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G L O B E L I C S W O R K I N G P A P E R S E R I E S
THE GLOBAL NETWORK FOR ECONOMICS OF LEARNING, INNOVATION, AND COMPETENCE BUILDING SYSTEM
Drivers of eco-innovation in the manufacturing sector of Nigeria
Maruf Sanni and Michael Francis
Working Paper No. 2017-03
ISBN: 978-87-92923-23-3
www.globelics.org
Drivers of eco-innovation in the manufacturing sector of Nigeria
Maruf Sanni1 and Michael Francis 2
1National Centre for Technology Management, Federal Ministry of Science and Technology, Obafemi Awolowo University, Ile Ife, Nigeria
2Department of Economic History and Development Studies University of KwaZulu-Natal, South Africa
Email: [email protected]
2
Abstract
In Nigeria, the manufacturing sector has the potential to make significant contribution to the
economy by creating jobs, generate wealth and drastically reduce the level of poverty. However,
the sector has not lived up to expectation in recent years. Virtually all major companies in
Nigeria provide their own electricity through diesel generators with implications for greenhouse
gas emissions. Fortunately, the manufacturing sector also has the potential to be the driving force
for overcoming the challenges of technological and environmental changes but only when the
production process is integrated within the concept of eco-innovation. This paper therefore
investigates the determinants of eco-innovation in the manufacturing sector of Nigeria based on
empirical data from the Nigerian 2005-2007 national innovation survey. Using binary logistic
regression, the study reveals that important drivers of eco-innovation in the manufacturing sector
of Nigeria are innovation persistence, regulatory framework, cost savings from material and
energy use. Collaboration with the public research institute` comes up as important sources of
knowledge for eco-innovation. Our article brings to the fore the importance of innovation
leadership or persistence as a veritable innovation management strategies that could help firms
become a leader in the green market. These contributions are imperative for the creation and
evolution of firm's competitive advantage in the emerging green market.
Keywords: eco-innovation, driver, manufacturing sector, firm, innovation persistence, Nigeria
3
1. Introduction
Innovative pathways to an environmentally sustainable economic growth, gaining insights and
understanding country specific challenges in terms of their technological capabilities are crucial
to economic development. Innovation process ingrained in sustainable development has been
touted to play an important role in this context. Outcomes of such innovation process are termed
eco-innovation, defined as the “the production, assimilation or exploitation of a product,
production process, service or management or business methods that is novel to the firm [or
organization] and which results, throughout its life cycle, in a reduction of environmental risk,
pollution and other negative impacts of resources use (including energy use) compared to
relevant alternatives” (Kemp and Pearson, 2008:10). Such innovation helps in decoupling
environmental pressure and economic growth whether or not that effect is intended (OECD,
2009). This category of innovation is not necessarily new to the world but it should be new to the
firm or organization implementing or adopting it (OECD, 2005). In recent years, eco-innovation
has gained prominence in the literature not only because of its “double externality” nature
(Rennings, 2000) but also the fact that evidence has emerged that it also adds value to firm
competitiveness and transition to sustainable societies (Machiba, 2010; Carrillo- Hermosilla et
al., 2010).
Based on the specificity of double externalities, eco-innovation has been designated as special
type of innovation because it reduces the negative environmental externalities and it is also
subjected to knowledge spillover externalities both of which could reduce firm’s investment in
eco-innovation (Ghisetti and Pontoni, 2015; Ghisetti and Rennings, 2014; Rexhäuser and
Rammer, 2014; Rennings, 2000). Based on this fact, eco-innovation is conceptualized as being
strongly policy-driven as well as influenced by “policy push/pull effect” (Rennings and Rammer,
2009; Cleff and Rennings, 1999). Other distinguishing characteristics of eco-innovation are that
it is also affected by both the organizational, social and institutional settings (Horbach, 2008;
Rennings, 2000).
In view of the above, drivers of eco-innovation has been receiving increasing attention in the
mainstream literature in the past few years. Some scholars have traced these trends and carried
out a thorough review of the determinants of eco-innovation at international, national, industrial,
sectoral and firm levels (for e.g. see del Rio et al., 2016; Ghisetti and Pontoni, 2015 and Díaz-
4
García et al., 2015). Theoretical bases for many of these studies have come mainly from
innovation economics (Rennings, 2000), environmental economics (Jacob et al., 2002),
evolutionary economics (Unruh, 2000; Foxon et al., 2005, etc.) and resource-based view
Kammerer, 2009). Because of the eco-innovation potential to reduce costs of negative
externalities on the environment as well as contributing to industrial competitiveness, sustainable
societies and overall human well-being, determining the drivers of eco-innovation is very
important. It could also assist policy makers in developing instruments that could encourage eco-
innovation development and adoption in the industrial sector of the economy.
Emerging literature has shown that eco-innovation is driven by both “market-pull” and
“technology-push” dynamics. However, as a result of the double externality issue, policy
(regulatory) push/pull effect has been identified as crucial to its implementation and adoption by
firms (Horbach et al., 2012). In recent times, drivers of eco-innovation have been grouped into:
“market-pull”, “technology-push”, “firm specific factors”, and “policy” determinants (Horbach
et al., 2012). Factors under “market-pull” include cost savings (Rennings, 2000), market share
(Triguero et al., 2013), economic performance (Adelegan et al., 2010; Wagner, 2007), market
demand for green products (Triguero et al., 2013; Rehfeld et al., 2007), economic performances
(Horbach, 2008) and customer benefits (Kammerer, 2009). With regard to the “technology-
push”, some of the factors are firm's technological and management capabilities (e.g.
engagement in R&D, staff training, in-house software acquisition etc.) (Horbach, 2012; 2008),
collaboration with research institutes, access to external knowledge (Triguero et al., 2013),
organizational innovation and management strategies (Wagner, 2008; Rehfeld et al., 2007).
Other factors such as the sector, firm age, internationalization, location, innovation persistence,
firm size are classified under “firm specific factors” (del Rio et al., 2016; Ghisetti and Pontoni,
2015; Cainelli et al., 2012; Mazzanti and Zoboli, 2009; Horbach, 2008; Wagner, 2008; Rennings
et al., 2006). For the policy (regulatory) driver, the factors include the existing regulations,
expected future regulations, access to existing subsidies and fiscal incentives (Triguero et al.,
2013; Horbach, 2008).
Despite the relatively large empirical evidence on the drivers of eco-innovation, two critical
issues are still largely unexplored. For instance, it is still unclear to what extent is eco-innovative
behaviour path dependent. Although this issue has been examined within the mainstream
5
innovation (Antonelli et al., 2012; Raymond et al., 2010; Roper and Hewitt-Dundas 2008), very
few studies have tested the concept of ‘innovation breads innovation’ at firm-level in eco-
innovation studies with notable exceptions to (Chassagnon and Haned, 2015; Horbach, 2008).
There is the need to bring more empirical evidence to the issue of innovation leadership,
persistence and path-dependency in eco-innovation studies. Analysis such as this is important so
as to reveal whether firms that consistently eco-innovate in the past are also more likely to be
serial eco-innovator. At the same time, the influence of international factors such as home
competitors, member of conglomerates, collaboration with foreign firms, effects of foreign
equity, influence of international conventions and codes of practice, effects of customers in
foreign markets are largely missing in eco-innovation studies (del Rio et al., 2016). While
considering the effects of export propensity of local firm and multinational ownership of firms
on eco-innovation, Cainelli et al. (2012) found them not to be important as drivers of eco-
innovation. Issues such as these call for further study to ascertain their veracity. Other area of
importance that is yet to be thoroughly explored in eco-innovation studies is that of the regional
dynamics of eco-innovation. Majority of empirical evidence on eco-innovation comes from
Western and Southern Europe and USA (del Río et al., 2016; Díaz-García et al., 2015; del Río et
al., 2013; Gee and McMeekin, 2011; De Marchi, 2012; Cainelli et al., 2012) with studies
conducted in newly industrializing and developing countries largely missing. Very few studies
from newly industrializing countries such as China are slowly emerging (Yang and Yang, 2015;
Cai and Zhou, 2014). Meanwhile, it is critically important to explore the regional dynamics of
eco-innovation since it is usually difficult if not impossible to generalize studies from one
country to other regions given the great disparities in national innovation systems, willingness-
to-pay for green products by buyers and the environmental readiness of firms (del Rio et al.,
2016). Kemp and Oltra (2011, p. 252) have also substantiated this fact by stating that “eco-
innovation is context-specific which is why we need research from those countries, by
researchers from those countries who understand the broader context and societal processes in
which eco-innovation is embedded”. It is within these existing knowledge gaps that this paper
intends to contribute. In other words, this paper contributes to the existing literature by
expatiating the concepts of innovation persistence and path dependency, international openness
as well as regional dynamics in eco-innovation studies. The article is structured as follows. The
second section discusses relevant literature on the drivers of eco-innovation in the manufacturing
6
sector. Section 3 specifies the methodology adopted for the study. Section 4 reports the analysis
of data and discussion of results. Section 5 concludes and suggests policy recommendations.
2. Drivers of eco-innovation in the manufacturing sector
Empirical analyses on the determinants of eco-innovations only started coming out around late
1990s. In the 1990s, some scholars clamoured for the need for research activities to explore the
relationship between environmental management and production strategy (Gupta, 1995; Sarkis
and Rasheed, 1995) due to the impacts of organizational activities on the environment (Kitazawa
and Sarkis, 2000). At the same time, many firms have engaged in eco-innovation activities for
many other reasons. One of the critical factors has been an improvement in business performance
(Adelegan et al., 2010; Bansal and Gao, 2006; González-Benito and González-Benito, 2005).
One of the few articles specifically on eco-innovation in the manufacturing sector of Nigeria also
found out that the pulp and paper industry in Nigeria showed a strong relationship between green
technology use and financial performance (Adelegan et al., 2010). In the studies of Darnall et al.
(2008) and Ahmad and Schroeder (2003), they found out that engagements in environmental
management practices or eco-innovation activities were positively related to the financial result
and greater operational efficiency. Some authors have also opined that when firms adopt an eco-
innovative management strategies, they tend to increase their competitiveness through cost
reduction, quality improvement and implementation of new processes and products (Yang et al.,
2010; Parnell, 2008; Shrivastava, 2008; Bresciani and Oliveira 2007). In addition to these
factors, adoption of environmental management systems like ISO 14001 have been found out to
influence market share, firm’s image, risk portfolios, firm’s efficiency and international sales
growth (Jacobs et al., 2010; Zeng et al., 2008; Wagner, 2007). For any country to actually
unravel the potentials of eco-innovation, it is imperative that drivers and barriers to eco-
innovation are identified. Many inventions have failed to make it to the market because of
complexities surrounding drivers and barriers of innovation (Bleischwitz, 2007). Eco-innovation
as a special type of mainstream innovation is not an exception. Within the context of eco-
innovation, drivers are generally understood as specific and evident agents or factors leading to
increased or reduced pressure on the environment while barriers are considered as those forms of
market imperfections that hinder markets from adopting eco-innovations (Bleischwitz et al.,
7
2007). In broad term, both can be viewed either from the demand or supply side of eco-
innovation.
Both the fields of innovation and environmental economics have made a lot of contributions to
the determinants of eco-innovation both at the micro and macro levels. For instance, in the field
of innovation, studies have shown that demand factors in general (Horbach et al., 2012; Horbach,
2008) and collaboration with environmentally concerned stakeholders in particular (Wagner,
2007) are crucial in the production of eco-innovations. Meanwhile, management literature on
corporate social responsibility strategy had indicated that societal pressure and demand for
environmentally-friendly products and processes may not necessarily be a prerequisite to
increase investments in eco-innovation. Most of the scholars in this field are of the opinion that
more often than not, firms respond to the societal pressure and demand for environmentally-
friendly products by putting in minimum investment in eco-innovation which indicates their
interests towards the environment (Darnall, 2006; Bansal and Hunter, 2003; Potoski and Prakash,
2003; Suchman, 1995). The importance of technological and organisational capabilities as
motivating factors for promoting eco-innovations in manufacturing firms have also been
suggested (Horbach, 2008).
Some literature in the field of environmental economics has highlighted the significance of
environmental regulation and standards and policies as important drivers of eco-innovation
among manufacturing firms (Milliman and Prince, 1989; Brunnermeier and Cohen, 2003). Many
firms now perceived regulation not as a factor that increases cost of production but rather a
stimulator of firms’ innovativeness that might make firms to be competitive in eco-innovation
markets (Porter and Van Der Linde, 1995a). However, within the context of impact of regulation
on eco-innovation, the importance of firms’ innovation capabilities and their respective strategies
for eco-innovation have been stressed. For instance, low innovative firms may adopt eco-
innovation as a means to reduce production costs and comply with the minimum environmental
standards, while high innovative firms may adopt eco-innovation in order to enter new markets
(Grubb and Ulph, 2002). This fact has a lot of policy implications for the effectiveness of
regulations for firms such that policy on regulation with the aim of stimulating eco-innovation
could potentially differ depending on whether or not firms are already ahead of their competitors
in eco-innovation investments and activities (Kesidou and Demirel, 2012).
8
This section presents factors that prompt firms to adopt eco-innovation as a strategy that may
allow them shift from business-as-usual towards a new sustainable growth path. Based on
empirical evidence (Horbach et al., 2012; Horbach, 2008; Rennings, 2000) we develop a
framework that considers four groups of factors that could drive eco-innovation at firm level:
technology-push, demand-pull, regulatory policy determinant and firm-specific factors. This
framework is shown in figure 1. Under the regulatory policy determinant factor we have
‘meeting regulatory requirement by the government’ (Borghesi et al., 2015; Demirel and
Kesidou, 2011; Rennings, 2000; Porter and van der Linde, 1995a &1995b). Those categorized as
demand-pull factors are satisfying customer demand, energy cost savings and improvement in
the quality of goods and services (del Río et al., 2013; Kesidou and Demirel, 2012; Demirel and
Kesidou, 2011; Belin et al., 2011). We classified factors such as engagement in R&D, staff
training, in-house software development, acquisition of external knowledge, customer and
competitors as sources of knowledge, access to formal sources of knowledge (proxy by public
research institutes), networking strategies (proxy by collaboration incidence) as technology-push
factors (Borghesi et al., 2012; Horbach et al., 2012, Di Marchi, 2012; Mondéjar-Jiménez, et al.,
2013; Triguero et al., 2013; Horbach, 2014; 2008; Belin et al., 2011; del Rio 2005). Some of the
firm-specific factors are home competition, firm size, internationalization, innovation persistence
and sector (based on energy intensity) (Chassagnon and Haned, 2015; Horbach, 2014; 2008;
Cainelli et al., 2012).
2.1 Regulatory framework as a driver of eco-innovation
Interestingly, there is no consensus on a specific definition of ‘‘regulation’’. Meanwhile,
regulation has been popularly defined as sustained and focused control exercised by a public
agency over activities that are valued by a community (Selznick, 1985). This study will adopt
this definition not because of its popularity but because it fits perfectly well within the context of
the discussions on eco-innovation. Many scholars are with the views that environmental policy
and regulations are crucial to eco-innovation as they may force firms to create innovative
products or adopt practices that are less harmful to the environment. For instance, in a study
carried out on the United States, Japan and Germany using patent data, it was found out that
innovation decisions of companies were mainly driven by national regulation, not by regulation
abroad (Popp, 2006). In the same light, in the case of the Spanish pulp and paper industry,
9
studies showed that it was regulation pressure and corporate image that drove firms to adopt
cleaner technology (Del Rio Gonzalez, 2005). Also in Nigeria, the paper and pulp industry has
reported that national regulations such as guidelines and standards for the mitigation and control
of pollution and environmental impact assessment, audit, monitoring and compliance, effluent
treatment plants for liquid waste are very crucial for adoption of eco-innovation in the production
process (Adelegan et al., 2010). In the meantime, there are opposing views regarding the role of
environmental regulation on eco-innovation. There are scholars with opinions that the costs
incurred by a firm as a result of strict environmental regulation reduce its competitiveness and
productivity (Palmer et al., 1995). This is based on the fact that in a bid to meet up with the
requirement of the new environmental regulations, firms redistribute their exiting labour and
capital resources and consequently resources may be diverted away from productive investments
(Doran and Ryan, 2012). As a result of this, the capability of firms to be competitive at the
national and international levels may be hampered. The authors of the supporting propositions
firmly believe that appropriately designed environmental regulations have the ability to promote
environmentally friendly innovation and in the process create a ‘‘win-win’’ opportunities which
result in increased productivity and a greener environment (Porter and van de Linde 1995a). It is
unclear however how these situations will play out within the context of developing countries
such as Nigeria with different low level of technological capabilities and complex political
structures. This line of thought leads this study to pose the following hypothesis to be tested:
H1: One of the main drivers of eco-innovation is as a result of firm’s compliance with
environmental policy.
2.2 Demand-pull factors as drivers of eco-innovation
Demand-pull elements in eco-innovation have usually been overlooked (Kesidou and Demirel,
2012) as it is commonly assumed that that market forces alone are insufficient to provide
innovation incentives. Meanwhile, many consumers are usually not willing to pay for
environmental innovations (Rennings, 2000) because many of the eco-innovative products are
still very costly (Rehfeld et al., 2007). Also, Taylor et al. (2006) have asserted that demand-pull
factors are more likely to be more applicable within the context of adoption and the diffusion of
eco-innovations. In the end, it seems as if demand-pull factors concern more about the adoption
10
and diffusion stages of eco-innovation activities where emphases are placed on the role of
government on regulating the production of environmental innovations so as to increase the
customer awareness and subsequently promote adoption and usage of eco-innovative products.
Meanwhile, new studies are now showing that demand-pull factors are imperative in promoting
eco-innovations (Kesidou and Demirel, 2012; Horbach, 2008; Wagner, 2007). There are scholars
who have shown that demand side factors are important drivers of eco-innovations most
especially in the area of environmental product innovations (Cleff and Rennings, 1999). Green
et al. (1994) have also found that firms launch green products as a strategy to increase market
share. Some authors have also tried to identify and investigate the effects of incentives
attributable to environmental pressure from customers and the public (Horbach, 2008; Popp et
al., 2006; Florida, 1996). It has also been highlighted that demand-pull factors are usually
motivated or reinforced by environmental regulations and standard such as taxes and subsidies
which might affect the intrinsic and external motivations of customers (Belin et al., 2011). There
are also studies which have shown that willingness to pay for environmentally-benign products
spurs firms to promote eco-innovations. For instance, Guagnano (2001) highlighted in a study
that over 80% of customers were willing to pay more for green household products and this
singular act could stimulate eco-innovation among manufacturing firms. The result of this study
has also been validated in Canada, France, Germany, Italy, Japan, Spain, the United Kingdom
and the United State where customers are willing to pay 5 to 10% more for green products
(Manget et al., 2009). Studies have also shown that market demand factors are responsible for
reasons to start eco-innovation, although results on the level of association of investment
committed and eco-innovation are mixed (Kesidou and Demirel, 2012).
Furthermore, there has been an increasing trend in the role played by the changing local
consumption patterns in many African countries most especially the emerging economies such as
Nigeria. This new consumption pattern could have a lot of implications for eco-innovation. In the
past, environmental awareness about the impact of consumption was common among the well-
educated and rich consumers in the developed countries. In recent time however, many of the
consumers in the emerging economies are becoming aware of the level of impact of the goods
and services they consume (Guarin and Knorringa, 2012). In view of these issues raised above, it
11
goes to show that firms must necessarily improve the quality of its goods and services in order to
be able to reduce the environmental impact of such goods and services. This issue is of
paramount importance for many firms in the developing countries such as Nigeria where
incremental innovation predominates because of inadequate technological capabilities. In the
meantime, the empirical evidence to corroborate these assumptions are extremely limited and as
such the study proposes that:
H2a: Improvement in the quality of goods and services is significantly related to propensity
to eco-innovate
2.2.1 Energy cost savings as one of the main effects of eco-innovation
Another critical driver of eco-innovation has been identified as energy cost-savings. This is
usually contextualized through a better use of energy and raw materials (Rennings, 2000; Green
et al., 1994). Eco-process innovations bring about change in products and services which reduces
negative externalities on environment when compared with other similar production process
alternatives (Rennings, 2000). These processes are usually internal to the firm as well as the
technological capabilities to drive them. Triguero et al. (2013) have claimed that eco-process
innovations and recycling are facilitators of cost saving within an enterprise. Porter & Linde
(1995b) has also reported that cost savings while reducing resource inefficiency has the ability to
initiate eco-innovation. They based this on the assumption that when productivity is increased by
monitoring, better resource utilization, waste minimization, there is high probability for firms to
develop eco-innovation. However, there are mixed results with regard to the influence of cost
savings on eco-innovation. For instance, Horbach et al. (2012), Kesidou and Demirel (2012),
Belin et al. (2011), Demirel and Kesidou (2011) and Horbach (2008) found positive and
statistically significant effects of cost savings on eco-innovation while in Rave et al. (2011) it
was negative and statistically relevant. Meanwhile, it was not statistically significant in studies
conducted by Triguero et al. (2013) and Cleff and Rennings (1999). However, within the context
of the case study where energy poverty is a big challenge to the manufacturing sector, this study
argues that both high energy and material prices can be incentives to eco-innovate. At the same
time quite a number of the firms in the manufacturing sector in Nigeria are energy-intensive
ranging from high to moderate (see table 1). Based on this, we test the following hypothesis:
12
H2b: Cost savings due to efficiency in material and energy use are one of the main effects of
eco-innovation activities.
Table 1: Firm’s classification based on energy consumption intensity Energy Intensity Manufacturing sub-sector No of Firms Low energy intensity Furniture 34
Machinery, equipment and vehicles 26 Rubber and plastics products 18 Publishing, reproduction of recorded media 37
Moderate energy intensity Leather tanning and dressing etc. 14 Textiles and wearing apparel 26 Food and beverages 96 Wood and paper products etc. 25
High energy intensity Chemicals and chemical products 62 Fabricated metal etc. 31 Non-metallic mineral products 37 Basic metals and recycling 20
Based on classification by UNIDO (2010)
2.3 Technology-push factors as drivers of eco-innovation
Empirical evidence has shown that under the technology-push factors, the level of technological
capabilities, which are the accumulation of human capital (e.g. trained managers and employees)
and knowledge stocks acquired through research and development (R&D) activities are essential
for the development and diffusion of eco-innovation (Johnstone et al., 2012; Popp et al., 2011b;
Loschel, 2002). Other capabilities that could further induce eco-innovation include managerial
and relational capabilities (Sáez-Martínez et al., 2014). Scholars from the field of resource-based
perspectives, hold the view that “green capabilities” are important internal factors (Hart, 1995;
Kammerer, 2009). Triguero et al. (2013) has also found out that technological and managerial
capabilities enhance the ability to develop eco-innovative products as well as improve the
technical knowledge obtained from external sources (suppliers, independent users, universities,
joint-ventures and affiliate firms). According to them, firms’ assets such as skills, knowledge,
and links with other firms are crucial in the development of process innovation.
13
Many authors have also talked about the interaction of R&D efforts and external networking as
important factors that could enhance propensity of firms to innovate (Cohen and Levinthal
1989). They based this on the assumption that when a firm engages in R&D, its level of
absorptive capacity increases giving the firm the capacity to recognise and assimilate appropriate
external knowledge to introduce new products or processes. In other words, existence of an in-
house R&D capacity is required by firms so as to be able to internalize external knowledge.
Therefore, a necessary condition for eco-innovation could be the interaction of R&D efforts and
networking with external agents such as customers, suppliers, competitors and public research
bodies (De Marchi, 2012). However, there are other studies which claim that R&D is less
important to eco-innovation adoption when compared with foreign-ownership and collaboration
strategies (Cainelli et al. (2011). In the same light, Cuerva et al. (2014) suggested that even
though R&D and human resources promote mainstream innovation, the case is not the same for
eco-innovation. Based on these mixed results, we test whether engagement in R&D in slowly
industrializing nation with fragmented national innovation system like Nigeria would engender
eco-innovation in the manufacturing sector. The hypothesis is set up as follows:
H3a: Existence of in-house R&D is an important element of eco-innovation
2.3.1 Knowledge dynamics and sources of eco-innovation
Knowledge is one of the basic ingredients for innovative activities which are often specific to
sectors and firms (Malerba and Orsenigo, 1996, 1997). Subjects of discussion around sources of
information and knowledge bases used in eco-innovative activities are not examined in detail in
the literature (Ghisetti et al., 2014; Horbach et al., 2013; Rennings and Rammer, 2009) with one
exception by De Marchi and Grandinetti (2013). Meanwhile, Rennings and Rammer (2009) in a
study of German firms have found out that knowledge inputs for innovation activities in the
areas of energy and resource efficiency come from varied sources. They highlighted that German
firms interacted with actors such as the suppliers, competitors as well as universities and public
research institutes with more emphasis on the external sources of information, but that they also
rely more strongly on internal sources. The implication of their study suggests that eco-
innovation may draw from external knowledge and competences outside the core competences of
the firms (Teece et al., 1997). In the studies of Ghisetti et al. (2014), the finding revealed that
14
knowledge sourcing has varied impacts on the firm’s propensity to introduce eco-innovation and
on the different portfolios of eco-innovation. For instance, while extensive interactions many be
useful to the firm, comprehensive externally acquired knowledge can become difficult to
internalize. Meanwhile, according to the results of Horbach et al. (2013) eco-innovative
activities require more external sources of knowledge and information than mainstream
innovations. In addition to this, they asserted that eco-innovation have propensity to search and
use more knowledge and information than the mainstream innovation. They also concluded that
internal R&D is not the most important source of innovation (Horbach et al., 2013). For some of
the reasons raised above, this study will investigate the impact of knowledge sources on eco-
innovation. Following from above, this study puts forward the following proposition:
H3b: Propensity to eco-innovate depends on acquisition of external knowledge
2.3.2 Networking strategy and eco-innovation
Another factor that is relevant to eco-innovation is how wide a particular firm is willing to search
for knowledge by collaborating with different partners in the implementation of innovation. Eco-
innovation is known for its technicality and high risk profile (Teece, 1986). Based on this fact,
eco-innovative firms do collaborate in the areas of technological, marketing and organizational
issues (De Marchi, 2012) as well as modifications in the raw materials used or management of
the pollutants. This idea of networking strategy becomes important because the relationship
between information flows and cooperation/collaboration/networking among the many partners
in the innovation process have the capacity to motivate eco-innovation. For example,
collaborations with knowledge institutions, competitors, users and access to technology support
services have been found out to stimulate firms to carry out eco-innovation (Triguero, 2013).
There are few literature that have discussed this aspect of innovation process with regard to eco-
innovative firms despite the fact that personal and strong ties with external partners are important
for successful introduction of eco-innovations (Huggins et al., 2010). In this light, inadequate
appropriate knowledge sources makes their search, usage and management crucial for the
viability of learning-by-interacting (Ghisetti et al., 2014).
H3c: Appropriate networking strategies promotes eco-innovation
15
2.4 Firm’s specific factors and eco-innovation
There are indications that globalisation and the integration of manufacturing firms from
developing countries into global value chains has the potential to motivate demand for eco-
innovations. This is based on the assumption that many of the firms in the developing countries
today do not operate alone. They are ingrained in networks and long term business collaborations
with many lead firms in the developed countries (Brandi, 2012). These often lead firms to
structure their value chain so as to respond to consumer demand or to increase their market share
by a way of capturing ‘green’ niche market in the developed or emerging markets (organic food,
herbal medicine, energy saving electronics). As a result of these business interests, many firms
from developing countries comply with basic standard on issues such as food security, carbon
footprint, food safety etc. on the international market. Issues relating to global value chains such
as these are known to promote environmental protection that can in turn stimulate eco-innovation
within the production systems in developing countries (Brandi, 2012). There are also instances
where stiff competition in home markets as a result of emergence of international competitors
push local firms to look for opportunities in the international markets (Zahra and George, 2002).
Considering the fact that many of the firms at the local markets are small, they tend to cooperate
with international partners so as to increase their chances of surviving in the highly competitive
markets (Brouthers, 2002). Empirical evidence has also suggested that firms with higher level of
internationalisation have propensity to adopt eco-innovation more intensively (Cainelli et al.,
2010). These empirical evidences led us to propose the following hypothesis:
H4a: International openness of the global market pushes local firms to introduce eco-innovations
2.4.1 Innovation persistence and eco-innovation
Studies have shown that many firms that have introduced one or more categories of innovation in
the past are not only probably going to show more propensity to innovate more in the future but
also likely to engage in innovation activities persistently (Frenz and Ietto-Gillies, 2007). This
concept is also closely related to the idea of Nelson and Winter (1982) where they asserted that
“success breeds success”. The same concept has also been echoed by Baumol (2002) which
highlighted that firms with substantial appropriate technological capabilities have higher
propensity to innovate. This process has been referred to as “innovation breeds innovation”. The
16
authors are of the opinions that successful previous innovations are prerequisites for investment
into future R&D and persistent innovation. This idea could also be traced back to Rosenberg
(1976) where the author opined that the innovative capabilities developed by firms as a result of
their investments in R&D do not necessarily depreciate rapidly over time. Rather this formal or
informal knowledge may be used consistently to develop several other innovations. In essence,
these empirical results show that firms that have been innovative in the past have higher
probability of being innovative in the present or future (Horbach, 2008). This proposition is
working on the assumption that innovation leaders are those with dynamic capability to develop
and implement eco-innovation. Such firms have high level of absorptive capacities which allows
them to recognize innovation opportunity as a result of their proactive investment policy and
enhanced innovativeness (Chassagnon and Haned, 2015; Horbach, 2008). As important as this
concept is for policy, very few studies have tested its validity in eco-innovation studies. We
contribute to this debate by proposing the following hypothesis:
H4b: Firms that persistently record high number of innovations are more likely to
introduce eco-innovation
3 Methods
The study adapted and expanded the frameworks developed by Horbach et al. (2012), Di Marchi
(2012), Horbach (2008) and Rennings (2000) (See figure 1). In order to be able to achieve the
objective of this study, the drivers of eco-innovation are categorized into four groups:
technology-push, demand-pull, regulatory policy determinant and firm-specific factors. These
categories of variables are stated in table 2. This categorization of factors set the background for
analytical discussions. It also describe how these factors interact with the environmental,
political and institutional structures so as to suggest appropriate eco-innovation policies that is
capable of successfully guiding transition to green economy in the manufacturing sector of
Nigeria.
17
Figure 1: Conceptual Framework for the Determinant of Eco-innovation
3.1 Instrument and Data
For the purpose of this study, the Nigerian innovation survey for the 2005-2007 data was
obtained. The survey implementation and procedures were based on the “Guidelines for
Collecting and Interpreting Innovation Data” jointly developed by the OECD, and the Eurostat
popularly referred to as Oslo Manual (OECD, 2005). The innovation survey used a structured
questionnaire to obtain information from the manufacturing firms in the country. The survey
took place between November, 2009 and July, 2010. The questionnaire that was later developed
had 13 sections. The sampling of data used a multistage systematic random sampling technique.
Technology-push Factors
In-house software development
Acquisition of external knowledge
Customers
In-House R&D
Training
Regulatory Policy Determinant
Regulatory framework
Demand-pull Factors
Satisfy customer
Increase quality of goods and services
Firm’s specific factors
Foreign competition
Innovation persistence
Sector
Eco-innovation
Energy cost savings
Networking Strategies
Public Research Institutes
Competitors
18
Sectoral classification of economic activities was based on the Industrial Classification of all
Economic Activities (ISIC revision 3.1). The enterprise with activities falling between divisions
15 – 37 were classified as manufacturing firms. Based on the Memorandum of Understanding
between National Centre for Technology (an agency of the government with mandate to carry
out the survey) and the National Bureau of Statistics (NBS), the database for the firms was
obtained from the NBS business directory while the remaining samples were gathered from the
Nigerian Stock Market trade database. The NBS Business Directory had more than 10,000 firms
while the Stock Market trade list had close to 200 firms. Based on their sheer contribution and
impact on the economy, a census of all enterprises on the Stock Market trade list belonging to the
manufacturing sector was used. In the case of the NBS Business Directory, a proportional
probability sampling (PPS) technique with a threshold of a minimum of 10 employees was used
to select firms. Stratification of the firms was based on sector and employee size. The PPS
approach was also used for the selection of firms from each sub-sector of interest. For instance,
where there are fewer firms in a particular sector, a higher proportion of such firms was selected.
A case in point is that of the cement manufacturing industry which had only 8 firms. In this
particular case, all the firms were selected in the sample for the survey. The samples selected
from the NBS Business Directory and that of the Stock Market trade list were combined to
obtain a total of 1000 manufacturing firms after extensive cleaning of the database had taken
place.
In order to increase the response rate, the physical addresses of the firms were confirmed and the
CEO/MD in each of the 1000 firms was chosen as the contact person. All the firms with no
traceable addresses or that are insolvent were removed from the sampled database and replaced
with closely matched firms in terms of sector of operation and location. This exercise was carried
out so as to maintain the sample size of 1000 firms. Another method adopted to improve
response rate was the follow-up exercise carried out by the field officers. Some of the measures
included contacting firms prior to the conduct of the survey and attaching a cover letter from the
Minister of Science and Technology and the Statistician- General of the National Bureau of
Statistics with the survey instrument. Other actions taken included telephone calls, re-visits etc.
The questionnaire was administered by field officers using face-to-face approach. At the end of
the survey administration, a total number of 574 completed questionnaires were retrieved from
19
the manufacturing sector. But the number reduced to 521 firms from the manufacturing sector
after final data cleaning representing a response rate of 48.5%. Out of the 521 firms, only 82.5%
of the (430 firms) firms recorded at least one of the four categories of innovation (product,
process, market and organization). The rest, 17.5% (91 firms) did not innovate. However, since
we are dealing with only innovative firms, the rest of the analysis is based on 430 firms. The
operationalization of the variables and descriptive analysis of the variables are shown in table 1.
Table 2: Variables used in the study Variable Name Variable
Description N MIN MAX MEDIAN MEAN SD
Dependent Variable
Eco-innovation 1 realization of innovations with high or medium environmental effects, 0 other innovations
430 0 1 1 0.58 0.49
Regulatory Policy Determinant
Regulatory framework 1 Met regulatory requirements, 0 otherwise (1 highly relevant and medium, 0 other)
430 0 1 1 0.58 0.49
Market pull factors
Satisfy customer demand
1 Satisfy customer demand , 0 otherwise (1 highly relevant and medium, 0 other)
350 0 1 1 0.85 0.36
Energy Cost Savings
1 Reduce materials and energy per unit output, 0 otherwise (1 highly relevant and medium, 0 other)
430 0 1 0.50 0.50 0.50
Increase quality of goods and services
1 Improved quality of goods and services, 0 otherwise (1
429 0 1 1 0.68 0.49
20
highly relevant and medium, 0 other)
Technology push factors
In-House R&D
1 During 2005-2007 enterprise engaged in intramural (in-house) , 0 otherwise
430 0 1 0 0.41 0.49
Training
1 During 2005-2007 enterprise engaged in training, 0 otherwise
430 0 1 1 0.64 0.48
In-house software development
1 During 2005-2007 enterprise developed software in-house, 0 otherwise
430 0 1 0 0.23 0.42
Acquisition of external knowledge
1 During 2005-2007 enterprise acquired external knowledge, 0 otherwise
429 0 1 0 0.30 0.46
Customers as sources of knowledge
Customers or clients (1 highly relevant and medium, 0 other)
430 0 1 1 0.65 0.48
Competitors as sources of knowledge
Competitors, other firms (1 highly relevant and medium, 0 other)
429 0 1 1 0.55 0.50
Public Research Institutes as sources of knowledge
Public Research institutes (1 highly relevant and medium, 0 other)
430 0 1 0 0.26 0.44
Networking strategies
Constructed measure of whether or not the firm engages in joint activity with any of several actors. 1 if this is so and 0 otherwise
308 0 1 0 0.21 0.40
Firm’s specific factors
21
Home competitor
Market position threatened by entry of new competitors (1 highly relevant, 0 other)
346 0 1 1 0.53 0.50
Innovation leadership Number of innovations enterprise implemented during 2005-2007 (1 Highly innovative ≥3, 0 Less innovative ≤2)
430 0 1 1 0.60 0.49
Control variables
Firm Size Log of firm’s size in 2007
430 2.30 8.15 4.32 4.42 1.28
Internationalization 1 Enterprise is part of a group; 0 otherwise
430 0 1 0 0.23 0.42
Sector Manufacturing sector classified by the 2-digit ISIC (categorized by energy intensity see table 1)
3.2 Estimation techniques
Descriptive analysis was used to discuss the firm’s profile with regard to cluster of factors such
as the regulatory policy determinant, demand-pull factor, technology-push factors, firm’s
specific factor and other variables such as firm size, affiliations to a business group or parent
company and sector of the firms. The dependent variable used in this study is based on the
outcome of the innovations introduced by the firm with regard to a particular variable “reduced
environmental impacts or improved health and safety”. Firms are allowed to choose four options,
reporting if the outcome of innovation was non-existent, low, medium or high. The dependent
variable, Eco-innovation, takes the value 1 if, in the period 2005–2007, the enterprise reported
high or medium importance on the outcome of innovation and 0 otherwise. The drivers of eco-
innovation were analysed using binary logistic regression. It examines the relationship between
multiple explanatory variables and a dichotomous dependent variable, and estimates the
22
probability of occurrence of an event by fitting data to a logistic curve (Park, 2013). Description
of the independent variables is shown in table 2. In order to find empirical evidence to the
theoretical propositions on the determinants of eco-innovations, we estimated three models: first,
we carried out a discrete choice model detecting the specificities of eco-innovations with regard
to energy intensive sectors. Second, we introduced sector of the manufacturing firms in order to
establish if sector of the firms has any significant impact on eco-innovation drivers. Third, the
study attempts to differentiate between different impacts areas both for product and process
related eco-innovations so as to find out the relevance of these impacts to the overall contribution
of the reduction of firm’s carbon footprints (Triguero et al., 2013). This line of thought rests on
the assumption that the ability of the firms to develop and internalise eco-innovations is a
function of their capability to combine process innovations and product innovations with
environmental strategies (Oltra and Saint Jean, 2005). We limited our analysis to only the
innovative manufacturing firms so as to understand the specificity of eco-innovation drivers as
well as limit the effect of selection bias on the analysis. Furthermore, some of these analyses will
also allow us to be able to compare with other studies in the literature that had used similar
methods and data (Horbach et al., 2012; Horbach, 2008; Wagner, 2008; Rehfeld et al., 2007).
3.3 Control variables
In order to ascertain the main determinants of the technological environment that may influence
innovation activities of eco-innovative firms, we controlled the study for firm size and whether a
firm is part of a group of companies or not. This is based on the fact that some literature on eco-
innovation have revealed that many small and medium-sized enterprises find it difficult to eco-
innovate as a result of the complexity of eco-innovation as well as the extent of investment
required to transit to clean technologies (Borghesi et al., 2012; Borghesi et al. 2015; Kesidou and
Demirel, 2012; Russo and Fouts, 1997; Noci and Verganti, 1999; King and Lenox, 2000;
Hemmelskamp, 1999). The control variable Firm_size was constructed as the log of employee
size in 2007. We also controlled undue advantage that might come to firms with parent
companies with a lot of resources and knowledge by defining a binary variable
internationalization, equal to 1 if firm is a part of a group of another company and 0 otherwise
(see table 2). At another level of analysis, we also controlled for sectoral differences so as to take
into consideration the context of specific industry within the manufacturing sector. This becomes
23
important because understanding inter-industry differences brings into the open the specific
characteristics of innovative processes with regard to the knowledge sources and learning
processes that motivate such processes (Rennings et al., 2006; Wagner, 2008; Oltra and Saint
Jean, 2008, Dosi, 1982). More importantly, Ashford et al. (1985) submitted that even though
stringency of regulation is very important in stimulating eco-innovative behaviour, disparity in
the level of regulation levied on different sectors and different time period with which to comply
with the directives are equally crucial.
4 Analysis of Data and Discussion of Results
4.1 Descriptive Analysis
The analysis in the table shows the background information on both the eco-innovative and non-
eco-innovative firms. A cursory look at the descriptive analysis reveals that majority of the eco-
innovative firms are big (del Rio 2005; 2009). For instance, according to the employee size and
whether firms are part of a group of not, over 65% are large in terms of the firm size while 69%
of the firms belong to group of companies. It was interesting to find out that many of the eco-
innovative firms (87.1%) are likely to comply with government regulations when compared with
the non-eco-innovators (12.9%). Studies carried out by del Rio (2005; 2009) have also found
similar trends among eco-innovative firms. Further comparative analysis of the internal
characteristics of the two categories of firms shows that they are heterogeneous. The issue of
heterogeneity of eco-innovative and non-eco-innovative firms had earlier been noted by De
Marchi and Grandinetti (2013), Brunnermeier and Cohen (2003) and Horbach (2008). For
instance, with regards to firm’s innovation persistence, measured in terms of number of
innovation introduced (product, process, marketing and organizational) during 2005-2007. Our
results showed that eco-innovative firms are more innovative (76.8% vs 23.2%). This may not
come as a surprise because the ability of firms to think beyond mainstream innovation and
engage in eco-innovation activities could in itself be innovative. Looking at these results, it is
not surprising therefore that analysis in table 3 shows that eco-innovative firms had engaged
more in in-house R&D (75.3%), in-house software development (65.3%), acquisition of external
knowledge (66.9%) and staff training (72.1%). These activities are crucial to the growth and
development of firms because R&D enhances technological capabilities (Horbach, 2008;
Rehfeld et al., 2007). However, these results should be interpreted carefully considering the fact
24
that very few firm engage in R&D (see table 3). For instance, over 70% of the eco-innovative
firms only conduct in-house R&D occasionally. In general, this descriptive analysis suggests that
big green firms may be more innovative than the non-green firms. The reason for this could be
attributed to the technicality required and extra costs often incurred in the implementation of
eco-innovation and since the big firms are usually exposed to high stock of financial, human and
technological resources they are more likely to successfully introduce eco-innovation (De
Marchi and Grandinetti 2012; Teece 1986). Another reason that could explain this is that in
many instances, smaller firms are not aware of the market potential of eco-innovation or its cost
saving attributes (Brammer et al. 2012). We also noticed that majority of the eco-innovators are
found within the high energy-intensive sub-sectors. For instance, 71.0%, 61.3% and 64.9% of the
eco-innovators are found in the energy-intensive sub-sectors such as chemicals and chemical
products, fabricated metal etc. and non-metallic mineral products. This result probably explains
why most of the eco-innovative firms have engaged in cost-saving strategies to lower their
expenses on energy supply. According to the result in table 3, over 87% of the eco-innovative
firms engage in cost-saving strategies to reduce material use and energy. Previous studies have
earlier noted that cost savings enhances adoption of eco-innovation (Pereira & Vence, 2012) so
as to reduce energy and raw material use (Horbach et al., 2012).
25
Table 3: Comparative analysis of eco-innovative and non-eco-innovative firms
Variable Total No. of Firms
1EIF %
2NEIF %
Regulatory policy determinant Regulatory framework 249 87.1 12.9 Demand-pull factors Satisfy customer demand 296 70.9 29.1
Energy Cost Savings 215 87.4 12.6
Increase quality of goods and services 290 76.2 23.8
Technology-push factors In-House R&D 178 75.3 24.7
Staff training 276 72.1 27.9
In-house software development 101 65.3 34.7
Acquisition of external knowledge 130 66.9 33.1
Customers 279 73.8 26.2
Competitors 235 72.3 27.7
Public Research Institutes 110 85.5 14.5
Networking strategies 63 79.4 20.6
Firm’s specific factors Home competitor 184 75.0 25.0 Innovation persistence Highly innovative 259 76.8 23.2
Less innovative 171 29.8 70.2
Firm size Small firms 155 45.8 54.2 Big firms 275 65.1 34.9
Internationalization 100 69.0 31.0
Sector Furniture 34 55.9 44.1 Machinery, equipment and vehicles 26 61.5 38.5 Rubber and plastics products 18 72.2 27.8
Publishing, reproduction of recorded media 37 37.8 62.2
Leather tanning and dressing etc. 14 57.1 42.9 Textiles and wearing apparel 26 38.5 61.5 Food and beverages 96 59.4 40.6 Wood and paper products etc. 25 48.0 52.0 Chemicals and chemical products 62 71.0 29.0 Fabricated metal etc. 31 61.3 38.7 Non-metallic mineral products 37 64.9 35.1 Basic metals and recycling 20 50.0 50.0 1 Eco-innovative firms; 2Non-eco-innovative firms
26
4.2 Econometric analysis of the drivers of eco-innovation
4.2.1 Regulatory Policy Determinant
Results emerging from the econometric analysis in table 4 give a very strong credence to the
influence of regulatory environment to eco-innovation. The result shows a positive effect of
regulatory environment on eco-innovation as shown by the coefficient of regression (B). The
result implies that those firms who responded positively to the regulation are 18 times more
likely to be eco-innovative than those who did not abide by the regulation (see table 4). This is
shown by the odd ratio in table 4 (Exp [B]). This finding is in affirmation with other similar
studies (Borghesi et al., 2015; Demirel and Kesidou, 2011; Horbach 2008; 2010; Frondel et al.
2007; Brunnermeier and Cohen 2003; Porter and van der Linde 1995b). More importantly, this
result validates hypothesis H1 which states that one of the main drivers of eco-innovation is as a
result of firm’s compliance with environmental policy. In other words, this finding has shown
that meeting regulatory requirement is significantly more important for eco-innovations than for
non-eco-innovative firms.
4.2.2 Demand-pull factors
Introduction of eco-innovation has the potential to improve productivity if the production process
reduces inputs and saves cost (Kesidou and Demirel, 2012; Demirel and Kesidou, 2011; Frondel
et al. 2007). The result of analysis in table 4 indicated that eco-innovation has the propensity to
save cost especially when the introduction of the product or process results in the reduction of
material and energy use. As a matter of fact, those firms with the habit of saving energy cost are
5.6 times likely to be more eco-innovative than the firms who do not care about energy cost
savings (see table 4). Similar studies (Rave et al. 2011; Horbach 2008; Frondel et al. 2007) have
affirmed that cost savings could motivate firms to introduce eco-innovations. Based on this fact,
hypothesis H2b that states that cost savings due to efficiency in material and energy use are one
of the main effects of eco-innovation activities is validated. The explanation for this could be that
the manufacturing firms in the country would like to have any product or participate in any
process that will help save energy in the production process as a result of inadequate access to
energy in the country. It has been earlier noted that majority of the firms in the country power
their operations on diesel-powered plants (Eleri et al. 2011). In the same light, analysis of
whether improvement in goods and services is significantly related to propensity to eco-innovate
27
or not was also carried out. The result showed that there is evidence to believe that firms that
focus on improving the quality of their goods and services also have tendency to eco-innovate.
More also, the result in table 3 shows that firms that are characterised with improved quality of
goods are 3.2 times more likely to be eco-innovative than those other firms that pay no attention
to improvement in goods and services. Going by this finding, the hypothesis H2a which state that
improvement in the quality of goods and services is significantly related to propensity to eco-
innovate is validated.
4.2.3 Technology-push factors
In general, innovation studies have indicated that the internal R&D efforts and training of
personnel in innovation management are crucial to the development of innovation as they
increase the effectiveness of available information and knowledge. R&D engagement also
increases “absorptive capacity” of firms as it helps to generate new knowledge which could help
engender innovations (Cohen and Levinthal, 1989). Interestingly, many of the technology-push
factors like engagement in in-house R&D, staff training and acquisition of external knowledge in
this study do not seem to be important to propensity to eco-innovative (see table 4). These
factors do not have any significant effects on propensity to eco-innovate among the
manufacturing firms. Based on these results, H3a which states that existence of in-house R&D is
an important element of eco-innovation is nullified. The reason for this could be that factors that
are external to the firms are more important to eco-innovation more than those that are internal to
them. Similar results have been found within the low- and-medium technology Spanish
manufacturing firms (Bagchi-Sen 2001; MacPherson and Ziolkowski 2005). The reasons that
have been adduced for this is that such firms usually take advantage of other innovation activities
such as design, the use of advanced machinery, technological consultants, R&D outsourcing,
cooperative agreements, or seeking the services of qualified researchers (Cockburn and
Henderson 1998; Veugelers and Cassiman 1999). On the same point, studies such as that of
Hemmelskamp (1999) have found out that eco-innovative firms often compensate for low R&D
intensity with external source of knowledge. Based on the result coming from this study, one
might argue that with regard to the introduction of eco-innovation, substitution effect is what is
at play among the manufacturing firms in Nigeria. To buttress this point, it is interesting to note
that consultation with public research institutes by the firms came up as important sources of
28
knowledge used by the firms to complement in-house R&D engagement. This fact again
reinforces substitution effect as eco-innovation strategies by the firms. This is in line with the
transaction cost theory that argues that the procurement of external R&D may substitute for
internal R&D investment (Pisano 1990; Williamson 1985). Another way of looking at this result
is that firms engage in cooperation with knowledge institutions such as research institute so as to
capture a new market and develop highly technical innovation (Tether and Tajar 2008). This
finding is also in line with Di Marchi (2012) as well as Cainelli et al. (2011) where they asserted
that presence of knowledge transfer mechanism from knowledge institutions is an important
factor in the introduction of eco-innovation. Critical analysis of the results showed that firm that
consult research institutes as sources of eco-innovation are likely to be 3.1 times more eco-
innovative than those who did not use these source of information for innovation.
At the same time, findings such as these are characteristic of a young market typical of a sub-
sector like eco-innovative firms in the developing countries such as Nigeria where majority of
the innovations are usually incremental with little or no R&D component. One other aspect of
technology-push factors that has significant impact on propensity to eco-innovate is the
development of in-house software. The significant impact of this factor could be seen as an
existence of knowledge capital endowment (Horbach, 2008) of the firms. It also reveals that
adoption of eco-innovation strategies such as the development of in-house software application
promotes creation of new knowledge and capabilities (Laperche and Lefebvre, 2012).
Meanwhile, it will be worthwhile to find out the extent to which this factor enhances eco-
innovation as virtually all eco-innovation studies have failed to capture it even though it
represents veritable source of organization and managerial capabilities.
4.2.4 Firm specific factors and propensity to eco-innovate
This section explores other firm specific factors such as competitors at home markets and
innovation persistence that could impact implementation of eco-innovation at firm-level. Issues
relating to global value chains such as carbon footprint and food safety are known to promote
environmental protection that can in turn stimulate eco-innovation within firms and production
systems in developing countries (Brandi, 2012). The result of our analysis shows that local
manufacturers are negatively affected by the presence of foreign competitors in the local market.
29
Based on the finding from this study, we nullified H4a which states that international openness of
the global market pushes local firms to introduce eco-innovations. This result negates the
findings of Zahra and George (2002) where they concluded that stiff competition in home
markets as a result of emergence of international competitors push local firms to look for
opportunities in the international markets. The reason for this could be that the local firms do not
possess the technological and organizational capability to structure their value chain processes so
as to respond to consumer demand or to increase their market share by a way of capturing
‘green’ niche market in the developed or emerging markets (organic food, herbal medicine,
energy saving electronics). However, other hypothesis (H3b) set up to test propositions of impact
of networking strategies on eco-innovation propensity is nullified as we found no significant
effect of this strategy.
This study also extends the debates on the impact of innovation leadership on eco-innovation an
area which has been largely neglected in the mainstream literature on environmental innovation.
Innovation leadership as captured in this study as innovation persistence has been defined as the
‘dynamic capability of an innovative firm to seize new innovation opportunities as a result of a
proactive investment policy and enhanced innovativeness’ (Chassagnon and Haned, 2015; pg.
196). In order to test the robustness of including innovation persistence within our own context,
we carried out analysis with or without the moderating effect of innovation persistence variable.
Result of the analysis as shown in Appendix 1 reveals that inclusion of innovation persistence
variable actually improved the model specification. This can be seen in the reduction of the -2
Log likelihood from 199.05 to 190.17. The significance of this variable is also shown by the
increase in the Nagelkerke (Pseudo) R2 that moved from 55% to 58% (see appendix 1). After
establishing the importance of this variable, we tested its impact and other drivers of eco-
innovation in table 4. We found out that innovation leaders are also eco-innovative. As a matter
of fact, the results in table 4 shows that they are 3.8 times more likely to introduce eco-
innovation than the non-green oriented firms. Chassagnon and Haned (2015) and Horbarch
(2008) have attempted to explain this by stating that innovation leaders have the capability to
positively react to the dynamics of competitive environment by absorbing and utilizing new
opportunities. This capability ultimately allows them to strike a balance between economic
performance and environmental performance in a strong selection environment such as that of
30
the green innovation (Carrillo-Hermosilla, 2010; Van der Panne, 2003). Innovation leaders are
also known to reorganize knowledge that had been used to produce past innovations to create
new ones. From the results of the analysis above, we validate H4b that states that firms that
persistently record high number of innovations are more likely to introduce eco-innovation. It is
not surprising for eco-innovation to be significantly associated with innovation leadership
considering the fact that eco-innovation is highly technical (Porter and van der Linde 1995a) and
are usually more costly than the non-eco-innovative ones (Triguero et al. 2013) as such they may
require certain competencies that are usually embedded in innovation leaders. At the same time,
some studies have shown that success of a particular innovation serves as motivation for others
as a result of accumulation of competencies and monopoly power (Raymond et. al., 2010; Peter,
2008; Baumol, 2002; Nelson and Winter, 1982).
We also examine sector-specific effects when compared with the food and beverage sector (the
reference). The results in table 4 show that sub-sectors such as furniture, publishing,
reproduction of recorded media, leather tanning and dressing and textiles and wearing apparel
are less likely to introduce eco-innovation when compared with the food and beverage sub-
sector. We noticed that a lot of the high energy intensive sub-sectors appear not to have any
effect on eco-innovation. This portends both challenges and opportunities for the national
economy. The challenges are seen in term of the carbon footprint while the sub-sectors could
also be an avenue for the government and other stakeholder to pursue an aggressive eco-
innovative strategy.
Table 4: Binary logistic regression of the drivers of eco-innovation among the manufacturing firms Variable B S.E. Exp(B)
Regulatory Policy Determinant Regulatory framework 2.76** 0.51 15.85
Market pull factors Satisfy customer demand 0.14 0.65 1.15
Energy Cost Savings
1.81** 0.45 6.09
Increase quality of goods and services
1.17* 0.59 3.22
Technology push factors In-House R&D -0.37 0.50 0.69
Staff training
-0.05 0.56 0.95
In-house software development
1.31* 0.57 3.72
31
Acquisition of external knowledge
-0.16 0.50 0.85
Customers
0.95 0.64 2.57
Competitors
-0.78 0.56 0.46
Public Research Institutes
1.08* 0.55 2.96
Networking strategies
0.36 0.56 1.44
Firm’s specific factors Home competitor -0.96* 0.46 0.38
Innovation persistence
1.33** 0.48 3.76
Control variable Firm Size 0.07 0.16 1.07
Internationalization
0.69 0.52 2.00
Sector (ref: Food and beverages) Food and beverages
Furniture
-1.86* 0.84 0.16
Machinery, equipment and vehicles
-0.41 0.96 0.66
Rubber and plastics products
0.49 1.28 1.64
Publishing, reproduction of recorded media
-1.74* 0.84 0.18
Leather tanning and dressing etc.
-2.54* 1.10 0.08
Textiles and wearing apparel
-2.18* 1.00 0.11
Wood and paper products etc.
0.75 1.06 2.12
Chemicals and chemical products
-0.39 0.75 0.68
Fabricated metal etc.
-1.72 0.89 0.18
Non-metallic mineral products
-0.23 0.80 0.79
Basic metals and recycling
-1.10 1.00 0.33
Nagelkerke (Pseudo) R2 = 0.63; Goodness of fit= χ2 =160.12**; -2 Log likelihood = 169.75; No of Obs=270 **p<0.01; * p<0.05; S.E. = Standard error
5. Drivers of eco-innovation among the manufacturing firms producing innovative products and processes
This study also moves further to find out if the same set of factors drive eco-innovation among
the manufacturing firms producing innovative products or processes. This comes from the fact
that the capability of the firms to produce eco-innovative products is a function of their
competence to combine product and process innovations with environmental goals (Oltra and
Saint Jean, 2005). In other words, there is a strong association between product and process
innovation developments (Reichstein and Salter, 2006). Study on the disaggregation of product
32
and process innovation developments such as this could provide insight into the understanding of
policies that could be used to promote either product or process eco-innovation among the
manufacturing firms (Pujari, 2006; Pujari et al., 2003). Some scholars have also suggested that
there is a difference among product and process innovation persistence (Roper and Hewitt-
Dundas, 2008). Empirical evidence for these two categories of eco-innovations is scarce.
However, some of the few evidence on the determinants of product eco-innovation suggest that
technological and managerial capability are very crucial to the development of product eco-
innovation (Horbach, 2008) as well as networking with the research agencies. In terms of process
innovation, it has been reiterated that they are internally stimulated at the firm-level. As a result
of this, technological capabilities within the firm are therefore important determinations of eco-
process innovations. Some scholars have shown that eco-process innovations that are connected
to material and energy use are positively affected by networking with knowledge institutions
such as universities and research institutes (Horbach et al., 2012). At the same time, cost-savings
with efficient use of materials and energy are also important factors for process eco-innovations
(Green et al., 1994; Rennings, 2000). Interestingly, analysis in table 5 reveals that similar factors
are at play in driving eco-innovative products or processes. For instance, both categories of eco-
innovations are influenced by regulatory environment, energy cost savings in relation to
materials and energy use, in-house software development, public research institutes and innovation
persistence. These findings are in line with argument put forward by Pavit (1984) where it was
asserted that both demand-pull and technology-push arguments could be used to explain end-of-
pipe and integrated technology eco-innovations. This result also confirms that innovative firms
often benefit from locked-in effect of success provided by ability to continuously innovating
irrespective of market externalities (Geroski et al., 1997; Nelson and Winter, 1982). However,
for product eco-innovation, local manufactures at home are threatened by the foreign competitors
in Nigeria market. The result of the analysis in table 5 shows that firms that are experiencing stiff
competition from foreign competitors in the home market are less likely to eco-innovate.
Innovation persistence also came up as an important factor for firms engaging in both product
and process eco-innovations. It has also been noted by Fontana and Moriniello (2011) that
technological leadership has a positive influence on innovation persistence in product innovation.
However, our result shows that those introducing product innovation are 9 times likely to eco-
33
innovate when compared with those implementing process innovations where the firms are 4
times likely to do the same.
Table 5: Binary logistic regression of the drivers of eco-innovation among the manufacturing firms producing innovative products and processes 1Product 2Process
Variable B S.E. Exp(B) B S.E. Exp(B)
Regulatory Policy Determinant Regulatory framework
3.35** 0.74 28.59 2.49** 0.54 12.01
Market pull factors Satisfy customer demand
-0.16 1.00 0.85 -0.21 0.69 0.81
Energy Cost Savings
2.74** 0.67 15.47 1.70** 0.46 5.50
Increase quality of goods and services
0.58 0.82 1.79 0.87 0.62 2.38
Technology push factors In-House R&D
1.12 0.72 3.07 -0.16 0.51 0.86
Staff training
-0.72 0.80 0.48 -0.44 0.61 0.64
In-house software development
1.55* 0.78 4.73 1.33* 0.61 3.80
Acquisition of external knowledge
0.11 0.68 1.11 -0.13 0.54 0.88
Customers
1.39 0.81 4.02 1.19 0.71 3.30
Competitors
-1.22 0.76 0.29 -0.83 0.60 0.43
Public Research Institutes
1.61* 0.77 5.02 1.10* 0.56 3.01
Networking strategies
-0.30 0.75 0.74 0.50 0.59 1.65
Firm’s specific factors Home competitor
-1.39* 0.66 0.25 -0.93 0.48 0.39
Innovation persistence
2.22** 0.83 9.18 1.57** 0.57 4.80
Control variable Firm Size
0.10 0.20 1.11 0.11 0.17 1.12
Internationalization
0.59 0.65 1.81 0.81 0.54 2.24
Sector (ref: Food and beverages) Furniture
-2.33* 1.03 0.10 -1.84* 0.84 0.16
Machinery, equipment and vehicles
-0.38 1.50 0.69 -0.40 0.96 0.67
Rubber and plastics products
0.32 1.40 1.37 0.29 1.30 1.34
Publishing, reproduction of recorded media
-2.38* 1.08 0.09 -1.67* 0.88 0.19
Leather tanning and dressing etc.
-3.72* 1.52 0.02 -2.09* 1.15 0.12
Textiles and wearing apparel
-4.18* 1.36 0.02 -2.28* 1.01 0.10
Wood and paper products etc.
0.27 1.26 1.31 0.70 1.10 2.02
34
Chemicals and chemical products
0.98 1.16 2.67 -0.09 0.83 0.92
Fabricated metal etc
-0.68 1.34 0.50 -1.88* 0.90 0.15
Non-metallic mineral products
0.95 1.13 2.59 -0.18 0.91 0.84
Basic metals and recycling
-1.20 1.35 0.30 -1.05 1.00 0.35
1Nagelkerke (Pseudo) R2 = 0.68; Goodness of fit= χ2 =126.16**; -2 Log likelihood = 103.85; No of Obs=205 2Nagelkerke (Pseudo) R2 = 0.59; Goodness of fit= χ2 =126.11**; -2 Log likelihood = 155.57; No of Obs=239
**p<0.01; * p<0.05; S.E. = Standard error
5 Conclusions and Policy Recommendations
This paper examined the drivers of eco-innovation in the manufacturing sector of Nigeria. The
study was carried out with the broad objective of complementing the scarce knowledge base of
eco-innovation and policies in developing countries with specific focus on innovation persistence
and international openness. Specifically, the study explored the role of demand-pull, technology-
push and firm’s specific factors in stimulating eco-innovation. It also checked for the drivers of
eco-innovation when the data is disaggregated between the product and process innovations. The
study explored to what extent is innovation leadership or capability to consistently innovate
influence introduction of eco-innovation while also focusing on the impact of foreign
competition in the local market.
In the final analysis of the comparison between eco-innovative and non-eco-innovative firms,
results suggest that both the eco-innovative and non-eco-innovative firms are heterogenous in
their internal and external characteristics. There are also reasons to believe that most eco-
innovative firms are more technical, large and highly innovative. From the result of the
econometric analysis, we found strong support for the effect of environmental policy on eco-
innovation. Findings implied that by setting strict technology standards, regulations could
stimulate investments in eco-innovation. This also supports Porter Hypothesis with a lot of
implications for environmental innovation policy.
On the demand-pull factors, the findings of this study suggest that demand factors such as cost
savings and improvement in the quality of goods and services have significant impacts on the
decision of firms to invest in eco-innovation. Although, many studies have suggested that
internal R&D efforts and training of personnel in innovation management are very relevant to the
35
introduction of eco-innovation, interestingly our results suggest otherwise. However, we did find
that development of in-house software development is important for eco-innovation strategies.
We also found empirical evidence that support important role of knowledge institution such as
public research institutes to firms in introducing eco-innovation. This led us to suggest that
implementing eco-innovation requires more knowledge-based competencies than the mainstream
innovations. We also noted that innovation persistence is crucial for the introduction of eco-
innovation and that involvement of foreign competitors in the local market hampers eco-
innovation. This could be as a result of the fact that the local firms do not have sufficient
technological capability to compete favorably with the foreign firms.
Our results have policy implications for both the policy makers and the industry managers. With
regards to regulation, empirical evidence shows that eco-innovative firms respond positively to
regulatory measures. It follows therefore that, there may be the need for the policy makers to
proffer flexible polices that would engender more eco-innovation among the manufacturing
firms. Some of such policies may include introduction of soft instruments such as voluntary
commitments, eco-audits and eco-labels and renewable energy subsidies. These instruments have
the potential to positively affect eco-innovative behaviours of firms if they are properly
implemented. By a way of entrenching energy cost saving behaviours within the manufacturing
sector, managers should explore the adoption of the ISO 14000 environmental management
systems while those who are already certified should be motivated by the policy makers by
giving them tax holidays. We also noted that there are opportunities for the introduction of
energy efficient strategies in the high intensive manufacturing sector. Our findings also show that
one other relevant factors explaining eco-innovation is the existence of knowledge transfer
mechanisms and involvement in networks between the manufacturing firms and formal
knowledge institutions such as public research institute. It is imperative therefore that policy
makers should introduce initiatives that could engender more interactions among these actors in
the network.
This study is not oblivious of other factors that were not covered which could affect introduction
of eco-innovation because of the usual limitation of data from cross-sectional survey. Even
though some of the unobserved heterogeneity were controlled for, we understand that there could
36
still be some important drivers of eco-innovation such as the institutional innovation
intermediaries (Polzin et al., 2016), roles of firm’s strategic suppliers (Roscoe et al., 2016),
financial performance (Lee and Min, 2016) political economy, firm’s environmental strategies
and nature of the technology del Rio (2005) which are also very relevant to introduction of eco-
innovation. Nonetheless, this study has made a significant contribution to the drivers of eco-
innovation with specific reference to innovation persistence and international openness from
developing country perspective. Our article has brought to the fore that innovation leadership or
persistence is a veritable innovation management strategies that could help firms become a
leader in the green market. These contributions are critical for the creation and evolution of
firm's competitive advantage in the emerging green market.
Acknowledgements
The corresponding author acknowledges the School of Social Sciences, University of Kwa Zulu
Natal, South Africa for the help and support he got as a PhD candidate. The authors also thank
Rasmu Lema, Franco Malerba, Micheline Goedhuys, Jacob Rubæk Holm, Daniel Hain, Bengt-
Åke Lundvall, Abiodun Egbetokun, as well as discussants and participants at the Africalics PhD
Visiting Fellowship final presentation, Africalics Academy in Mombasa, Kenya (2015),
Globelics Academy in Tampere, Finland (2015) and Innovation and Entrepreneurship Theory
workshop, Rockslide, Denmark for valuable comments on earlier versions of this paper. The
usual disclaimer applies.
37
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Appendix 1
Table 4: Binary logistic regression of the drivers of eco-innovation among the manufacturing firms with or without innovation persistence
1Without innovation
persistence 2With innovation persistence
Variable B S.E. Exp(B) B S.E. Exp(B)
Regulatory Policy Determinant Regulatory framework
2.60** 0.42 13.42 2.56** 0.44 12.98
Market pull factors Satisfy customer demand
0.30 0.57 1.35 0.19 0.59 1.21
Energy Cost Savings
1.32** 0.38 3.74 1.43** 0.39 4.17
Increase quality of goods and services
1.12* 0.50 3.06 0.97 0.53 2.64
Technology push factors In-House R&D
-0.22 0.43 0.81 -0.33 0.45 0.72
Staff training
0.21 0.46 1.23 -0.02 0.49 0.98
In-house software development
0.70 0.49 2.02 0.86 0.51 2.36
Acquisition of external knowledge
-0.13 0.42 0.88 -0.14 0.44 0.87
Customers
1.17* 0.56 3.21 1.18* 0.57 3.25
Competitors
-1.05* 0.50 0.35 -1.10* 0.52 0.33
Public Research Institutes
1.18* 0.50 3.25 1.12* 0.50 3.05
Networking strategies
0.45 0.51 1.57 0.45 0.53 1.57
Firm’s specific factors Home competitor
-0.76 0.40 0.47 -0.78 0.41 0.46
Innovation persistence
1.26** 0.42 3.52
Control variable Firm Size
0.06 0.14 1.06 0.04 0.14 1.05
Internationalization
0.43 0.46 1.54 0.43 0.46 1.54
1Nagelkerke (Pseudo) R2 = 0.55; Goodness of fit= χ2 =132.94**; -2 Log likelihood = 199.05; No of Obs=273 2Nagelkerke (Pseudo) R2 = 0.58; Goodness of fit= χ2 =141.82**; -2 Log likelihood = 190.17; No of Obs=273
**p<0.01; * p<0.05; S.E. = Standard error