solid waste disposal and recycling problems. This cluster includes research subjects of green chemistry, environmental assessment, environmental compatibility, paper mill waste, and municipal solid waste. Modern industrial production inevitably comes up with undesirable output, even some pollutive and poisonous substance. Poliakoff (2007) contributed with unsustainable chemical manufacturing and 12 modern principles of green chemistry [71]. Green technologies are developed to realise removal of heavy metals, cyanobacteria, and other hazardous material in water [72, 73]. Some novel processing and methods have also been presented to deal with solid waste, such as industrial and municipal solid waste [74].The #8 cluster reflects the functional materials with unique characterisation and thermal hazard evaluation. The research subjects are mainly about organic peroxide, scanning calorimetry, incompatible material, and thermal hazard. Newly found material characteristics, effective processing adjustment, and novel monitoring tools have been presented. Topics include ionic liquids with unique advantages showing higher selectivity, fast rates, and greater enzyme stability [75]; organic synthesis using microreactor technology having better thermal stability than traditional batch synthesis [76]; polylactide, as packaging material, being suitable for industrial usage, as well as its environmental implications [77]; and for thermal hazard, some novel calorimetric tests and simulation evaluating methods have been presented [78, 79].The #9 cluster concentrates on biological materials and engineering applications. It includes research subjects of alginate, bacterial inactivation, silica gel, catalyst, and immobilisation. Several highly cited papers are about microalgae encapsulation technology [80], green biocides [81], encapsulation in chitosan-based nanomatrix [82], and polyphenol recovery from pomegranate peels [83].


## 4. Conclusions and Policy Implications

Green technology is seemed to be used increasingly widely in different disciplines. This study uses knowledge mapping tools of CiteSpace and VOSviewer software to examine the development of green technology theme. We find that green technology concept came into being in the 1960s and became gradually popular in the 2000s. The research interest of green technology has been growing dramatically in the recent decade, with a sharp increase in published research papers and citation records.Of the total 1136 green technology papers covering 149 research fields, the top three fields are environmental sciences, green sustainable science technology, and engineering environmental, and there exists about a quarter ratio of the total sample literature about environmental sciences. We can expect that more and more green technologies will be developed in the near future. From the cited journals of green technology, we find that the top 10 journals areJournal of Cleaner Production, Resources Conservation and Recycling, Environmental Science and Technology, Science, Journal of Hazardous Materials, Industrial and Engineering Chemistry Research, Bioresource Technology, Journal of Chemical Technology and Biotechnology, Chemical Review, and MIS Quarterly, with the use of parameter of centrality and publishing number. In the WoS database, 13 highly cited papers are related to the theme of green technology from 2009 to 2020, and they can be ascribed to chemistry, engineering, economics and business, and geosciences fields.From the co-authorship analysis of green technology, we find that the network of research cooperation is quite weak. Only three little networks are labelled with different colours. From the country and institution analysis, we find that developed countries (the USA, England, etc.) and developing countries (China, Malaysia, etc.) have quite a few documents of green technology, and according to the parameter of CN and total link strength value, we obtain the top 15 counties. After the institution analysis of the green technology literature, 12 important institutions in 8 countries are recognised, but no dominant institutions have become eccentric. We find that they perform their research quite independently. In the knowledge mapping of cluster analysis, 10 keyword clusters of green technology papers are in the WoS database and three clusters are of economical theme, five clusters are of engineering application, and two clusters are of chemical issues.In the future, we should strengthen the achievements of green technology progress, promote the level of innovation, and accelerate the regional flow of innovation factors. We should solve the bottleneck of green technology development of high-levelled human, material, and financial resources; focus on the “double base” construction to address key technical problems affecting industrial development, and break through the “neck” technical problems. At the same time, administrative departments should strengthen financial support for high-quality economic development; enhance the efficiency of financial investment in green technology and industry; and increase the auditing and inspection intensity of the use of financial investment funds to improve the interactive quality of green technological progress, financial investment, economic quality, and development level.



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*Source: 6298813-2021-11-27.xml*