The antecedents of green innovation performance: A model of learning and capabilities
Gema Albort-Morant âŽ, Antonio Leal-Millán, Gabriel Cepeda-Carrión
Universidad de Sevilla, Spain
article info abstract
Article history:
Received 1 February 2016
Received in revised form 1 March 2016
Accepted 1 April 2016
Available online xxxx
Environmental management and green practices have a narrow linkage with firm innovativeness. Companies
that are pioneers in green innovation strategies might reach and sustain competitive advantages. Thus, successful
green innovation performance (GIP) helps firms to achieve greater efficiency as well as to establish and strengthen their core competences. This study focuses on the dynamic capabilities (DC) and ordinary capabilities (OC)
like antecedents of GIP, and the relationship between these constructs. Proposing a mediation model to analyze
both direct and indirect relationships, this study applies variance-based structural equation modeling through a
partial least squares to a sample of 112 firms from the Spanish automotive components’ manufacturing sector.
The results suggest that both the direct effect and indirect effect of capabilities (DC and OC) on GIP are positive
and significant, and improve the prediction of firm’s GIP. Furthermore, the structural model supports that DC
influence GIP by reconfiguring relationship-learning capabilities (a type of OC).
© 2016 Elsevier Inc. All rights reserved.
Keywords:
Dynamic capabilities
Ordinary relationship learning capabilities
Green innovation performance
Partial least square
1. Introduction
The ecofriendly impact of the human behavior is a constantly growing global concern for people, policy makers, countries, and organizations. Governments have applied corrective policies in the last years to
diminish or palliate such environmental damage (Chen, 2008). Companies are not immune to this reality. On the contrary, as every multifaceted system in search for the equilibrium that will ensure long-term
survival, companies should respond successfully to a dual adjustment
dynamic. On the one hand, to reach a clear level of market efficiency,
which involves enhancing the use of its resources and capabilities,
which always have a limit—competitive adjustment. On the other
hand, to overcome a certain degree of consistency with the society
within which the organization operates—legitimacy adjustment.
In order to subsist inside the presently stormy and hypercompetitive
scenarios, companies must foster innovativeness. To this end, companies must remain up to date of the manifold market changes, fluctuations, and tendencies that are persistently arising. This objective
involves a customer orientation, and a green orientation strategy. In
this line, the ultimate aim of developing a green product/service innovation strategy deals with enhancing the firm’s survival and performance
(Laforet, 2009).
The increasing societal demands compel companies to integrate sustainability topics into their regular activity so that companies can reach
their social, environmental, and economic goals. Two major driving
forces promote green management (Chen, 2008): (1) the international
set of norms and regulations concerning environmental protection, and
(2) the consumers’ environmental consciousness (Chen, Lai, & Wen,
2006). Whatever are the goals that lead companies to undertake
environmental management – complying with environmental
laws and regulations, becoming more competitive, gaining legitimacy,
etc. – integrating environmental sustainability issues into business
strategy and greening the innovation process are becoming a strategic
opportunity for companies (Porter & Reinhardt, 2007). Hence, following
several studies, environmental management and green practices
present a narrow linkage to firm innovativeness (Aragón-Correa,
1998; Pérez-Valls, Céspedes-Lorente, & Moreno-GarcÃa, 2015).
In this sense, companies that are pioneers on green innovation
strategies might be able to reach and sustain competitive advantages.
Thus, successful green innovation performance (GIP) helps companies
to achieve greater efficiency as well as to establish and strengthen
their core competences and to enhance their green image. Consequently, all these actions may eventually enable companies to reach superior
performance and higher profitability (Chen, 2008).
Literature on the capabilities-based view and the knowledgecreating view of the firm focuses on both ordinary capabilities (OC)
and dynamic capabilities (DC) as the most valuable antecedents that
provide sustainable competitive advantage, and on interaction as a
key component for the access, attainment and development of new
knowledge that is necessary to improve the results of innovation.
Interaction may take place within a firm and between firms and other
organizations. Firms use different networking mechanisms to access
knowledge outside their frontiers. Extensive literature discusses various
organizational features corresponding to different mechanisms that facilitate knowledge flows among different actors and enable relational
learning activities.
Journal of Business Research xxx (2016) xxx–xxx
⎠Corresponding author.
E-mail addresses: [email protected] (G. Albort-Morant), [email protected]
(A. Leal-Millán), [email protected] (G. Cepeda-Carrión).
JBR-09017; No of Pages 6
http://dx.doi.org/10.1016/j.jbusres.2016.04.052
0148-2963/© 2016 Elsevier Inc. All rights reserved.
Contents lists available at ScienceDirect
Journal of Business Research
Please cite this article as: Albort-Morant, G., et al., The antecedents of green innovation performance: A model of learning and capabilities, Journal
of Business Research (2016), http://dx.doi.org/10.1016/j.jbusres.2016.04.052
This situation is even more critical in natural-resources intensive
sectors, such as the automotive industry, which causes an important
environmental impact. For this reason, firms must consider any
measure aiming at improving those sectors’ environmental efficiency
and at enhancing the GIP. However, little empirical research addresses
the question of how different capabilities, as antecedents, affect the
improvement of GIP. This study focuses on the automotive sector.
This study examines the extent to which the existing internal capabilities of firms and their interaction with external sources of knowledge
– enhancement relationship learning – affect their level of GIP. Section 2
reviews the theoretical framework that forms the basis of this empirical
analysis. Section 3 presents an empirical analysis building on information about 112 firms from the Spanish automotive components’
manufacturing sector. Finally, Section 4 summarizes the results and
discusses the main points arising from the analysis. The results confirm
the positive role on GIP of both the direct effect and indirect effect of
firm capabilities. Furthermore, the findings support that DC influence
GIP by reconfiguring relationship-learning capabilities and accessing
knowledge outside firms’ boundaries.
2. Theoretical background
2.1. GIP
In the environmental era, firms should integrate ideas to protect the
environment. For this reason, green innovation is essential for firm’s
business management. An efficient management can create value,
leverage a competitive advantage, and increase the firm’s performance
(Chang & Chen, 2013).
Innovation is an important way to mitigate or avoid environmental
damage. Green technologies provide two main benefits for
organizations: the commercial rewards from creating environmentally
sustainable products, and the financial benefits that can increase competitiveness. Customers around the world want and expect to purchase
ever more environmentally friendly products and services. Certainly,
green innovation is a strategic need for firms which offers a great chance
for meeting customers’ demands without harming the ecosystem.
Historically, firms have seen investing in eco-friendly behaviors as
an excessive investment, but today’s strict ecological rules and the
prevalence of environmentalism are changing competitive strategies,
policies, and patterns for firms (Porter & Reinhardt, 2007). The ‘green’
label is an incentive for continuous innovation, creating new market
opportunities for firms to satisfy new consumer demands and thus
create value and improve performance.
Green innovation can consist of either green products or green
processes. Green innovation comprises innovation in technologies for
energy saving, pollution prevention, waste recycling, green product designing, and corporate environmental management (Chen et al., 2006).
2.2. The link between dynamic capabilities, relationship learning – as
ordinary capabilities – and the firm’s GIP
In line with the resource-based view (RBV), the differences in
performance between companies owe to their specific sets of resources
and capabilities. Therefore, such resources and capabilities are the
source of competitive advantage (Helfat & Peteraf, 2003). The RBV
assumes the heterogeneous distribution of resources and capabilities
among companies and its maintenance over time (Ambrosini &
Bowman, 2009).
At the current period of widespread crisis, with a significant shortage
of resources in all sectors, organizations need more than ever to be able
to distribute their available resources among the alternatives, to try to
adapt in the best way and as quickly as possible to the turbulence of
the environment (Prahalad & Ramaswamy, 2004). Consequently,
organizations must develop DC to evolve, advance, grow, adapt, and,
ultimately, survive. Such DC development allows companies to sit
some firm foundations that support their strategy. Nonetheless,
although DC’s outlook follows the RBV (Makadok, 2001), and RBV
highlights resource combinations selection, DC emphasizes resource
regeneration. This way, DC are the capacity of the firm to reconfigure
resources into new combinations of ordinary – or operational – capabilities (OC).
The literature offers numerous definitions of DC. The concept of DC
has undergone a terminological evolution thanks to the contributions
and disagreements of different authors. Teece, Pisano, and Shuen
(1997) first coin this concept and define DC as firms’ ability to integrate,
build, and reconfigure internal and external competencies to manage
rapidly changing environments. Cepeda and Vera (2007) and Zahra,
Sapienza, and Davidsson (2006) refer to DC as the processes to reconfigure a firm’s resources and operational routines in the manner that its
principal decision-makers envision and deem appropriate.
This article adopts Pavlou and El Sawy’s (2011, p. 243) conceptualization. Extending earlier works by Teece (2007) (sensing the environment to seize opportunities and reconfigure assets), and Teece et al.
(1997) (reconfiguring, learning, integrating, and coordinating), these
authors propose a framework that contains four DC that function as
tools that enable the reconfiguration of existing operational capabilities:
(1) sensing, (2) learning, (3) integration, and (4) coordination
capabilities.
Several authors propose the need to differentiate among types of
processes and routines available in firms. Thus, Zollo and Winter
(2002) and Winter (2003) distinguish between ordinary – operational
– (zero-order) and dynamic (first-order) capabilities. Ordinary capabilities focus on the operational working of the firm, including both staff
and line activities; these are “how we earn a living now†capabilities.
Dynamic capabilities relate to the transformation of ordinary capabilities causing changes in the firm’s products or production processes, or
create new ordinary capabilities.
Karna, Richter, and Riesenkampff (2015) distinguish five categories
of ordinary capabilities: (1) operations/processes, (2) product/service/
quality, (3) resources/assets, (4) organization/structure, and (5) customer/supplier relationships. This study uses customer/supplier relationships because of the importance that the innovation literature
grants to knowledge sharing and relational learning activities.
When firms share information and knowledge with customers and
suppliers, they enhance their knowledge base, capabilities, and
competitiveness through relationship-level learning. This framework
broadly adopts the meaning from Cheung, Myers, and Mentzer (2011)
and the original definition from Selnes and Sallis (2003, p. 86) of the
relationship-learning activities:
[Relationship learning activities are] “an ongoing joint activity between the customer and the supplier organizations directed at sharing
information, making sense of information, and integrating acquired information into a shared relationship-domain-specific memory to improve the range or likelihood of potential relationship-domain-specific
behaviorâ€.
Relationship learning is thus a process to increase future behavior in
a relationship. This study proposes that relationships vary in terms of
their relationship learning capabilities (RLC), and thus some relationships perform better because they have developed appropriate learning
mechanisms. Following Selnes and Sallis (2003), this study’s research
model presents RLC as a construct comprising three ordinary capabilities: (1) information sharing capability (ISC), (2) joint sense-making
capability (JSC), and (3) knowledge integration capability (KIC).
The foundation of cooperative nets between companies and
stakeholders is critical in innovation progress (Bossink, 2002). Through
alliances and relationships, organizations can effectively innovate by
sharing complementary assets and skills (Powell, 1998). Organizations
can consequently create partnerships, joint ventures, inter-firm nets,
and R&D conglomerates (Doz, Olk, & Smith Ring, 2000). This idea is
the basis of Chesbrough’s (2003) open innovation theory, which argues
that companies can combine external and internal ideas and market
2 G. Albort-Morant et al. / Journal of Business Research xxx (2016) xxx–xxx
Please cite this article as: Albort-Morant, G., et al., The antecedents of green innovation performance: A model of learning and capabilities, Journal
of Business Research (2016), http://dx.doi.org/10.1016/j.jbusres.2016.04.052
pathways to take advantage of their technologies. A fruitful green innovation process requires collaboration and knowledge exchange with
external stakeholders. Furthermore, many organizations lack
knowledge and capabilities to foster green innovations. For example,
in the automotive components’ manufacturing sector, if a company
needs to reduce its products’ environmental impact – supposing that
the company does so at many points in the supply chain and that the
firm itself does not participate in all product manufacturing stages – collaboration with other companies in the product’s value chain is necessary (Petruzzelli, Dangelico, Rotolo, & Albino, 2011). Additionally, the
sophistication of ecological problems forces firms aiming to perform
green innovations to build a solid, broad net of links with their
customers and suppliers (Ngai, Jin, & Liang, 2008). These stakeholders
are a source of eco-friendly knowledge and capabilities outside the
firm’s core domain. The relevance of RLC in developing green innovations is so essential.
The capabilities-based view of the firm proposes that, to gain competitive advantage, firms need OC, which let them operate their selected
outlines of business efficiently, and DC, which assist them to promote
existing OC or to create new ones (Karna et al., 2015). However, a strong
debate exists over this field, “riddled with inconsistencies, overlapping
definitions, and outright contradictions†(Zahra et al., 2006, p. 917).
Even today, the relationship between DC, OC, and competitive
advantage and performance remains controversial.
The literature provides extensive, although not general, evidence of
the enhancing effect of DC and OC on innovation and performance
(Karna et al., 2015). On the one hand, some authors and several empirical studies suggest a direct effect of DC on performance and competitive
advantage (Karna et al., 2015; Teece, 2007; Teece et al., 1997). On the
other hand, some authors disagree with this direct relationship between
DC and performance. For instance, Helfat et al. (2007) decouple the notion of DC and performance and contend that DC do not unavoidably
lead to competitive advantage, because although DC may change the resource base, DC may not create any valuable, rare, inimitable, and nonesubstitutable (VRIN) resources (Zahra et al., 2006; Eisenhardt & Martin,
2000). This view questions the direct relationship between DC and
performance. Instead, Pavlou and El Sawy (2011) propose an indirect
relationship. These authors offer empirical evidence that DC indirectly
influence performance by reconfiguring existing operational (ordinary)
capabilities into superior ones that better match the changing
environment. Therefore, Pavlou and el Sawy (2011) also differentiate
between OC and DC, and argue that competitive advantage and
performance come from new configurations of resources and OC, and
not from DC per se, introducing the mediating role of OC in the relationship between DC and performance in new product development.
Recently, Karna et al. (2015) investigate the role of OC and DC as
drivers of the financial performance of firms under different environmental conditions by meta-analyzing 115 empirical studies comprising
121 samples. Their results suggest that the performance effects of both
types of capabilities are positive and similar in magnitude. Environmental dynamism reinforces the effects of both ordinary and dynamic
capabilities. Furthermore, the two types of capabilities present a close association. These findings provide support for a moderate capabilitiesbased view of the firm, rather than one that considers dynamic capabilities as superior to ordinary ones. Therefore, Karna’s study reaffirms the
idea that variations in capabilities across firms are central to explaining
variations in competitive advantages and performance.
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