Analyzing The Scientific Evolution of Sustainable Technology Research in Business and Management Science

Morteza Akbari, Rahime Zaman Fashami, and Maryam Khodayari


Sustainable development poses many challenges to the world (Mulder, Ferrer, & Lente, 2011; Okura, 2010). Pollution, famine, depletion of mineral and organic resources, and the destruction of nature are only some of these challenges (Akbari & Asadi, 2008; Asadi, Akbari, Sharifzadeh, & Hashemi, 2009; Mirakzadeh, Akbari, Ghiasvand Ghiasy, Hashemi, & Rezvanfar, 2012). Humans must take fundamental steps to address these obstacles and take them seriously (Eustachio, Caldana, Liboni, & Martinelli, 2019). In this regard, the number of documents in this field has been growing in recent decades (Khan, 2020; Uusitalo et al., 2019; Wang & Zhan, 2019; Zhang et ah, 2019). Publications in the fields of “environmental technology”, “clean technology”, “green technology”, and “renewable energy technology” have also increased as sustainable technologies, which counteract pollution and reduce energy and mining consumption (Bjornali & Ellingsen, 2014; Chen, Huang, Zhong, & Ruizhi, 2015; Dickel, 2018; Johansen, 2019; Roshdi, Hasannasab, Margaritis, & Rouse, 2018; Sjdd & Frishammar, 2019; Sung, Choi, & Song, 2019; Yang, Nie, & Huang, 2019). Because the goal of sustainable technology is to minimize waste, it has to reduce material and energy inputs, which is in line with the most important biological goals (Srebrenkoska, Fidancevska, Jovanov, & Angusheva, 2013).

Different dimensions of sustainable technology have been studied (Cui, 2018; Garcia- Berna et ah, 2019; Pang & Zhang, 2019; Tang, Liao, Wan, Herrera-Viedma, & Rosen, 2018), and one study was conducted on sustainable technology based on a bibliometric analysis, which examines co-citation and keyword developments (Akbari, Khodayari, Danesh, Davari, & Padash, 2020). This differs from the present study, which examines co-citation and co-coupling. Using a bibliometric analysis, this paper studies documents available in the Web of Science (WoS) Core Collection (CC) record. The study comprises a bibliometric analysis built on 688 articles on sustainable technology, published from 1985 to 2019.

This study identifies items such as top-cited papers, most relevant keywords, most productive authors, top authors production over the time, and most productive countries, and through reviewing and drawing co-citation and co-coupling maps while identifying the research gap, suggests future research areas.


The present study, which is one type of descriptive-analytical research, was done through bibliometric techniques. To recover the records of this research, the search in the core collection section of the Web of Science database, (hereafter referred to as WoS for short) was extracted on March 18, 2020, from 1985 to 2019. The search formula is as follows: “SUSTAINABLE* TECHNOLOGY*” OR “CLEAN* TECHNOLOGY*” OR “GREEN* TECHNOLOGY*” OR “ENVIRONMENTAL* TECHNOLOGY*” OR “RENEWABLE* ENERGY* TECHNOLOGY*”. The publishing field is a “Topic”.

Searching for these keywords in the topic section, we found 6,401 records. The number was reduced to 3,945 records by applying the filter of “Articles”; with the application of the “English language” filter, the number of articles reached 3,801 articles. Since in the present study we have been looking for articles with a business and management approach, the 14 categories expressed below were selected. Business (122 cases), business finance (8), economics (308), management (137), development studies (23), multidisciplinary sciences (97), social sciences interdisciplinary (9), international relations (18), information science library science (8), operations research management science (61), education educational research (14), political science (16), public administration (15), and sociology (7). Finally, the number of articles settled at 688.

The bibliography is a mathematical and statistical system used to describe the existing state of science and technology (Jiang-hua, 2006). A bibliographic analysis is an significant instrument for summarizing the results of historical studies and determining the course of future research (He, Zhang, Gong, & Zhou, 2019).

The core determination of this study is to report the trend of publications and citations from the beginning until present in the field of sustainable technology and draw scientific maps. In this regard, we are trying to find: (1) top-cited papers; (2) most relevant keywords; (3) most productive authors; (4) top authors production over the time; (5) top most productive countries, as well as drawing (1) a co-citation analysis and (2) a co-coupling analysis. VOSviewer was used to simplify convinced relatives by creating grids and charts built on information distributed from the WoS database. VOSviewer is a software database developed by Van Ak and Waltman. This software is widely used and its purpose is to create, imagine and discover logical diagrams of bibliography (Castillo-Vergara, Alvarez-Marin, & Placencio-Hidalgo, 2018; Wang & Yang, 2019). Descriptive maps and tables are drawn using Bibliometrix® package. The Bib- liometrix® software is an R-tool that was well known by Aria and Cuccurullo (Aria & Cuccurullo, 2017) (Figure 8.1).


Methodological approach (author’s presentation).


Bibliographic explanatory analysis

The explanatory analysis of bibliography uses many functions. As Tables 8.1-8.5 show, functions such as key statistics regarding the data, prominent cited papers, most related keywords, top effective authors, and most productive regions. This information helps us comprehend the field of sustainable technology better.

In Figure 8.2, using the R studio language, the effective authors as regards of the quantity of documents has been introduced. The next figure (Figure 8.3) shows the authors’ productions over time according to the number of articles and times cited.

As we see in Figure 8.4 - most productive countries - the USA has the highest productivity in the field of sustainable technology, followed by China, the United Kingdom, and Germany.

TABLE 8.1 Key statistics regarding the data




Sources (Journals, Books, etc.)


Keywords plus (ID)


Author’s keywords (DE)




Average citations per documents




Author appearances


Authors of single-authored documents


Authors of multi-authored documents


Single-authored documents


Documents per author


Authors per document


Co-authors per documents


Collaboration Index


TABLE 8.2 Prominent cited papers



TC per year































TABLE 8.3 Most related keywords

Author keywords (DE)


Kcywords-plus (ID)


Green Technology




Renewable Energy




Clean Technology








Sustainable Development








Environmental Technology




Climate Change






Research and development


Environmental Policy




TABLE 8.4 Most effective authors



Song ML


Wang SH


Hekkert MP


Urpelainen J


Watanabe C


Fare R


Grosskopf S


Jacobsson S


Managi S


Negro SO


TABLE 8.5 Most productive regions



















United Kingdom
















































Top effective authors

FIGURE 8.2 Top effective authors.

Authors effectiveness over time

FIGURE 8.3 Authors effectiveness over time.

Most productive countries

FIGURE 8.4 Most productive countries.

Document co-citation analysis

A document co-citation analysis, with cited references, was performed in order to develop the theoretical basics of the 688 papers in the illustration. The primary example of 26,121 cited references was concentrated in documents with at least 10 citations, resulting in 71 documents (Table 8.6).

Figure 8.5 demonstrations the bibliometric grid built on paper co-citation analysis, which contains five collections.

Cluster A: Gain lasting competitive advantage from environmental opportunities

Cluster A includes 23 articles, labeled as ‘gain lasting competitive advantage from environmental opportunities’. By examining the views of strategic management experts, we find that organizations have no choice to gain and sustain lasting competitive advantage to stay protected from drastic environmental changes and to adapt to competitive requirements (Barney, 1991; Mata, Fuerst, & Barney, 1995; Porter & Linde, 1995).

There are two approaches to explain sustainable competitive advantage in organizations. The first is based on the theory of industrial organization, as in Michael Porter’s ideas (Porter & Linde, 1995). He attributes competitive advantage to environmental opportunities. According to Porter’s hypothesis, stricter environmental regulations lead to improved business competitiveness by enhancing efficiency and encouraging innovation. This hypothesis implies that stricter ecological rules lead to the detection and overview of cleaner technologies and ecological enhancements, and result in innovation and the efficiency of processes and products (Porter & Linde, 1995).

TABLE 8.6 Co-citation grid of cited references


Cited reference




(Porter & Linde, 1995)


Gaining sustainable competitive advantage from environmental opportunities through two approaches:

  • 1. Industrial organization
  • 2. Firm resources

(Brien, Jones, & Porter, 1995)


(Hart, 1995)


(Barney, 1991)


(Cohen & Levinthal, 1990)


(Tushman & Anderson, 1986)


(Rogers, 1995)


(Russo & Fonts, 1997)


(Stern. 2007)


(Ajzen, 1991)


(Christmann, 2000)


(Cohen Sc Winn, 2007)


(Fornell & Larcker, 1981)


(Klassen Sc McLaughlin, 1996)


(Schumpeter, 1942)


(Shrivastava, 1995)


(DiMaggio & Powell, 1983)


(Eisenhardt, 1989)


(Hockerts & Wiistenhagen, 2010)


(Miles, Huberman, Huberman, & Huberman, 1994)


(Nemet, 2009)


(Rennings, 2000)


(Teece, 1986)



(Jacobsson Sc Johnson, 2000)



Innovation System (TIS)

(Jacobsson Sc Bergek, 2004)


(Kemp, Schot, Sc Hoogma, 1998)


(Carlsson, Jacobsson, Holmen, Sc Rickne, 2002)


(Jacobsson Sc Lauber, 2006)


(Geels, 2002)


(Unruh, 2000)


(Bergek, Jacobsson, Carlsson, Lindmark, Sc Rickne, 2008)


(Hekkert, Suurs, Negro, Kuhlmann, Sc Smits, 2007)


(Dosi, 1982)


(Winter & Nelson, 1982)


(Lundvall, 1992)


(Foxon et ah, 2005)


(Freeman, 1987)


(Carlsson et ah, 2002)


(Davis, 1985)


(Edquist, 1997)


(Hughes, 1983)



(Milliman & Prince, 1989)


Environmental policies and incentives for technology innovation and change

(JafFe, Newell, Sc Stavins, 2005)




Cited reference




(Jaffe, Newell, tk Stavins, 2002)


(Dixit, Dixit, & Pindyck, 1994)


(Jung, Krutilla, Sc Boyd, 1996)


(Krass, Nedorezov, & Ovchinnikov, 2013)


(Downing Sc White, 1986)


(Requate Sc Unold, 2003)


(Requate, 2005a)


(Arora Sc Gangopadhyay, 1995)


(Fischer, Parry, Sc Pizer, 2003)


(Montero, 2002)


(Benjaafar, Li, Sc Daskin, 2013)


(Requate, 2005b)


(Weitzman, 1974)



(Acemoglu, Aghion, Bursztyn, Sc Heinous, 2012)


Patent data is an indicator of technological developments

(Johnstone, Hascic, Sc Popp, 2010)


(Lanjouw Sc Mody, 1996)


(Popp, 2002)


(Popp, Newell, Sc Jaffe, 2010)


(Lewis Sc Wiser, 2007)


(Arrow, 1962)


(Carolyn Fischer Sc Newell, 2008)


(Griliches, 1990)


(Newell, Jaffe, Sc Stavins, 1999)


(Dechezlepre Sc Me, 2008)


(Popp, Hascic, Sc Medhi, 2011)



(Chung, Fare, Sc Grosskopf, 1997)


Separate undesirable outputs from desired outputs

(Fare, Grosskopf, Lovell, Sc Pasurka, 1989)


(Shephard, 1970)


Co-citation grid of cited references

FIGURE 8.5 Co-citation grid of cited references.

Another approach was built on the interior capabilities of the organization. Barney found that competitive advantage based on an organization’s internal capabilities is the best source of competitive advantage (Barney, 1991). Research has shown that the benefits based on the intrinsic capabilities of organizations, more than the ecological opportunities, can determine the competitive situations of firms and are a more reliable base for the source of competitive advantage. As organizations’ resources are different and heterogeneous, they have different strategies for gaining a competitive advantage. As is clear in the articles in this cluster, organizations’ resources lead to increased corporate performance (Klassen & McLaughlin, 1996) and profitability (Russo & Fouts, 1997). Hart (1995) states that corporate strategy and competitive advantage inevitably depend on capabilities, such as an organization’s absorptive capacity (Cohen & Levinthal, 1990), which facilitate environmentally sustainable economic activity. Environmental destruction provides opportunities for companies to improve environmental and social performance by implementing technological innovations (Teece, 1986) to improve waste management practices and to reduce materials and energy used for production (Cohen & Winn, 2007; Stern, 2007). Innovations are transmitted to the members of the public structure through communication channels over a specific time, known as the theory of diffusion of innovation (Rogers, 1995).

Cluster B: Technological Innovation System (TIS)

Cluster В includes 18 articles, labeled as ‘Technological Innovation System’ (TIS). The TIS is introduced as part of the innovation system approach (Edquist, 1997). Innovation systems are a very important basis of technology development. The development of an innovation system and changes in current innovation systems evolve as the technology does (Hekkert et al., 2007). The rudimentary idea of the TIS is that the factors influencing technological developments are not found solely in separate companies or research institutions, but in a broad social structure in which companies, in addition to knowledge institutes, are located (Lundvall & Dosi, 1988). The TIS possibly will be useful at least at three levels of analysis: Technology means a field of knowledge a product, or a related set of products and artifacts to satisfy a particular (social) function. This system explains why and how sustainable (energy) technologies are developed and disseminated in society (Jacobsson & Johnson, 2000). Challenges have been identified for policymakers who want to affect the evolution of the renewable energy sector as sustainable technologies. First, since the energy system is so vast, policy-making in this area must be long term. Second, policymakers are focusing on creating incentives to invest in these areas and providing direct and indirect subsidies to companies to exploit renewable energy and new technologies to reduce environmental damage (Jacobsson & Bergek, 2004) as well as creating incentives to innovate in these technologies (Foxon et al., 2005). And third, given that policymaking is purely a political business, therefore, penetrating lobbying for political goals and the design of the institutional frameworks should be taken into account, as advocates of the energy system frequently seek to disseminate renewable resources by influencing the institutional framework to keep businesses in their favor (Jacobsson & Bergek, 2004). The actors of this system, including the legislature, government, corporations, information, networks, and communications that exist between these components, lead to a series of innovative events that ultimately cause the development of technology. Proposed functions for the TIS include entrepreneurial activities, knowledge production and dissemination, system orientation, market-shaping, resource mobilization, and legitimization (Bergek, Jacobsson, Carlsson, et al., 2008; Hekkert, Suurs, Negro, Kuhlmann, & Smits, 2007).

Cluster C: Environmental policies and incentives for technology innovation and change

Within this cluster, 15 articles are all about ‘environmental policies and incentives for technology innovation and change’. These incentives and environmental policy include direct control, subsidies, taxes (Jung et al., 1996; Krass et al., 2013; Requate & Unold, 2003), free marketable licenses and auctioned licenses (Fischer et al., 2003; Milliman & Prince, 1989; Requate, 2005a, 2005b), emission standards, and performance standards (Montero, 2002). These incentives encourage companies to innovate in technologies that reduce pollution (Downing & White, 1986). Jatfe et al. (2005) stated that there are binary approaches to developing new technology. One approach is to develop new technology by designing eco-friendly rules to raise apparent marketplace efficiency and maximize flexibility in compliance. Another is to implement strategies that directly encourage the expansion and distribution of ecologically sociable technologies. Environmental impacts are meaningfully influenced by technological developments, and partially, environmental policies create new constraints and incentives that affect technologicaladvances (Jaffe et al., 2002). Arora and Gangopadhyay (1995) explains that higher revenue points in advanced countries have amplified requests for ecological quality and have forced corporations to address ecological worries more extremely.

Cluster D: Patent data is an indicator of technological developments

Acemoglu et al. (2012) state that factories have two outputs according to the technologies they use: clean output and dirty output. Therefore, innovations should be made in the technologies used by factories that reduce pollution. In addition to the issues raised in the previous cluster (government policies and incentives), one of the other things that will lead to an rise in invention in sustainable technologies is an increase in energy prices (Popp et al., 2011). In this way, increasing the price of energy leads to innovation in technologies that result in energy savings. Therefore, investing in these innovations is very important (Newell et al., 1999). Patent data is a unique resource for reviewing technical changes (Griliches, 1990). It can be used to determine the level of innovation in sustainable technologies (Lanjouw & Mody, 1996) and to assess the effect of energy values on efficient energy inventions (Popp, 2002).

Cluster E: Separate undesirable outputs from desired outputs

Within this cluster, three articles are all about ‘separate undesirable outputs from desired outputs’. The final output of any industry includes desirable and undesirable outputs, for example smog. To remove such an unwanted output, Chung et al. (1997) presented a Malmquist- Luenberger index that solves the problem of co-production of wanted and unwanted productions. Fare et al. (1989) also presented a hyperbolic efficiency measure and Shephard (1970) later developed the performance of the output distance, in which the input levels are constant and the proportional increase is determined by the output.

Document co-coupling analysis

This part explains the present trends in the sustainable technology scope through investigating bibliographic co-coupling among the documents between 1997 and 2019. Figure 8.6 demonstrates a bibliographic network with eight clusters of 688 documents, out of which 84 were selected through the main overall link strength. The minimum number of citations of a document was 50. Finally, the major set of linked objects consists of 69 documents. Cluster 5, which can be seen at the corner of the map, is associated with clusters 3 and 8 and separated from the other clusters. Clusters 1 to 4 and 6 to 8 are closely structured, which indicates strong ties between their fields. We labeled the clusters as follows: cluster 1 - environmental policies; cluster 2 - renewable energy technologies (RET) development; cluster 3 - responses to environmental technologies; cluster 4 - TIS functions; cluster 5 - environmental performance analysis; cluster 6 - incumbents and entrepreneurial firms; cluster 7 - technological change; and cluster 8 - social dynamics and technology development. Table 8.7 shows the trends presented in clusters 1 to 8.

The bibliographic network of sustainable technology

FIGURE 8.6 The bibliographic network of sustainable technology.

TABLE 8.7 Summary of the eight recognized bibliographic co-coupling clusters






Regulation, policies, governmental activities and their impact on technology choice, investment and adoption


Inventory theory, game theory, Hechscher-Ohlin


Factors that drive the diffusion and development of RET


Choice experiment


Corporate behaviors in response to environmental needs


RBV theory, Kuznet curve


Key activities of TIS




Evaluation and measurement of environmental changes




Differences between entrepreneurial firm and incumbents



Dynamics between innovation system components that lead to technological changes



Role of networks and community on technology development


Cluster 1: Environmental Policies

Cluster 1 consists of 15 articles labeled as ‘environmental policies’. This cluster concentrates on the impacts of governmental principles and policies on environmental technology choice and adoption. Moreover, the articles in this cluster focus on governmental incentives that motivate firms to choose or diffuse clean technologies or not. As researchers mentioned, theory demonstrates and empirical research confirm that technological innovation and dissemination are the responses to the market incentives, which planned regulations can create. In the absence of environmental policies or poor policies, investment in development and diffusion of new environmental technologies is probably less than social desirability (Jaflfe et al., 2005).

In this cluster, several authors tried to develop a model that examines the effects of environmental regulations on a firm’s technology choice. Policies like: taxes, tax refunding, cap-&-trade, research subsidies, pricing, and cap are listed (Acemoglu, Akcigit, Hanley, & Kerr, 2016; Amacher, Koskela, & Ollikainen, 2004; Chung, 2014; Cohen, Lobel, & Perakis, 2016; Drake, Kleindorfer, & Van Wassenhove, 2016; Gersbach & Requate, 2004; Gong & Zhou, 2013; Jaffe et al., 2005; Krass et al., 2013; Luo, Chen, & Wang, 2016; Nesta, Vona, & Nicolli, 2014; Popp, 2011; Taylor, Rubin, & Hounshell, 2005; Toptal, Ozlii, & Konur, 2014; Xu, He, Xu, & Zhang, 2017). In addition to the above, some authors mention other elements that affect technology choice such competition and co-opetition (Luo et al., 2016), the cost structure of firms and quality competition (Amacher et al., 2004), and consumer rebates (Krass et al., 2013). Some researchers found that firms’ responses to a tax increase may not be the same; while an initial tax increase may provoke greener technology, a higher tax increase may have reverse results (Krass et al., 2013). Others recommend that besides taxes other policies would be complementary (Krass et al., 2013; Nesta et al., 2014).

Cluster 2: Renewable Energy Technologies (RET) development

Concerned about climate change, Renewable Energy Technologies (RET) development is important for lower emissions and costs, so this cluster - called ‘renewable energy technologies development’ - includes 15 articles and focuses on the issues that cause the diffusion and development of RETs successfully. All scholars, directly or indirectly, have pointed out that one of the most important elements contributing to the progress of RET is political mechanisms. This indicates that cluster 1 is related to cluster 2. As Figure 8.2 shows, the two clusters in some areas are intertwined, which reflects their close relationship. Several authors have cited policies such as feed-in tariffs (Cherni & Kentish, 2007; Kumbaroglu, Madlener, & Demirel, 2008; Lewis, 2014; Lewis & Wiser, 2007; Madlener & Stagl, 2005; Pfeiffer & Mulder, 2013), mandatory market share policy equal to the renewable portfolio standard (Cherni & Kentish, 2007; Lewis & Wiser, 2007), tradable ‘green’ certificates (Bergmann, Colombo, & Hanley, 2008; Cherni & Kentish, 2007; Madlener & Stagl, 2005), auction or bidding (Cherni & Kentish, 2007; Lewis & Wiser, 2007; Madlener & Stagl, 2005), and research development, demonstration, and deployment (RD3) (Lewis, 2014; Lewis & Wiser, 2007; Siddiqui & Fleten, 2010). In addition, some researchers have investigated the role of learning on the development of RETs (Kobos, Erickson, & Drennen, 2006; Kumbaroglu et al., 2008; Lewis & Wiser, 2007; Madlener & Stagl, 2005; Neij, 1997; Pfeiffer & Mulder, 2013; Siddiqui & Fleten, 2010; Watanabe, Wakabayashi, & Miyazawa,

TABLE 8.8 Types of energy

Type of energy



(Bergmann et al., 2008; Cherni & Kentish, 2007; Kobos et al., 2006;

Kumbaroglu et al., 2008; Lewis, 2014; Lewis & Wiser, 2007; Madlener & Stagl, 2005; Maxim, 2014; Pfeiffer & Mulder, 2013)


(Bergmann et al., 2008; Cherni & Kentish, 2007; Kobos et al., 2006;

Kumbaroglu et al., 2008; Lewis & Wiser, 2007; Lewis, 2014; Madlener & Stagl, 2005; Maxim, 2014; Neij, 1997)

Solar power

(Bergmann et al., 2008; Kobos et al., 2006; Kumbaroglu et al., 2008; Lewis, 2014; Maxim, 2014; Pfeiffer & Mulder, 2013; Watanabe et al., 2000)


(Bergmann et al., 2008; Cherni & Kentish, 2007; Kobos et al., 2006; Madlener & Stagl, 2005; Maxim, 2014; Pfeiffer К Mulder, 2013; Siddiqui et al., 2007)


(Bergmann et al., 2008; Cherni & Kentish, 2007; Kumbaroglu et al., 2008; Maxim, 2014; Pfeiffer & Mulder, 2013; Siddiqui et al., 2007)


(Bergmann et al., 2008; Maxim, 2014; Pfeiffer & Mulder, 2013)

Tidal and wave

(Bergmann et al., 2008)

Wastes combustion

(Bergmann et al., 2008; Siddiqui et al., 2007)

2000). The findings suggest that policies intended at promoting RET - over a long-term period via learning — can drive wider development. Moreover, many authors have mentioned that some market conditions affect RET development, like: (1) capacity of the network (Cherni & Kentish, 2007; Hayes & Horne, 2011; Kobos et al., 2006; Lewis, 2014; Lewis & Wiser, 2007; Madlener & Stagl, 2005; Maxim, 2014; Neij, 1997; Pfeiffer & Mulder, 2013), (2) demand and supply trends (Cherni & Kentish, 2007; Kobos et al., 2006; Kumbaroglu et al., 2008; Lewis & Wiser, 2007; Madlener & Stagl, 2005; Pfeiffer & Mulder, 2013; Sid- diqui, Marnay, & Wiser, 2007), and (3) cost of RET (Bergmann et al., 2008; Cherni & Kentish, 2007; Kobos et al., 2006; Siddiqui et al., 2007). It should be mentioned that policies about local or international investment in RETs are also considered (Lewis, 2014; Lewis & Wiser, 2007) (Table 8.8). The most repeated types of RET in the literature are:

Cluster 3: Responses to environmental technologies

Cluster 3, which contains 10 articles, focuses on how firms behave and respond to environmental needs and the reasons for that behavior. The cluster is called ‘responses to environmental technologies’. According to the map, this cluster is associated with clusters 1, 2, 4, 5, 6, and 8, which represents the closeness of their fields. This cluster considers the different firm’s responses, taking into account the level of development of the countries. Some authors represent the behavioral differences between developed countries and developing ones in technology adoption (Arora & Gangopadhyay, 1995; Blackman & Bannister, 1998; Dasgupta, Laplante, Wang, & Wheeler, 2002; Harstad, 2012; Nameroff, Garant, & Albert, 2004). Scientific data states that economic development and income level can affect the choice of technologies (Arora & Gangopadhyay, 1995; Dasgupta et al., 2002). They also explain that in developed countries pollution regulations are more serious because (1) pollution damage attracts more attention, (2) there is a higher budget for enforcement activities, and (3) there are more environmental standards (Dasgupta et al., 2002). Besides this, researchers express that developed countries have fewer environmental misuse cases (Arora & Gangopadhyay,

TABLE 8.9 Type of technologies

Type of technology


Pollution prevention

(Klassen & Whybark, 1999; Norberg-Bohm, 1999)

Comprising product and process adoption

(Klassen & Whybark, 1999)

Management systems

Pollution control technologies

Comprising remediation

End-of-pipe technologies

Industrial ecology

(Norberg-Bohm, 1999)

Resource productivity


1995; Harstad, 2012). Also, several authors have pointed out the voluntary behavior of firms (Arora & Gangopadhyay, 1995; Sarkar, 2008) because of the reputation or anticipation of stricter regulation (Arora & Gangopadhyay, 1995), and gaining competitive advantages (Klassen & Whybark, 1999; Nameroff et al., 2004; Sarkar, 2008) while some others express managerial issues (Klassen & Whybark, 1999; Nameroff et al., 2004; Sarkar, 2008). Moreover, several authors mention the effects of market conditions such as competition (Arora & Gangopadhyay, 1995; Blackman & Bannister, 1998; Klassen & Whybark, 1999), oil price increase, and the crises faced by most power utilities (Karekezi, 2002), and industrial dynamics (Nameroff et al., 2004) (Table 8.9).

Cluster 4: Technological Innovation System (TIS) functions

Cluster 4, which contains 10 articles, is called “technological innovation system functions” and describes key activities and components of TIS that influence the achievement or failure of technology development. Cluster 4 has a very strong relationship with cluster 7. As Figure 8.3 shows, the two clusters are tightly intertwined and overlap. On the other hand, it is also associated with clusters 6 and 8, and in rare cases with clusters 1 and 3. We can say that environmental policies affect these functions and renewable energy development depends on them. Many authors have cited the TIS functions described in cluster В of the previous section (Bergek, Jacobsson, & Sanden, 2008; Hekkert & Negro, 2009; Negro, Hekkert, & Smits, 2007; Negro, Suurs, & Hekkert, 2008). Other researchers have pointed out the role of technological, political, and resource uncertainty on entrepreneurs’ decision making (Meijer, Hekkerta, & Koppenjan, 2007) and others still have highlighted the role of innovation history and innovation context in strategy determination (Raven, 2007).

Cluster 5: Environmental performance analysis

This cluster, it can be said, is separated from the rest of the clusters and is only associated with cluster 3 and in diminutive points with cluster 8. It is called ‘environmental performance analysis’ and consists of 6 articles. Using data envelopment analysis (DEA), the authors present models that examine the producing of agreeable and disagreeable outputs, taking into account traditional production rates and technological changes (Fare & Grosskopf, 2004; Fare, Grosskopf, & Pasurka, 2007; Kortelainen, 2008; Sahoo, Luptacik, & Mahlberg, 2011).

They cite the concept of ‘disposability’, which refers to negative or positive adoption of regulation change (Fare & Grosskopf, 2004; Sahoo et al., 2011; Sueyoshi & Goto, 2012a, 2012b). Others point out two approaches of DEA: radial and/or nor-radial (Sahoo et al., 2011; Sueyoshi & Goto, 2012b, 2012a), and also explain that different models have different estimations (Sahoo et al., 2011; Sueyoshi & Goto, 2012b).

Cluster 6: Incumbents and entrepreneurial firms

This cluster is called ‘incumbents and entrepreneurial firms’ and consists of 6 articles, which express the role of ‘incumbents’ with high market shares and ‘entrants’ with high environmental performance and differences between their activities in terms of environmental issues, as well as their opportunities and challenges. Most scholars hint that the cooperation of both types of firms as a network is necessary for technological improvement (Dangelico, Pontrandolfo, & Pujari, 2013; Hockerts & Wiistenhagen, 2010; Musiolik, Markard, & Hekkert, 2012). Firms cooperate in networks not only for knowledge producing and sharing, competencies integration, and participation (Dangelico et al., 2013) but also for creating strategic supportive systems (Musiolik et al., 2012). Business models of companies are different and each business must create new values according to its business model, so companies must pay attention to their value proposition in their business models. Findings show that large firms tend to be close to previous business models and entrepreneurial firms are more flexible (Bohnsack, Pinkse, & Kolk, 2014). Barriers that SMEs would confront have also been studied. Researchers explain that while SMEs have limited financial resources, they can benefit from other social capital, such as reputation or equity (Halme & Korpela, 2014).

Cluster 7: Technological change

Cluster 7, which called ‘technological change’, includes 5 articles describing innovation systems processes that lead to technological changes. The core concept is the innovation system, but the main focus is on the dynamics between the components of the system (functions), which are expressed in cluster 4 (Bergek, Jacobsson, Carlsson, et al., 2008; Hekkert et al., 2007). Scholars provide frameworks for mapping the process and analyze the relationship between the components’ special social structure (Bergek, Jacobsson, Carlsson, et al., 2008; Collinson & Gregson, 2003; Hekkert et al., 2007; Jacobsson & Johnson, 2000). Authors emphasize the role of networks and networking (Collinson & Gregson, 2003; Jacobsson & Johnson, 2000).

Cluster 8: Social dynamics and technology development

This cluster includes 4 articles, labeled as ‘social dynamics and technology development’. It explains that social issues can change sustainable technology outcomes. The concept of ‘community formation’ is a highlight of this cluster (Breukers & Wolsink, 2007; Walker, Devine-Wright, Hunter, High, & Evans, 2010). Researchers have identified the role of trust in technology development, considering the contexts and conditions in which technology is implemented (Walker et al., 2010). Some scholars explain the effects of local social acceptance on technology implementation. They state that local ownership and participation can improve the projects (Breukers & Wolsink, 2007). Also ‘participatory backcasting approach’ as a holistic level of social processes is introduced, in which we can forecast the amount of participation of stakeholders (Quist & Vergragt, 2006). One researcher expresses the notion of eco-innovation in this cluster (Kemp, 2010).

The relative importance of clusters

Table 8.10 shows the cluster approach and citation impact per cluster. The research trends presented in clusters 1 to 8 are associated with the clusters of co-citation. For example, cluster 1 builds upon theories of cluster C, but clusters 6 and 8 are related with no cluster.

As stated in Table 8.6, the content of the articles in the first cluster in co-coupling is the same as cluster C in co-citation and the articles in both clusters are related to environmental laws and regulations, government activities, the motivations for businesses to capitalize on

TABLE 8.10 Summary of the eight recognized bibliographic co-coupling clusters



Citation impact per cluster

Cluster approach


number of citations










Field understudy








Regulation, policies, governmental activities and their impact on technology choice, investment and adoption


Renewable Energy Technologies Development





Factors that drive the diffusion and development of RET


Responses to Environmental Technologies





Corporate behaviors in response to environmental needs


Technological Innovation System Functions





Key activities of the TIS









Evaluation and measurement of environmental changes


Incumbents and Entrepreneurial Firms





Differences between

entrepreneurial firm and incumbents








The dynamics between the components of the innovation system and environmental policies that lead to technological change


Social Dynamics and Technology Development





Role of networks and community on technology development

The evolution of sustainable technology 145

Number of articles per year per cluster

FIGURE 8.7 Number of articles per year per cluster.

these technologies, and the use of green technologies to decrease environmental pollution. The content of the articles in the second cluster in co-coupling are the same as cluster D in co-citation, as the articles in both clusters are about developing sustainable technologies. One of the significant issues that shows the expansion of these technologies is patent data. The next cluster, which corresponds to the first cluster in co-citation, is about companies’ behavior in dealing with environmental opportunities. It was stated that companies adopt either an external approach (Michael Porter’s industrial organization theory) or an internal approach (resource-based theory) regarding the exploitation of environmental opportunities. The fourth cluster corresponds to cluster В in co-citation because both proposed the TIS and its functions. The fifth cluster discusses measuring and analyzing the performance of companies in the environment. In the last cluster of the co-citation, criteria were also expressed for measuring undesirable outputs and separating desirable outcomes from undesirable ones. Finally, in the seventh cluster, the factors of change and innovation in sustainable technologies are discussed. In the co-citation, they are presented in two clusters - В and C. Two very important factors in the implementation of technological changes are the dynamics of components of innovation system and the government’s policies to motivate companies. Articles in the sixth and eighth clusters in this section did not correspond to the articles of the co-citation, so no cluster is mentioned in the table.

Table 8.10 also displays statistics according to citations to evaluate qualified importance of clusters identified. Cluster 7 is the most cited and followed by cluster 3. It pinpoints that these clusters (‘technological change’ and ‘responses to environmental technologies’) are relatively important.

According to Figure 8.7, the oldest cluster is cluster 3, compared to cluster 1, which is the most recent one. It can be seen that work on ‘environmental policies’ was started in 2004 up to 2017 as a more recent topic, while ‘responses to environmental technologies’ started in 1995, which means that corporates’ behavior was the first focus area of researchers. Cluster 2 is the oldest cluster (17 years old) and cluster 4 is the youngest one (5 years old). It indicates that scientists have worked on ‘renewable energy technologies development’ for 17 years, whereas cluster 4, which is integrated tightly with cluster 7 - the most cited cluster - has been worked especially with a downward slope, only for 5 years. After 2010, it seems clusters 8 and 7 lost scholars’ interest, besides studies on all clusters that stopped in 2014 except cluster 1 whose density is the highest. It can be noted that authors have recently been interested in ‘environmental policies’ but not with a steady slope. The least published cluster with articles is 8 and the most productive year was 2007 with 10 articles among all clusters.


According to our study, there are two groups in the production and application of sustainable technologies. The first is companies and factories that produce sustainable technologies. The second includes companies and factories that use sustainable technologies, as well as individuals, communities, and groups that benefit from the output of these factories. The first group is the supply sector and the second group is the demand sector.

By examining and studying the articles in the clusters presented in the co-citation and co-coupling, we conclude that in the use of sustainable technologies, the supply part has often been studied. For example, the creation of a technology system for innovation in sustainable technologies has been proposed. On the other hand, the role of the government in encouraging both manufacturing and consumer companies has also been studied.

While the demand side of these technologies should also be considered, consumer behavior, their consumption trends, and social dynamism should be studied both before and after the adoption of technology, because the rate of dissemination and development of sustainable technologies is contingent on the level of acceptance of these technologies by society and consumers. As mentioned earlier, companies need clean technologies to produce clean outputs, and the cost of these technologies is very high, so it will directly affect the price of their outputs and will lead to higher prices. Therefore, the amount purchased by the consumer will be affected. It is important to examine the behavior of the end consumer, which has not been enough considered in prior research. Instead, the level of acceptance of these technologies by indigenous and local people should also be studied. Consumption trends are another important factor that affects the development and creation of sustainable technologies and that has been overlooked in previous studies. The above is briefly shown in Figure 8.8.

Limitation and future research directions

The first limitation of this study is use of WoS as a database. It is recommended to use other data sources such as Scopus or Google Scholar, although WoS is one of the most valid databases. Also, it is suggested that future studies should be set and examined on the different quantity of citations. Besides this, WoS categories studied in this research include the field of social sciences, so future studies could be conducted in other categories. Moreover, we only reviewed documents in English, so other languages would be useful for future studies. Finally, it is strongly stated that future studies should be done the on-demand part, especially in consumer behavior and social dynamism.

Research gap in sustainable technology

FIGURE 8.8 Research gap in sustainable technology.


In light of global warming and the destructive effects of industrialization, sustainable technology is one of the largest priorities of countries. In this paper, using the bibliometric method, we consider studies that were done between 1995 and 2019 in the scope of sustainable technology with a management and economic approach. With the help of the Bibliometrix package of R, quantitative statistics on the bibliography were extracted and a descriptive analysis was presented. The main information about the data shows the general information about the scope, most cited papers, and their total citations. For example it was shown that Hekkert MP (2007), Bergek (2008), Hart (1997), etc. were the most productive authors and the highest contributing authors by the number of their articles were Song, Wang, and Hekkert, etc.; while the most productive countries were the USA, China, and United Kingdom and the most relevant keywords were innovation, policy, performance, etc. Also with the help of VOSviewer software, co-citation and co-coupling were mapped. Using the co-citation tool, we reviewed the theories that exist in this field, and we can say that two well-known theories in the field of sustainable technology are resource-based (RBV) theory and Porter’s industrial organization theory. With the help of co-coupling, we considered the trends in this area. We introduced 5 clusters in co-citation: A - Gain lasting competitive advantage from environmental opportunities; В - Technological Innovation System (TIS); C - Environmental policies and incentives for technology innovation and change; D - Patent data is an indicator of technological developments; and E - Separate undesirable outputs from desired outputs. We also introduced 8 clusters in co-coupling as follows: 1 - environmental policies; 2 - RET; 3 - responses to environmental policies; 4 - TIS functions; 5 — environmental performance analysis; 6 - incumbents and entrepreneurial firms; 7 — technological change; and 8 - social dynamics and technology development. Also, the importance of these clusters was demonstrated using statistics; cluster 7 was identified as the greatest significant cluster with regard to citations. By studying trends, two main sides of sustainable technology development were identified: supply and demand. Actors such as the government, technology companies (manufacturers and suppliers), and society - which includes individuals, groups, and communities - play their role in this field. Also, we found that despite the importance of the demand part, especially of the consumer, in terms of consumer behavior, consumption trends, social structure dynamics with new technology adoption, not enough study has been done of this area. Without considering the demand side, it can be said that sustainable technology development is not possible. Individuals, groups, and communities play a significant role in the implementation of technology, as they are the end-users of those technologies.

Case study

As mentioned before, decision making on RETs by management is one of the greatest central roles in sustainable technology development. Here we have two examples of private companies that decided to use sustainable technology to show their focus on the environment.

A Honar Tabiat Segal Company in the field of agricultural products and outputs in Iran, with its management team, is one of the sustainable farmers that produces healthy products. Thinking based on creating an appropriate and economical solution based on maintaining the quantity and quality of water and soil is an idea that is the basis of management’s decision to highlight sustainability issues. Healthy production and healthy society and the use of the latest technologies in the world and its localization in Iran is a goal to which the Honar Tabiat Segal pays special attention. Seeds, fertilizers, and substrate are the three areas in which the company works. In the field of seeds, one of the innovations used in this company is coated seed technology, a state-of-the-art technology. Eco-friendly advantages of this technology are: 1 - the biological compounds are not toxic to birds and, of course, cannot be absorbed by them, so they are not good sources of food and naturally protect them from birds; 2 - unlike other seeds, coated seeds have a good protective performance through adequate irrigation, the water accumulated in the seed prevents the dehydration and effluence of the water; 3 - improving soil quality; 4 - reduce the need for fertilizer; 5 - better use and saving of water. Water Absorbing Seed Process (WASP) is one of the latest coated seed technologies used in Honar Tabiat Segal. In other fields, Honar Tabiat Segal uses more sustainable technology.

В Jacob (Paya Tarh Form) is a manufacturer of modular shelving systems in Iran. Jacob’s shelving systems can be installed as a modular classification system in any environment and can be adapted to different spaces. Despite the high cost of raw materials, Jacob has decided to use metals (iron) instead of wood in its products because the use of wood is harmful to trees and the environment. Environmental benefits of metal usage are 1 - compatibility with environment; 2 - it is easily returned to nature because iron is a natural element; 3 - no environmental pollution; 4- recyclability.

Case questions

  • 1. What is the role of manager’s decision making in sustainable technology?
  • 2. Does knowledge management affect the performance of the organization in the field of sustainable technology?
  • 3. Which competitive advantage mangers can gain by decision on sustainable technology?
  • 4. Does industry have an effect on sustainable technology acceptance, development, and implementation?

Key terms and definitions

Clean technology: It covers to any procedure, creation, or facility that decreases undesirable effects on the environment by significantly improving energy efficacy, sustainable usage of capital, or ecological protection habits.

Consumer behavior: This means studying the processes related to the selection, purchase, use, or disposal of products, services, thoughts, or experiences by individuals to meet their needs and desires.

Environmental technology: This is the application of one or more environmental sciences to monitor and preserve the usual environment and capital and to control the harmful effects of humanoid conflict.

Green technology: This is technology that is ecologically friendly, built on the manufacture progression or stream chain. It concerns the production of clean energy as well. Clean energy is the usage of substitute energies and technologies that are less damaging to the environment than fossil fuels.

Renewable energy technologies: These allow us to generate energy, warmth, and gas from renewable bases.

Social dynamics: This (or sociodynamics) refers to the group behavior that is the consequence of interactions between different group members.

Sustainable technology: Some technologies that allow more valuable usage of normal properties and a reduction in the ecological effect of other technological benefits.

Technological innovation system (TIS): This can be considered a dynamic system of agents that interrelate with each other in an economic/industrial area under specific institutional substructure and that contribute to the production, dissemination, and exploitation of technology.


Acemoglu, D., Aghion, P., Bursztyn, L., & Heinous, D. (2012). The environment and directed technical change. American Economic Review, /02(1), 131-166.

Acemoglu, D., Akcigit, U., Hanley, D., Sc Kerr, W. (2016). Transition to Clean Technology Ufuk Akcigit. Journal of Political Economy, 124(1), 52-104.

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179-211.

Akbari, M., Sc Asadi, A. (2008). A comparative study of Iranian consumers' versus extension experts’ attitudes towards Agricultural Organic Products (AOP). American Journal of Agricultural and Biological Science, 3(3), 551-558.

Akbari, M., Khodayari, M., Danesh, M., Davari, A., & Padash, H. (2020). A bibliometric study of sustainable technology research. Cogent Business & Management, 7(1). 11075.2020.1751906

Amacher, G. S., Koskela, E., & Ollikainen, M. (2004). Environmental quality competition and eco-labeling. Journal of Environmental Economics and Management, 47(2), 284-306. https://doi. org/10.1016/S0095-0696(03)00078-0

Aria, M., Sc Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959-975.

Arora,S.,&Gangopadhyay,S. (1995). Toward a theoretical model ofvoluntary overcompliance. Journal of Economic Behavior and Organization, 28(2), 289-309. (95)00037-2

Arrow, K. J. (1962). The economic implications of learning by doing. The Review of Economic Studies, 29(3), 155.

Asadi, A., Akbari, M., Sharifzadeh, A., Sc Hashemi, S. M. (2009). Analysis of factors affecting agricultural organic products diffusion among consumers: Perception of extension workers. World Applied Sciences Journal, 6(3), 331-338. Retrieved from j&q=&esrc=s&source=web&cd=l&cad=rja&ved=0CCwQFjAA&url=http%3A%2F%2Fidosi. org%2Fwasj%2Fwasj6%283%29%2F5.pdf&ei=fYbXUtPDI8SprAfl4YGIAg&usg=AFQjCNG- gidVCXROu_wlMBszEuYCOEJ-OPQ&bvm=bv. 59568121, d.bmk

Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99-120.

Benjaafar, S., Li, Y., & Daskin, M. (2013). Carbon footprint and the management of supply chains: Insights from simple models. IEEE Transactions on Automation Science and Engineering, 10(1), 99-116.

Bergek, A., Jacobsson, S., Carlsson, B., Lindmark, S., Sc Rickne, A. (2008). Analyzing the functional dynamics of technological innovation systems: A scheme of analysis. Research Policy, 37(3), 407-429. https://doi.Org/10.1016/j.respol.2007.12.003

Bergek, A., Jacobsson, S., Sc Sanden, B. A. (2008). “Legitimation” and “development ofpositive externalities”: Two key processes in the formation phase of technological innovation systems. Technology Analysis and Strategic Management, 20(5), 575-592.

Bergmann, A., Colombo, S., & Hanley, N. (2008). Rural versus urban preferences for renewable energy developments. Ecological Economics, 65(3), 616-625. https://doi.Org/10.1016/j.ecolecon. 2007.08.011

Bjornali, E. S., & Ellingsen, A. (2014). Factors affecting the development of clean-tech start-ups: A literature review. Energy Procedia, 58, 43-50.

Blackman, A., Sc Bannister, G. J. (1998). Community pressure and clean technology in the informal sector: An econometric analysis of the adoption of propane by traditional Mexican brick- makers. Journal of Environmental Economics and Management, 35(1), 1—21. jeem. 1998.1019

Bohnsack, R., Pinkse, J., Sc Kolk, A. (2014). Business models for sustainable technologies: Exploring business model evolution in the case of electric vehicles. Research Policy, 43(2), 284-300. https:// 2013.10.014

Breukers, S., Sc Wolsink, M. (2007). Wind power implementation in changing institutional landscapes: An international comparison. Energy Policy, 35(5), 2737-2750. https://doi.Org/10.1016/j. enpol.2006.12.004

Brien, L. O., Jones, C., Sc Porter, M. E. (1995). The competitive advantage of the inner city. Harvard Business Review, 73(3), 55-71.

Carlsson, B., Jacobsson, S., Holmen, M., & Rickne, A. (2002). Innovation systems: Analytical and methodological issues. Research Policy, 31(2), 233-245. S0048-7333(01)00138-X

Castillo-Vergara, M., Alvarez-Marin, A., & Placencio-Hidalgo, D. (2018). A bibliometric analysis of creativity in the field of business economics. Journal of Business Research, ///(December 2017), 1-9. https://doi.Org/10.1016/j.jbusres.2017.12.011

Chen, J., Huang, S., Zhong, W., & Ruizhi, W. (2015). Green technology choice under environmental taxes. 2015 12th International Conference on Service Systems and Service Management (ICSSSM), 1-6. IEEE.

Cherni, J. A., tk Kentish, J. (2007). Renewable energy policy and electricity market reforms in China.

Energy Policy, 35(7), 3616—3629. https://doi.Org/10.1016/j.enpol.2006.12.024 Christmann, P. (2000). Effects of “best practices” of environmental management on cost advantage: The role of complementary assets. Academy of Management Journal, 43(4), 663-680. https://doi. org/10.2307/1556360

Chung, S. (2014). Environmental regulation and foreign direct investment: Evidence from South Korea. Journal of Development Economics, 108, 222-236. Chung, Y. H., Fare, R., & Grosskopf, S. (1997). Productivity and undesirable outputs: A directional distance function approach. Journal of Environmental Management, 51(3), 229-240. https:// 1997.0146

Cohen, B., & Winn, M. I. (2007). Market imperfections, opportunity and sustainable entrepreneur- ship. Journal of Business Venturing, 22(1), 29—19. Cohen, M. C., Lobel, R., & Perakis, G. (2016). The impact of demand uncertainty on consumer subsidies for green technology adoption. Management Science, 62(5), 1235-1258. https://doi. org/10.1287/mnsc.2015.2173

Cohen, W. M., tk Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35(1), 128. Collinson, S., & Gregson, G. (2003). Knowledge networks for new technology-based firms: An international comparison of local entrepreneurship promotion. R and D Management, 33(2), 189- 208. https://doi.Org/10.l 111/1467-9310.00292

Cui, X. (2018). How can cities support sustainability: A bibliometric analysis of urban metabolism.

Ecological Indicators, 93, 704-717. https://doi.Org/10.1016/j.ecolind.2018.05.056 Dangelico, R. M., Pontrandolfo, P., & Pujari, D. (2013). Developing sustainable new products in the textile and upholstered furniture industries: Role of external integrative capabilities. Journal of Product Innovation Management, 30(4), 642-658. Dasgupta, S., Laplante, B., Wang, H., tk Wheeler, D. (2002). Confronting the environmental Kuznets curve. Journal of Economic Perspectives, /6(1), 147-168. Davis, P. (1985). Clio and the economics of QWERTY. American Economic Review, 75, 332-337. Retrieved from ?seq=l#metadata_info_tab_contents Dechezlepre, A., A, M. G., tk Me, Y. (2008). The Clean Development Mechanism and the international diffusion of technologies: An empirical study. 36, 1273-1283. https://doi.Org/10.1016/j.enpol.2007.12.009 Dickel, P. (2018). Exploring the role of entrepreneurial orientation in clean technology ventures.

International Journal of Entrepreneurial Venturing, /0(1), 56-82.

DiMaggio, P., tk Powell, W. (1983). The iron cage revisited: Institutional isomorphism in organizational fields. American Sociological Review, 48(2), 147-160.

Dixit, A. K., Dixit, R. K., & Pindyck, R. S. (1994). Investment under uncertainty. Princeton, NJ: Princeton University Press.

Dosi, G. (1982). Technological paradigms and technological trajectories: a suggested interpretation of the determinants and directions of technical change. Research Policy, 11(3), 147-162.

Downing, P. B., tk White, L. J. (1986). Innovation in pollution control. Journal of Environmental Economics and Management, /3(1), 18-29. Drake, D. F., Kleindorfer, P. R., & Van Wassenhove, L. N. (2016). Technology choice and capacity portfolios under emissions regulation. Production and Operations Management, 25(6), 1006-1025. /poms. 12523

Edquist, C. (1997). Systems of innovation: technologies, institutions, and organizations. London: Psychology Press.

Eisenhardt, К. M. (1989). Building theories from case study research. Academy of Management Review, /4(4), 532-550. Eustachio, J. H. P. P., Caldana, A. C. F., Liboni, L. B., & Martinelli, D. P. (2019). Systemic indicator of sustainable development: Proposal and application of a framework. Journal of Cleaner Production, 241, 118383. Fare, R., & Grosskopf, S. (2004). Modeling undesirable factors in efficiency evaluation: Comment. European Journal of Operational Research, /57(1), 242-245. S0377-2217(03)00191-7

Fare, R., Grosskopf, S., Lovell, С. A. K., & Pasurka, C. (1989). Multilateral productivity comparisons when some outputs are undesirable: A nonparametric approach. The Review of Economics and Statistics, 71, 90-98.

Fare, R., Grosskopf, S., & Pasurka, C. A. (2007). Pollution abatement activities and traditional productivity. Ecological Economics, 62(3-4), 673-682. https://doi.Org/10.1016/j.ecolecon.2006.08.014 Fischer, C., Parry, I. W. H., & Pizer, W. A. (2003). Instrument choice for environmental protection when technological innovation is endogenous. Journal of Environmental Economics and Management, 45(3), 523-545. Fischer, C., & Newell, R. G. (2008). Environmental and technology policies for climate mitigation. Journal of Environmental Economics and Management, 55(2), 142-162. https://doi.Org/10.1016/j. jeem.2007.11.001

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement errors. Journal of Marketing Research, 18(1), 39-50. Foxon, T. J., Gross, R., Chase, A., Howes, J., Arnall, A., Sc Anderson, D. (2005). UK innovation systems for new and renewable energy technologies: Drivers, barriers and systems failures. Energy Policy, 35(16), 2123-2137. https://doi.Org/10.1016/j.enpol.2004.04.011 Freeman, C. (1987). Technology policy and economic performance: Lessons from Japan. Pinter Pub Ltd (November 1, 1987).

Garcia-Berna, J. A., Fernandez-Aleman, ). L., Carrillo de Gea, ). M., Nicolas, J., Moros, B., Toval, A., ... Calero, C. (2019). Green IT and sustainable technology development: Bibliometric overview. Sustainable Development, (November 2018), 1-24. Geels, F. W. (2002). Technological transitions as evolutionary reconfiguration processes: A multilevel perspective and a case-study. Research Policy, 3/(8-9), 1257-1274. S0048-7333(02)00062-8

Gersbach, H., Sc Requate, T. (2004). Emission taxes and optimal refunding schemes. Journal of Public Economics, Щ3-4), 713-725. Gong, X., & Zhou, S. X. (2013). Optimal production planning with emissions trading. Operations Research, 6/(4), 908-924. Griliches, Z. (1990). Patent statistics as economic indicators: A survey. Journal of Economic Literature (Vol. 28). Halme, M., Sc Korpela, M. (2014). Responsible innovation toward sustainable development in small and medium-sized enterprises: A resource perspective. Business Strategy and the Environment, 23(8), 547-566.

Harstad, B. (2012). Buy coal! A case for supply-side environmental policy. Journal of Political Economy, /20(1), 77-115.

Hart, S. L. (1995). A natural-resource-based view of the firm. Academy of Management Review, 20(4), 986-1014.

Hayes, G., Sc Horne, J. (2011). Sustainable development, shock and awe? London 2012 and civil society. Sociology, 45(5), 749—764. He, M., Zhang, Y., Gong, L., Sc Zhou, Y. (2019). ScienceDirect Bibliometrical analysis of hydrogen storage.

(29). https://doi.Org/10.1016/j.ijhydene.2019.07.014 Hekkert, M. P., Sc Negro, S. O. (2009). Functions of innovation systems as a framework to understand sustainable technological change: Empirical evidence for earlier claims. Technological Forecasting and Social Change, 76(4), 584-594.

Hekkert, M. P, Suurs, R. A. A. A., Negro, S. O., Kuhlmann, S., & Smits, R. E. H. M. H. M. (2007). Functions of innovation systems: A new approach for analysing technological change. Technological Forecasting and Social Change, 74(4), 413-432. https://doi.Org/10.1016/j.techfore.2006.03.002 Hockerts, K., Sc Wiistenhagen, R. (2010). Greening Goliaths versus emerging Davids - Theorizing about the role of incumbents and new entrants in sustainable entrepreneurship. Journal of Business Venturing, 25(5), 481-492. https://doi.Org/10.1016/j.jbusvent.2009.07.005 Hughes, T. P. (1983). Networks of Power: Electric supply systems in the US, England and Germany, 1880- 1930. Baltimore, MD: Johns Hopkins University.

Jacobsson, S., & Bergek, A. (2004). Transforming the energy sector: The evolution of technological systems in renewable energy technology. Industrial and Corporate Change, 13(5), 815-849. https://

Jacobsson, S., & Johnson, A. (2000). The diffusion of renewable energy technology: An analytical framework and key issues for research. Energy Policy, 28(9), 625-640. S0301-4215(00)00041-0

Jacobsson, S., & Lauber, V. (2006). The politics and policy of energy system transformation - explaining the German diffusion of renewable energy technology. Energy Policy, 34(5), 256-276. https://doi.Org/10.1016/j.enpol.2004.08.029

Jaffe, A. B., Newell, R. G., & Stavins, R. N. (2002). Environmental policy and technological change.

Environmental and Resource Economics, 22(1-2), 41-70.

Jaffe, A. B., Newell, R. G., & Stavins, R. N. (2005). A tale of two market failures: Technology and environmental policy. Ecological Economics, 54(2-5), 164-174.

Jiang-hua, L. (2006). Hydrogen energy: Green energy in the future [JJ. Modern Chemical Industry, 26(sup 2), 10-15.

Johansen, K. (2019). Local support for renewable energy technologies? Attitudes towards local nearshore wind farms among second home owners and permanent area residents on the Danish coast. Energy Policy, 132, 691-701. https://doi.Org/10.1016/j.enpol.2019.04.027 Johnstone, N.. Hascic, I., & Popp, D. (2010). Renewable energy policies and technological innovation: Evidence based on patent counts. Environmental and Resource Economics, 45(1), 133-155.

Jung, C., Krutilla, K., Sc Boyd, R. (1996). Incentives for advanced pollution abatement technology at the industry level: An evaluation of policy alternatives. Journal of Environmental Economics and Management, 50(1), 95-111.

Karekezi, S. (2002). Renewables in Africa - Meeting the energy needs of the poor. Energy Policy, 50(11-12), 1059-1069. Kemp, R. (2010). Eco-innovation: Definition, measurement and open research issues. Economia Politico, 27(3), 397-420.

Kemp, R., Schot, J., Sc Hoogma, R. (1998). Regime shifts to sustainability through processes of niche formation: The approach of strategic niche management. Technology Analysis and Strategic Management, 10(2), 175-195. Khan, I. (2020). Sustainability challenges for the south Asia growth quadrangle: A regional electricity generation sustainability assessment. Journal of Cleaner Production, 243, 118639. https://doi. org/10.1016/j.jclepro.2019.118639

Klassen, R. D., Sc McLaughlin, С. P. (1996). The impact of environmental management on firm performance. Management Science, 42(8), 1199-1214.

Klassen, R. D., & Whybark, D. C. (1999). The impact of environmental technologies on manufacturing performance. Academy of Management Journal, 42(6), 599-615. Kobos, P H., Erickson, J. D., & Drennen, T. E. (2006). Technological learning and renewable energy costs: Implications for US renewable energy policy. Energy Policy, 34(13), 1645—1658. https://doi. org/10.1016/j.enpol.2004.12.008

Kortelainen, M. (2008). Dynamic environmental performance analysis: A Malmquist index approach. Ecological Economics, 64(4), 701-715. https://doi.Org/10.1016/j.ecolecon.2007.08.001 Krass, D., Nedorezov, T., & Ovchinnikov, A. (2013). Environmental taxes and the choice of green technology. Production and Operations Management, 22(5), 1035-1055.

Kumbaroglu, G., Madlener, R., & Demirel, M. (2008). A real options evaluation model for the diffusion prospects of new renewable power generation technologies. Energy Economics, 30(4), 1882-1908. https://doi.Org/10.1016/j.eneco.2006.10.009 Lanjouw, J. O., Sc Mody, A. (1996). Innovation and the international diffusion of environmentally responsive technology. Research Policy, 25(4), 549-571. Lewis, J. I. (2014). The rise of renewable energy protectionism: Emerging trade conflicts and implications for low carbon development. Clobal Environmental Politics, 14(4), 10-35.

Lewis, J. I., & Wiser, R. H. (2007). Fostering a renewable energy technology industry: An international comparison of wind industry policy support mechanisms. Energy Policy, 35(3), 1844-1857. https://doi.Org/10.1016/j.enpol.2006.06.005

Lundvall, B.-A. (1992). National systems of innovation: An analytical framework. London: Pinter. Lundvall, B.-A., & Dosi, G. (1988). Innovation as an interactive process: From user-producer interaction to the national system of innovation. Technical Change and Economic Theory, 1988, 349-369. Luo, Z., Chen, X., & Wang, X. (2016). The role of co-opetition in low carbon manufacturing. European Journal of Operational Research, 253(2), 392-403. https://doi.Org/10.1016/j.ejor.2016.02.030 Madlener, R., & Stagl, S. (2005). Sustainability-guided promotion of renewable electricity generation. Ecological Economics, 53(2), 147-167. https://doi.Org/10.1016/j.ecolecon.2004.12.016 Mata, F. J., Fuerst, W. L., tk Barney, J. B. (1995). Information technology and sustained competitive advantage: A resource-based analysis. MIS Quarterly, 19(4), 487-505.

Maxim, A. (2014). Sustainability assessment of electricity generation technologies using weighted multi-criteria decision analysis. Energy Policy, 65, 284-297. https://doi.Org/10.1016/j.

enpol. 2013.09.059

Meijer, I. S. M., Hekkerta, M. P., & Koppenjan, J. F. M. (2007). The influence of perceived uncertainty on entrepreneurial action in emerging renewable energy technology; biomass gasification projects in the Netherlands. Energy Policy, 35(11), 5836-5854. https://doi.Org/10.1016/j. enpol.2007.07.009

Miles, M. B., Huberman, A. M., Huberman, M. A., Sc Huberman, M. (1994). Qualitative data analysis: An expanded sourcebook. London: Sage.

Milliman, S. R., & Prince, R. (1989). Firm incentives to promote technological change in pollution control. Journal of Environmental Economics and Management, 17(3), 247-265.

Mirakzadeh, A. A., Akbari, M., Ghiasvand Ghiasy, F., Hashemi, S. M., & Rezvanfar, A. (2012). Attitudes of Iranian consumers’ towards agricultural organic products (AOP). African Journal of Agricultural Reseearch, 7(20), 3088-3095. Montero, J. P. (2002). Permits, standards, and technology innovation. Journal of Environmental Economics and Management, 44(1), 23-44. Mulder, K., Ferrer, D., Sc Lente, H. Van. (2011). What is sustainable technology? Perceptions, paradoxes and possibilities. Sustainability Responsibility Accountability, 44(0), 0-7. https://doi. org/lO.llll/jiec.12033

Musiolik, J., Markard, J., Sc Hekkert, M. (2012). Networks and network resources in technological innovation systems: Towards a conceptual framework for system building. Technological Forecasting and Social Change, 79(6), 1032-1048. https://doi.Org/10.1016/j.techfore.2012.01.003 Nameroff, T.)., Garant, R. J., Sc Albert, M. B. (2004). Adoption of green chemistry: An analysis based on US patents. Research Policy, 33(6-7), 959-974. https://doi.Org/10.1016/j.respol.2004.03.001 Negro, S. O., Hekkert, M. P., Sc Smits, R. E. (2007). Explaining the failure of the Dutch innovation system for biomass digestion-A functional analysis. Energy Policy, 35(2), 925—938. https://doi. org/10.1016/j.enpol.2006.01.027

Negro, S. O., Suurs, R. A. A., Sc Hekkert, M. P. (2008). The bumpy road of biomass gasification in the Netherlands: Explaining the rise and fall of an emerging innovation system. Technological Forecasting and Social Change, 75(1), 57-77. https://doi.Org/10.1016/j.techfore.2006.08.006 Neij, L. (1997). Use of experience curves to analyse the prospects for diffusion and adoption of renewable energy technology. Energy Policy, 25(13), 1099—1107. s0301-4215(97)00135-3

Nemet, G. F. (2009). Demand-pull, technology-push, and government-led incentives for non- incremental technical change. Research Policy, 38(5), 700-709. https://doi.Org/10.1016/j.respol. 2009.01.004

Nesta, L., Vona, F., & Nicolli, F. (2014). Environmental policies, competition and innovation in renewable energy. Journal of Environmental Economics and Management, 67(3), 396-411. https://doi. org/10.1016/j.jeem.2014.01.001

Newell, R. G., Jaffe, A. B., & Stavins, R. N. (1999). The induced innovation hypothesis and energysaving technological change. The Quarterly Journal of Economics, 114(3), 941—975.

Norberg-Bohm, V. (1999). Stimulating “green” technological innovation: An analysis of alternative policy mechanisms. Policy Scietices, 32(1), 13-38. https://doi.Org/10.1023/A:1004384913598 Okura, M. R. (2010). Review of global problems: The search for equity, peace, and sustainability.

Journal of Political Science Education, 6(2), 210-211. Pang, R., & Zhang, X. (2019). Achieving environmental sustainability in manufacture: A 28-year bibliometric cartography of green manufacturing research .Journal of Cleaner Production, 233, 84-99.

Pfeiffer, B., & Mulder, P. (2013). Explaining the diffusion of renewable energy technology in developing countries. Energy Economics, 40, 285-296. https://doi.Org/10.1016/j.eneco.2013.07.005 Popp, D. (2002). Induced innovation and energy prices. American Economic Review, 92(1), 160—180.

Popp, D. (2011). International technology transfer, climate change, and the clean development mechanism. Review of Environmental Economics and Policy, 5(1), 131-152. req018

Popp, D., Hascic, I., & Medhi, N. (2011). Technology and the diffusion of renewable energy ★. Energy Economics, 33(4), 648-662. https://doi.Org/10.1016/j.eneco.2010.08.007 Popp, D., Newell, R. G., Sc Jaffe, A. B. (2010). Energy, the environment, and technological change. In Bronwyn H. Hall Sc Nathan Rosenberg (Eds.), Handbook of the economics of innovation (Vol. 2, pp. 873-937). North-Holland: Elsevier.

Porter, M. E., & Linde, C. van der. (1995). Toward a new conception of the environment-competitiveness relationship. Journal of Economic Perspectives, 9(4), 97-118. https://doi.Org/10.1257/jep.9.4.97 Quist, J., Sc Vergragt, P. (2006). Past and future of backcasting: The shift to stakeholder participation and a proposal for a methodological framework. Futures, 38(9), 1027-1045. https://doi. org/10.1016/j. futures.2006.02.010

Raven, R. (2007). Niche accumulation and hybridisation strategies in transition processes towards a sustainable energy system: An assessment of differences and pitfalls. Energy Policy, 35(4), 2390—2400. https://doi.Org/10.1016/j.enpol.2006.09.003

Rennings, K. (2000). Redefining innovation - Eco-innovation research and the contribution from ecological economics. Ecological Economics, 32(2), 319-332. S0921-8009(99)00112-3

Requate, T. (2005a). Dynamic incentives by environmental policy instruments - A survey. Ecological Economics, 54(2-3), 175-195. https://doi.Org/10.1016/j.ecolecon.2004.12.028 Requate, T. (2005b). Timing and commitment of environmental policy, adoption of new technology, and repercussions on R & D. Environmental and Resource Economics, 31(2), 175-199. https://doi. org/10.1007/sl0640-005-1770-x

Requate, T., Sc Unold, W. (2003). Environmental policy incentives to adopt advanced abatement technology: Will the true ranking please stand up? European Economic Revieu>, 47(1), 125-146. Rogers, E. M. (1995). Diffusion of innovations (Vol. 12). New York: Free Press.

Roshdi, I., Hasannasab, M., Margaritis, D., & Rouse, P. (2018). Generalised weak disposability and efficiency measurement in environmental technologies. European Journal of Operational Research, 266(3), 1000-1012. https://doi.Org/10.1016/j.ejor.2017.10.033 Russo, M. V., Sc Fouts, P. A. (1997). A resource-based perspective on corporate environmental performance and profitability. Academy of Management Journal, 40(3), 534-559. https://doi. org/10.2307/257052

Sahoo, В. K., Luptacik, M., & Mahlberg, B. (2011). Alternative measures of environmental technology structure in DEA: An application. European Journal oj' Operational Research, 215(3), 750-762. https://doi.Org/10.1016/j.ejor.2011.07.017

Sarkar, R. (2008). Public policy and corporate environmental behaviour: A broader view. Corporate Social Responsibility and Environmental Management, 15(5), 281-297. Schumpeter, J. (1942). Capitalism, socialism and democracy. New York: University of Illinois.

Shephard, R. W. (1970). Theory oj' cost and production functions.Princeton, N|: Princeton University Press.

Shrivastava, P. (1995). Environmental technologies and competitive advantage. Strategic Management Journal, 16( SI), 183-200.

Siddiqui, A. S., & Fleten, S. E. (2010). How to proceed with competing alternative energy technologies: A real options analysis. Energy Economics, 52(4), 817-830. https://doi.Org/10.1016/j. eneco.2009.12.007

Siddiqui, A. S., Marnay, C., Sc Wiser, R. H. (2007). Real options valuation of US federal renewable energy research, development, demonstration, and deployment. Energy Policy, 55(1), 265-279. https://doi.Org/10.1016/j.enpol.2005.ll.019

Sjoo, K., Sc Frishammar, J. (2019). Demonstration projects in sustainable technology: The road to fulfillment of project goals .Journal of Cleaner Production, 228, 331-340. jelepro.2019.04.302

Srebrenkoska, V., Fidancevska, E., Jovanov, V., Sc Angusheva, B. (2013). Sustainable technology and natural environment. Proceedings of XXI International Scientific and Professional Meeting" Ecological Truth" ECO-IST’13, 238-242. University of Belgrade, Technical Faculty, Bor.

Stern, N. (2007). The economics of climate change: The stern review. The Economics of Climate Change: The Stern Review, 9780521877, 1-692. Sueyoshi, T., Sc Goto, M. (2012a). DEA radial and non-radial models for unified efficiency under natural and managerial disposability: Theoretical extension by strong complementary slackness conditions. Energy Economics, 34(2), 700-713. https://doi.Org/10.1016/j.eneco.2011.12.013 Sueyoshi, T., Sc Goto, M. (2012b). Returns to scale and damages to scale on U.S. fossil fuel power plants: Radial and non-radial approaches for DEA environmental assessment. Energy Economics, 34(b), 2240-2259. https://doi.Org/10.1016/j.eneco.2012.07.024 Sung, B., Choi, M. S., Sc Song, W. Y. (2019). Exploring the effects of government policies on economic performance: Evidence using panel data for Korean renewable energy technology firms. Sustainability, 1/(8), 19. Tang, M., Liao, H., Wan, Z., Herrera-Viedma, E., Sc Rosen, M. A. (2018). Ten years of sustainability (2009 to 2018): A bibliometric overview. Sustainability, /0(5). Taylor, M. R., Rubin, E. S., & Hounshell, D. A. (2005). Control of S02 emissions from power plants: A case of induced technological innovation in the U.S. Technological Forecasting and Social Change, 72(6 SPEC. ISS.), 697-718. https://doi.Org/10.1016/j.techfore.2004.ll.001 Teece, D. J. (1986). Profiting from technological innovation: Implications for integration, collaboration, licensing and public policy. Research Policy, /5(6), 285-305. 10.1016/0048-7333(86)90027-2

Toptal, A., Ozlii, H., Sc Konur, D. (2014). Joint decisions on inventory replenishment and emission reduction investment under different emission regulations. International Journal of Production Research, 52(1), 243-269. Tushman, M. L., & Anderson, P. (1986). Technological discontinuities and organizational environments Philip Anderson. Administrative Science Quarterly, 3/(3), 439-465.

Unruh, G. C. (2000). Understanding carbon lock-in. Energy Policy, 28(12), 817-830. https://doi. org/10.1016/S0301-4215(00)00070-7

Uusitalo, V., Kuokkanen, A., Gronman, К., Ко, N., Makinen, H., & Koistinen, K. (2019). Environmental sustainability assessment from planetary boundaries perspective - A case study of an organic sheep farm in Finland. Science of The Total Environment, 687, 168—176. https://doi. org/10.1016/j.scitotenv.2019.06.120

Walker, G., Devine-Wright, P., Hunter, S., High, H., & Evans, 13. (2010). Trust and community: Exploring the meanings, contexts and dynamics of community renewable energy. Energy Policy, 38(b), 2655-2663. https://doi.Org/10.1016/j.enpol.2009.05.055

Wang, H., & Yang, Y. (2019). Neighbourhood walkability: A review and bibliometric analysis. Cities, 9T(September 2018), 43-61. https://doi.Org/10.1016/j.cities.2019.04.015

Wang, Q., & Zhan, L. (2019). Assessing the sustainability of renewable energy: An empirical analysis of selected 18 European countries. Science of The Total Environment, 692, 529-545. https://doi. org/10.1016/j.scitotenv. 2019.07.170

Watanabe, C., Wakabayashi, K., & Miyazawa, T. (2000). Industrial dynamism and the creation of a ‘virtuous cycle’ between R&D, market growth and price reduction. The case of photovoltaic power generation (PV) development in Japan. Technovation, 20(6), 299-312. SOI 66-4972(99)00146-7

Weitzman, M. L. (1974). Prices vs. quantities. The Review of Economic Studies, 41(4), 477-491.

Winter, S. G., & Nelson, R. R. (1982). An evolutionary theory of economic change. University of Illinois at Urbana-Champaign’s Academy for Entrepreneurial Leadership Historical Research Reference in Entrepreneurship.

Xu, X., He, P., Xu, H., & Zhang, Q. (2017). Supply chain coordination with green technology under cap-and-trade regulation. International Journal of Production Economics, 183. https://doi. org/10.1016/j.ijpe.2016.08.029

Yang, Y., Nie, P., & Huang, J. (2019). The optimal strategies for clean technology to advance green transition. Science of The Total Environment, 134439. https://doi.Org/10.1016/j.scitotenv.2019.134439

Zhang, X., Chen, N., Sheng, H., Ip, C., Yang, L., Chen, Y.....Niyogi, D. (2019). Urban drought

challenge to 2030 sustainable development goals. Science of The Total Environment, 693, 133536. https://doi.Org/10.1016/j.scitotenv.2019.07.342



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