In this section, the study presents the results of performance analysis and bibliometric analysis. From sections 3.1. to 3.7, the study will answer the research questions 1 to 7, respectively. Sections 3.8, 3.9. and 3.10. will answer research questions 8, 9, and 10, respectively.
3.1 Publications by Year
Fig.1 presents the trend in the number of articles published in the combined research area of trade and environment. The first paper in this area was published by Pethig (1976), where the author tested hypotheses based on Neo-classical Trade Theory for pollution generating industries in different countries. However, since the focus of the present bibliometric study is the last two decades, the scope of articles is limited to those published from 2000 to October 2021. As is visible in Fig.1, overall, there is an increasing trend in the number of publications during the period of analysis. The highest numbers of articles (107 articles) were published in 2019 and 2020 followed by 100 articles in 2018. The lowest number of published articles during the study period (25 articles) was in 2004. In the year 2021, up to 12 October 2021, 97 articles were published in this area of research. Thus, the trade-environment intersection area of research is even now an increasingly sought-after topic in the academic research arena.
3.2 Publications by Countries
Table 3 shows the top 20 publishing countries in terms of affiliation of corresponding author’s country on the trade-environment research theme. Each of these 20 countries published a minimum of 13 articles. Top publishing countries are the USA, China, United Kingdom, Germany, and Australia with each country contributing more than 50 articles. In terms of total citations, the USA again ranked first with 8400 citations followed by the United Kingdom with 3577 citations and China with 3093 citations. However, in terms of average citations per document, Hong Kong is ranked first with 63.46 average citations followed by Sweden (40.18) and the Netherlands (39.10). From table 3, it can be seen that only China and India are the developing countries that are featured in the top 20 publishing countries in terms of the number of publications in the trade-environment intersection area of research.
Table 3
Top 20 Publishing Countries
Country
|
No. of Publications
|
Total Citations
|
Average Citations Per Article
|
USA
|
259
|
8400
|
32.43
|
CHINA
|
162
|
3093
|
19.09
|
UNITED KINGDOM
|
95
|
3577
|
37.65
|
GERMANY
|
74
|
1959
|
26.47
|
AUSTRALIA
|
57
|
1827
|
32.05
|
CANADA
|
49
|
1372
|
28.00
|
JAPAN
|
44
|
1046
|
23.77
|
FRANCE
|
41
|
766
|
18.68
|
ITALY
|
35
|
1315
|
37.57
|
SPAIN
|
34
|
1252
|
36.82
|
NORWAY
|
30
|
584
|
19.47
|
NETHERLANDS
|
29
|
1134
|
39.10
|
SWITZERLAND
|
26
|
858
|
33.00
|
SWEDEN
|
22
|
884
|
40.18
|
INDIA
|
21
|
485
|
23.10
|
KOREA
|
18
|
426
|
23.67
|
AUSTRIA
|
16
|
547
|
34.19
|
FINLAND
|
15
|
221
|
14.73
|
HONG KONG
|
13
|
825
|
63.46
|
DENMARK
|
13
|
346
|
26.62
|
3.3 Most frequent Journals
A total of 1390 articles appeared in 324 journals. Fig. 2 lists the top 20 journals based on the highest number of articles on the trade-environment concept. The top publishing journals are Journal of Cleaner Production with 133 publications followed by Environmental and Resource Economics with 115 and Ecological Economics with 112 publications. Table 4 shows the most impact-full journals based on the total citations, h-index, m-index, and g-index. h-index is the Journal’s number of published articles(h) each of which is cited in other papers h times. m-index is the ratio of h-index divided by the number of years since the first paper was published in the journal. g-index is the (unique) largest number such that the top g articles received (together) at least g² citations. Based on the three indices and total citations, the top and the impactful sources are Journal of Cleaner Production, Environmental and Resource Economics, Ecological Economics, Energy Economics, and Journal of Environmental Economics and Management. According to Bradford’s law (Bradford, 1934; Hjørland and Nicolaisen, 2005), these five journals are the core journals as they together account for 1/3rd of the total publications in the trade and environment research theme (Fig. 3).
Table 4
Most Impact-full Journals
Sources
|
Total Citations
|
Number of Articles
|
h-index
|
g-index
|
m-index
|
Year of First Article
|
JOURNAL OF CLEANER PRODUCTION
|
4599
|
126
|
35
|
62
|
1.59
|
2000
|
ENVIRONMENTAL AND RESOURCE ECONOMICS
|
2064
|
111
|
25
|
40
|
1.14
|
2000
|
ECOLOGICAL ECONOMICS
|
5707
|
106
|
38
|
74
|
1.73
|
2000
|
ENERGY ECONOMICS
|
2844
|
76
|
31
|
51
|
1.41
|
2000
|
JOURNAL OF ENVIRONMENTAL ECONOMICS AND MANAGEMENT
|
3768
|
75
|
34
|
60
|
1.70
|
2002
|
RESOURCES, CONSERVATION AND RECYCLING
|
1862
|
54
|
22
|
42
|
1.05
|
2001
|
RESOURCE AND ENERGY ECONOMICS
|
548
|
27
|
12
|
23
|
0.57
|
2001
|
INTERNATIONAL ENVIRONMENTAL AGREEMENTS: POLITICS, LAW AND ECONOMICS
|
295
|
26
|
10
|
16
|
0.67
|
2007
|
WORLD ECONOMY
|
514
|
26
|
12
|
22
|
0.55
|
2000
|
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
|
1038
|
20
|
15
|
20
|
0.88
|
2005
|
BUSINESS STRATEGY AND THE ENVIRONMENT
|
843
|
19
|
14
|
19
|
0.67
|
2001
|
ENVIRONMENT AND DEVELOPMENT ECONOMICS
|
484
|
16
|
9
|
16
|
0.41
|
2000
|
JOURNAL OF WORLD TRADE
|
104
|
15
|
6
|
9
|
0.33
|
2004
|
RESOURCES POLICY
|
417
|
14
|
10
|
14
|
0.45
|
2000
|
AUSTRALIAN JOURNAL OF AGRICULTURAL AND RESOURCE ECONOMICS
|
227
|
13
|
9
|
13
|
0.41
|
2000
|
MARINE POLICY
|
262
|
13
|
8
|
13
|
0.62
|
2009
|
WORLD DEVELOPMENT
|
278
|
13
|
11
|
13
|
0.52
|
2001
|
ECONOMIC MODELLING
|
264
|
12
|
7
|
12
|
0.32
|
2000
|
FOREST POLICY AND ECONOMICS
|
156
|
12
|
7
|
12
|
0.78
|
2013
|
ENVIRONMENTAL ECONOMICS AND POLICY STUDIES
|
72
|
11
|
5
|
8
|
0.23
|
2000
|
3.4 Most Relevant Authors
Productivity and impact are two of the important criteria to evaluate the relevance of an author in a particular research field. The productivity of an author can be measured by the number of articles produced in a given period and impact can be evaluated by the total number of citations received in each year (Forliano et al., 2021). Fig. 4 presents the most relevant authors list with both these measures. In the figure, the line represents the authors’ timeline, bubble size is proportional to the number of documents, and darkness of bubbles is proportional to total citations. It can be noted that Chen Y (10), Cole MA (8), and Liu Y (8) are the most productive authors during the timeline. Further, Cole MA (509 in 2003), Elliott RJR (386 in 2003), and Lai K-H (350 in 2012) received the highest number of citations in a year.
To know the most relevant authors, some studies advocate computation of author-based measures including h-index, m-index along with total citation (TC), and the number of publications (NP) (Bretas and Alon, 2021; Forliano, et al., 2021). Table 5 presents the top 20 productive authors based on these four measures. The most cited authors in the list are Cole MA (921), Elliott RJR (593), and Lai K-H (506). Cole MA is also the best combination of productivity and impact, as the author has 8 publications and an h-index of 8 (each article received a minimum 8 number of citations). This author is followed by Rutherford TF with 7 publications and an h-index of 7 and Chen Y with 6 publications and an h-index of 6. The m-index is used to avoid penalizing the younger scholars who have just started publishing in this area. m-index is defined as the h-index weighted for the activity period of an author (Hirsch, 2007). Wang Y and Nassani AA are the most recent productive authors in this area and both started publishing in 2018. Their respective m-indices are 1.25 and 0.75.
Table 5
Most productive authors based on h-index
Element
|
h-index
|
m-index
|
TCa
|
NPb
|
PY_startc
|
COLE MA
|
8
|
0.421
|
924
|
8
|
2003
|
BÖHRINGER C
|
6
|
0.462
|
278
|
7
|
2009
|
LIU Y
|
5
|
0.5
|
145
|
7
|
2012
|
RUTHERFORD TF
|
7
|
0.538
|
360
|
7
|
2009
|
WANG Y
|
5
|
1.25
|
118
|
7
|
2018
|
CHEN Y
|
6
|
0.462
|
105
|
6
|
2009
|
ELLIOTT RJR
|
5
|
0.263
|
596
|
6
|
2003
|
FREDRIKSSON PG
|
5
|
0.25
|
306
|
6
|
2002
|
HUANG Y
|
4
|
0.4
|
86
|
6
|
2012
|
LAI Y-B
|
5
|
0.278
|
55
|
6
|
2004
|
GREAKER M
|
5
|
0.263
|
132
|
5
|
2003
|
HAMDI-CHERIF M
|
4
|
0.571
|
199
|
5
|
2015
|
LAI K-H
|
5
|
0.455
|
507
|
5
|
2011
|
LI J
|
4
|
0.235
|
45
|
5
|
2005
|
LI Y
|
3
|
0.375
|
62
|
5
|
2014
|
LI Z
|
3
|
0.333
|
102
|
5
|
2013
|
MCAUSLAND C
|
5
|
0.25
|
142
|
5
|
2002
|
NASSANI AA
|
3
|
0.75
|
83
|
5
|
2018
|
REILLY JM
|
5
|
0.385
|
168
|
5
|
2009
|
WANG S
|
5
|
0.294
|
112
|
5
|
2005
|
a=total citations, b= number of publications, c= year of the first published paper
3.5 Most Productive Institutions
Table 6 describes the top 20 affiliated institutes of authors based on their number of publications. In total 1269 institutes were involved in the publications of articles in the trade-environment research theme. Among the top 20 research institutes, 6 were from China, and 5 were from the USA. One interesting finding is that both these countries are also leading ones in terms of the highest number of articles (Table 2). However, although Germany, Canada, Japan, France, Italy, and Spain featured in the top 10 publishing countries, none of the institutes from these countries are in the list of top 20 most productive institutes. The University of California has the highest number of publications with 33 publications. This is followed by Tsinghua University with 22 articles and Peking University with 17 articles.
Table 6
Most Productive Institutions
Affiliations
|
Country
|
Articles
|
UNIVERSITY OF CALIFORNIA
|
USA
|
33
|
TSINGHUA UNIVERSITY
|
China
|
22
|
PEKING UNIVERSITY
|
China
|
17
|
KING SAUD UNIVERSITY
|
Saudi Arabia
|
16
|
UNIVERSITY OF BIRMINGHAM
|
UK
|
16
|
WAGENINGEN UNIVERSITY
|
Netherlands
|
16
|
LUND UNIVERSITY
|
Sweden
|
14
|
RENMIN UNIVERSITY OF CHINA
|
China
|
14
|
THE HONG KONG POLYTECHNIC UNIVERSITY
|
Hong Kong
|
14
|
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
|
USA
|
13
|
TIANJIN UNIVERSITY
|
China
|
13
|
UNIVERSITY OF MARYLAND
|
USA
|
13
|
NORTHEASTERN UNIVERSITY
|
USA
|
12
|
POTSDAM INSTITUTE FOR CLIMATE IMPACT RESEARCH
|
Germany
|
12
|
UNIVERSITY OF MANCHESTER
|
UK
|
12
|
AUSTRALIAN NATIONAL UNIVERSITY
|
Australia
|
11
|
FINNISH ENVIRONMENT INSTITUTE
|
Finland
|
11
|
NORTH CHINA ELECTRIC POWER UNIVERSITY
|
China
|
11
|
SICHUAN UNIVERSITY
|
China
|
11
|
STANFORD UNIVERSITY
|
USA
|
11
|
3.6 Citations Analysis
The number of citations received by a document is considered to be one of the most suitable measures to identify the most influential articles in the current research front (Merigo et al., 2015). Citation analysis enables the establishment of intellectual linkages by using citations and references of the published articles (Appio et al., 2014). Table 7 represents the top 20 research publications by the global citations (GC), where GC means the number of citations received by the documents from the entire database including works in other research areas and disciplines. Local citations (LC) are the number of citations received by the documents within the collected database only (in this study citation received from 1390 documents). In Table 7, the average number of global citations received each year (GC/Y) and normalized global citations are also shown. In the present study, Christmann and Taylor (2001) received the most GCs (657) followed by Zhu and Sarkis (2006) with 598 GCs and Tanner and Kast (2003) with 528 GCs. The leading articles in terms of LCs are Levinson and Taylor (2008) with 48 LCs followed by Cole and Elliott (2003) with 24 LCs and Managi et al. (2009) with 22 LCs. The top three articles in terms of the highest LCs focused on the relationship between environment and international trade. While the first two articles focused on PHH/PHE, Managi et al. (2009) worked on the theme of trade openness and environment quality. In terms of GC/Y and normalized total citations, Wu and Pagell (2011) ranked first followed by Zhu and Sarkis (2006) and Christmann and Taylor (2001). While the first two articles were concerned with green or sustainable supply chain management, the study by Christmann and Taylor (2001) focused on the positive environmental effects of globalization.
Table 7
Top 20 most relevant documents in the dataset ordered by the global citations received (GC)
Authors
|
Title
|
Journal
|
Year
|
GCa
|
LCb
|
GC/Yc
|
Normalized GC
|
Christmann and Taylor
|
Globalization and the environment: determinants of firm self-regulation in China
|
Journal of international business studies
|
2001
|
657
|
10
|
31.29
|
14.13
|
Zhu and Sarkis
|
An inter-sectoral comparison of green supply chain management in China: drivers and practices
|
Journal of cleaner production
|
2006
|
598
|
3
|
37.38
|
12.58
|
Tanner and Kast
|
Promoting sustainable consumption: determinants of green purchases by Swiss consumers
|
Psychology and marketing
|
2003
|
528
|
0
|
27.79
|
8.32
|
Wu and Pagell
|
Balancing priorities: decision-making in sustainable supply chain management
|
Journal of operations management
|
2011
|
483
|
2
|
43.91
|
13.20
|
Levinson and Taylor
|
Unmasking the pollution haven effect
|
International economic review
|
2008
|
391
|
48
|
27.93
|
9.15
|
Cole and Elliott
|
Determining the trade-environment composition effect: the role of capital, labor, and environmental regulations
|
Journal of environmental economics and management
|
2003
|
387
|
24
|
20.37
|
6.10
|
Druckman and Jackson
|
The carbon footprint of UK households 1990-2004: a socio-economically disaggregated, quasi-multi-regional input-output model
|
Ecological economics
|
2009
|
380
|
2
|
29.23
|
8.70
|
Carter et al.
|
Environmental purchasing and firm performance: an empirical investigation
|
Transportation research part e: logistics and transportation review
|
2000
|
364
|
3
|
16.55
|
8.17
|
Cederberg and Mattsson
|
Life cycle assessment of milk production - a comparison of conventional and organic farming
|
Journal of cleaner production
|
2000
|
363
|
0
|
16.50
|
8.15
|
Weber and Matthews
|
Quantifying the global and distributional aspects of American household carbon footprint
|
Ecological economics
|
2008
|
361
|
3
|
25.79
|
8.45
|
Beise and Rennings
|
Lead markets and regulation: a framework for analyzing the international diffusion of environmental innovations
|
Ecological economics
|
2005
|
307
|
4
|
18.06
|
6.47
|
Rehfeld et al.
|
Integrated product policy and environmental product innovations: an empirical analysis
|
Ecological economics
|
2007
|
295
|
3
|
19.67
|
7.02
|
Xing and Kolstad
|
Do lax environmental regulations attract foreign investment?
|
Environmental and resource economics
|
2002
|
283
|
18
|
14.15
|
7.33
|
Lai and Wong
|
Green logistics management and performance: some empirical evidence from Chinese manufacturing exporters
|
Omega
|
2012
|
274
|
3
|
27.40
|
7.37
|
Tukker et al.
|
Exiopol - development and illustrative analyses of a detailed global mr ee sut/iot
|
Economic systems research
|
2013
|
251
|
0
|
27.89
|
9.55
|
Managi et al.
|
Does trade openness improve environmental quality?
|
Journal of environmental economics and management
|
2009
|
247
|
22
|
19.00
|
5.65
|
Wiedmann et al.
|
Quo Vadis Mrio? Methodological, data and institutional requirements for multi-region input-output analysis
|
Ecological economics
|
2011
|
235
|
2
|
21.36
|
6.42
|
Oltra and Saint Jean
|
Sectoral systems of environmental innovation: an application to the French automotive industry
|
Technological forecasting and social change
|
2009
|
227
|
1
|
17.46
|
5.19
|
Damania et al.
|
Trade liberalization, corruption, and environmental policy formation: theory and evidence
|
Journal of environmental economics and management
|
2003
|
221
|
19
|
11.63
|
3.48
|
Carlson et al.
|
Sulfur dioxide control by electric utilities: what are the gains from trade?
|
Journal of political economy
|
2000
|
216
|
6
|
9.82
|
4.85
|
a= global citations, b= local citations, c= global citations/year
3.7 Keyword Analysis
The frequency of occurrence and relevance of keyword plus and author keywords are analyzed here. Table 8 represents the top 20 most frequently occurring keywords plus and authors keywords. Among the keywords used in the search query for this study, “Environmental Policy” is the most frequently occurring keyword in both keywords plus and author's keywords list. Among keywords other than those used in the search query, the frequently occurring keywords include climate change, China, sustainable development, emissions trading, and Carbon dioxide (CO2 emission) in the top 20 lists of keywords plus and authors keywords. Fig. 5 (A) and Fig. 5 (B) depict the word cloud of the top 50 keywords plus and authors keywords, respectively. The top two keywords were not shown in the word clouds because they consist of the set of terms used to build up the query. Word cloud/tag cloud helps to quickly identify the most prominent words in the literature and the importance of each word is shown in the font size or color/shade of the words. In both these figures, one can see that emission control, China, commerce, climate policy, sustainability, carbon emission, carbon leakage, environmental Kuznets curve, pollution haven hypothesis are the most blooming keywords suggesting that these keywords occurred most frequently.
Table 8
Most Frequent Keywords
Keywords Plus
|
No. of articles
|
Authors Keywords
|
No. of articles
|
Environmental policy
|
564
|
Environmental policy
|
114
|
Environmental protection
|
345
|
Environmental regulation
|
81
|
Environmental economics
|
279
|
Climate policy
|
68
|
International trade
|
241
|
International trade
|
66
|
Emission control
|
206
|
China
|
62
|
Commerce
|
191
|
Climate change
|
58
|
Climate change
|
161
|
Environment
|
54
|
Environmental regulations
|
154
|
Trade
|
54
|
Trade-environment relations
|
152
|
Carbon leakage
|
35
|
Sustainable development
|
149
|
Sustainable development
|
32
|
Emissions trading
|
138
|
Sustainability
|
31
|
Carbon emission
|
132
|
Emissions trading
|
30
|
Carbon dioxide
|
130
|
Cap-and-trade
|
29
|
China
|
124
|
Environmental regulations
|
27
|
Economic and social effects
|
118
|
Pollution
|
20
|
Environmental impact
|
108
|
Co2 emissions
|
19
|
United states
|
102
|
Foreign direct investment
|
19
|
Trade-off
|
100
|
Uncertainty
|
19
|
Carbon
|
98
|
Pollution haven hypothesis
|
17
|
Economics
|
96
|
Cap and trade
|
16
|
3.8 Conceptual structure
The conceptual structure represents the relationship among concepts and words in a set of publications. This structure embodies themes based on the connection between the keywords (De la Hoz-Correa et al., 2018). The conceptual structure can be explained with the help of the co-occurrence network and the thematic evolution of keywords. Co-occurrence networks link the keywords that occur simultaneously in an article, thereby indicating that a relationship exists between the concepts. Thematic map or evolution analyzes the evolution of the topic over time.
In this study, the co-occurrences were identified between the author's keywords, as they are more comprehensive in representing an articles’ content in comparison to other types of keywords (Zhang et al. 2016). By following the Louvain cluster algorithm (Blondel et al., 2008), the study detected 50 most developed keywords that were connected, which is represented in Fig. 6. In the figure, the words with higher identified co-occurrences word will appear in the center. The proportion of bubbles represents the occurrence of the keywords in the dataset. The links or the edge size is proportional to item co-occurrence. Each color defines a cluster. In the present study, there are five clusters. They are,
- Red Bubbles: environmental policy, international trade, sustainability, porter hypothesis
- Blue Bubbles: environmental regulation, China, air pollution, environmental protection
- Green Bubbles: climate policy, climate change, carbon leakage, emissions trading
- Purple Bubbles: environment, sustainable development, pollution
- Yellow Bubbles: co2 emissions, foreign direct investment, pollution haven hypothesis, environmental Kuznets curve
The study presented a thematic evolution of the topic in different periods in Fig. 7 to get more comprehensive information about the sub-topic. Notably, co-occurrence of top 250 high-frequency author’s keywords was considered and two cut-off points were identified by the software tool as 2011 and 2017. As a result, the strategic diagrams for three consecutive sub-periods, 2000-2011, 2012-2017, and 2018-2021 were produced, which is shown in Fig. 7. The first slice contains the topic of 11 years, whereas the second slice contains the topic of 6 years and the third slice is only 4 years because very limited papers are published in the early years and abundant articles are published in recent years (Fig. 7). Thematic maps are very helpful to the researchers to examine the evolution of themes in the four different quadrants (Cobo et al., 2011), identified based on their centrality (plotted on the X-axis) and density (plotted on the Y-axis). Centrality measures the extent to which a theme is connected to other themes in the domain and the relevance of the theme in the overall development of a particular domain. Density measures the extent to which the keywords in a given cluster are internally connected and measures the development of the specific research theme. In the thematic map, the upper right quadrant contains the motor theme, which means high centrality (significance) and high density (well developed). The lower-left quadrant represents low centrality and low density that means the emerging or the declining theme or topic. The upper-left quadrant with low centrality and high density shows highly developed and isolated or specialized themes and, the lower-right quadrant shows basic and transversal themes.
As it is clear from Fig. 7 (A), (B), and (C), the majority of the themes in the present study are located in the top-right and bottom-right quadrants. This implies that the topics are highly significant (high centrality) and either highly developed (high density) or low developed (low density) for the development of the trade-environment intersection research domain. Studies related to environmental regulations, carbon leakage, climate policy, international trade, and cap-and-trade that were in the lower-right quadrant with low density and high centrality in the first period have moved to high density and high centrality quadrant in the second period. However, in the latest period again these topics have moved to low density and high centrality quadrant. This implies that these themes developed during the second time period and have now become general or basic themes for various studies in the overall research domain. Topics such as environmental protection, economic growth, air pollution, international environmental agreements, and CO2 emission were remain in the low density and high centrality quadrants. That means they are highly significant to the overall research domain but are not that much developed. Thus, there is scope for researchers to pursue future work on these topics. The topic of sustainability started as an emerging topic in the first two periods and is now the most influential and highly developed topic. On the whole, it can be seen that the time horizons of the periods have decreased but the number of topics has increased, signifying the growing richness and diversity of work in the intersection of trade and environment research front.
3.9 Intellectual Structure
The intellectual structure of science mapping helps to analyze how an author’s work impacts a given scientific community. It represents the relationship between the cited references in the database by using a co-citation network to capture the intellectual structure (Small, 1973). Co-citation analysis helps to identify clusters of papers that share similar content (Elango, 2019). As, it is useful to know the structure, directions, and development of the research areas (Liu et al., 2015). Co-citation analysis analyzes the frequency of two documents being cited together by other documents (Small, 1973). Here, the unit of analysis is cited references that are cited by the documents of the collected dataset and the co-citation strength between two references will be more if they receive more citations from the documents.
The co-citation network of references for the present study is shown in Fig. 8. The size of the nodes represents the number of citations received by the references in the dataset and the thickness of the edge (the line between the nodes) is in proportion to the strength of co-citation. As shown in Fig. 8, the co-citation network resulted in 4 different clusters in four different colors. Betweenness centrality (Freeman, 1978) of a node plays an important role in the network analysis, as the higher the betweenness centrality of a node higher will be the importance of the article (Koseoglu, 2016b; Huang et al., 2021; Kang et al., 2021). It is defined as the shortest path between nodes that passes through a particular node and the node having higher betweenness scores control all the information and play the role of gatekeeper and broker in the network analysis (Wang et al., 2016; Freeman, 1978). Cluster-1 (Red) comprises 22 contributions, spanning from 1990 to 2012. In this cluster, the article by Copeland and Taylor (2004) plays an important role with a betweenness centrality value of 161.17, followed by Antweiler et al. (2001) with a centrality value of 82.91 and Levinson and Taylor (2008) with a centrality value of 31.74. Cluster-1 identified articles that use pollution haven hypotheses and environmental Kuznets curve to explain the relationship between trade and environment. For example, Copeland and Taylor (2004) theoretically and empirically examined the relationship between international trade, economic growth, and the environment. Antweiler et al. (2001) investigated how the openness of international trade in the goods market affects pollution concentration. Levinson and Taylor (2008) theoretically and empirically examined the effect of environmental regulations on trade flows by applying the pollution haven hypothesis. Cluster-2 (Blue) comprises 17 documents, ranging from 1960 to 2005. Based on centrality, the top three most important articles are Babiker (2005) (centrality value of 54.78), Barrett (1994) (centrality value of 39.29), and Markusen (1975) (centrality value of 38.55). Cluster-2 mainly focuses on the relationship between environmental policies (climate change policy, carbon tax, international environmental agreements) and international trade. Cluster-3 (Green) comprises 6 documents where the most prominent articles were Copeland (1994) (centrality value of 385.78) and Baumol (1988) (centrality value of 102.11). This cluster focused on the linkage between environmental regulation and international competitiveness (Jaffe, 1995) and the use of international trade theory in environmental concepts (Pethig, 1976). The article Copeland (1994) that takes a pivotal role in this cluster describes how different types of policy reforms in tax regimes and quota regimes make a trade and pollution distortion in a small open economy. Cluster-4 (Violet) comprises of 3 contributions which includes Davis (2010) (centrality value of 4.42), Peters (2008) (centrality value of 2.37) and Peters 2011 (centrality value of 2.31). This cluster mainly focuses on how international trade (export and import) plays a significant role in explaining carbon emission.
3.10 Bibliographic Coupling Analysis
To understand the current development of themes in the research field, the present study performed the bibliographic coupling analysis of documents. Bibliographic coupling is a scientific technique that will indicate when two publications share common references, and hence almost the same content (Kessler, 1963; Weinberg, 1974). This helps the researchers to know the current developmental structures in the research field. In the present study, for a better understanding and analysis, only the document that has at least 20 citations in Scopus and a total link strength of 3 or more are considered. Thus, by following these criteria, 447 articles got selected from the total sample of 1390 articles. Again, among the 447 articles, only 378 articles had a total link strength of 3 or more. By performing bibliographic coupling of these 378 articles in VOSViewer, the study got 6579 links with 11748 total link strength. Here, the links show the number of common references cited in the two documents, and the total link strength is the total number of commonly cited references among one document with all other linked documents.
Through this bibliographic coupling analysis, the study identified 6 clusters and each color represents a cluster (Fig. 9). In Fig. 9, documents having high similarity are placed closer to each other, and which have low similarity are placed far from each other. The size of the bubble is in proportion to the number of total citations. Table 9 summarizes the results of the bibliographic coupling analysis obtained from the VOSViewer software.
Cluster1: Emission Trading and Abatement Cost
Cluster 1 is the largest among all the six-cluster consisting of 132 articles with 7091 citations and 53.72 average citations per article. A total of 331 authors contributed to this cluster with 31 single-authored articles. This cluster mainly focuses on emission trading and abatement cost (Carlson et al., 2000; Carbone et al., 2009; Goulder et al., 2010; Aichele and Felbermayr, 2012; Kriegler, et al., 2015). Energy Economics and Ecological Economics are the important journals in this cluster, each of which published 27 and 21 articles respectively.
The most highly cited article in this cluster is Carlson et al. (2000) which examined the performance of the sulfur dioxide allowance market. That is, the process and the amount of allowance trading that helps to reduce the abatement cost of controlling SO2. The next highly cited work is Tacconi (2012), which redefined and identified the key elements of payment for environmental services from both environmental economics and ecological economics perspective. Another highly cited article in this cluster is by Sims (2010) that provided empirical evidence on the socioeconomic impacts of protected areas in Thailand.
Cluster2: Environmental performance and green supply chain management
Cluster 2 comprises 68 articles with 6838 total citations and 100.53 average citations per article (which is the highest amongst all other clusters). A total of 165 authors contributed to this cluster with 9 single-authored articles. The cluster mostly focused on environmental performance (Christmann and Taylor, 2001; Delmas and Blass, 2010; Carrión-Flores and Innes, 2010) and green supply chain management (Carter et al., 2000; Zhu and Sarkis, 2006; Wu and Pagell, 2011). The leading journals in this cluster were Journal of Cleaner Production, and Business Strategy and the Environment, each of which published 10 articles related to the theme of the cluster.
The most cited article is Christmann and Taylor (2001) that examined the effect of globalization on the self-regulating environmental performance of Chinese firms. This is followed by Zhu and Sarkis (2006) that examined the drivers and practices of green supply chain management in three manufacturing sectors of China and compared the results among them. The third most cited article in this cluster is Wu and Pagell (2011) where the focus was on how companies handle their environmental issues under the green supply chain management decision process.
Cluster3: Environmental Kuznets Curve and Composition Effect
Cluster 3 consists of 52 documents with 4339 total citations and 83.44 average citations per article. A total of 122 authors contributed to this cluster with 11 single-authored articles. The most important journals in this cluster are the Journal of Cleaner Production and Ecological Economics, each of which provided 12 and 8 articles, respectively. The environmental Kuznets curve (Cole, 2003; Esty and Porter, 2005; Culas, 2007; Managi et al., 2009; He and Wang., 2012) and composition effect (Cole and Elliott, 2003; Managi et al., 2009; Shahbaz et al., 2019) are the central themes in this cluster.
Cole and Elliott (2003) is the most cited article in this cluster, where the authors analyzed the determinants of composition effect of trade liberalization on the environment by focusing on differences in capital-labor endowments and differences in environmental regulations. This is followed by the study Managi et al. (2009) that examined the impact of trade openness and income on environmental emission, and Sadorsky (2012) that empirically examined the dynamic relationship between energy consumption, trade (export and import), and output in seven South American countries.
Cluster4: Carbon Footprints and Multi-regional input-output model
Cluster 4 consists of 50 contributions from 167 authors with 4 single authors articles. The cluster received 3957 total citations and 79.14 average citations per article. The leitmotif of this cluster is concerned with carbon footprints (Druckman and Jackson, 2009; Weber and Matthews, 2008; Jakhar, 2015) and the use of a multi-regional input-output model (Druckman and Jackson, 2009; Wiedmann et al., 2011; Qi et al., 2014). Again, the Journal of Cleaner Production is the most important journal in this cluster which published 18 articles followed by Ecological Economics which published 13 articles.
The most-cited article in this cluster is Druckman and Jackson (2009), which examined the various attributes of CO2 emission (carbon footprints) from the different segments of society of UK households and the study is based on a quasi-multi-regional input-output model. In their analysis, they consider both the consumption perspective and production perspective of CO2 emissions. The next important studies in this cluster are Weber and Matthews (2008) that analyzed the importance of globalization (international trade) and distributional aspects in estimating US household carbon footprints, and Wiedmann et al. (2011) that summarized the current state of development, methodological implication, and the future option of multi-regional input-output analysis (MRIO).
Cluster5: Pollution Havens
Cluster 5 contains 44 articles, which have been cited 2974 times with 67.59 average citations per article. A total of 96 authors contributed to this cluster with 7 single-authored documents. The main journals included in this cluster are the Journal of Environmental Economics and Management (14) and Ecological Economics (6). Authors in this cluster mostly focused on the pollution haven hypothesis and effect (Levinson and Taylor, 2008; Zeng and Zhao, 2009; Mulatu et al., 2010; Manderson and Kneller, 2012; Rezza, 2013; Chung, 2014).
The most highly cited article in the cluster is Levinson and Taylor (2008), in which the authors have tested the pollution haven effect by empirically examining the effect of pollution abatement cost on trade flows (net import). This is followed by Ederington et al. (2005), which proposed three reasons for the failure of previous empirical testing of pollution haven effect and empirically tested the results. The third important study is Zeng and Zhao (2009) that tested the pollution haven hypothesis by considering industrial agglomeration and manufacturing pollution on agricultural productivity.
Cluster6: Trade Liberalization and Environmental Policy
Cluster6 comprises only 32 articles (least among all the clusters) and obtained 1928 citations with 60.25 average citations per article. Interestingly, in this cluster, there are 14 single-authored articles. and On the whole, 45 authors contributed to this cluster. Journal of Environmental Economics and Management (11) and, Environmental and Resource Economics (6) are the major sources of publication in this cluster. Articles in this cluster focused on the concept of trade liberalization and environmental policy (Tanguay, 2001; Damania et al., 2003; Burguet and Sempere, 2003; Cole, 2006).
The most highly cited article in this cluster is Xing and Kolstad (2002), which empirically examined the impact of environmental policy on the foreign direct investment of both high polluting industries and low polluting industries. The study found that there is a significant impact of host countries' laxity of environmental regulation on FDI for high polluting industries and insignificant for low polluting industries. This is followed by Damania et al. (2003), which focused on the intersection between trade liberalization, environmental policy determination, and corruption, and Cole (2006) that explored the relationship between trade liberalization and energy use.
Table 9
Overview of Bibliographic Coupling
Cluster No.
|
Cluster Color
|
Number of Paper
|
TLS*
|
Top Sources
|
TC*
|
Main Topic
|
1
|
Red
|
132
|
3813
|
Energy Economics (27) Ecological Economics (21)
|
7091
|
Emission Trading and Abatement Cost
|
2
|
Green
|
68
|
3873
|
Journal of Cleaner Production (10)
Business Strategy and the Environment (10)
|
6836
|
Environmental performance and green supply chain management
|
3
|
Blue
|
52
|
5320
|
Journal of Cleaner Production (12)
Ecological Economics (8)
|
4339
|
Environmental Kuznets Curve
|
4
|
Yellow
|
50
|
1885
|
Journal of Cleaner Production (18)
Ecological Economics (13)
|
3957
|
Carbon Footprints and Multi-regional input-output model
|
5
|
Purple
|
44
|
5928
|
Journal of Environmental Economics and Management (14)
Ecological Economics (6)
|
2974
|
Pollution Havens
|
6
|
Aqua
|
32
|
2716
|
Journal of Environmental Economics and Management (11)
Environmental and Resource Economics (6)
|
1928
|
Trade Liberalization and Environmental Policy
|
*TLS=Total Link Strength
*TC=Total Citations