Date: 31-01-2018 By: Sven Hogenhuis
Student number: 10776176
Supervisors: Drs. P.V.Trietsch, M.Phil Study: Economie & Bedrijfskunde
Specialization: Financiering & Organisatie Ecs for Thesis: 12
University of Amsterdam
The Impact of a Corporate Investment
Announcement Involving Electric Vehicles
On the Market Value of Car Manufacturers
1
Abstract
The purpose of this study is to examine the effects of corporate investment announcements involving electric vehicles on the market value of car manufactures. Event study methodology was used to determine the impact on the market value in reference to corporate investment announcements. The abnormal returns of 219 announcements were collected from 23 car manufactures. These announcements were categorized in eight different groups, namely: production engineering, research & development, new plant & plant upgrade, battery development & production, EVs infrastructure and joint ventures. The average abnormal return of the entire dataset was 0.29% and was significantly higher than zero with a significance level of 1%. Only the average abnormal returns of the categories new plant & plant upgrade and battery development & production were significantly higher than zero with respectfully a significance level of 5% and 10%.
Hierbij verklaar ik, Sven Hogenhuis, dat ik deze scriptie zelfgeschreven heb en dat ik de volledige verantwoordelijkheid op me neem voor de inhoud ervan.
Ik bevestig dat de tekst en het werk dat in deze scriptie gepresenteerd wordt origineel is en dat ik geen gebruik heb gemaakt van andere bronnen dan die welke in de tekst en in de referenties worden genoemd.
De Faculteit Economie en Bedrijfskunde is alleen verantwoordelijk voor de begeleiding tot het inleveren van de scriptie, niet voor de inhoud.
2
Table of Contents
1. Introduction ... 2
1.1 Problem definition ... 3
1.2 Search strategy & paper structure ... 4
2. Theoretical Background ... 6
2.1 What is the definition of a corporate investment? ... 6
2.2 Impact of an investment announcement on the market value of a company ... 6
2.3 Investment activities contributing to the development, production and sales of
electric vehicles ... 7
3. Data & Methodology ... 10
3.1 Sample selection ... 10
3.2 Announcement selection ... 11
3.3 Data processing ... 12
4. Results ... 14
4.1 Results found by conducting a t-test ... 14
4.2 Results found by conducting a sign test ... 15
5. Conclusion ... 17
6. Discussion, Limitations and Recommendations ... 18
6.1 Discussion ... 18
6.2 Limitations ... 18
6.3 Recommendations ... 18
Literature List ... 20
Appendices ... 25
Appendix A | List of the investment announcements categorized by car manufacture. .... 25
Appendix B | Histograms and boxplots ... 29
1. Introduction
3
1.1 Problem definition
The electric vehicle (EV) market is evolving rapidly. In 2016 over 2 million electric cars were used, whereas in 2015 the car stock was just over 1 million. Sales of EVs hit a new record with over 750 thousand units sold worldwide (IEA, 2017). There are multiple causes for the increase in popularity of EVs.
The climate goals set in the Paris Agreement (United Nations, 2015) played a underlying role, when it comes to the increase in popularity of EVs. For instance, as result of the Paris Agreement, the EU has set a main goal to reduce the greenhouse gas emissions by at least 40% by 2030 compared to 1990 (European Council, 2017). To realize these climate goals, strict rules concerning car emissions are being introduced, resulting in a higher tax rate for cars with high emissions (IEA, 2017). France and the United Kingdom even announced a ban on sales of car with internal combustion engines in 2040 (Ryan & Shankleman, 2017). Other countries installed financial incentives to make EVs more attractive to buy (IEA, 2017). Thomas (2009) stated that if all the internal combustion vehicles in the United States were replaced by EVs the greenhouse gasses would decrease with 44%. Moreover, the oil consumption would decrease by nearly 100%.
Another explanation for the increase in market share could be the batteries used in EVs. The Lithium-ion batteries used today have improved, both in reliability and power storage. (Zhang et all., 2017). As result of this development the EVs have longer range than before, increasing to a point where the mileage will almost be the same as a conventional internal combustion vehicle. Furthermore, costs of these batteries will keep declining in the future; meaning the price of an electric car will decrease (US Department of Energy, 2017).
According to Dijk, Orsato & Kemp (2013), the growing popularity in EVs is due to increasing environmental concerns, more efficient batteries and lower overall driving costs. This could imply that car manufactures are choosing to diversify their fleet, not only offering vehicles that run on fossil fuels, but also vehicles that are battery powered. Car manufactures sometimes even radically change their sales strategy, from selling conventional internal combustion vehicles to exclusively selling EVs and Hybrid cars in the future (Behrmann & Rolander, 2017).
Consequently, due to the shift to EVs, investments need to be made by the car manufactures. These investments include research and development, production engineering investments and investments in new plants or plant renewal (Lienert, 2018). When car manufactures are publicly traded, investments need to be announced. These announcements could have an impact on the market value of the company. Ramiah, Martin & Moosa (2013) stated that an announcement of green policies can have a strong impact on the stock returns for all kinds of industries. There is multiple research on the effect of announcements on the market value of a company, for example: Jones, Danbolt & Hirst (2007), Chan, Gau & Wang (1995), Dos Santos, Peffers & Mauer (1993) and Yung, Lu and Zhou
4
(2014). Nevertheless, there is a lack of research concerning the impact of investment announcement involving EVs on the market value of car manufactures.
This paper aims to clarify the effect on the market value of a car manufacturer announcing a corporate investment in EVs, by introducing the following research question:
Does a corporate investment announcement, from a car manufacturer,
involving electric vehicles have a positive impact its market value?
To formulate an answer on this question, three questions need to be clarified first. These sub-questions will give insights to answer the main research question. The sub-sub-questions are:
What is the definition of a corporate investment?
What is believed to be the impact on the market value of a company when announcing a corporate investment?
What kinds of investment activities are contributing to the development, production and sales of electric vehicles?
The sub-questions are answered by reviewing the literature available on the subjects: investment announcement and electric vehicles. After having insight on these sub-questions, the research question is answered by conducting quantitative research using the event study methodology.
1.2 Search strategy & paper structure
An extensive literature review was performed to answer the sub-questions stated above. The relevant information and research papers from the academic world were collected from the online library of the University of Amsterdam (UvA) named CataloguePlus. Terms as ‘electric vehicles’, ‘announcements’, ‘investment’, ‘event study’ and ‘automotive industry’ were used to find the right academic research papers. The papers consulted were from leading journals, such as The Journal of Financial Economics, The European Journal of Finance and Energy Policy. Because, Elsevier published most of the journals used, their database was also scanned separately for more papers on the relevant topics associated with investment announcements and EVs.
An event study was performed to find a conclusion on the research question. The paper of F. Jong (2007) and the research of Brown and Warner (1980) were used to gain a better understanding on performing an event study. DataStream was used to find the corresponding returns of all the car
5
manufactures represented. The daily returns from January 1, 2005 until thirty-first of December 2017 were used to identify the abnormal returns.
The news article database LexisNexis was used to find all the investment announcements involving electric vehicles done by car manufactures. For each car manufacture the search terms ‘invest’, ‘investment’ and ‘electric’ were used. The longlist generated was filtered for the years 2008 until 2017. This process identified a total of 219 announcements.
This paper contains six chapters. Chapter 2 gives the theoretical background, presenting the definition of a corporate investment, explaining the impact of a corporate investment announcement on the market value of a company and elaborating on the kinds of corporate investments support the growth of the EV market. The third chapter gives insight on the methodology used to solve the formulated research question. The results of the event study are presented in chapter four and in chapter five the overall conclusion is given. Lastly, there is room for discussion and recommendations. In this last chapter, the flaws and setbacks of the study are altercated and recommendations for additional research are given. A literature list and appendix have been added at the end of this paper.
6
2. Theoretical Background
This chapter will give insight on the sub-questions mentioned in chapter one by conducting a literature review. The first paragraph discusses the general impact on the market value of a company when it is announcing a corporate investment. The second paragraph explains the definition of a corporate investment and the third paragraph elaborates on the different kinds of corporate investments contributing to the development, production and sales of electric vehicles.
2.1 What is the definition of a corporate investment?
To better understand why there is an impact on market value by a corporate investment announcement, it is useful to set a definition of a corporate investment. The Cambridge Dictionary (2018) defines a corporate investment as “an act of putting money, effort, time, etc. into something to make a profit or
get an advantage”.
In research conducted by Grabowski (2014), a corporate investment consists of four elements. First of all, a corporate investment is a contribution of money or assets. Secondly, there is a certain time period in which an investment is installed. Thirdly, investments have an element of risk. Lastly, corporate investments contribute to the economic development of the host, the host being the company initiating the investment.
This clarification of the definition of a corporate investment assist in a further understanding of the main research question. The following paragraph will elaborate on the impact of a corporate investment announcement on the market value of a company.
2.2
Impact of an investment announcement on the market value of a
company
An announcement is defined as an official statement given by someone to give information about something (The Cambridge Dictionary, 2017). Multiple studies have empirically researched the impact of a corporate investment announcement on stock returns. These studies implicate that, on average, a corporate investment announcement has a positive effect on the market value (McConnell and Muscarella, 1985; Chen, 2006). In addition, investments are expected to affect the long-term performance of a firm. As Fama (1970; 1991) describes in his papers, when stock markets are efficient, an announcement of a corporate investment could result in a reaction of the stock market adjusting the company’s market value by the change in expected value of the investment.
Furthermore, other research concluded an increase in capital budget the year before the announcement could develop in a positive abnormal return in the announcement period (McConnell & Muscarella, 1985). Chan et al. (1990) found a positive abnormal return when research and development (R&D) investments increased. Although, when researching low tech companies the
7
abnormal returns were negative in correlation with R&D investments (Chan et al. 1995). Together this shows that the market can identify and separate good investments form bad investments.
Also, Dos Santos, Peffers & Mauer (1993) saw that an innovative investment announcement in the IT sector increased the market value of a firm while conservative investment did not. It goes without saying that this does not need to be the case for the automobile sector, but it is valuable knowledge going into to this research.
Additionally, it can be concluded that a negative investment announcement, such as a cut in the capital budget, has an unfavorable effect on the market value as described in a study by Goel & Shawky (2009).
Results of a study by Jones, Danbolt & Hirst (2004) found a positive average abnormal return in reference to a corporate investment announcement. Their paper concluded the market to react more in favor to investments that create new opportunities, than investments that do not create new opportunities.
After considering the information given in this paragraph altogether, there is sufficient evidence to suggest that an investment announcement, in general, is positively correlated with the market value of a firm given this announcement is positive, innovative and has a good future prospect. The EV sector is considered to be innovative and increasingly popular (Dijk et al., 2013). This could indicate that the abnormal returns are positively different form zero. The next paragraph will expound the types of investment activities that contribute to the development, production and sales of electric vehicles.
2.3 Investment activities contributing to the development, production
and sales of electric vehicles
One of the main challenges of driving electric is the high cost of the technology needed to propel the vehicle (Catenacci, 2013). Battery powered vehicles are more expensive than the normal internal combustion engine vehicles. Reasons for the difference in price are the initial investments. These investments are higher compared to the investments required for internal combustion engine vehicles (Kley et al., 2011). However, Weiss et al. (2012) explains that, due to technological advancements, the price of an EV will decline in time. Reason for this decrease in cost is corporate investment in R&D of lithium-ion battery packs (Wood, 2015), which increases the efficiency of the batteries and thus lowers the price. Therefore, the development and production of batteries is seen as one of the activities that car manufactures need to invest in.
The battery provides the energy needed to propel the vehicle. This battery in charged at a charging station while parked via a cord that is connected to the power grid. The charging of the battery takes longer than filling up the fuel tank of a conventional vehicle. Charging usually takes place at home or at work (Davies & Kurani, 2013). However, as He et al. (2013) explains, to insure the growth of the EV market, it is crucial to establish a public charging infrastructure. Moreover, the time period of charging needs to decrease to compete with convention vehicles (Meintz et al., 2017). Meintz
8
et al. (2017) also state that fast charging stations are the solution for this problem, enabling EV driver to travel longer distances in a faster time period. Multiple car manufactures are already investing in public charging stations (Campbell, 2017). Although, additional investments in charging stations need to be made to safeguard the growth of the EV market, that is why charging infrastructure is the second activity to invest in as car manufacture.
Another investment activity for car manufactures is R&D. Lichtenberg & Siegel (1989) found a positive correlation between R&D investment and the returns of a company in general. Multiple studies dating back to 1958 (Griliches, 1958; Chauvin & Hirschey, 1993; Sharma, 2011; Wang et all., 2017), show the same evidence. R&D expenditures of EVs include, for instance, the electric motor. Developing and testing the electric motor could result in a more efficient use of the energy provided by the battery (Doppelbauer & Winzer, 2017). Advanced electric motors could give an advantage on the competition; hence investing in R&D could result in higher returns.
When the board of a car manufacture approves a new EV model for mass production, cost will occur for the development of the complex components for EVs. Investments in product engineering could lead to lower development costs and improve the quality and of the product (Hong et al., 2006). This is favourable, because the market share of the car manufacture could increase when the product is of a higher quality than the product of the competition. This is acknowledged by Cantner, Krüger & Söllner (2012). The investments in product engineering can be seen as an investment activity that could contribute to the manufacturing of EVs. Hence, the inclusion of this investment activity as one that contributes to the EV market.
A substantial amount of corporate investing goes to building new manufacturing facilities and to the renewal of old facilities. Toyota and Mazda invested $1.6 billion in a new factory in the United States (Riley, 2017). Building new plants and upgrading old facilities is necessary when manufacturing a new model or when the facility is out-dated and not efficient anymore. Inefficiency can lead to higher costs, which are unfavourable. Hence investments in this activity could proof useful.
Car manufactures often join forces to invest in multiple activities, such as R&D and production engineering and manufacturing (Inkpen, 2008). A joint venture is a construction where two or more firms invest in the same activity together, by creating a new firm together. The parties usually invest an equal share of the total investment sum (Geringer & Hebert, 1989). The main reason for a joint venture is to share the cost of investment activity and gain knowledge from each other. This could lead to an advantage over the competition (Cambre-Fierro, 2011). One of the latest joint ventures is a 50-50 partnership between Ford Motor Company and the Chinese car manufacture Anhui Zotye Automobile. This joint venture will solely focus on building EVs (Tovey, 2017). After reviewing the information on joint ventures, it can be concluded that this investment activity is contributing to the production of electric vehicles.
The above-named investment activities will from a classification for the corporate investments announcements collected for this study. Section 3.2 will elaborate more on the specific groups formed.
9
These groups will increase the level of understanding regarding what kind of investment announcement have a greater impact on the market value of a car manufacture. This could be vital information to form a conclusion. The next chapter will discuss the methodology adopted to answer the main research question.
10
3. Data & Methodology
This chapter will give insight on the methodology used to formulate the main research question. The chapter consists of three paragraphs, starting with the sample selection. The second paragraph elaborates on the selection of the corporate investment announcements. The last paragraph discusses the processing of the data.
3.1 Sample selection
A sample selection of 23 car manufactures was constructed using DataStream. The sample of car manufactures is worldwide orientated and the companies are publicly traded. This sample represents the market well, because these are the only public traded car manufactures that have invested in electric vehicles till the end of 2017. Table 3.1 shows all the car manufactures that are included in the sample.
Table 3.1: Sample of Car Manufactures
Audi AG Hyundai Motor Group Anhui Jianghuai Automobile co., Ltd. Mitsubishi Motors Corporation Brilliance AUTV. HDG. Nissan Motor co., Ltd
BMW AG Porsche AG BYD Auto PSA Groupe Daimler AG Renault S.A. Fiat Chrysler TATA Motors Ford Motor Company Tesla Inc.
Geely Automobile Toyota Motor Corporation General Motors Corporation Volkswagen AG
Great Wall Motor Co. Volvo Car Corporation Honda Motor Company, Ltd.
Table 3.1: Sample of the 23 car manufactures in alphabetic order. The car manufactures represent the total population, because these companies are the only publicly traded car manufactures that announced investments contributing towards the EV market.
The stock prices, starting from January first 2005 till December thirty-first 2017, were collected. Only General Motors Corporation and Tesla Inc. have shorter periods due to two different reasons. Firstly, as a result of bankruptcy in 2008 (Vlasic, 2008), General Motors Corporation only has stock price data starting from October 17, 2010. Secondly, Tesla Inc. initial public offering (IPO) was on the
twenty-11
ninth of June 2010 (Nasdaq, 2017), hence no data exist before this date. The daily returns of the stock prices were calculated by dividing the appreciation of the price with the original stock price. The mathematical formula is shown below.
𝑆𝑡𝑜𝑐𝑘 𝑅𝑒𝑡𝑢𝑟𝑛 = (𝑃!− 𝑃!) 𝑃!
𝑃! is the initial stock price and 𝑃!is the stock price at the end of the period, which in this case is the stock price the next day and therefore the appreciation.
The next step is to identify the corporate investment announcement made by these companies. The following paragraph will be disclosing the manner in which these announcements were found.
3.2 Announcement selection
The announcements were found using the newspaper database LexisNexis. The search terms: ‘invest’, ‘investment’, and ‘electric’ gave an excellent backbone to start with. The next step was to filter the news articles on the car manufactures and time period. The time period used was from January 1 2008 until the thirty-first of December 2017. When the database showed multiple articles with the same investment activity on the same date or a day later, the first article with the earliest date was included in the sample. The total amount of investments announcement found was 219.
Table 3.2: the different kinds of investment activities arranged by number of observations and the
average number of announcement per company. The average number of announcement per company shows that not all companies invest in the same activities. Battery development and production is invested in the most by companies, whereas EVs infrastructure is invested in the least by companies.
The announcements were categorized by the investment activities discussed in in section 2, namely: New Plant & Plant upgrades, Production engineering, Research & Development, Battery Development & Production, EVs Infrastructure and Joint Ventures. The table 3.2 portrays all the groups with the
Investment
Announcement Category
Number of Observations
Average no. of
Announcement per Company
New Plant & Plant Upgrades 53 2.52
Production engineering 52 2.47
Research & Development 33 2.20
Battery Development & Production 29 1.81
EVs Infrastructure 22 3.14
Joint Ventures 29 2.07
Total 219 9.52
12
number of observed announcements and the average amount of announcement per category for a car manufacture. The average number of announcements by a company was 9.52. The company with the highest number of announcements is Daimler AG with 21 announcements. The lowest number of announcements was made by TATA Motors with only three announcements to account for. The average number of announcement per company shows that the investment activity ‘EVs Infrastructure’ was implemented by the lowest number of companies, whereas ‘Battery development & Production was initiated by the most companies. A full list of the event dates and investment announcements, with corresponding investment activity is included in Appendix A.
3.3 Data processing
Event study methodology was used to find an answer to the main question. An event study examines the behavior of firms’ stock price around corporate events (Kothari and Warner, 2004). The corporate events in this case are the corporate investment announcements made by the car manufactures.
The main purpose of an event study is to find the abnormal return corresponding with the event. In this study, the mean adjusted return method is used to calculate the abnormal returns. Abnormal returns (𝐴𝑅!) are determined by the return in the event window (𝑅!) minus the normal return (𝑁𝑅!). The equation used is shown below.
𝐴𝑅! = 𝑅!− 𝑁𝑅!
Since a corporate investment announcement could have an effect before and after the actual announcement, an event window is created. This window consists of the day before and the day after the announcement. The average return of this 3-day period is listed as 𝑅!. An estimation of some parameter is necessary to establish the normal return. First of all, an estimation period needs to be decided. In this study, the estimation period is 36months starting a month prior to the announcement. That is why stock returns dating all the way back to 2005 where needed to find the abnormal return for announcement done in 2008. Brown & Warner (1980) also used the 36-month period.
The month prior is chosen to exclude any biases in the calculation of the normal return. To abnormal returns shall be tested if they are significantly positively different form zero. The average of the abnormal returns of al the events was calculated by dividing the total sum of the abnormal returns by the number of observations, creating the cumulative abnormal returns (𝐶𝐴𝑅!). The formula for this calculation is shown below.
𝐶𝐴𝑅! = 1 𝑁× 𝐴𝑅!
13
After taking all of the above in account, a hypothesis was formed in order to clarify the main research question.
Hypothesis 0: The total average abnormal return does not differ from zero.
Hypothesis 1: The total average abnormal return positively differs from zero.
The hypothesis given above only takes the whole sample in consideration. Therefore, Eight sub hypotheses have been formed to see whether the abnormal returns for each investment activity differ positively from zero. These hypotheses are constructed the same was as hypothesis 1 and are shown below. All the hypotheses are tested one-sided.
Hypothesis 1a: The average abnormal return of the investment activity “New Plant & Plant Upgrades” differs positively from zero.
Hypothesis 1b: The average abnormal return of the investment activity “Product Engineering” differs positively from zero.
Hypothesis 1c: The average abnormal return of the investment activity “Research & Development” differs positively from zero.
Hypothesis 1d: The average abnormal return of the investment activity “Battery Development & Production” differs positively from zero.
Hypothesis 1e: The average abnormal return of the investment activity “EVs Infrastructure” differs positively from zero.
Hypothesis 1f: The average abnormal return of the investment activity “Joint Ventures” differs positively from zero.
14
4. Results
4.1 Results found by conducting a t-test
Table 4.1 shows the average abnormal return for the total dataset and for each investment category. The table also illustrate the t-test results, standard deviation, number of positive and negative observations and the confidence intervals for the dataset as a whole and for each category. The abnormal return value for the overall dataset is 0.29%, and is significantly different from zero with a significance level of 1%. The null hypothesis is therefore rejected. This is in line with previous studies mentioned in chapter 2.
Table 4.1: This table shows the results of the t-test performed to see whether the assumption that an investment announcement involving EVs has a positive impact on the market value of a car manufacture holds. *, ** And *** represents that the p-value is lower than respectfully 10%, 5% and 1% significance level. The values in brackets in the column “Mean” represent the t-values
‘Obs.’ stands for the number of observations, ‘Std. dev.’ stands for standard deviation and ‘Pos./Neg.’ stands for the number of positive and negative abnormal return values.
The category “New Plant & Upgrade Plant” is significantly different from zero with a significance level of 5% and “Battery development & Production” is significantly different from zero with a significance level of 10%. This means there is sufficient evidence to reject the null sub-hypothesis of a and d. However, the other investment activities are not significantly different from zero. This is in contradiction with previous studies, which suggested, if a corporate investment announcement is positive, innovative and has good prospects for the future, the abnormal return should significantly be higher than zero.
Investment Announcements Obs. Mean Std. dev. Confidence interval
Product Engineering 52 0.0002
(0.10) 0.0130 -0.0034 0.0038
Research & Development 33 0.0038
(1.24) 0.0177 -0.0025 0.0101
New Plant & Upgrade Plant 53 0.0039**
(2.05) 0.0140 0.0000 0.0078
Battery development & Production 29 0.0042*
(1.43) 0.0159 -0.0018 0.0103 EVs Infrastructure 22 0.0002 (0.10) 0.0105 -0.0044 0.0048 Joint Ventures 29 0.0051 (1.13) 0.0241 -0.0041 0.0143 Total 219 0.0029*** (2.67) 0.0159 0.0008 0.0050
Table 4.1 Descriptive data and t-test results
15
A reason for the contradicting findings could have been caused by the distribution of the categories being different than the overall dataset or due to the low number of observations in some of the categories. Therefore, a Skewness/Kurtosis test for normality was conduct. The result showed that the complete dataset and the categories ‘New plant & Plant Upgrade’, ‘Research & Development’ and ‘Joint Ventures’ had p-values smaller than a significance level of 1%, which suggested that the data of these variables were not normally distributed. When a significance level of 10% was applied, the category ‘Battery Development & Production” would also be considered not normally distributed with a p-value of 0.0603. Table 4.2 shows the result of the Skewness/Kurtosis test for normality.
Table 4.2 Results of the Skewness/Kurtosis test for normality
Investment Announcements Obs. Probability of Skewness
Probability of
Kurtosis 𝐶ℎ𝑖
!
Product Engineering 52 0.5614 0.2264 (0.3888) 1.89
Research & Development 33 0.0001 0.0012 18.95*** (0.0001)
New Plant & Upgrade Plant 53 0.0000 0.0000 31.46*** (0.0000)
Battery development &
Production 29 0.0419 0.1812 5.62* (0.0603) EVs Infrastructure 22 0.7594 0.8805 (0.9435) 0.12 Joint Ventures 29 0.0000 0.0001 24.96*** (0.0000) Total 219 0.0000 0.0000 (0.0000) .***
Table 4.2: This table shows the result of the Skewness/Kurtosis test for normality. *** Stands for the 1% significance level, whereas * stand for the 10% significance level. The numbers in the brackets represents the p-values of the corresponding chi2. The categories new plant and plant upgrades, research and development and joint venture, as well as the entire dataset suggest, with a significance level of 1%, that their distribution is not normal. The category battery development and production shows the same results for a significance level of 10%.
Dyckman et al. (1984) concluded that, when testing abnormal returns, the use of the t-test does not alter the outcome not normally distributed for a leptokurtic distribution. A distribution is leptokurtic when there is a high concentration of data at the mean with long tails. After examining the histograms and boxplots of the entire dataset and the separate categories, it is assumed that the total dataset and the different categories are from a leptokurtic distribution. The histograms and boxplots are stated in appendix B. Nevertheless, a non-parametric sign test was conducted to determine the significance of the abnormal returns.
4.2 Results found by conducting a sign test
The results of the sign test do not make a difference considering the categories that were not significantly greater than zero found in the t-test performed in section 4.1. However, the categories that seemed to be not normally distributed by the Skewness/Kurtosis test of normality show a p-value
16
greater than the highest significance level of 10%, which means that the sub-hypotheses a, c and f are considered not accepted. In addition, the category “Battery Development & Production” is not significantly different from zero using the sign test.
Only the p-value of the average abnormal returns of the total dataset is smaller than the 5% significance level. The p-value for the total dataset is 0.0393, thus there is sufficient evidence to suggest that the null hypotheses could be rejected. The p-value, positive and negative observations are all shown in table 4.3. This could be explained by the sign test being not as accurate as the t-test.
Table 4.3 sign test results
Investment Announcements Positive Observations Negative Observations p-value Production engineering 27 25 0.4449
Research & Development 20 13 0.1481
New Plant & Plant Upgrade 31 31 0.1358
Battery development & Production 17 17 0.2291
EVs Infrastructure 11 11 0.5841
Joint Ventures 16 13 0.3555
Total 118 101 0.0393**
Table 4.3: this table shows the results of the sign test performed. The 5% significance level is denoted as **. Only the total dataset is significantly higher than zero with a significance level of 5%. The t-test portrayed in 4.1 gave the same result only with a lower significance level. This makes the t-test more accurate than the sign test.
17
5. Conclusion
This research was conducted to find an answer on the question: ‘Does a corporate investment
announcement from a car manufacture involving electric vehicles have a positive impact on the market value?’. A quantitative study was carried out and the event study methodology was used to find the
abnormal returns of the investment announcement dates. Calculating these returns and testing whether the average abnormal returns differ positively from zero can provide an answer on the main question.
Three sub-question where introduced to better understand and to give a more comprehensive answer to the main research question. The first sub-question corresponded to the impact of an announcement on the market value of a company in general. The literary review showed that, announcements declaring a positive and innovative investment with good future prospects impact the market value favorably.
The second sub-question clarified the definition of a corporate investment. It was stated by the Cambridge Dictionary and by research of Grabowski (2014), that a corporate investment is the act of putting money somewhere to get a profit later on. Corporate investment can also be divided into four elements, namely: (1) a contribution of money or assets, (2) it has a certain time period, (3) it has an element of risk and (4) is has a contribution to the economic development of the host.
The last sub-question gives insight on the different kinds of investment activities that contribute the EV market. From these activities a list of 8 categories was formed. These categories should have given better insight on the impact of different investment activities on the market value of a car manufacturer.
The results suggest that there is sufficient evidence with a significance level of 1% to assume that the mean of the abnormal return is positively different from zero, which implies that there is a positive impact on the market value of a car manufacturer, when a corporate investment is announced. Furthermore, there is sufficient evidence with a significance level of 5% that announcing an investment in building a new plant or upgrading an existing plant, positively impacts the market value of the car manufacture. The same holds for an investment announcement in the developing and production of batteries. The only difference is the significance level, which is 10% for the investment announcement in battery development and production.
18
6. Discussion, Limitations and Recommendations
6.1 Discussion
Although the results illustrated in chapter 4 and 5 are support earlier studies, such as the study of Jones et al., (2007), this only applies to the dataset as a whole. For most of the separate investment categories, there was evidence to suggest a positive average abnormal return. This is not in line with previous discussed literature. A reason for this outcome could be the number of observations. 219 observations are not enough when divided into 8 categories. Consequently, testing the smaller categories could result in not finding a significant difference, which is stated in other literature and thus harm the internal validity of this study. Construct validity could be in danger, when taking the selection of the categories into account. The categories were formed directly after reading the news articles about the investments. Perhaps it was better to first collect all the corporate investment announcements and sort them at a later stage.
6.2 Limitations
The data used in this paper had some limitations. First of all, the number of announcement may not represent the population due to their only being 219. This could have caused a type II error, since for many categories the null hypothesis was not rejected. Secondly, this study solely took in consideration the impact of investment announcements on the market value. It did not elaborate what kind of factors could altercate the abnormal returns. Control variables such as, firm size, size of investments and market capitalisation could have explained more in-depth why the hypothesis could be considered true or not. Thirdly, finding all the announcements and categorizing the announcements proved to be difficult, seeing not all announcements were clear or did not specify on the investment activity. Also, it could be useful to set the announcements on electric vehicles off to the announcements that are not associated with electric vehicles. Hereby, a comment could be made whether these announcement have a different outcome considering the impact on the market value. Finally, there was not enough time to extend this study further due to time restrains. This is unfortunate considering the topic is very interesting.
6.3 Recommendations
A few recommendations to improve further studies are given in this section. First of all, adding of explanatory variables and expanding the number of announcements could make improvement of this study. Although, this study showed a significant positive average normal return, it also tried to show what kind of investment could have a positive impact on the market value. Unfortunately, it failed to do so. Therefore, as recommendation for further research, explanatory variable such as, project size, firm size, and market capitalization should be added to improve the clarification on what kind of
19
factors play a role on the market value considering corporate investment announcements. Additionally, more announcements should be added to increase the sample size. In addition further research could add announcements that do not relate to electric vehicles.
20
Literature List
Announcement [Def. 1]. (n.d.). In The Cambridge Dictionary, Retrieved January 28, 2018, from https://dictionary.cambridge.org/dictionary/english/announcement.
Behrmann, E., Rolander, N., & Rauwald, C. (2017, July 05). Volvo Vaults to Volts, Planning to Pull Plug on Gasoline Engines. Retrieved January 29, 2018, from
http://www.bloomberg.com/news/articles/2017-07-05/volvo-cars-joins-electric-race-with-plan-for-five-battery-models
Brown, S. J., & Warner, J. B. (1980). Measuring security price performance. Journal of Financial
Economics,8(3), 205-258. doi:10.1016/0304-405x(80)90002-1
Cambra-Fierro, J., Florin, J., Perez, L., & Whitelock, J. (2011). Inter-firm market orientation as antecedent of knowledge transfer, innovation and value creation in networks. Management Decision,49(3), 444-467. doi:10.1108/00251741111120798
Cantner, U., Kruger, J. J., & Sollner, R. (2012). Product quality, product price, and share dynamics in the German compact car market. Industrial and Corporate Change,21(5), 1085-1115.
doi:10.1093/icc/dts002
Catenacci, M., Verdolini, E., & Fiorese, G. (2013). Going electric: expert survey on the future of battery technologies for electric vehicles. Energy Policy,61, 403-413.
Chan, S. H., Martin, J. D., & Kensinger, J. W. (1990). Corporate research and development expenditures and share value. Journal of Financial Economics,26(2), 255-276. doi:10.1016/0304-405x(90)90005-k Chan, S. H., Gau, G. W., & Wang, K. (1995). Stock Market Reaction to Capital Investment Decisions:
Evidence from Business Relocations. The Journal of Financial and Quantitative Analysis,30(1), 81. doi:10.2307/2331254
Chen, S. (2006). The Economic Impact of Corporate Capital Expenditures: Focused Firms versus Diversified Firms. Journal of Financial and Quantitative Analysis,41(2), 341-355.
doi:10.1017/s002210900000209x
Chauvin, K. W., Hirschey, M. (1993). Advertising, R&D Expenditures and the Market Value of the Firm. (Mergers and Acquisitions). Financial Management,22(4), 128-140.
21
Davies, J., & Kurani, K. S. (2013). Moving from assumption to observation: Implications for energy and emissions impacts of plug-in hybrid electric vehicles. Energy Policy,62, 550-560.
doi:10.1016/j.enpol.2013.06.126
De Jong, F. (2007). Event Study Methodology. Tilburg University.
Dijk, M., Orsato, R. J., & Kemp, R. (2013). The emergence of an electric mobility trajectory. Energy
Policy,52, 135-145. doi:10.1016/j.enpol.2012.04.024
Doppelbauer, M., & Winzer, P. (2017). A lighter motor for tomorrows electric car. IEEE Spectrum,54(7), 26-31. doi:10.1109/mspec.2017.7951719
Dyckman, T., Philbrick, D., & Stephan, J. (1984). A Comparison of Event Study Methodologies Using Daily Stock Returns: A Simulation Approach. Journal of Accounting Research,22, 1-30.
doi:10.2307/2490855
European Council. (2017, October 13). Council Conclusions on the Paris Agreement and Preparations for the UNFCCC Meetings. Retrieved January 12, 2018, from www.consillium.europa.ue/en/press/press-releases/2017/10/13/conclusions-paris-agreement-and-unfccc-meetings/
Fama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of
Finance,25(2), 383. doi:10.2307/2325486
Fama, E. F. (1991). Efficient Capital Markets: II. The Journal of Finance,46(5), 1575-1617. doi:10.1111/j.1540-6261.1991.tb04636.x
Geringer, J. M., & Hebert, L. (1989). Control and Performance of International Joint Ventures. Journal of
International Business Studies,20(2), 235-254. doi:10.1057/palgrave.jibs.8490359
Goel, S., & Shawky, H. A. (2009). Estimating the market impact of security breach announcements on firm values. Information & Management,46(7), 404-410. doi:10.1016/j.im.2009.06.005
Grabowski, A. (2014). The Definition of Investment un the ICSID Convention: A Defence of Salini. Chicago Journal of International Law,15(1), 13th ser., 287-308.
Griliches, Z. (1958). Research Costs and Social Returns: Hybrid Corn and Related Innovations. Journal of
22
He, F., Wu, D., Yin, Y., & Guan, Y. (2013). Optimal deployment of public charging stations for plug-in hybrid electric vehicles. Transportation Research Part B: Methodological,47, 87-101.
doi:10.1016/j.trb.2012.09.007
Inkpen, A. C. (2008). Knowledge transfer and International Joint Ventures: The Case of Nummi and General Motors. Strategic Management Journal,29(4),447-453.
International Energy Agency. (2017). Global EV Outlook 2017(Rep.). France: IEA Publications. Investment [Def. 1]. (n.d.). In The Cambridge Dictionary, Retrieved January 16, 2018, from
https://dictionary.cambridge.org/dictionary/english/investment.
Jones, E., Danbolt, J., & Hirst, I. (2004). Company Investment Announcements and The Market Value of The Firm. The European Journal of Finance,10(5), 437-452.
Kley, F., Lerch, C., & Dallinger, D. (2011). New business models for electric cars—A holistic approach. Energy Policy,39(6), 3392-3403. doi:10.1016/j.enpol.2011.03.036
Kothari, S., & Warner, J. B. (2004). The Econometrics of Event Studies. SSRN Electronic Journal. doi:10.2139/ssrn.608601
Lee, H. J., Ahn, H. J., Kim, J. W., & Park, S. J. (2006). Capturing and reusing knowledge in engineering change management: A case of automobile development. Information Systems Frontiers,8(5), 375-394. doi:10.1007/s10796-006-9009-0
Lichtenberg, F., & Siegel, D. (1989). The Impact of R&D Investment On Productivity - New Evidence Using Linked R&D-LRD Data. National Bureau of Economic research. doi:10.3386/w2901
Mcconnell, J., & Muscarella, C. (1985). Corporate capital expenditure decisions and the market value of the firm. Journal of Financial Economics,14(3), 399-422. doi:10.1016/0304-405x(85)90006-6 Meintz, A., Ahmed, S., Bloom, I., Burnham, A., Carlson, B., Dias, F., . . . Zhang, J. (2017). Enabling fast
charging – Introduction and overview. Journal of Power Sources,367, 216-227. doi:10.1016/j.jpowsour.2017.08.008
Nasdaq. (n.d.). TESLA, INC. (TSLA) IPO. Retrieved January 23, 2018, from http://www.nasdaq.com/markets/ipos/company/tesla-inc-665410-63240
23
Ramiah, V., Martin, B., & Moosa, I. (2013). How does the stock market react to the announcement of green policies? Journal of Banking & Finance,37(5), 1747-1758. doi:10.1016/j.jbankfin.2013.01.012 Riley, C. (2017, August 4). Toyota and Mazda to build $1.6 billion factory in the U.S ... Retrieved January
16, 2018, from money.cnn.com/2017/08/04/news/economy/mazda-toyota-jobs-factory-trump/index.html
Ryan, C., & Shankleman, J. (2017, July 25). U.K. Joins France, Says Goodbye to Fossil-Fuel Cars by 2040. Retrieved January 12, 2018, from http://www.bloomberg.com/news/articles/2017-07-25/u-k-to-ban-diesel-and-petrol-cars-from-2040-daily-telegraph
Santos, B. L., Peffers, K., & Mauer, D. C. (1993). The Impact of Information Technology Investment Announcements on the Market Value of the Firm. Information Systems Research,4(1), 1-23. doi:10.1287/isre.4.1.1
Sharma, M., (2011). Market Valuation of Research and Development Investments by Indian Firms.
Paradigm,15(1,2), 34-38. doi:10.1177/0971890720110106
Thomas, S. (2009). "how green are electric vehicles?". International Journal of Hydrogen Energy,37, 6053-6062.
Tovey, A. (2017, August 22). Ford plugs in to China's electric car market with joint venture. Retrieved January 25, 2018, from http://www.telegraph.co.uk/business/2017/08/22/ford-plugs-chinas-electric-car-market-joint-venture/
United Nations. (2015). The Paris Agreement(pp. 1-27, Rep.).
United States Department of Energy. (2017). Cost and Price Metrics for Automotive Lithium-Ion
Batteries(Rep.). Washington, United States of America: US DOE.
Vlasic, B. (2008, November 11). G.M., Once a Powerhouse, Pleads for Bailout. Retrieved January 25,
2018, from http://www.nytimes.com/2008/11/12/business/12auto.html
Wang, Y., Rong, D., Kai, S. K., & Weiguo, F. (2017). Effects of R&D policy choice on accounting performance and market value. R&D Management,47(4),545-556. doi:10.1111/radm.12225 Weiss, M., Patel, M. K., Junginger, M., Perujo, A., Bonnel, P., & Grootveld, G. V. (2012). On the
electrification of road transport - Learning rates and price forecasts for hybrid-electric and battery-electric vehicles. Energy Policy,48, 374-393. doi:10.1016/j.enpol.2012.05.038
24
White, A. J., Shepardson, D., Shirouzu, N., Carey, N., Frost, L., Sage, A., & Cremer, A. (2018, January 16). Global carmakers to invest at least $90 billion in electric vehicles. Retrieved January 14, 2018, from http://www.reuters.com/article/us-autoshow-detroit-electric/global-carmakers-to-invest-at-least-90-billion-in-electric-vehicles-idUSKBN1F42NW
Wood, D. L., Li, J., & Daniel, C. (2015). Prospects for reducing the processing cost of lithium ion batteries. Journal of Power Sources,275, 234-242. doi:10.1016/j.jpowsour.2014.11.019
Yang, J., Lu, W., & Zhou, C. (2014). The immediate impact of purchasing/sales contract announcements on the market value of firms: An empirical study in China. International Journal of Production
Economics,156, 169-179. doi:10.1016/j.ijpe.2014.06.002
Zhang, C., Cheng, G., Ju, Q., Zhang, W., Jiang, J., & Zhang, L. (2017). Study on Battery Pack Consistency Evolutions during Electric Vehicle Operation with Statistical Method. Energy Procedia,105, 3551-3556. doi:10.1016/j.egypro.2017.03.816
25
Appendices
Appendix A | List of the investment announcements categorized by car
manufacture.
The date of the announcements and type of announcement are also included. The values highlighted in yellow could not be used due to the bankruptcy of General Motors.
Company Event Dates Investment category
Audi 27/12/2010 27/12/2011 28/12/2012 27/12/2013 27/12/2014 28/12/2015 Production engineering Production engineering Production engineering Production engineering Production engineering Production engineering BMW 05/11/2010 21/02/2011 21/02/2011 09/07/2012 24/07/2012 13/05/2013 25/07/2013 09/05/2014 23/01/2015 02/09/2015 21/01/2016 28/01/2016 17/07/2017 17/09/2017 12/10/2017 27/11/2017 05/12/2017 16/12/2017 New Plant/Production Production engineering Research & development New plant & Plant Upgrade EVs infrastructure Production engineering EVs infrastructure New plant & Plant Upgrade EVs infrastructure EVs infrastructure New plant & Plant Upgrade EVs infrastructure New plant & Plant Upgrade Production engineering Joint venture Great wall motors Battery development & production EVs infrastructure Research & development Brilliance 13/11/2009 25/05/2013 06/12/2013 30/10/2017 New plant & Plant Upgrade Production engineering Production engineering Battery development & production BYD 29/09/2008 26/10/2009 07/11/2009 25/01/2010 27/05/2010 09/05/2011 04/05/2013 10/11/2013 15/07/2014 24/05/2016 15/07/2016 16/05/2017 07/06/2017 16/09/2017 15/11/2017 Joint venture Battery development & production Research & development Battery development & production Joint venture DAIMLER Battery development & production Joint venture DAIMLER New plant & Plant Upgrade New plant & Plant Upgrade New plant & Plant Upgrade Joint venture Production engineering Production engineering New plant & Plant Upgrade New plant & Plant Upgrade Daimler 20/06/2008 22/05/2009 08/10/2009 27/05/2010 28/01/2013 01/02/2013 04/05/2013 16/02/2016 Research & development Investment in Tesla New plant & Plant Upgrade Joint venture BYD Joint venture Ford, Nissan Joint venture with Other Company Joint venture BYD EVs infrastructure
26
06/04/2016 16/06/2016 22/09/2016 16/10/2016 29/11/2016 03/03/2017 21/03/2017 06/07/2017 17/07/2017 05/09/2017 14/09/2017 22/09/2017 17/11/2017 Battery development & production Research & development Production engineering New plant & Plant Upgrade EVs infrastructure EVs infrastructure Research & development Battery development & production Production engineering Production engineering EVs infrastructure New plant & Plant Upgrade Battery development & production Geely 12/03/2010 08/01/2016 08/01/2016 Production engineering New plant & Plant Upgrade Production engineering Great wall 01/06/2012 28/06/2013 28/09/2017 12/10/2017 Production engineering New plant & Plant Upgrade Battery development & production Joint venture BMW Fiat Chrysler 24/09/2008 27/05/2009 27/05/2009 12/01/2015 11/02/2016 14/06/2016 31/07/2017 Production engineering New plant & Plant Upgrade Production engineering New plant & Plant Upgrade Production engineering Joint venture Research & development Ford 06/04/2009 06/05/2009 09/12/2009 11/01/2010 18/03/2010 24/05/2010 25/10/2010 15/08/2012 28/01/2013 17/07/2013 12/10/2015 11/12/2015 03/01/2017 03/01/2017 15/02/2017 03/10/2017 08/11/2017 Battery development & production New plant & Plant Upgrade New plant & Plant Upgrade Production engineering New plant & Plant Upgrade Production engineering Production engineering Research & Development Joint venture NISSAN, DAIMLER Research & development Research & development Research & development New plant & Plant Upgrade Production engineering Research & development Research & development Production engineering General Motors 01/08/2008 13/08/2009 07/12/2009 07/12/2009 07/12/2009 26/01/2010 13/04/2010 03/08/2010 29/09/2010 01/11/2010 07/01/2011 26/01/2011 13/05/2011 13/06/2011 21/10/2011 19/10/2012 08/04/2014 08/04/2014 29/10/2014 New plant & Plant Upgrade Battery development & production New plant & Plant Upgrade New plant & Plant Upgrade Battery development & production New plant & Plant Upgrade Battery development & production Joint venture in other company New plant & Plant Upgrade Production engineering EVs infrastructure Battery development & production Production engineering Joint venture in other company Production engineering Production engineering New plant & Plant Upgrade Battery development & production New plant & Plant Upgrade
27
26/06/2015 11/06/2016 17/01/2017 30/06/2017 Production engineering New plant & Plant Upgrade Research & development Research & development Honda 21/05/2008 24/04/2010 10/01/2013 11/08/2013 10/01/2017 07/02/2017 07/12/2017 21/12/2017 Production engineering Production engineering New plant & Plant Upgrade Battery development & production New plant & Plant Upgrade Production engineering Battery development & production Production engineering Hyundai/KIA 27/10/2008 28/07/2010 29/12/2011 14/03/2012 03/04/2012 17/04/2014 06/01/2015 17/02/2016 Research & development Production engineering Research & development Battery development & production Battery development & production Research & development Research & development Production engineering JAC 22/06/2017 09/08/2010 08/09/2010 22/01/2013 20/05/2014 21/07/2015 18/11/2015 07/09/2016 Production engineering New plant & Plant Upgrade Battery development & production Production engineering Research & development Research & development Battery development & production Joint venture (with Volkswagen) Mitsubishi 18/03/2010 12/07/2010 12/10/2012 26/06/2013 10/12/2015 30/06/2016 19/12/2016 15/09/2017 New plant & Plant Upgrade Battery development & production New plant & Plant Upgrade EVs infrastructure Research & development New plant & Plant Upgrade Research & development Joint venture RENAULT NISSAN Nissan 09/07/2008 03/03/2009 13/04/2009 20/07/2009 18/03/2010 07/12/2010 15/09/2017 17/09/2017 Joint venture Renault Battery development & production Company from New plant & Plant Upgrade New plant & Plant Upgrade Joint venture RENAULT Joint venture RENAULT MITSUBISHI Production engineering PSA 03/12/2009 13/04/2010 16/07/2010 28/02/2011 15/11/2011 05/04/2016 28/09/2016 12/12/2016 06/12/2017 Joint venture china New plant & Plant Upgrade Research & development Research & development Research & development Production engineering Joint venture New plant & Plant Upgrade Production engineering Porsche 19/11/2011 18/07/2014 04/12/2015 04/12/2015 New plant & Plant Upgrade Research & development Production engineering New plant & Plant Upgrade Renault 21/01/2008 09/07/2008 03/03/2009 19/05/2009 13/04/2009 16/09/2009 Production engineering Joint venture Nissan Battery development & production Battery development & production Joint venture Production engineering
28
06/10/2009 06/11/2009 08/12/2009 29/01/2010 07/12/2010 15/06/2015 20/03/2017 15/09/2017 10/10/2017 New plant & Plant Upgrade New plant & Plant Upgrade Battery development & production Joint venture Joint venture NISSAN Production engineering Production engineering Joint venture NISSAN MITSUBISHI EVs infrastructure TATA Motors 18/09/2009 01/10/2012 21/12/2015 Production engineering New plant & Plant Upgrade Research & development Tesla* only check from 29/06/2013 23/10/2013 27/01/2014 21/04/2014 04/07/2014 29/08/2014 30/04/2015 02/09/2015 20/07/2016 03/12/2016 EVs infrastructure New plant & Plant Upgrade EVs infrastructure EVs infrastructure EVs infrastructure EVs infrastructure Battery development & production New plant & Plant Upgrade Production engineering Toyota 28/05/2008 21/05/2010 24/10/2011 24/07/2012 16/03/2017 10/04/2017 04/08/2017 15/09/2017 26/09/2017 26/06/2017 06/10/2017 18/12/2017 New plant & Plant Upgrade Investment in tesla New plant & Plant Upgrade New plant & Plant Upgrade Research & development New plant & Plant Upgrade New plant & Plant Upgrade Battery development & production New plant & Plant Upgrade New plant & Plant Upgrade New plant & Plant Upgrade Battery development & production Volkswagen 09/05/2008 09/06/2010 26/09/2011 21/11/2014 23/01/2015 18/02/2015 05/06/2015 15/06/2016 15/12/2016 11/09/2017 11/09/2017 16/11/2017 18/11/2017 19/12/2017 Battery development & production New plant & Plant Upgrade New plant & Plant Upgrade Research & development EVs infrastructure EVs infrastructure New plant & Plant Upgrade Battery development & production (location) EVs infrastructure Production engineering Battery development & production Production engineering Research & development EVs infrastructure Volvo 26/02/2011 18/07/2013 22/05/2017 06/11/2017 New plant & Plant Upgrade Research & development Research & development Production engineering
29
Appendix B | Histograms and boxplots
Histogram of the total dataset Histogram of the category EV infrastructure
Histogram of the category Joint Ventures Histogram of the category Engineering & Production
Histogram of the category Research & Development Histogram of the category Battery Development & production
Histogram of the category New Plant & Plant Upgrade
30
Boxplot of the total dataset and the categories.
The box plot should be interpreted as follows from top to bottom: the total dataset EV infrastructure, Joint Ventures, Product Engineering, Research & Development, New plant & Plant upgrades and Battery Development & Production.
