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The politics of the private sector: investigating the role of
Corporate Political Activities as a key component of the Innovation
strategies of Europe’s automotive corporations
Master Thesis – Final submission
Student: Yosif Touma (Student no.11806133)
Supervisor: dhr. dr. Alexander Alexiev
Course: Master Thesis – Innovation Management & Entrepreneurship
Master Business Administration
Faculty of Economics and Business
Date: 17/08/2018
Word count: 12,474
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Abstract
In 2015 the European automotive industry was shook by the Dieselgate scandal and affected the
corporate approach to influencing public policy in accordance to their innovation strategy. This
following thesis aims to contribute to the existing academia on the matter of corporate lobbying as a
rent-seeking tool and examine its effects on market performance as well as on R&D policy. By
applying rich secondary data to a fixed and random effects regression models, the research was able
to identify corporate political actions as beneficial for corporate R&D efficiency. Additionally, the
results of the research identified a weak direct link between lobbying efforts and market performance.
This finding has been further applied and discussed in terms of the current position of the European
automotive industry. The paper further discusses some of its limitations and offers direction for future
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Statement of originality
This document is written by Yosif Touma (Student no. 11806133), who declares to
take full responsibility for the contents of this document.
I declare that the text and the work presented in this document is original and that no
sources other than those mentioned in the text and its references have been used in
creating it.
The Faculty of Economics and Business is responsible solely for the supervision of
completion of the work, not for the contents.
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Table of contents
List of tables, figures and abbreviations. . . 6
Introduction. . .
7
1. Literature review. . .
9
1.1. Introduction to Corporate Political Activities. . . 9
1.2. Role of CPA on public administration. . . 11
1.3. Innovation in the European Automotive market. . . 13
1.4. Linking Corporate lobbying and Innovation strategy. . . 16
2. Methodology. . . 20
2.1. Sample and data collection. . . 20
2.2. Variables and measures. . . 21
2.3. Methods. . . 24
3. Results. . . 27
4. Discussion. . . 36
4.1. Implications. . . 36
4.2. Limitations and future research. . . 39
5. Conclusion. . . 40
Bibliography. . . 41
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List of figures, tables and abbreviations
Figure 1. Political Strategies and Sustainable competitive advantage according to the
Dynamic Capabilities Framework ... 10
Figure 2. Law-making process in the EU ... 14
Figure 3. Contour plot of lobbying-R&D interaction ... 31
Table 1. Summary statistics ... 27
Table 2. Pairwise correlations (Pearson's correlation coefficient) ... 28
Table 3. Tested models summary ... 29
Table 4. Fixed effects estimation results ... 30
Table 5. Random effects estimation results ... 32
Table 6. Robust vs. Non-robust standard errors comparison. ... 34
CPA – Corporal Political Activity
EU6 – European emission standards regulation for light passenger and commercial
vehicles No.6 and effective 2014
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Introduction
Arrests within the board of directors and a billion euro fine for the largest European automaker – this
is the sum-up of the regulatory sanctions against Volkswagen AG following the Dieselgate scandal
in 2015 (Cremer and Schwartz, 2018; McGee, 2018). And while fabricated laboratory testing
remained a concern for most major industry players ever since, their management has not stayed still
and adjusted their external political influences to their product development and innovation strategy.
The following paper provides an alternative view to corporate lobbying within the European
automotive industry as it attempts to demonstrate its relativity to R&D effectiveness. The European
market for passenger cars has changed remarkably since the implementation of the European
Emission Standards regulation, proposed in 2007 and fully enforced in 20141. The new regulations
required swift reaction by many of the leading players in the industry in an attempt to reduce their
fleet’s emissions and hence – any potential regulatory penalties. The imposed limitations on CO2
emission by passenger cars meant that a lot needed to change for many automakers and innovation
strategies had to be significantly altered in order to achieve the regulators requirements and improve
the efficiency of their products. The following paper will further investigate the effects of newly
imposed regulations on the innovation strategies of firms within the European automotive industry.
The role of Corporate Political Activities, i.e. CPA, in recent years has emerged as a key strategic
tool for many organisations in the EU as it allows them to influence the external political environment.
Despite extensively researched, the topic of corporate lobbying remains underdeveloped, particularly
when viewed as an alternative approach to firm’s innovation strategy. In contrast to existing research on the topic, the following paper will focus on the ability of firms to influence the external political
environment by implementing Corporate Political Activities to support its operations, hence capturing
the effects of lobbying on R&D efficiency. Based on secondary quantitative data and empirical
8 analysis, the findings of this study are expected to either confirm or refute the effects of corporate
lobbying efforts on R&D effectiveness and market performance.
In addition, the paper will attempt to add value to the existing literature, as research addressing the
specific causes and outcomes to corporate political activities within the European automotive industry
is currently very limited. The emergence and developments of the Dieselgate scandal have certainly
changed the European car market and particularly the trends within corporate lobbying. Furthermore,
the enhanced transparency promoted by the European commission through the European
Transparency register has allowed for rich set of data, unavailable to most previously conducted
empirical researches. Utilising such increasingly available to the public secondary data has also
allowed for academic contribution to theories identifying CPA as rent-seeking practice, as empirical
evidence on the topic within the European market is currently very limited (Brown, 2016a; Lux,
Crook & Woehr, 2011).
The ultimate aim of the thesis is to provide meaningful insight for the industry and an academic basis
that would influence innovation and lobbying strategies in future. The following paper will provide
an insight to the academic literature on the basis of which the thesis research will be conducted. The
literature review draws a logical path towards the central research question, formed around the
investigated variables as illustrated by the conceptual model. In addition, the paper includes a detailed
explanation of the methodology used to derive the results of the study, including some the sources of
secondary data and statistical methods used to test the zero hypothesis. The paper concludes with a
discussion section that links the present research to existing literature linked to the topics of
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1. Literature review
1.1. Introduction to Corporate Political Activities
Governmental regulations and policies represent a key component influencing innovation as these
also stimulate novelty by setting a level playing field for all industry players. Such intervention may
be even more needed in cases in which the environmental benefit of an innovation does not
necessarily translate into financial gain for a company (Rennings, 2000). The regulations within the
automotive industry for instance have contributed tremendously towards innovation within a sector
in which being green has not been a main concern previously. Since the adoption of the European
emission standards for new vehicles2 however, automakers have been forced to comply and gradually
minimise the negative environmental impact of their products. As a result of the progressively
stringent emission standards, innovation has been flourishing – both within the traditional combustion
engine models as well as the newly developing market for zero emission vehicles (hybrids, electric
vehicles, etc.). This example once again demonstrates how compliance with newly imposed
regulations requires innovation (Oliver and Holzinger, 2008). Michael Porter describes such changes
in government factors as an external force, often perceived as exogenous and uncontrollable (1979).
In contrast, Epstein (1969) argues that government can be viewed as an opportunity to create a more
favourable environment for the firm. The relevance of such non-market factors and their interrelation
with corporate strategies has been further investigated by Yoffie (1987) and Barron (1995).
The organisation’s capability to effectively influence the formal institutions and hence the external environmental factors has become ever so important for many multinationals within the automotive
industry. In practice, once faced with regulatory pressure to innovate, corporations may adopt
strategies different than compliance. Instead, most corporations engage in Corporate Political
Activities aiming to shape government policies in ways favourable to the firm (Hillman, 2005; Keim
& Schuler, 2004; Oberman, 1994). Researchers within business and public policy (Baron, 1995; Keim
10 and Zeithaml, 1986; Lord; Oliver and Holzinger, 2008; Rugman and Verbeke, 1993; Yoffie, 1987)
outline three main types of CPA – defensive, proactive and reactive (i.e. compliance). The defensive
approach suggests engaging in activities to oppose regulatory change and retain the current status
quo, hence undermining the role and impact of innovation (Oliver and Holzinger, 2008). Compliance
strategies on the other hand are focused at exploiting firm’s internal resources in order to comply with imposed or anticipated regulations, in an attempt to maintain or create competitive advantage (Oliver
and Holzinger, 2008). The speed of corporation reaction towards newly imposed legislation is crucial
in determining the effectiveness of its compliance strategy. In contrast, the proactive strategies as
identified by Oliver and Holzinger are aimed at shaping the regulatory change in an attempt to gain
competitive advantage, often with a focus on the long-run (Figure 1). Efficient political influence in
such cases may, for instance, be aimed at decreasing the compliance costs for the company engaging
in a proactive strategy or increase its chances in obtaining subsidies to support required R&D.
Figure 1. Political Strategies and Sustainable competitive advantage according to the Dynamic Capabilities
Framework
Yoffie (1987) further argues that firms would avoid involvement in political activities only if the
11 show an alternative approach by some of the industry leaders. According to Oliver and Holzinger
(2008), political influence is often the favourable strategy for larger organisations, such that are
dependent on the political environment, possess material interest in the public policy in question, and
view a political issue as particularly salient. Ansolabehere, de Figueiredo and Snyder Jr. (2003)
investigate campaign funding in the US as a market for public policy and offer an alternative view of
CPA and subsequent performance. In their research, they describe CPA as an “arms race” amongst
firms and argue that incremental spending on political activity does not lead to marginal rents, but
instead leads to a zero sum game (Brown, 2016a). Nonetheless, despite contradicting, this alternative
approach addressing the Tullock Paradox (Tullock, 1972) has had limited empirical support in CPA
literature (Mathur et al., 2013). These ideas also reinforce the view that benefits of adopting CPA go
beyond financially measured performance.
The effectiveness of political influence strategies is also highly dependent on the dynamic capabilities
of the firm, such as predictions and early knowledge of impending or potential legislative or public
policy changes, as well as the ability to respond appropriately before those changes are implemented
(Oliver and Holzinger, 2008). Moreover, an anticipatory rather than reactionary green strategy may
result in better reputation and stronger position for a firm, allowing it to change the existing policies
(Russo and Fouts, 1997).
1.2. Role of CPA on public administration
Unstable political environment may present companies engaging in value creating corporate political
activities with an additional barrier despite their efforts and progress towards influencing government
policies. In contrast to the sustainable policies implemented throughout the Democrat’s mandates in the US between 2009-2017, Donald Trump’s cabinet drives the government’s focus away from issues
linked to sustainability, pollution and climate change. The changes within the political environment
in the US would inevitably affect the automotive industry, for instance by cutting out funds for
12 In addition to an inevitable shift for Tesla and the company’s political influence, such measures would
certainly limit the chances for other promising start-ups with strong drive for innovation and
sustainable future.
Walley and Whitehead (1994) argued that there are no reasons why regulation would actually be
needed for firms to adopt profit-increasing innovations. Despite win-win situations might exist by
chance, they are very rare, and, given the magnitude of some investment for regulation compliance,
the financial return is likely to be negative (Walley and Whitehead, 1994). Porter and van der Linde
(1995) on the other hand investigate pollution as a fundamental cause of resource wasting (energy,
materials, etc.). According to their approach, somewhat challenging the idea of Walley and
Whitehead, more rigorous environmental policies may in fact have positive impact on innovations,
to an extend that may offset the costs of complying with these policies. There are indeed many ways
that improving a company's environmental performance may lead to better (Porter & van der Linde,
1995). According to the theory, also known as the ‘Porter hypothesis (PH)’, more stringent and
flexible environmental regulations, such as taxes and tradable permits, would be beneficial for the
economy, hence stimulating innovations that may often end up offsetting the costs associated with
complying with these policies.
Relying on an extensive survey from OECD (i.e. The Organisation for Economic Co-operation and
Development), Lanoie, Patry and Lajeunesse (2007) examined the complete causality chain of the
Porter hypothesis (i.e. from environmental regulations and corresponding R&D actions to business
performance) and according to their findings, environmental regulation stringency affects R&D
spending positively. In a more recent research based on a sample of 17 Quebec firms within the
manufacturing sectors, Lanoie, Johnstone, Lucchetti and Ambec (2008) found that more severe
regulations only led to small gains in productivity. The introduction of time lags (i.e. 3-4 years)
between changes in the severity of environmental regulations enabled Lanoie et al. (2008) to capture
13 research in an attempt to capture the effects of newly imposed regulation on corporate strategy and
investment decisions.
Organisational rent-seeking is a commonly discussed topic within research focused on the CPA –
Firm performance relationship (Faccio, 2006; Oliver and Holzinger, 2008; Hadani and Schuler,
2013). In its essence, the idea behind this concept may be outlined as firm’s attempts of allocating
resources towards activities that would allow them to extort value from the external environment.
These activities may be implemented either within the market or non-market (i.e. public policy arena)
strategy of the company, attempting to shape the legislative framework towards their private
advantage and hence – financial gains (Baron, 1995).
The legislative level indeed provides the opportunity for firms to infiltrate the system with their
interest and influence laws that are still in their early stages of development and are yet to be passed
(Kaiser, 2013). In contrast, the administrative level includes the next step of the process,
responsibility for which is held by various regulatory bodies. Regulatory rules embody codified laws,
derived from legislatively passed regulations, however only concerned with the implementation of
the law (Yackee and Yackee, 2006). During the law-creating process, companies may be actively
involved in shaping the path of the rule as it goes from an initial proposal to a final, passed regulation
(Brown, 2016c). In order to capture rents during the public policy process, firms tend to adopt two
types of tactical approaches – pressure and information gathering. This present research will be
primarily focused on one of the key pressure mechanisms, i.e. corporate lobbying.
1.3. Innovation in the European Automotive market
The current research is primarily focused on studying the effects of corporate political activities and
more specifically the extent to which lobbying practises may influence innovation strategies of
European automotive corporations. The debate over the effect of CPA on firm performance has grown
substantially as a result of increasing firm investments in corporate political activities (Bonica, 2016).
14 of various automakers towards changes in the political environment. Despite applicable to the
industry in question, there are certain limitations to be considered. A key point defended by Oliver
and Holzinger (2008) research is linked to the long-term implications of adopting proactive strategy,
which may not always be the case.
The wide range of approaches towards corporate lobbying has been evident in the European Union
in recent years. The Council of the EU brings together the governments of the EU's 28 member states
and is one of the most important decision-making bodies in the
EU.3 Any newly proposed EU bill within has to pass an initial
screening within the Council, hence providing a fertile territory
for corporate lobbyists who use their influence to secure a desired
outcome (fig 2). Broadly, the Council adopts far more
business-friendly positions than the Parliament, while member states are
often keen to promote the lobby positions of major l companies
and adopt them as their own. Corporate lobbyists can use their
influence through member states' governments to influence EU
decision-making, i.e. via member states' membership of Commission expert groups; via 'comitology'
committees, which oversee the implementation of EU laws; and through informal routes, such as
personal contacts between EU and national leaders (Corporate Europe Observatory, 2017).
In September 2015, car manufacturer Volkswagen was caught in the use of “defeat devices” –
software enabling its diesel cars to pass pollution emissions tests, while actually exceeding EU
pollution limits by more than ten times once on the road (Topham, Clarke, Levett, Scruton & Fidler,
2015). Gradually, it became clear that emissions cheating has been a widespread practice in the car
industry, with official investigations currently underway against other car producers, including
Daimler, Audi, Fiat-Chrysler and Renault (Schmitt, 2017). The Dieselgate scandal exposed how
3 https://europa.eu/european-union/about-eu/institutions-bodies/european-council_en
15 Commission decision-makers, working with member state governments, placed the car lobby in a
powerful position regarding the regulation of toxic emissions, to the detriment of the health of
countless European citizens. According to a recent report by two large NGO’s (Hubner, 2017),
Dieselgate was the result of corporate-driven deregulation, with both member states and European
institutions “complicit in turning a blind eye to industry-wide abuse”. The study highlights how both
the European Commission and Member States overlooked industry-wide abuse of the system for
emission regulation, and as part of the ‘Better Regulation’ reform agenda even invited the car industry
to shape regulation as well as its enforcement. The car industry has used the rhetoric and objectives
of the programme to its own advantage, according to the organisations, pushing market-driven
solutions, promoting industry-friendly impact assessments and arguing for voluntary agreements
instead of binding regulation (Hubner, 2017).
Meanwhile, citizens are left to feel that car manufacturers have shirked accountability for their
monumental toxic emissions fraud. Even in Germany, where the car industry provides hundreds of
thousands of jobs and generates billions in export profits each year, two thirds of the population
declared for tougher action against the car industry over Dieselgate (Schumacher, 2017). This new
wave of criticism around excessive car industry influence comes after the German government and
carmakers worked out a deal at the Berlin ‘Diesel Summit‘ in August 2017, a conference to which
environment NGOs and consumer representatives were not invited (Schmitt, 2017). At the meeting,
car manufacturers pledged to provide software updates for the 5.3 million diesel cars on Germany‘s
roads that were fitted with the defeat devices. Nonetheless, this low-cost solution will only reduce
emissions marginally, whilst ultimately avoids a much more costly, proper technical adaptation of
the cars that would lower NOx emissions to legal levels.
In its Dieselgate report (Gieseke and Gerbrandy, 2017), the European Parliament outlines quite
clearly how the European Commission must improve its ways of working to help curb the car
industry’s influence over policy-making. Among other things, their demands include measures to prevent industry dominance in advisory groups and a transparency boost for the EU policy-making
16 process in general. One may have thought that the dominance of corporate interests in relevant
Commission expert groups would have been reigned in after the scandal broke, however a recent
investigation by the Corporate Europe Observatory (2017) revealed their continuing dominance in an
important EU advisory groups on car emissions rules.
Jaffe and Palmer (1997) investigated the relationship between total R&D expenditures (i.e. the
number of successful patent applications) and costs linked to decreasing pollution (a proxy for the
stringency of environmental regulations). They found a positive link with R&D expenditures (an
increase of 0.15% in R&D expenditures for a pollution abatement cost increase of 1%), however no
statistically significant link with the number of patents was established. In their 2008 paper, Ambec
and Lanoie have also explored whether or not a “green” strategy translates into profitable future for the firm. According to their research, an ambitious innovation strategy is likely to lead to better
environmental performance, which in turn is expected to result in either higher revenues or lower
costs for the firm.Lobbying on the other hand can be the tool to allow exactly the opposite – less
ambitious innovation strategy is unlikely to cause any changes to the environmental performance.
Ambec et al. (2008) highlight the importance of looking at both sides of the balance sheet in order to
answer the question set by the study – “Does it pay to be green?”. The current research attempts to
build upon this idea by investigating the effectiveness of R&D investments.
1.4. Linking Corporate lobbying and Innovation strategy
According to Dahan (2005), lobbying is considered key when forming the political capability of a
corporation. Kanol (2015) further described the rapidly developing trend as “a mechanism that exerts
influence on an existing political authority”, the authority being an elected politician or an appointed
regulator (McGrath, 2013; McKay, 2011). Yackee and Yackee (2006) also look at the key role which
regulators have within the private industries on which they often have a thorough effect by writing
specific, enforceable rules based on the existing legislation. Failure of firms to comply with such rules
17 law formulation in order to help shape policy in a favourable manner (McKay, 2011). The European
automotive industry makes no exception and lobbyists often have a key role aimed at influencing
authorities to create a more profitable climate for their private clients.
That impact of corporate political activities on firm performance remains comparatively less
researched, particularly when looking at meaningful empirical evidence to either support or refute
link within the mentioned relationship (Brown, 2016a; Hillman, 2005; Oliver and Holzinger, 2008;
Lux et al., 2011). According to Lord (2000) for instance, congressional staff perceived professional
lobbying as the most effective measure of influencing congressional legislative policy in the US.
Banker, Das and Ou (1997) provide an alternative view of the relationship between firm-level
outcome and CPA while investigating airline carriers, whilst Bowman, Navissi and Burgess (2000)
focus their research on pharmaceutical firms. Both of the studies determined that expected policy
changes have a direct effect on market value, hence supporting the argument of the present research
that lobbying efforts aimed at shaping policy have a direct effect the value of the firm.
Despite the healthy development of academic literature concerning lobbying and interest groups in
the US, publications focused on the EU market remain limited, currently marked only by some
isolated and limited in scope of analysis studies (; Bunea and Baumgartner, 2014; Coen, 2007; Julio,
2014; Mathur, Singh, Thompson, and Nejadmalayeri, 2013; Wiesenthal, Leduc, Köhler, Schade, and
Schade, 2010).
The relation between R&D efforts and market performance has also been thoroughly analysed in
existing literature (Borghesi and Chang, 2015; Mathur, Singh, Thompson, and Nejadmalayeri, 2012;
Julio, 2014; Kim and Kim, 2012; Rudy and Johnson, 2016). Wiesenthal et al. (2010) investigate the
18 In contrast to existing academic research in the field, the current paper will investigate the effects of
lobbying efforts to the R&D effectiveness on both market and firm-level performance, or as
formulated in the research question of the study:
What are the effects of corporate lobbying on R&D effectiveness
within the European automotive sector?
Evidence of such positive relationship can be found in some topical literature, however in other
context. Richter, Samphantharak & Timmons (2009) research associated lobbying with lower
corporate tax rates in a wide-ranging sample of public companies. Lee and Baik (2010) paper also
identifies a positive link between lobbying efforts to the disbursements given to domestic firms by
the US government in anti-dumping petitions. In a study investigating US electric utility corporations,
Bonardi, Holburn and Vanden Bergh (2006) have similarly concluded that lobbying efforts were
positively related to firm’s subsequent allowed rate of returns by the utilities' public commissions.
Brown (2016b) further linked lobbying to higher return on invested capital (ROIC) and return on
19 Therefore, aimed at contributing to the existing body of literature on the topic of rent-seeking, the
present research will attempt to confirm whether increased Lobbying efforts has a direct, positive
effect on Market performance when combined with R&D Investments, hence deriving the following
conceptual model based on hypothesis H1 and H2:
H1. Lobbying investments influence the effectiveness of R&D investments of automotive firms in the
European market.
H2. Increased lobbying efforts affect the performance of automotive firms in the European market.
H2a. Increased financial efforts, i.e. lobbying investments
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2. Methodology
The results of the following study are based on a substantial quantitative evidence collected through
database research (e.g. Eurostat, Euromonitor, etc.), official corporate publications (e.g. annual
reports) and other European registries (e.g. Transparency register by the European Commission).
Empirical analysis has been the preferred approach, as numerical data is expected to provide clear
measurable evidence for any relation between the observed variables. Furthermore, the rich secondary
data available suggests conclusions would be inductively drawn and primarily focused on individual
interest groups.
2.1.Sample and data collection
The sample that has been used for the purpose of the research includes the 26 most R&D intensive
public listed companies operating within the ‘Automobiles & parts’ sector in the EU as defined by FTSE’s latest industry classification benchmark (i.e. Auto Parts; Automobiles; Commercial Vehicles & Trucks; Tires subsectors)4 within the captured period (2010-2017). The available data would allow
the study to be extended further to other industries or/and analysed on a national level. Furthermore,
the panel data collected would allow for higher control of the analysis, as it would observe the effects
of the studied causal relations shortly prior and following the introduction of the comparatively strict
EU6 regulations in 2014.
Some of the main data sources include:
Source 1. European environmental agency
https://www.eea.europa.eu/data-and-maps/data/co2-cars-emission-13
Source 2. European Vehicle Market Statistics Pocketbook 2016/17
https://www.theicct.org/sites/default/files/publications/ICCT_Pocketbook_2016.pdf
21
Source 3. The 2017 EU Industrial R&D Investment Scoreboard
http://iri.jrc.ec.europa.eu/scoreboard17.html
Source 4. Lobbying statistics (as declared to the EU Transparency Register)
Eurostat: http://ec.europa.eu/eurostat/data/database
Transparency register: http://ec.europa.eu/transparencyregister/public/homePage.do
http://www.integritywatch.eu/lobbyist.html
https://lobbyfacts.eu/
Source 5. Corporate annual reports
2.2.Variables and measures
The following research has partly followed the approach of Julio (2014) and investigated the
effectiveness of in-house R&D, however focused on market performance as the key analysed
determinant instead of product quality. Mathur et al. (2013) has further researched the role of
corporate lobbying on firm performance, hence providing a strong academic basis for the present
study. Some of the key variables, also used in previous empirical research (Borghesi and Chang,
2015; Brown, 2016a; Hill et al., 2013; Julio, 2014; Mathur et al., 2013), include the following:
2.2.1. Independent variable
The independent variable investigated in the following analysis is (XRD) Annual R&D investment,
i.e. the cash investment funded by the companies themselves (data available in sources 1, 2, 3 & 5,
section 2.1). The metrics used exclude R&D undertaken under contract for customers such as
governments or other companies as well as companies' share of any associated company or joint
venture R&D investment. Further definitions linked to the independent variable include:
R&D investments information is derived from various annual reports, hence the same remains subject to the accounting definitions of R&D.
22 Research is defined as original and planned investigation undertaken with the prospect of gaining new scientific or technical knowledge and understanding. Expenditure on research is recognised
as an expense when it is incurred.
Development is the application of research findings or other knowledge to a plan or design for the production of new or substantially improved materials, devices, products, processes, systems
or services before the start of commercial production or use. Development costs are capitalised
when they meet certain criteria and when it can be demonstrated that the asset will generate
probable future economic benefits. Where part or all of R&D costs have been capitalised, the
additions to the appropriate intangible assets are included to calculate the cash investment and
any amortisation eliminated.
2.2.2. Dependent variables
Following Mathur et al. (2013) approach, Total Net Sales has been used to determine market
performance (YMP), following the usual accounting definition of sales, excluding sales taxes and
shares of sales of joint ventures & associates. The dependent variable will be observed over several
time periods – t, t-1, t-2, etc., where t represents the observed period (data available in sources 2 & 3,
section 2.2). The total period subject of the research (i.e. 2010-2017) has been selected in accordance
with the introduction of EU6 standard in 2014 that provided the first more severe regulation within
the market. The panel data allows for the introduction of time lag, aimed at capturing the reactions of
different automakers in response to the previously announced and newly imposed regulation.
2.2.3. Moderator
The moderator of the research that would determine the relativity studied in Hypothesis 1 and 2 will
be (WLOB_C) Lobbying efforts represented by the total annual expenditure and (WLOB_TOT) number
of staff linked to corporate lobbying as declared to the Transparency register by the European
Commission (available in source 4, section 2.2). The Register is the unified document covering firms
23 voluntary, but necessary to gain access to EU institutions, data, public consultations, meetings with
Members of the European Parliament, Commissioners, Cabinet Members or representatives of the
Commission Services (e.g. Director Generals). The data firms have to provide when registering are
clarified in the Transparency Register Implementing Guidelines (JTRS, 2015), which in turn have
their legal basis in the Interinstitutional Agreement between European Commission and European
Parliament (EU Parliament & EU Commission, 2014). According to these guidelines, firms have to
insert their annual lobbying expenses either as an absolute amount, or as a selection within a
respective expense interval, of which 32 are available from zero to above ten million. Firms’ lobbying budget includes both direct (e.g. contact of Commission or Parliament officials) and indirect (e.g.
through other channels such as media, public events) lobbying activities. The budget is meant to cover
all costs of an office located in Brussels and in their national country as long as the activity is carried
out with the objective “of directly or indirectly influencing the formulation or implementation of policy and the decision-making process of the EU institutions” (JTRS, 2015, pp.9). Accordingly, the
lobbying expenses are only covering the efforts to influence political decisions at EU not at national
level. Moreover, according to the Register’s guidelines, firms have to update their data once a year at least, but are advised to do so even more timely where possible.
2.2.4. Test variables
Certain test variables have also been introduced in order to enable effective segmentation of the data
analysis (e.g. differentiate between companies that have or have not declared costs linked to corporate
lobbying; EU / non-EU firms). This has further focused the study in determining the effects of
lobbying towards innovation strategies of companies that do rely on such non-market practices.
2.2.5. Controlled/Isolated variables
Assuming several controlled/isolated variables that may undermine the relevance of XR&D and could
provide an alternative explanation of the effects observed in the study, is also crucial in order to
24 measure (but not limited to) indicators linked to Marketing, Leadership, Organisational structure, etc.
The current analysis has been based on the following:
Both Hansen and Mitchell (2000) and Brasher and Lowery (2006) research highlight firm size as a key determinant for corporate decisions linked to lobbying. In order to control the influence of
firm size, the current research utilises the accounted number of employees (WEMP), i.e. the total
consolidated average employees or year-end employees if average not stated.
Capital expenditure is “expenditure used by a company to acquire or upgrade physical assets such as equipment, property, industrial buildings. In accounts capital expenditure is added to an
asset account (i.e. capitalised), thus increasing the asset's base. It is disclosed in accounts as
additions to tangible fixed assets” (EU Commission, 2011). While resources constraints are not
expected to influence the decision to lobby, lack of resources may limit the actual lobbying
expenses (Mathur et al., 2013). Following Mathur et al. (2013) approach the current paper
consider Capex intensity ratio (WCPX, i.e. Capital expenditure to sales ratio) to clearly delineate
the impact of resource constraints on the intensity of lobbying efforts. Firms facing high ratio of
Capital expenditure to Net sales are expected to have comparatively limited focus on CPA, hence
– lower lobbying expenses (Mathur et al., 2013).
Further control has been established by using dummy (test) variable according to firm’s origin that adopts the value of ‘1’ in the cases in which the firm EU-based and ‘0’ if otherwise.
2.3.Methods
Both fixed-effects and random-effects estimations were conducted using STATA v13 statistical
software package. Whilst the fixed effects model allows for interpreting changes within firms over
time, the random effects allows capturing both within- and between-firm effects (Brown, 2016a). In
addition, the panel data used in the present research further inclines towards relying on fixed-effects
regressions due to the large number of observations per year per firm. Also known as longitudinal or
25 not across entities (i.e. national policies, federal regulations, international agreements, etc.), hence
accounting for individual heterogeneity. Furthermore, some studies have argued that fixed-effects
estimations with lagged variables resolves the reverse causality problem inherent in many business
related statistical tests. On the other hand, random effects estimations are valid when variation
between companies has an effect on the dependent variable (Beck and Katz, 2007). Since this study
is concerned with comparing organisational approaches when adopting CPA, and this difference is
not expected to be linked to subsequent financial performance, neglecting random effect from the
presented analysis would be problematic. Instead of relying on a single technique, both fixed and
random effects regressions have been estimated and reported, however further tests (i.e.
Breusch-Pagan LM and Hausman) have also been performed in order to determine the most efficient method
of testing the hypothesis of the current study.
2.3.1. Fixed effects equation
Yi(t) = αi + β'Xi(t-1) + W'Zi(t-1) + ui(t)
Where Yi(t) represents the dependent variable, i.e. Market performance (YMP), and measured within
the present research by Annual Net Sales, β'X – the captured independent (parameter) variable (i.e.
R&D expenditures, or XRD ), followed by W'Z, i.e. explanatory measurement (Lobbying efforts, or
WLOB_C & WLOB_TOT) and control items (Firm size and Capital expenditures - WEMP & WCPX
respectively). In the fixed effects model, αi represents an additional entity-specific intercept and ui(t) – error term.
2.3.2. Random effects equation
Yi(t) = αi + β'Xi(t-1) + W'Zi(t) + ui(t) + εi(t)
In contrast to the Fixed model estimation, the Random effects equation examines ui(t) as the between-entity error and εi(t) as the error term, which incorporates all other factors such as omitted variables.
26
2.3.3. Robustness checks and selectivity bias
Several robustness checks have been performed in order to support the method selection for the
present research. To ensure that problems of autocorrelation and reverse causality do not interfere
with the coefficient estimates, the study has considered and reported yearly regressions with lagged
explanatory variables as related to the dependent variable. Further, to ensure that selectivity bias is
not distorting the results of the research, Heckman's selection model has been performed in order to
analyse the impact of market performance on the firm’s lobbying strategy and intensity (Heckman, 1979).
27
3. Results
Table 1 displays the descriptive (summary) statistics, Table 2 displays the pairwise correlations
between variables and Table 3 and 5 display the results from a fixed and random effects estimations
respectively and generated by the xtreg function in STATA v13 software package. Models 1 and 3
are the controls only models, and Models 2, 4 and 5 test the effects of lobbying efforts as discussed
in Hypothesis 1, 2a and 2b. As evident from the pairwise correlation coefficients (Table 2), the
collinearity coefficients between the variables measuring lobbying efforts and market performance
are not high enough to distort the results of the regression, hence the research proceeded with
performing the fixed and random effects estimations.
Table 1. Summary statistics
Variable Mean Std.dev. Min Max Observations
R&D Investments overall 2,786.02 2,645.94 106.92 13,672.00 N = 202 between 2,548.52 185.38 10,114.13 n = 26 within 820.72 -1,538.11 6,343.89 T-bar = 7.769 Profit overall 5.27 4.88 -20.01 19.50 N = 202 between 3.74 -0.74 17.55 n = 26 within 3.78 -14.00 11.74905 | T-bar = 7.769
Net Sales overall 57,971.53 52,991.25 2,854.00 224,151.00 N = 202
between 52,098.21 2,979.50 188,661.10 n = 26 within 13,964.98 -16,084.72 98,784.28 T-bar = 7.77 Lobbying costs overall 585,762.40 605,863.80 10,000.00 3,300,000.00 N = 141 between 580,671.90 59,375.00 2,581,250.00 n = 25 within 272,088.70 -531,112.60 2,018,887.00 T-bar = 5.64 Total lobbyists declared overall 5.37 5.62 0.00 43.00 N = 143 between 3.68 1.33 18.38 n = 25 within 4.09 -10.00 30.00 T-bar = 5.72 CAPEX overall 4,600.05 5,699.03 175.70 30,941.90 N = 133 between 5,064.49 180.30 22,268.13 n = 25 within 2,399.68 -2,946.30 19,252.52 T-bar = 5.32 Employees overall 154,001.90 117,925.10 3,248.00 626,715.00 N = 193 between 114,919.20 3,248.00 502,237.30 n = 26 within 34,685.52 -15,415.31 300,679.10 T-bar = 7.42 R&D Intensity overall 4.93 2.32 1.60 21.10 N = 202 between 3.57 2.16 21.05 n = 26 within 0.45 3.52 6.42 T-bar = 7.77 CAPEX Intensity overall 5.91 3.61 0.00 22.97 N = 194 between 2.51 0.00 10.74 n = 26 within 2.55 0.72 18.39 T-bar = 7.46
28
Table 2. Pairwise correlations (Pearson's correlation coefficient)
Variable 1 2 3 4 5 6 7 8 9 1 R&D Investments 1 2 Profit -0.09 1 3 Net Sales 0.94*** -0.64 1 4 Lobbying costs 0.68*** 0.02 0.56*** 1 5 Total lobbyists declared 0.66*** -0.08 0.48*** 0.83*** 1 6 CAPEX 0.73*** -0.08 0.83*** 0.31*** 0.26*** 1 7 Employees 0.89*** -0.08 0.83*** 0.65*** 0.65*** 0.63*** 1 8 R&D Intensity 0.15** 0.05 -0.06 0.05 0.13 -0.07 0.15** 1 9 CAPEX Intensity 0.31*** 0.10 0.34*** 0.04 -0.05 0.69*** 0.27*** 0 1 *** < 0.01 **<0.05 * < 0.10.
3.1.Fixed effects regression
The R2 value, also known as the coefficient of determination, represents the proportion of variation
explained by the regression model above and beyond the mean model. In addition, the F-ratio
examines whether the overall regression model is an appropriate fit for the data collected. According
to the results of the performed fixed-effects regression presented in Table 4, variables included in
models 1, 2, 3, 4 and 5 (Table 3) explain 35.98%, 45.41%, 61.3%, 63.05% and 63.83% of the
variability of the dependent variable respectively. The relatively high (and significant) F-values also
suggest that the performed regression fit the panel data available.
Within-subjects R-squared values are included for the examined fixed effects models. It is important
to highlight that the additional tests containing explanatory variables have a higher R2 coefficients as
compared to the basic model, hence demonstrating that more marginal variance is explained by
adding in the lobbying efforts variables. Hypothesis 1 predicted a positive association between
lobbying efforts and R&D efficiency. The results derived by Model 2 appear to support Hypothesis
29 the low β-value suggests very low direct influence of lobbying efforts over R&D effectiveness according to the studied model. Furthermore, the effect of Total lobbyists declared to R&D Intensity
ratio, was found to be insignificant as p > 0.1.
The results of the models linked to Hypothesis 2 provide consistent support of the examined
collinearity. R-squared values increase from 45.41% observed in Model 3, which only included the
control variables, to 61.3% and 63.05% in Models 4 and 5 respectively. This observation confirms
that the examined explanatory variables indeed contribute highly to the model of the present research.
The findings of these regressions related to lobbying efforts as discussed in Hypothesis 2a and 2b
were also found to be significant with p = 0.048 for Model 4 and p = 0.007 for Model 5. However,
these regressions confirmed a negative collinearity of the examined explanatory variables and the
dependable variable, hence challenging the zero hypothesis, which suggested positive influence of
lobbying efforts on market performance. Instead, negative lobbying coefficients have been
established for both Models 4 and 5. Results for the effects of lobbying were found to be highly
significant for both models with p-value of 0.007 for Model 4 and p=0.025 for Model 5. Similar to
Model 1 and 2 examined above, the low β-coefficient for lobbying efforts within Model 4 suggests
very weak effect of lobbying investments on market performance. The findings of Model 5 on the
other hand can be interpreted as an expected decrease of €726,000 in Net Sales for every additional lobbyist declared during the previous period.
Table 3. Tested models summary
Model # Control Variables Dependent Variable Explanatory Variables
Firm Size CAPEX R&D Intensity Net Sales R&D Costs Lobbying costs Total lobbyists 1 X X X 2 X X X X X 3 X X X 4 X X X X X 5 X X X X X
30
Table 4. Fixed effects estimation results
H Variable (A) (B)
(1) (2) (3) (4) (5)
1, 2a Lobbying Costs (lag) 7.14e-07** -0.009**
1, 2b Total lobbyists declared (lag) -0.007 -726.302***
R&D Costs (lag) 8.062** 8.652**
Firm size 3.25e-06** 1.40e-06 0.123*** 0.056 0.050
Capital expenditures 3.23e-06 8.10e-06 2.201*** 1.666 1.632206
Constant 4.264195 4.183191 38479.4 34,164.93 31,606.91
F-value 5.21*** 9.27*** 41.17*** 11.50*** 16.83***
R-squared 0.0952 0.3598 0.4541 0.6130 0.6305
N=94 N=94 N=126 N=95 N=97
(DV = (A) R&D Intensity, (B) Net Sales)
***<0.01 **<0.05 *<0.10
3.2. Random effects regression
The results of the models tested by using random effects estimations as performed in STATA are
displayed in Table 5. In all random effects estimations, the overall R2 value has been computed
considering that the interpretation of random effects coefficients is the change in the dependent
variable when the independent variable changes across time and firms as one unit (Brown, 2016a).
Similar to the results of the fixed regression estimations performed, all models, which
incorporated measures of lobbying and R&D efforts, recorded higher R-squared values as
compared to the baseline Models 1 and 3 that only considered the effect of the control variables
and none of the explanatory ones. H1 predicted a positive relationship between lobbying efforts
and R&D intensity. According to the results when regression performed on Model 2, the
coefficient on lobbying costs variable is positive and significant (Model 2 β = 6.74e-07, p = 0.030), however results linked to total lobbyists declared variable (β = -0.00489) were found to be insignificant (p > 0.1). The results of the performed test we can conclude that lobbying
31 More specifically, given that lobbying costs are increased by €100,000 over time and across firms,
the model predicts an increase within R&D Intensity by 0.0674%.
Models 4 and 5 test Hypothesis 2a and 2b respectively, i.e. the relationship between lobbying
efforts and market performance. Both Models 4 and 5 suggest negative collinearity for the
examined explanatory variables with respect to the dependent variable (i.e. Net Sales).
Coefficients for the respective variables, i.e. Lobbing costs in Model 4 and Total lobbyists
declared in Model 5, have been determined as β = -0.00971 (p = 0.028) and β = -726.302 (p = 0). In other words, only an insignificant Net Sales increase may be accounted to a change within
Lobbying investments during the previous time period according to the studied model. It is
important to note that although the actual sign of the collinearity differs from the expectations,
the resulting coefficients remain very low, hence insufficient to definitively refute Hypothesis 2a.
Nonetheless, the results show that there is a clear negative collinearity when considering the total
lobbyists declared, hence challenging the zero hypothesis.
Figure 3. Contour plot of lobbying-R&D interaction
The contour plot displayed in Fig. 3 illustrates the interaction of the lagged lobbying investments and
R&D variables, with the colour coding outlining the dependent variable (i.e. Net Sales). The
32 rather challenging. Using the contour plot, on the other hand, allows for a comprehensive summary
of the interaction at different levels of main effects. For example, according to Fig. 3, the highest
performers were those that relied heavily on R&D, however the same firms did not necessarily invest
in lobbying (highlighted in red). Firms that did not focus on R&D were absent from the highest level
of performance, no matter how much lobbying effort was exercised. It is also interesting to note that
according to the contour plot some of the average performing firms were able to achieve stable results
with limited R&D investments, however slight increase in lobbying efforts determined their
advancement to a higher performance group according to their Net Sales (i.e. light blue yellow
green).
Table 5. Random effects estimation results
H Variable (A) (B)
(1) (2) (3) (4) (5)
1, 2a Lobbying Costs (lag) 6.74e-07** -0.00971**
1, 2b Total lobbyists declared (lag) -0.00489 -1239.18***
R&D Costs (lag) 10.6143*** 12.3746***
Firm size 3.09e-06** 1.32e-06 0.177108*** 0.07342** 0.05769** Capital expenditures 2.31e-06 6.65e-06 2.517893*** 2.53324*** 2.18967*** Constant 4.846*** 4.746*** 25157.78*** 17332.06*** 17343.84*** Walid Chi-Sq 9.70** 37.04*** 160.54*** 287.09*** 321.47***
R-squared 0.952 0.3595 0.4524 0.6113 0.6264
(DV = (A) R&D Intensity, (B) Net Sales)
***<0.01 **<0.05 *<0.10
3.3.Robustness checks and selection bias 3.3.1. Reverse causality
According to Bascle (2008) reverse (or simultaneous) causality may prove to be a critical issue in
management studies since many corporate level decisions are endogenously determined. In turn, it
may therefore be suggested that instead of CPA affecting firm’s market performance, higher Net
33 also been unable to provide strong support of such directional relationship as a number of studies
have found insignificant coefficients on performance measures as independent variables when related
to a dependent variable linked to corporate political activities (Hillman, 2005; Hadani, 2012). As a
robustness check both fixed effects and random effects models have been performed with the
predictor being Net Sales in period t-1 and lobbying effort as the observed variable at period t. Similar
to the results obtained by the identical tests performed by Hillman (2005) and Hadani (2012), none
of the coefficients on Net Sales appeared to be significant, hence suggesting that market performance
does not induce more lobbying efforts.
3.3.2. Robust standard errors
The results of the studied models described in Tables 4 and 5 include non-robust standard errors only,
which may challenge the heteroscedasticity of the collected data. As an additional robustness check,
the respective regressions have also been performed using Hubere-White robust errors. Despite no
effect on the β coefficients of the mentioned models, these may affect the p-value reported, hence the
significance of the findings. P-values for robust standard errors are, on average, higher and this may
lead to alternative interpretations as compared to standard non-robust errors (King and Roberts,
2015). In the present study, the examined coefficients, i.e. concerning the effects of the explanatory
variables, were somewhat affected when looking at the dichotomy between significance and
non-significance, with one variable becoming insignificant after applying the Hubere-White standard
errors (Table 6). Nonetheless, most p-values associated with the coefficients of interest were higher
than those in the initially described models. As a result, some changes within the significance
categories of the explanatory variables have also been observed. For instance, the p-value on the
lobbying intensity variable in Model 4 was 0.007 yet was 0.032 when taking robust standard errors
into consideration. A detailed comparison of the significance levels of the explanatory variable
coefficients between the original models and the models incorporating robust standard errors has been
34
Table 6. Robust vs. Non-robust standard errors comparison.
H Variable Model comparison, Dep. Variable: Net sales
FE RE FE Robust RE Robust
1 Lobbying Costs (lag) 7.14e-07** 6.74e-07** 7.14e-07** 6.74e-07* Total lobbyists declared (lag) -0.007 -.00489 -0.007 -.00489 2a Lobbying Costs (lag) -0.009** -0.00971** -0.009* -0.00971
2b Total lobbyists declared (lag) -726.302*** -1239.18*** -726.302*** -1239.18***
***<0.01 **<0.05 *<0.10
3.3.3. Method selection
Breusch Pagan Lagrangian multiplier test has also been performed via STATA software in order to
challenge the selection of fixed effects model instead of OLS. The test has been performed by utilising
the following command:
NetSales[Company1,t] = Xb + u[Company1] + e[Compnay1,t]
The results of the test have been identified as significant, i.e. chibar2 > 0 and p=0 for all examined
models, hence refuting OLS as most convenient approach to the present dataset as compared to the
individual effect models that the paper has used (Appendix 1).
Lastly, Hausman test has also been performed in order to challenge the effectiveness of the Random
when compared to the Fixed effects models. The output produced by STATA software package
provided Chi-squared values of 0.46 for Model 2 (p>0.1), 54.68 (p=0) for Model 4 and -24.11 for
Model 5, hence explicitly refuting the Random effects model as better fitted to the present data only
when performed on Model 5 (Appendix 2).
3.3.4. Selection bias
Additionally a Heckman Two-Step procedure was also included in the hypothesis testing of the
35 (2016a), an appropriate implementation of the Heckman model would be in cases in which samples
are non-random and there is a chance that omitted variables from a broader sample of firms will bias
results. The first step of the method consists of a selection equation, in which the control variables
are regressed on the exploratory variable, i.e. R&D and lobbying efforts. In this first step, the
dependent variable is binary (‘1’ = Firm is EU based, ‘0’ = otherwise), resulting in a correction factor
output, otherwise known as the ‘Inverse Mills Ratio’ (Bascle, 2008). The same coefficient should
then be included in the original equation as an additional variable in order to adjust for potential
selection bias. Therefore, an insignificant Inverse Mills Ratio coefficient (p > 0.05) suggests no
selection bias and the original results may be considered unbiased due to selection (Bascle, 2008).
Within the present research, both Heckman equations, the Inverse Mills Ratio within both Heckman
equations performed was insignificant (λ = -4606.902, p = 0.681 for R&D investments and λ = = -6489.572, p = 0.783 for Lobbying investments) and, therefore, selection bias is not present in the
36
4. Discussion
The following section will highlight the conclusions made following the tests performed as described
in Chapter 3. The paper will follow the logical sequence set in Chapter 1 and will link the results of
the present research to the existing body of theory. In addition, the following analysis will attempt to
investigate the reasons behind both the expected and unexpected trends as derived by the results of
the regression models. As discussed in all previous chapters, as well as supported by the data
collected, corporate lobbying is a key investment decision for the majority of the firms involved in
the European automotive sector. Tendency towards lobbying was one of the trends observed amongst
the 26 most R&D intensive firms in the market. According to the data provided by the EU
Transparency register, an average of €585,000 these firms have spent within the studied period. This tendency once again highlights that corporate lobbying has emerged as a strategic tool to influence
the surrounding political environment in a period of transition towards more strict regulations in the
Eurozone. Despite the increasing adoption of hybrid and electric car models in recent years,
regulation pressure automotive corporations to expedite innovation and develop products emitting
lower harmful emissions, in some cases sooner than physically possible. The pressure for higher
control and strict measures in favour of green policies pushed some of the leading automakers to go
beyond CPA in an attempt to oppose the newly imposed legislative changes. The following
sub-sections aim to investigate further the obtained results in an attempt to identify and evaluate the effects
of lobbying efforts on corporate innovation strategies and market performance.
4.1.Implications
4.1.1. Theory and academia
The present research has implications on both current theory and literature on the topics of innovation
and corporate political activities. The empirical results of the present paper build upon the idea of a
defensive approach to CPA as discussed in existing literature (Baron, 1995; Keim and Zeithaml,
37 automotive firms continuously invest in CPA despite the very low direct impact on market
performance as outlined by the results of the present study.
In contrast to previous research, pointing to direct impact on financial performance (Bonardi et al.,
2006; Brown, 2016a; Hillman, 2005; Mathur et al., 2013; Richter et al., 2009) the current paper
supports a competing view of CPA and subsequent performance. The results of the paper provide
significant and rare empirical evidence to support Ansolabehere et al. (2003). The paper builds upon
the ideas of rent-seeking through CPA, discussed in the works of Brown (2016a) and Lux et al. (2011).
Despite the results of the research showing very low direct relation of lobbying investments to market
performance as measured by the studied model, corporate lobbying is playing a key role within the
European automotive market.
In addition to this theoretical contribution, and as stated in the beginning of the paper, this study also
contributes to the topical literature concerning the transportation sector in the EU and, more
specifically within the automotive industry, as there has been limited research addressing CPA in
these domains. Political activity is crucial in this industry since rent-seeking firms may attempt to
increase market share or profitability through access to public policy makers and in lieu of
market-based, competitive measures. This is a particularly trending topic in recent years since the Dieselgate
scandal emerged in 2014, hence contributing to the relevance of the presented work.
4.1.2. Management
The research additionally implies some implications for management in the business world. The
findings related to the results of Model 2, confirming Hypothesis 1, for instance, serve as an additional
confirmation of majority existing research. The effects of CPA may indeed go beyond the
performance metrics of a firm and help shape the external environment in a direction, favourable for
the firm’s innovation strategy.
Although significant, the results of the Model 4 estimated a negative, however very low effect of
38 Hypothesis 2b was also found to be highly significant. Nonetheless, the coefficient estimated by
Model 5 was much lower, hence suggesting a more severe (negative) impact of intensified CPA
efforts (i.e. hiring more lobbyists) compared to increased lobbying investments. Despite challenging
the zero hypothesis, the findings of the research would hold some significant implications for
corporate decision-makers. Following strong market performance in the period 2010-2012, the net
sales of the three largest German automakers, i.e. Volkswagen, Daimler and BMW, grew at a slower
rate. The sales stagnation may be accounted to some extend to the strict measures imposed by EU6,
however the turning point for most CPA tendencies within the EU automotive industry in recent years
has been Dieselgate. Since the emergence of the scandal, lobbying investments and more significantly
– lobbying personnel – has been increased in order to handle the significantly greater amount of correspondence with the EU regulatory bodies. The negative PR most of the major automakers
received following the allegations of fabricated laboratory emission tests severely impacted EU diesel
sales. The combination of stagnated sales and intensified lobbying efforts has certainly contributed
to the results of the present paper. Although according to the present research CPA could potentially
enhance R&D effectiveness, the results also lead to the conclusion that lobbying efforts may intensify
in challenging market conditions, hence undermining the positive link to net sales as suggested by
the zero hypothesis.
The practical implications of the present research may also be explored in a slightly different
direction. In contrast to the majority of existing literature on CPA and as reviewed in Chapter 1, the
results of the current study were unable to identify a positive relationship between lobbying efforts
and market performance. Interpretations of the negative collinearity, specifically in terms of total
lobbyists declared, may also link to CPA efficiency, an idea also discussed by Brown (2016a). The
results of the present research suggest that firms that manage to optimise the amount of
representatives within the EU regulatory bodies develop a deep commitment to establishing
39 for more profitable lobbying and efficient political spending (Brown, 2016a) whilst limiting a
potential negative impact on market performance.
4.2.Limitations and future research 4.2.1. Limitations
Several limitations of the present paper can be identified. Firstly, historic data suggests that causality is difficult to surmise. Despite the model was tested in a reverse sequence (i.e. lagged market
performance tested on subsequent lobbying efforts as described in Section 3.4.1.) and found no
evidence of such inverse relationship, some concerns over reverse causality may remain. Secondly,
due to the highly concentrated industry the paper is concerned with, the sample for the research was
relatively small (N = 26). Despite the conclusions have been reinforced by relying on panel data (N
= 95), a richer sample would be optimal. Nonetheless, the discussed model provides a robust tool to
evaluate the extent to which lobbying affects innovation in other R&D intensive industries, such as
Pharmaceuticals & Biotechnology; Technology Hardware & Equipment; Electronic & Electrical
Equipment; Software & Computer Services; etc.
4.2.2. Future research
The availability of lobbying data declared to the EU Transparency register would further support a
potential cross-industry research. The emerging transparency and data availability on corporate
lobbying will be crucial to the development of increasing number of empirical studies focused on the
European market. Furthermore, encouraging transparency by declaring lobbying investments has
been a very recent trend in the EU. Enhancing the richness of lobbying data in the next few years will
certainly influence the significance of future research in the area. A qualitative study of the
relationship discussed in the current paper may an additional direction for future researchers. A case
study project on the large German automakers’ (i.e. Daimler, Volkswagen AG and BMW) response to the Dieselgate scandal may provide an invaluable inside of the industry as well as rare empirical
