Can green taxation trigger plug-in hybrid electric vehicle acquisition?

Victor Barros (Advance/CSG, ISEG-Lisbon School of Economics & Management, Universidade de Lisboa, Lisbon, Portugal)
Hugo Pádua (Advance/CSG, ISEG-Lisbon School of Economics & Management, Universidade de Lisboa, Lisbon, Portugal)

EuroMed Journal of Business

ISSN: 1450-2194

Article publication date: 27 June 2019

Issue publication date: 10 July 2019



The purpose of this paper is to analyse to what extent financial incentives under the green tax reform introduced in Portugal in 2014 drive behaviours of acquiring a plug-in hybrid electric vehicle (PHEV).


The existent literature identifies a number of factors that influence the interest for PHEV acquisition, including access to financial incentives. However, empirical evidence is not clear as to which factors are more relevant. The authors extend an existent theoretical model of five factors by including ten factors. On this basis, the study carries out a survey and develops a structural equation model to investigate what drives the interest to acquire a PHEV.


Financial incentives are superior to other factors in explaining the interest in acquiring a PHEV. Education, lower income levels, living in larger cities and driving smaller vehicles shape the interest on these vehicles differently. Financial incentives were found to closely offset the difference in price between conventional vehicles and plug-in hybrids.

Social implications

This study finds that public policies can be powerful in shaping consumers’ behaviour, although the amount of the financial incentive is key to triggering a large-scale effect.


The survey in this study allows an in-depth and ex ante analysis of the interest in acquiring PHEV under a green tax reform, taking into account other dimensions and socio-economic variables not accounted for in existent studies.



Barros, V. and Pádua, H. (2019), "Can green taxation trigger plug-in hybrid electric vehicle acquisition?", EuroMed Journal of Business, Vol. 14 No. 2, pp. 168-186.



Emerald Publishing Limited

Copyright © 2019, Emerald Publishing Limited

1. Introduction

The need to redefine public policies to mitigate climate changes and resource exploitation (e.g. energy, raw materials and water), has been on the radar of governments all over the world. The academic literature has rapidly focussed on this topic and new approaches in supply chain management research have been developed to promote an efficient resource use and the reduction of environmental impacts (Toma et al., 2016; La Scalia et al., 2019), taking into account the profitability of each anthropic activity, including transports.

Forecasts from the International Energy Agency (IEA, 2017) show the relevance to focus on plug-in hybrid electric vehicles (PHEV). By 2020 the number of models offered by carmakers should double comparing to 2015 to about 40 PHEV and 20 electric vehicles (EV). Accordingly to Bloomberg New Energy Finance (2018), in OECD Europe total sales in 2030 should reach 2.0m and 4.7m for EV and PHEV, respectively. Until 2050 a crossover point is expected between these technologies. PHEV’s annual sales should be at 3.1m in 2050, while EV should stand at 6.4m. Nevertheless, PHEV shall drive consumers towards greener consumer options in the medium term. The global market of EV passed 4m in 2018, but it only represents 2.5 per cent of the total vehicles sold worldwide. Are public policies effective in triggering a large-scale effect?

While empirical evidence suggests that policy incentives can exert a positive influence on the adoption of EVs (Langbroek et al., 2016), the literature is lacking regarding whether, and which motivations can effectively drive the acquisition of greener vehicles. Junquera et al. (2016) study consumers’ willingness to acquire an EV, although the authors focus mainly on technical specifications of electric cars. Ozaki and Sevastyanova (2011) developed a model to explain the primary motivations for the acquisition of “greener” vehicles, while prior and subsequent studies have focussed on factors of that framework, namely on financial incentives (Klein, 2007; Gallagher and Muehlegger, 2011; Sierzchula et al., 2014; Mannberg et al., 2014), the effect of technology (Egbue and Long, 2012; Larson et al., 2014) and fuel efficiency and environmental awareness (Heffner et al., 2007; Turrentine and Kurani, 2007; Diamond, 2009; Gallagher and Muehlegger, 2011; Krause et al., 2016), amongst other factors. More recently, Krupa et al. (2014) added clarification to the attributes and attitudes towards PHEVs.

In this study, we take advantage of a green tax reform introduced in Portugal in 2014 to comprehensively study the factors that can drive the interest in the acquisition of a PHEV. Our research goal is to assess whether the level of financial incentives introduced by a green tax reform is effective in explaining the interest in acquiring a PHEV. The reform targeted vehicles other than those fully powered by combustion engines, with particular emphasis on PHEVs. Green energy tax reforms were implemented all over Europe, creating financial mechanisms to favour the acquisition and use of PHEVs and EVs. The primary purpose of these actions was to shape individuals’ behaviours towards more sustainable transportation practices, as hybrid and EV can significantly reduce greenhouse gas emissions in transport (Duvall et al., 2007; Smith, 2010) and can mitigate the effects of peaks in the demand for fossil fuels (Andersson et al., 2010). However, the motivations for acquiring a PHEV may go beyond the financial incentives provided, and cannot be explained solely by economic factors (Klein, 2007).

The important research of Ozaki and Sevastyanova (2011) suggests that environmental awareness, the technological aspect of the vehicle, the reduction of oil dependence, the image, and financial incentives, are all drivers for the interest of acquiring a PHEV. In fact, effective communications regarding climate change issues may shape consumers’ behaviour (Peattie et al., 2009). However, modern green tax systems can fail their purpose, either because of insufficient financial benefits provided to consumers, or else because of their limitations in shaping consumers’ behaviour beyond financial motivations. Also, previous studies mostly focussed on current drivers of either PHEVs or EVs. The main aim is to assess whether tax incentives are the most relevant factor in explaining the interest in acquiring PHEV and we focus on interest (ex ante), rather than on past choices (ex post), as the target population is composed by consumers not driving either a PHEV or an EV. The focus on financial incentives is relevant given the socio-economic and cultural characteristics of Portugal that are different from the context of other relevant studies (e.g. Sprei and Wickelgren, 2011; Schafer, 2011; Qiao, 2014). Also, we extend the theoretical framework of Ozaki and Sevastyanova (2011) of five factors by adding five other factors. In this context, we develop a structural equation modelling (SEM), using data from a survey. The survey allows an in-depth analysis of the interests of acquiring PHEVs under a green tax reform, taking into account other dimensions and socio-economic variables not accounted for in existent studies.

Results suggest that financial incentives are the primary factor in explaining the interest in the acquisition of PHEV, validating our primary research goal. This relationship does not vary with household size but is valid for respondents driving smaller vehicles, more educated, with lower levels of income, and living in larger cities. Yet, financial incentives should cover, on average, 87 per cent of the price difference between PHEV and combustion engine vehicles to trigger PHEV acquisition. Results also suggest that factors identified in the literature other than financial incentives are not valid predictors for the interest in acquiring a PHEV. That is to say, factors detailed in the literature that shaped acquisition decisions of current users of PHEVs or EVs do not hold for non-users. Collectively, our results suggest that in countries less engaged in environmentally sustainable practices the access to financial incentives is pivotal in shaping consumer interest in PHEV.

This study contributes to the existent literature by focussing on whether financial incentives under a green tax reforms are likely to influence consumers’ choices. To date, exploratory studies focussed on samples of drivers who have already acquired a PHEV or an EV, and the primary research purpose is rarely to explore the effects of tax policies. Our results also fit in with those of literature exclusively focussed on EVs.

This study also contributes to the public debate, by confirming the Government’s ability to influence consumer behaviour, although policies must also account for consumer characteristics. Findings suggest that tax policies can effectively shape consumers decisions towards PHEV and EV acquisition. However, these policies may not yield the required financial incentive to trigger PHEV acquisition and eventually a large-scale effect. Governments in countries with socio-economic and cultural conditions as Portugal should give primacy to financial incentives when implementing green tax reforms.

In the following section, an overview of the existent literature in the motivations for PHEV and EV acquisition is offered, which assists in framing the research objectives of this study. The paper progresses by describing the methodology and suitability tests. In the fourth section is analysed the results. To conclude, the findings from the empirical analysis are discussed and policy conclusions are put forward.

2. Literature review

2.1 Motivations to acquire a hybrid electric vehicle

The introduction of a green tax system aims mainly to shape individuals’ behaviour towards more sustainable practices, and frequently incorporate financial incentives in corporate income and taxation on motor vehicles. However, the literature reveals that there are motivations for buying a PHEV beyond the scope of these financial incentives. Ozaki and Sevastyanova (2011) study the motivations for the adoption of a PHEV and groups the motivations in five main indicators/groups. The first group is financial benefits and other tax advantages. Consumers aim to obtain financial benefits from fuel efficiency (Heffner et al., 2007; Klein, 2007), which can be achieved by switching from more expensive and larger-engine vehicles to less powerful and more fuel-efficient hybrid vehicles (Haan et al., 2006).

As pointed out by Gallagher and Muehlegger (2011), the option for a PHEV comes as a response to rising fuel prices and tax incentives. However, the appeal of financial incentives might be limited to offset the high prices of hybrid technologies (Krause et al., 2016). Such an effect limits the goal for green tax reforms of influencing large-scale sustainable behaviours.

Conversely, Hirte and Tscharaktschiew (2013) argue that travelling with EVs should be taxed, and not subsidised. We expect financial incentives to pay a critical role in explaining the interest in acquiring PHEV in Portugal. The second group of motivations accounts for the social effect of driving a more environmentally friendly vehicle. Heffner et al. (2007) suggest that consumers consider their role in preserving the environment by demonstrating high levels of environmental awareness and by taking actions to reduce their ecological footprint. Consumers seek to acquire hybrid EV to express and communicate their ecological concerns (Klein, 2007). The studies of Gallagher and Muehlegger (2011) and Turrentine and Kurani (2007) also point out that these consumers explicitly seek to be seen driving environmentally friendly vehicles.

The third group focusses on compliance with the norms of the community in which consumers are inserted (Ozaki and Sevastyanova, 2011) – image. Environmentally friendly consumers tend to be clustered in green communities. This reality creates a stigma that not possessing a hybrid EV is a reflection of not sharing the community’s norms and values (Kahn, 2007; Krupa et al., 2014).

Both environmental awareness and image relate to the growing concept of social responsibility. The concept is increasing in importance for individuals and also for organisations (Chatzoglou et al., 2017; Jones et al., 2007), has been evolving (Caulfield, 2013), and is affected by stakeholders attitudes towards the concept (Bella and Al-Fayoumi, 2016). Green tax reforms frequently introduce measures for corporations, which can help them to be more socially responsible and may affect accounting figures (Grbac and Lončarić, 2009; Oberhofer and Fürst, 2012; Belyaeva, 2015).

The fourth group of motivations for the acquisition of a PHEV emerges from studies focussed on new technologies (Turrentine and Kurani, 2007). Consumers in this group have a positive attitude towards innovation and are mainly earlier adopters (Heffner, 2007). Literature has also pointed out that consumers’ interest to adopt new technologies depends on their attitudes towards technology (Giovanis et al., 2018). The production of innovative technologies also depends on characteristics of producers, such as their level of technological intensity (Karagouni, 2018), yet studies have documented the need for companies to follow a road of the green economy (Vrontis et al., 2016). The automotive industry is facing significant restructurings to face PHEV and EV developments, and some players opted for joint-ventures or mergers and acquisitions (e.g. PSA and Opel or Renault and Nissan). Yet, mergers and acquisitions are growing in several domains (Christofi et al., 2017). Acquisition of PHEV may also depend on brand loyalty. On this regard, Loureiro et al. (2012) developed a relevant study on brand attachment and vehicle acquisition. Technological development was more relevant to explain vehicle purchasing behaviour in Denmark than the tax reform in 2007 and rising fuel prices (Mabit, 2014), and technology also appears to the likelihood of adopting greener vehicles in Norway (Orlov and Kallbekken, 2019). Recently, Krupa et al. (2014) developed a similar study to that of Ozaki and Sevastyanova (2011). They find that the technological factor was the most frequent motivation indicated by survey participants, and that battery-related concerns and financial issues are the main obstacles to the market penetration of PHEVs in the USA. These results are also supported by the previous studies of Caperello and Kurani (2012) and Graham-Rowe et al. (2012). Other studies suggest that the reliability of PHEVs is a key consideration for consumers’ willingness to adopt them (Deloitte, 2010), which combines battery life, charging time, the durability of the electrical components, and access to qualified maintenance (Caperello and Kurani, 2012; and Graham-Rowe et al., 2012).

The fifth and last group of motivations for the acquisition of a PHEV focusses on consumers’ aim to be independent from oil producers through the reduction of fuel consumption (Heffner et al., 2007). Consumers’ attitude towards plug-in hybrids may be significantly influenced by their saving intentions, once sustainable energy consumption behaviour exhibits a strong relationship with energy conservation intentions (Sheau-Ting et al., 2016). The study of Diamond (2009) focussed in the USA find gasoline prices more related to hybrid adoption than incentive policies.

Krupa et al. (2014) added a factor to the framework of Ozaki and Sevastyanova (2011). They consider the conditional effect of the current vehicle on the interest for the acquisition of a hybrid electric plug-in. Hidrue et al. (2011) also support this understanding. Consumers owning larger vehicles are less likely to adopt a PHEV, as the latter were compact models at the time (Hidrue et al., 2011). Demographic factors, education, household size, location and income may also drive consumers’ interests towards the acquisition of a PHEV (Klein, 2007; Ozaki and Sevastyanova, 2011; Mannberg et al., 2014). Mannberg et al. (2014) argue that education can have a positive effect on the adoption of green vehicles, while low-income households show less interest in plug-in hybrids. Considering these findings, we also expect that interest in PHEV is higher amongst more educated respondents.

Despite the factors identified above, the discussion as to whether greener vehicles can effectively shape transportation means is far from being consensual. Qiao (2014) sheds light on this issue by studying policy options in China towards the adoption of new energy vehicles. The author concludes that policies implemented in China are not effective in triggering interest in new energy vehicles. Other countries provide different experiences. Sprei and Wickelgren (2011) focussed on Swedish policies to stimulate new energy vehicles acquisition, although cultural and economic factors may well justify the fact that Sweden is leading the reduction of CO2 emissions in Europe. The authors defend that the involvement of the Swedish government with carmakers and the attitude of the population towards a greener economy were effective. New Zealand experience also shows paradoxical outcomes. While the initial strategy to promote new energy vehicles was not effective in its early stages, the New Zealand authorities cooperate with different entities in a broad strategical approach to widen the acceptance of electric cars (Schafer, 2011). Our study is innovative because Portuguese policies aimed similar results although incorporating different mechanisms and under a diverse socio-economic and cultural context. Also, cultural aspects may well justify consumer options, and existent studies call for more research on the introduction of greener policies under different settings (Qiao, 2014).

The call for an ecological footprint has a broader scope than the simple adoption of greener vehicles, as the energy sourcing is pivotal in assessing the ecological benefit from shifting to PHEV. For instance, Miglietta et al. (2018) study how the water footprint from types of crops derived from the production of biodiesel in Italy can be optimised. The authors highlight that several policies target an ecological footprint although environmental impacts may follow a trend other than the one defined by these policies.

2.2 Motivations for the introduction of the green tax reform in Portugal: EU targets

The EU Commission prepared a draft for green tax reforms with the objective to encourage the acquisition of PHEVs, among others. The Commission emphasised the importance of reforms to ensure the balance of public accounts and sustainable growth (CGTR, 2014). A similar understanding was highlighted in the conclusions of the European Council of 28 to 29 June 2012:

“Fiscal policy should contribute to fiscal consolidation and sustainable growth”.

EU principles drive the route for the green taxation reform in Portugal. Despite the introduction of the reform in 2014, several European countries had already implemented strategies to encourage the acquisition of green vehicles, starting from 2012.

The Paris agreement signed in 2016 after the COP 21 conference held in Paris regarding climate changes and EU targets intensified the public debate regarding the implementation of tax systems to encourage the acquisition of greener vehicles. Gass et al. (2014) presented a study at the 2011 World Renewable Energy Congress in Sweden, which compiled the incentives created for the acquisition of EVs at the European level. Many EU members opted to implement measures similar to the Portuguese experience, such as Denmark, France and Greece.

In Portugal, the Law No. 82-D/2014 of 31 December 2014, which is called the “green taxation law”, amends environmental tax rules in the energy, emissions, transport, water, waste, land use, forest and biodiversity sectors. A system to encourage the scrapping of old cars was also enacted. The draft of the green tax reform was highly debated and contested by opposition political parties, especially during a debate in the Portuguese Parliament on 26 November 2014. The discussion highlighted the need for an innovative and substantial green tax reform[1].

The most relevant tax incentives on vehicles acquisition are as follows. First, the creation of a threshold for the depreciable amount of €50,000 (acquisition cost or revalued amount) for PHEV and of €62,500 for EV, above which depreciations are not accepted as a tax expense. The limit for combustion engine vehicles was €25,000.

Second, the reduction of autonomous taxation rates up to 50 per cent for expenses related to PHEV and EV. Third, deduction of VAT on the purchase, manufacture or import, rental, use, processing and repair of PHEV and EV. The VAT was not deductible for combustion engine vehicles, except for commercial vehicles. Fourth, tax incentives for car scrappage. The government also implemented several parking spaces dedicated to PHEV and EV with embedded outlets for charging for free. A carbon tax that is levied on petroleum products also aimed to increase running costs for combustion engine vehicles. The measures above applied to individual consumers and also to both corporately related drivers and sole proprietorship. Although several benefits were oriented for corporate users, the green taxation reform aimed to influence all types of consumers. Benefits for corporate users may also affect consumer decisions towards PHEV, although indirectly. For instance, a common practice amongst several Portuguese larger corporations is to include the use of light vehicles as a compensation package for employees. The increase in PHEV and EV enlarges the network for charging stations, making these vehicles more attractive to all consumers. Also, the reform narrowed the price gap between combustion engine vehicles and both PHEV and EV, especially for business-related individuals, which may also affects indirectly individual consumers.

3. Methodology

A survey was conducted targeting users of light passenger vehicles. The research design aims to understand whether the access to financial incentives, introduced by the green tax reform, along with environmental awareness, technology, oil producer’s independence, image factors, and several social-economic factors (current vehicle size, residence, income, household size and education level) explain the interest for the acquisition of PHEVs.

Several survey questions focus on a retrospective view, as they attempt to assess respondents’ opinions that influenced past decisions, mitigating biases in our results (Glass and Arnkoff, 1997). The survey is divided into three parts. The first part seeks to assess the interest for PHEVs and to identify which vehicle is currently driven by respondents. The second part focusses on the variables defined in the literature that may shape the acquisition of a PHEV. At this stage, the questionnaire is divided into questions for individual and for business users (vehicles owned by economic agents operating under the corporate income tax and sole proprietorship), with adaptations to the context and reality of each of these groups. The segmentation is justified by the fact that some relevant measures under the green tax reform targeted these users. Nevertheless, the low response rate of business-users made this segmentation unsuitable. Yet, individuals represent the majority of users. In 2017, passenger cars accounted for 85.2 per cent of total brand-new light vehicles sold in Portugal, while commercial vehicle filled the remaining 14.8 per cent, accordingly to the Portuguese Association of the Automobile Industry (ARAN). The third part covers the socio-economic indicators of respondents. The detailed survey and the link between each question and the corresponding constructs may be disclosed upon request.

The survey was disseminated through several channels. First, through associations dedicated to the automobile sector and later through social media to cover the broad population of drivers of light vehicles. The sample of individual users comprises 177 valid responses, and respondents are relatively diverse. Unfortunately, the attitude of the Portuguese population was already documented as not being likely to answer academic questionnaires (e.g. Lopes, 2008) and our study is not an exception. Relevant studies on greener vehicles were also developed using a low response rate, as the work of Qiao (2014) that uses 100 observations for consumers living in Shanghai.

Our understanding is that the sample fits the characteristics of the Portuguese driving population. Our sample is composed of 57 per cent male. While the Portuguese population in 2017 is formed of 52 per cent female according to the National Statistics Office, male has a long tradition in being the driver within the household. In 2018 the Portuguese Institute of Mobility and Land Transport (IMT) reported active driving licenses of about 6.5m citizens, of which 3.7m (57 per cent) were male. Regarding drivers age, our sample average is 34 and half of the sample is in the range of 24 to 45 years old. Also accordingly to the IMT, the population of drivers with an active licence in 2018 in the range 20 to 50 years old totalled 3.7m, equivalent to 56.7 per cent. About 1.3m (19.6 per cent) drivers with an active licence are within the range 30 to 39 years old. Moreover, measures of skewness and kurtosis suggest that our sample per age closely follows a normal distribution. The National Statistics Office reports for 2018 an average household size of 2.5. In our sample, the household size is 3, on average, and ranges between 1 and 8. Regarding district of residence, the Portuguese National Statistics Office reported 2.83m (27.5 per cent) residents in the district of Lisbon and 1.72 million (16.7 per cent) in Porto, accounting for 44.1 per cent of the Portuguese population. In our sample, about 40.7 per cent of respondents have a residence in these districts (Lisbon 23.7 per cent and Porto 17.0 per cent). Despite the low response rate, the comparisons above between our sample and the characteristics of the Portuguese driving population yield us assurance for the empirical analysis and extrapolation of results[2] (Table I).

The survey addresses questions that were further combined as factors. The factor E assesses the environmental awareness of respondents focussing on whether driving PHEVs solve a set of ecological problems and focussing on recycling habits of respondents. OP accounts for respondents’ opinion regarding the importance of being independent from oil producers. The image (I) captures how respondents value the image attributes of being labelled as environmentally responsible. The interest in the adoption of new technologies is captured by the technological factor (T). The access to financial incentives (F) is built on several questions related to how respondents value several measures under the green tax reform. The construct INT identifies the interest for acquiring a PHEV and is composed by questions addressing how appealing the purchase of PHEV is and also whether respondents considered buying a PHEV the last time they searched for a new vehicle.

The primary purpose of this study is assess whether financial incentives under the green tax reform introduced in Portugal in 2014 drive behaviours of acquiring a PHEV, while other factors identified in the literature are also tested.

The research hypothesis are as follows:


Access to financial incentives (F) positively influences the interest in acquiring a PHEV.


The level of environmental awareness (E) positively influences the interest in acquiring a PHEV.


The image factor (I) positively influences the interest in acquiring a PHEV.


The aim of being independent from oil producers (OP) positively influences the interest in acquiring a PHEV.


The interest in adopting new technologies (T) positively influences the interest in acquiring a PHEV.

To test the hypotheses above, the SEM is designed in Figure 1. As previously mentioned, the size of the current vehicle (VS), residence (R), income level (INS), household size (HS) and education level (EDUC) of respondents were also taken into account, to extend and increase the explanatory power in the theoretical model. Also, correlations between the factor (I), and factors (T and E) were considered. When drivers use a PHEV, they may wish to convey the image attributes of being environmentally responsible, or of being a supporter of new technologies. Factor I incorporate this logic, and therefore it will be more realistic to consider the existence of this correlation in the model.

4. Results

4.1 Model fit for the theoretical model and modified model

To evaluate the adequacy of the theoretical model in Figure 1, indicators of model fit are presented in Table II. Guidance on a new model that may improve model fit is returned by AMOS software (Harrington, 2009); however, there is no theoretical support for these modifications. Modification indices with values higher than 10 are in evidence, which may suggest the existence of high levels of covariance between error constructs (Byrne, 2009). These items refer to the incentives granted for the acquisition of a PHEV, the feebate rate, and the environmental factor. Furthermore, the modification indices show that constructs e8 and e9 produce a negative variance, affecting the estimation generated by the model. Consequently, in the revision of the theoretical model, the technology factor was removed, which does not support H5. The technological component of PHEV may well not be perceived by consumers prior to an experience of driving a hybrid vehicle (Ozaki and Sevastyanova, 2011). PHEV represent a very small portion of vehicles in the total Portuguese fleet and most consumers may not be aware of the technologic factor of these vehicles. Communication regarding hybrid vehicles and their value added to consumers are vital for the adoption of innovation, as pointed out by Rogers (2003). Our results highlight that such communication may still be ineffective.

The modified model is an adjustment to the theoretical model and produces a better model fit (Table II). The technological factor was removed, and interactions between variables were added (e16-e17, e13-e25). Both GFI and AGFI improved and are closer to borderline acceptance levels. Increases in GFI from 0.70 in a modified model may be considered a significant improvement and the model should be accepted Bollen (1989). The CMIN/df suggests a better fit in the modified model, while the RMSEA reaches a value adequate for a good fit. Nevertheless, these values are only guidelines for the development of an SEM.

4.2 Confirmatory factorial analysis

Table III reports the estimates of the relationships contained in the theoretical model. In synopsis, the empirical results offer support for the validity of our primary research goal. The F factor (access to financial incentives) exhibits a positive influence on the interest in acquiring a PHEV (H1), whilst all other factors are rejected as valid factors to explain the variability on the incentive to acquire a PHEV (H2H5).

Next, we focus on the modified model which yields an interesting result already timidly documented by Hidrue et al. (2011). The access to financial incentives (F factor) is the most relevant factor to explain the interests to acquire a PHEV, although the size of the vehicle currently driven by respondents is also valid. The image attributes and environmental awareness may not be relevant in this context because the country is not recognised for leading the adoption of environmentally sustainable practices. Small activities as waste recycling are still far from the best practices. Environmental education programs for schools shows no proof of increasing environmental literacy (Spínola, 2015). Portugal is only at the 59th position in the climate and energy results accordingly to a ranking produced by Wendling et al. (2018). Also, in the environmental performance index Portugal is ranked 26th globally, although it is only ranked 21st if narrowing for North America and Europe. Therefore, our results suggest that in countries less engaged in environmentally sustainable practices the access to financial incentives is pivotal in shaping consumer interest in PHEV.

4.2.1 Simplified model

Contrary to existent empirical evidence and the theoretical model of Ozaki and Sevastyanova (2011), including the extension from Krupa et al. (2014), only two factors are validated in our model. That is to say, a large number of constructs do not add explanatory power. These constructs create divergences between theory and empirical evidence and may be justified by socio-economic and cultural characteristics of Portuguese consumers. To better assess the importance of the factors F and VS, in Figure 2, we develop the final structural model including only these two factors.

In fact, the model fit comparison in Table II suggest a better fit than both the theoretical and the modified model, which is in contrast with existent empirical evidence focussed on the effect of technology (Egbue and Long, 2012; Larson et al., 2014), fuel efficiency and environmental awareness (Heffner et al., 2007; Turrentine and Kurani, 2007; Gallagher and Muehlegger, 2011; Krause et al., 2016), amongst other factors[3].

4.2.2 Robustness tests

Following the analysis of the base model, a set of tests were developed to complement the results obtained in the previous section. First, we analyse the financial incentive required by respondents to favour a PHEV, rather than a conventional vehicle. We asked for the financial incentive needed for shaping the interest in purchasing a PHEV, rather than a similar combustion engine vehicle with a price gap of around €10,000[4]. This focus is relevant, as it helps to understand whether the Portuguese green tax reform establishes a financial incentive capable of shaping consumers’ behaviour.

Results suggest that the average financial incentive required is about €8,705, ranging from €7,618 and €9,793, with a 95% confidence interval. Surprisingly, the mean accounts for 87 per cent of the difference between the PHEV and a similar vehicle with a traditional combustion engine. That is to say, financial incentives are the main factor that triggers the interest of acquiring a PHEV, and the financial incentive should cover most of the difference between options. Surprisingly, some respondents require a financial incentive higher than this difference. Krause et al. (2016) already suggested that the appeal of financial incentives might be limited to offset the high prices of hybrid technologies. We confirm this understanding. Since factors other than financial incentives are not relevant, aspects such as battery life, charging time, the durability of the electrical components and access to qualified maintenance may be crucial for these respondents (Caperello and Kurani, 2012; Graham-Rowe et al., 2012) (Table IV).

A number of non-parametric tests were carried out to assess whether the incentive requested was sensitive to household size, vehicle size, level of education, income (net monthly) and residence (large city or small city).

Results did not return differences in the premium (financial incentive) required by each group. The sensitivity of the incentive requested for the household size is only significant at 11 per cent, which indicates variability between groups for the incentive requested to shape consumer’s behaviour.

Households composed of more than three people appear to request much higher financial incentives to influence acquisition choices.

The p-value for a Mann-Whitney test is of 0.018, thus rejecting the hypothesis of equality of distributions in both subsamples. The result reinforces the intuition that the size of the household is a driver to explain the optimal financial incentive required to trigger the acquisition of a PHEV.

The three models in our study revealed a significant relationship between access to financial incentives and interest in acquiring a PHEV. However, this relationship may be shaped by factors, such as education, income, and household size, amongst others. Table V presents estimates for the relation between access to financial incentives (F factor) and interest in acquiring a PHEV (INT factor). Samples were never divided into more than two levels for the different criteria, as a considerable number of responses were required to perform the analysis.

The coefficient between factors F and INT is not valid for respondents with undergraduate level education, from smaller cities, with household income above €2,000, and currently driving larger vehicles. The fact that financial incentives do not have a significant effect on PHEV interest amongst individuals from smaller cities and larger vehicles is consistent with the research of Krupa et al. (2014) and Hidrue et al. (2011). Contrary to Mannberg et al. (2014), in our study households with lower levels of income households exhibit a higher interest in acquiring a PHEV (Table V). The sample was divided into two groups to reach this conclusion, identifying families with net monthly income below and above the €2,000 threshold. One might argue that the limit to split our sample by level of income drives our results, yet our option for splitting at €2,000 accounts for two issues. First, up to this threshold is included 49.8 per cent of our sample and that the average disposable income of Portuguese families in a monthly basis in 2016, accordingly to in the National Statistics Office was about €2,200 (for 14 payments a year).

5. Conclusions

Financial incentives comprise a group of determinants for the acquisition of PHEVs (Ozaki and Sevastyanova, 2011; Krupa et al., 2014), although existent empirical evidence is not conclusive as to which determinant affects consumers’ behaviour the most. This study takes advantage of the implementation of the Portuguese green tax reform to assess whether financial incentives can influence the interest to acquire PHEVs. Grounded on the theoretical framework of Ozaki and Sevastyanova (2011), we develop an extended model to assess the effect of several factors on the interest for plug-in hybrids.

The model revealed a positive and significant effect of financial incentives over the interest to acquire a PHEV, which supports our research goal. Results did not confirm, however, the existence of a relationship between the interest for a plug-in hybrid and environmental awareness, technology, oil independence, image attributes, place of residence, level of education and household size.

The theoretical model drawn from existent literature exhibits a poor fit, revealing that there are inconsistencies between Ozaki and Sevastyanova’s (2011) framework and empirical evidence. We address two potential justifications for this misfit. First, cultural variables may be shaping consumers behaviour towards PHEV adoption (Qian and Yin, 2017). Portugal is a country with below average purchasing power in Europe, although levels of poverty are relatively low. The level of education is still far from the best patterns, and cultural aspects of the Portuguese population also differ from other countries within the Union. Second, our focus is on interests (ex ante) rather than on past choices (ex post), which is contrary to existent empirical evidence that focus on current drivers of greener vehicles (e.g. Ozaki and Sevastyanova, 2011).

A second model (modified model) was created, by excluding the technological factor, although reaffirmed the presence of a positive effect of access to financial incentives in the interest of acquiring PHEVs. Results, also show a positive effect for the size of the vehicle that respondents currently drive, which is in part in contradiction of with the conclusions of Ozaki and Sevastyanova (2011), Krupa et al. (2014), Deloitte (2010) and Hidrue et al. (2011). Insufficient communication about PHEV benefits (Rogers, 2003), ineffective educational programs (Spínola, 2015) and the environmental performance of the country (Wendling et al., 2018) may justify why the interest for PHEV acquisition of Portuguese drivers is primarily affected by the access to financial incentives. Surprisingly is that the technological factor is not supported in our model. This finding is in contrast to other international experiences. For instance, the case of Denmark (Mabit, 2014) and Norway (Orlov and Kallbekken, 2019) in which is technological factor of vehicles is relevant, while these countries are in 3rd and 14th position regarding the environmental performance index (Wendling et al., 2018), respectively.

Next, we simplified the theoretical model by eliminating all factors that did not explain the interest in acquiring a PHEV. However, this model continues to demonstrate a positive relationship between access to financial incentives and interest in acquiring PHEVs. The size of the vehicle currently driven by respondents also yields influence on the acquisition of plug-in hybrids. This simplified model exhibits acceptable adjustment values, reinforcing the idea that, out of a set of factors presented most by Ozaki and Sevastyanova (2011) with a sample of buyers of PHEV, only these two factors are, in fact, impacting the interest of non-users of greener vehicles. Follow-up tests suggest that interest in acquiring a PHEV is higher for lower-income households, residing in larger cities, with graduate education and currently driving smaller vehicles. Our results for the level of education are correlated with the findings of Mannberg et al. (2014) although their focus is on a country with a higher level of average education – Sweden. Larger cities are also more appealing for PHEV, as was already documented by Krupa et al. (2014) and Hidrue et al. (2011). Household size is not crucial to shaping consumers’ behaviour.

Despite the interesting findings and novelty of our study, limitations should be mentioned. The sample size although robust for statistical purposes does not allow complete generalisation to the interest of the Portuguese population in acquiring a PHEV. The survey was also sent to corporations to assess whether different patterns apply regarding the understanding of the green tax reform. However, the low response rate did not allow such analysis.

In this study, we extend the Ozaki and Sevastyanova (2011) framework, and findings are revealing. Future research can be conducted using the same framework exclusively for EV and also in markets in which the government exhibits a different attitude towards the adoption of environmental measures. Denmark is among others, an appealing market to focus on, as the government provides financial incentives and is also progressively restricting the use of combustion engine vehicles. Other avenues for future research also compare the interest in PHEV acquisition vs EV, giving the distinctive characteristics of both types of vehicles.

This study contributes to tax policy, by confirming the Government’s ability to influence drivers’ choices, although policies must account for characteristics of consumers. Those consumers who do not currently own a PHEV or an EV, do appreciate the incentives introduced by the green taxation reform, although this policy appears to be insufficient to trigger a large-scale effect. Cultural aspects may justify our conclusions, and further research on the topic is required. Our findings show that different countries need dissimilar policies to achieve the same worldwide objectives. Collectively, our results suggest that consumers in countries with below average purchasing power, and in countries less engaged in environmentally sustainable practices such as Portugal (Spínola, 2015; Wendling et al., 2018) the access to financial incentives appear to be superior in explaining the interest in PHEV than the experience from richer and more environmentally oriented predicts. Therefore, governments in countries with socio-economic and cultural conditions similar to Portugal should give primacy to financial incentives when implementing green tax reforms.


SEM: interest in acquiring a plug-in hybrid electric vehicle

Figure 1

SEM: interest in acquiring a plug-in hybrid electric vehicle

Simplified model

Figure 2

Simplified model

Sample composition and descriptive statistics

Panel A: Sample composition
Gender n % Education n %
Male 101 57.1 Elementary school 1 0.6
Female 75 42.4 Secondary school 57 32.2
No response 1 0.6 Undergraduate degree 79 44.6
Total 177 Master degree 39 22.0
Net monthly household income n % PhD 1 0.6
€0–€1,000 24 13.6 Total 177
€1,000–€2,000 64 36.2
€2,000–€3,000 57 32.2 Household size n %
€3,000–€4,000 18 10.2 1 16 9.0
>€4,000 14 7.9 2 24 13.6
Total 177 3 60 33.9
Residence n % 4 59 33.3
Lisbon (large city) 42 23.7 5 13 7.3
Porto (large city) 30 17.0 6 4 2.3
Other districts (smaller cities) 105 59.3 8 1 0.6
Total 177 Total 177
Panel B: Descriptive statistics
Subsample Mean Std Median Skewness Kurtosis
Household size 3.260 1.187 3.000 0.162 3.870
Age 34.38 12.68 30.00 0.480 2.040

Notes: Panel A below provides the frequency of responses for some factors that are included in the extension of the model from the study of Ozaki and Sevastyanova (2011). Descriptive statistics for household size are presented in Panel B

Model fit comparison: theoretical, modified and simplified model

Model fit indicators CMIN/df RMSEA GFI AGFI RMR
Theoretical model (Figure 1) 2.488 0.092 0.711 0.668 0.157
Modified model (Figure 1)a 2.071 0.078 0.753 0.714 0.102
Simplified model (Figure 2) 2.794 0.101 0.901 0.836 0.062
Reference values < 3 < 0.08 > 0.9 > 0.9 < 0.08

Notes: aIn the modified model, the technological factor was removed from the theoretical model and interactions between variables were added (e16-e17, e13-e25). This table includes indicators of model fit to evaluate the adequacy of all models. The goodness-of-fit statistic (GFI) and the adjusted goodness-of-fit statistic (AGFI) range from 0 to 1, with higher values being desired (Byrne, 1994). The GFI and the AGFI should exceed 0.9, and the χ2 statistics (CMIN/df) should be lower than 3 for a good fit. The root mean square error of approximation (RMSEA) and the root mean square residual (RMR) should both not exceed 0.08 (Hu and Bentler, 1999)

Estimates for the theoretical model, for the modified model and for the simplified model

Theoretical model (Figure 1) Modified model (Figure 1) Simplified model (Figure 2)
Estimate SE p-value Estimate SE p-value Estimate SE p-value
INT←F 0.257 0.097 0.008 0.199 0.089 0.025 0.267 0.096 0.005
INT←OP 0.055 0.107 0.607 0.121 0.104 0.243
INT←T 0.019 1.715 0.991
INT←E 0.043 0.174 0.807 0.046 0.139 0.744
INT←I 0.228 0.225 0.311 0.164 0.132 0.212
INT←VS 0.144 0.146 0.324 0.266 0.144 0.065 0.246 0.141 0.082
INT←R 0.07 0.143 0.626 ‒0.022 0.131 0.865
INT←INS 0.026 0.074 0.726 0.032 0.069 0.646
INT←HS 0.021 0.064 0.748 0.024 0.059 0.689
INT←EDUC 0.031 0.149 0.837 0.064 0.138 0.644

Note: This table presents the output from the SEM for both the theoretical model, for the modified model and also for the simplified model. In the modified model the technological factor is not included, and interactions between variables are added. In this simplified model the factors included are financial incentives (F) and vehicle size (VS). Significance level of 10 per cent

Mean of the financial incentive requested, by household size

Household size Mean n SD
1 8,437 16 7,731
2 8,000 24 5,367
3 6,592 60 4,694
4 10,260 59 8,219
5 9,231 13 8,156
6 20,250 4 17,424
8 12,000 1
Total 8,705 177 7,330

Notes: The table below shows the average financial incentive required in question 16, per dimension of the household. The price gap between the proposed options, PHEV or combustion engine vehicle, was set at €10,000. Question 16 is as follows: A Toyota Auris costs about €25,000, while the Toyota Prius Plug-in costs around €35,000, with features similar to the Auris. The difference in price is €10,000. What is the amount of premium (financial incentive) necessary for you to be interested in purchasing a Prius Plug-in, instead of an Auris?

Estimates (INT ← F), by group

Household size Monthly net household income
⩽3 > 3 ⩽ €2,000 > €2,000
p-value 0.038 0.081 p-value 0.070 0.403
Coefficient 0.128 0.203 Coefficient 0.166 0.400
Vehicle size Residence
Small Large Large city Small city
p-value 0.020 0.322 p-value 0.025 0.459
Coefficient 0.189 0.084 Coefficient 0.199 0.064
Education level
Underg. Grad.
p-value 0.419 0.000
Coefficient −0.088 0.214

Note: This table presents the simplified model for groups of variables, which aims to test if the relationship between access to financial incentives and the intention to acquire a PHEV is different within groups. Significance level of 10 per cent



The Minister for the Environment, Territory Planning, and Energy at the Portuguese Parliament on 26 November 2014: “Madam President and Honourable Members, let us make no mistake: this is not a debate on public finances and taxation, this is not a debate on energy and environmental policy; this is essentially a debate on a new model of development, growth, and employment. [...]. It was in the context of green growth that we decided to move forward with the green tax reform process 10 months ago, firstly because there is a need to improve efficiency in resources consumption, reduce energy dependence from abroad and to induce more sustainable activities and consumption behaviour, enhancing the freedom and responsibility of citizens and businesses” (Non-Official Translation).


To test the suitability of answers for each level of the Likert scale, we focus on the subject-to-variables ratio, in which ideal values should range from 5 to 10 (MacCallum et al., 1999; Garson, 2008). We combined responses that were chosen by less than five people to the closest category. The KMO test is of 0.784, and Bartlett’s test for sphericity yielded a χ2 of 2353.4, with 486 degrees of freedoms and sig. of 0.000. Bartlett’s test suggests that the sample has a normal multivariate distribution. However, the test is sensitive to deviations from the assumption of normal distribution of variables and, for large samples, it tends to reject the null hypothesis, even when correlations are small (Snedecor, 1989). The KMO test indicates an appropriate level of correlations between variables. The two tests, therefore, point to the existence of correlations between the variables, validating the factorial analysis.


The indicators GFI, AGFI and RMR improved to reach desired levels for the model fit. Despite the increase in the RMSEA, this indicator tends to favour models with a higher number of parameters. Taking into account that this simplified model was obtained after suppressing a considerable part of the parameters, the negative effect on the RMSEA was somehow expected. However, ideally, this value should be below 0.08, but it is also possible to accept a model if the value does not exceed 0.1 (Browne and Cudeck, 1992). The value of CMIN/df slightly deteriorates, although it remains at acceptable levels. The results of this simplified model are consistent with those of the other two models, maintaining the statistical significance and positive effect of access to financial incentives and car size for the interest in acquiring a plug-in hybrid.


A Toyota Auris costs about €25,000, while the Toyota Prius Plug-in costs around €35,000, with features similar to the Auris. The difference in price is €10,000.


Supplementary data available upon request from the author.


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Further reading

Carroll, A.B. (1999), “Corporate social responsibility: evolution of a definitional construct”, Business & Society, Vol. 38 No. 3, pp. 268-295.

Lopes, C.M.M. (2006), “The Portuguese tax system: complexity and enforceability”, Fiscalidade: Revista de Direito e Gestão Fiscal, Vol. 26/27, pp. 77-108.


The authors gratefully acknowledge financial support from FCT- Fundação para a Ciencia e Tecnologia (Portugal), national funding through research Grant No. UID/SOC/04521/2019.

Corresponding author

Victor Barros can be contacted at: