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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

http://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]

mailto:[email protected]

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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

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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-

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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

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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

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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.,

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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).

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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,

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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

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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

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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:

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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.

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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

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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

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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


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


1 During 2005-2007 enterprise developed software in-house, 0 otherwise

430 0 1 0 0.23 0.42


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).

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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


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


1.31* 0.57 3.72

31


-0.16 0.50 0.85

Customers

0.95 0.64 2.57

Competitors

-0.78 0.56 0.46


1.08* 0.55 2.96


0.36 0.56 1.44

Firm’s specific factors Home competitor -0.96* 0.46 0.38


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


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


1.55* 0.78 4.73 1.33* 0.61 3.80


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


1.61* 0.77 5.02 1.10* 0.56 3.01


-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


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


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


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


0.70 0.49 2.02 0.86 0.51 2.36


-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


1.18* 0.50 3.25 1.12* 0.50 3.05


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


1.26** 0.42 3.52

Control variable Firm Size

0.06 0.14 1.06 0.04 0.14 1.05


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

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