Business Analysis Methods in the European Car Market


The European automotive industry has long been a trailblazer for clean, efficient, and high-quality motor vehicles (Laux, 1992). Its rich history, dynamic market environment, and fierce competition are what shaped its economic landscape (European Automobile Manufacturer Association 2020). At present, Europe has grown to be a thriving economic hub. Some of the world’s car manufacturers with the largest market shares, such as VW Group (25.4%) and BMW Group (7%), originate in the Old World or have their headquarters here (Wagner, 2020). However, in the light of the recent events – namely, the major economic crisis following the COVID-19 outbreak – the dynamics are changing. ACEA (2020) reports that EU car sales will experience a projected 25% decline. Building resilience in times of hardship and in the face of fierce competition is something that allows any company to stay afloat (Holmes, 2020). Today, to make proper decisions and choose the best options, companies use business analysis that guides their actions. There are a variety of methods available for investigating a business case and gaining a deeper understanding of a company’s position on the market.

In the current business game, our team employs business analysis as a method for boosting our company’s competitiveness in the European car market and informing its strategic decisions. Therefore, the individual topic of this research is “Business analysis methods to enhance market strategy decisions in the European automotive industry.” The objectives of this paper can be summarized as follows:

  1. To identify the challenges and opportunities related to sales increases in the European automotive industry.
  2. To understand the role of competitors and market changes in the company’s market strategy.
  3. To explore simulation game reports and study the internal relationships across the company strategy, marketing strategy, and operational strategy.

The main body of the present paper is organized into two parts: the literature review and business analysis. The literature review summarizes recent and relevant research concerning the subject matter, namely, market competition, strategic management, operational management, and marketing. This subsection provides a comprehensive review of the role that business analysis plays in the modern business environment and its application in the European automotive industry in general. The second part, business analysis, touches upon communication and collaboration processes in our team. However, for the most part, the business analysis section focuses on the analysis of business game reports and critical reflection on their findings.

Literature Review

The Rationale for Individual Topic

Share in world automotive trade
Figure 1. Share in world automotive trade

The competitive automotive industry is vital to the European economy. As seen from Figure 1, the European automotive industry remains an undefeated giant of the global motor vehicle trade. Between the 1990s and the 2010s, Europe had been able to stay the leading region in terms of its global market share (around 52%) and see its main contender – North America – experience a slow but steady decline (Leonte & Orszaghova, 2013). Statista Research Department (2020) states that the United Kingdom ranks eighth among the world’s largest automotive exports, assuming the position between Mexico and Spain. With a market share of 18.1%, Germany is the absolute leader, while France, another thriving European economy, comes fifth with its market share of 4.5% (Koptyug, 2020; Marklines, 2020). As reported by ACEA (2020), an institution that represents European motor vehicle manufacturers, by 2020, Europe seeks to increase the industry’s share of the joint GDP up to an unprecedented 20%. To recapitulate, the European automotive industry is moving toward its ambitious goals; however, one should not forget that with rapid growth comes cutthroat competition.

The UK market does indeed enjoy the benefits of the thriving car industry as well as the vicinity of the world’s leading manufacturers – Germany and France. However, it is a double-edged sword, and the crowded market is dominated by well-established giants. Therefore, any UK-based company needs to be extremely strategic about its plans and long-term vision to gain competitive advantages (Meredith et al., 2017). This vision does translate into action: Holweg et al. (2009) observe that over the last few decades, the UK auto industry was able to depart from turbulence and poor labor relations and start offering competitive products.

It should be noted that for all the advantages that individual countries make on their own, the automotive industry, on the whole, is at a crossroads. In its white paper, IHS (2015) describes a concerning trend for automakers. Apparently, from the data provided, the car sales numbers are stagnating across the board (IHS, 2015; “Number of cars sold worldwide between 2010 and 2020”, 2020). They are practically flatlining on mature markets such as the European Union, the United States, and Japan. Winck (2019) links this phenomenon not only to the oversaturation of the global market but also to consumers’ changing views on car ownership. For many people belonging to the new generation, buying a car seems redundant. If they do want to do it, they do not settle, which further fuels competitiveness.

Harnessing the competitiveness of the automotive industry has been drawing the attention of the scientific community for quite a while now. Table 1 demonstrates the summary of key findings made by scholars regarding the subject matter. As seen in Table 1, almost all scholars point out that there is an ongoing paradigm shift in the automotive car industry. If before, it sufficed to establish cost leadership, today, the market conditions are becoming harsher and customers’ needs and preferences – more sophisticated. Some opinions cited in Table 1 contradict each other: for instance, while Holweg (2008) advocates for differentiation, Dietl et al. (2009) find that it is no longer enough. The general consensus may be found in the importance of product design and value creation to meet the ever-evolving needs of the customer.

Interestingly enough, not a single scholar or a group of scholars mentioned business analysis as a reliable source of competitive advantage for car companies. There might be two explanations for this rather peculiar pattern (Bonab, 2017). Firstly, in some countries, the automotive industry remains rigid and traditional, which makes it less receptive to cutting-edge technologies revolving around big data, artificial intelligence, and machine learning (Yannick, 2004; Aris et al., 2015). Secondly, a business analysis might be already implied when scholars discuss product development, strategic marketing, value creation, and other competitive advantages (Farhana & Bimenyimana, 2015). In this case, business analysis is not a competitive advantage on its own, but rather a sophisticated tool for boosting competitiveness (The International Institute for Business Analysis, 2012). Regardless of which explanation is true – a knowledge gap or covert implication, it is rather compelling to research the role of business analysis in the decision-making process. For this reason, the individual topic for this research is “Business analysis methods to enhance market strategy decisions in the European automotive industry.”

Table 1. Research summary regarding competitive advantages in the automotive industry (European and otherwise)

Research summary regarding competitive advantages in the automotive industry

Research summary regarding competitive advantages in the automotive industry

The Basic Concept of Business Analysis

Business analysis is a research discipline that seeks to identify the current needs of a business and offer solutions (Fleisher & Bensoussan, 2003). People who conduct business analysis – business analysts (BAs) – take a holistic view of an organization rather than focusing on particular aspects. Business analysis needs to be done in collaboration with a wide range of specialists to make sure that an organization undergoes a profound transformation that will take it to the next level of success, competitiveness, and sophistication. In essence, what a BA does is introduce and manage change in organizations, be they for-profit, non-profit, or state organizations (Magretta, 1999). This paper argues that robust business analysis is vital to any company’s competitiveness, especially when it comes to oversaturated, tough markets such as the European motor vehicle market.

The Influence of Competitors in The Market on a Company’s Strategy

Competition can be considered as one of the most important factors as it directly affects the success of a company. For example, it impacts the extent of the market share gained by a company, customers, and products. According to Gupta et al. (2016), those companies that constantly analyze their competitors, are more likely to gain higher profits and occupy a greater market share. Therefore, the main task for the effective application of competitive analysis is goal setting. Correct goals allow one to formulate hypotheses and focus on key information to verify them, which is obtained as a result of the given process (Doz & Prahalad, 2013). Making the most accurate forecast and analysis of potential actions of competitors is problematic (Rugraff, 2012). Moreover, the issue becomes more complicated when it comes to small enterprises (Jenkins & Williamson, 2015). At the same time, one should be aware that the actions of large firms are easier to predict due to their ability to quickly respond to changes in the competitive environment and take appropriate actions. However, the analysis of the competitive environment market should be carried out constantly and carefully.

It is important to understand that competitor analysis is an effective way to assess the goals of competing companies by identifying their weaknesses and strengths. It allows them to clarify opportunities and take into account the dangers that are associated with a particular business activity (Gupta et al., 2016). A thorough analysis of actions will be helpful in developing optimal solutions and actions for the successful development of the company in the automotive market. Effective building of a business strategy largely depends on the ability to predict the reactions of a company’s competitors to certain events, and business analysis can reliably support the given notion.

Decision Making in the Automotive Industry

First and foremost, business analysis informs the decision-making process. Therefore, to gain a deeper understanding of its role in the automobile industry, one needs to investigate how decisions are made in this field. Sissoko et al. (2018) write that akin to any other industry, car manufacturing requires a series of decisions, each of which is supported by data, modeling, and simulation. Monfared et al. (2002) emphasize the importance of the decision-making process: according to the researchers, modern manufacturing enterprises are forced to accommodate the continual change. If they are not able to do it, they risk becoming irrelevant and losing their competitive edge.

Aligned with changes are customer preferences. Lademann et al. (2001) state that the demand for cars is undergoing a shift of paradigm, probably, the main driver behind the change is the variety of alternative ways of purchasing care. The very decision-making process, preceding and accompanying the purchase, is transformed as customers are becoming more informed and able to access web data with more ease (Al-Fayad, 2018). Their taste is becoming more refined: a car transcends its physical characteristics and becomes a symbol of status, a personality extension, and a means of self-expression.

Business Analysis in the Automotive Industry

Like many other industries, the automotive industry succumbed to the reign of big data that is swaying the global business environment by offering tailored solutions and steering the direction of corporate development. Deloitte (2015) enlists the many advantages of using business analysis in the automotive industry. The experts state that at present, the automotive industry experiences a great deal of pressure regarding its supply chain capabilities. As Deloitte (2015) puts it, they are what can make or break a company. At best, business analysis gives businesses a competitive edge and drives growth. At worst, faulty or lacking business analysis puts automakers in all kinds of unfavorable scenarios with consequences ranging from shortages to government scrutiny and lost growth opportunities.

Like Lademann et al. (2001), Deloitte (2015) names ever-evolving customer preferences as one of the “why’s” of applying business analysis. According to Deloitte (2015), the role of the traditional car dealership, a longstanding companion of the automotive industry, is being questioned more than ever. However, even provided the knowledge is sufficient, the decision-making process is often impeded by various barriers, many of which are not unique to the automotive industry. They are not external threats but rather internal weaknesses. Goodwin and Wright (2014) state that any company requires decision support – a system in place that steers the process in the right direction, preferably with business data involved.

In reality, decisions are often postponed, which causes iterations and accumulation of financial and other costs. Goodwin & Wright (2014) point out that decision-makers and stakeholders have poor visibility on the entirety of the process and as complexity and uncertainty surge, there emerges more pressure to make irreversible, high-risk decisions. In addition, a single decision might directly influence the subsequent long-term outcomes and decision-making processes. For this reason, accurate business analysis is crucial to improve strategic decisions.


Research Methods

The present research started with a thorough literature review in order to understand the theoretical underpinnings of the subject matter and familiarize ourselves with the existing knowledge (DePoy & Gitlin, 2019). The purpose of the literature review was to identify the current needs and challenges of the automotive industry and the role that business analysis can play in resolving them. Apart from that, it was important to broaden our knowledge of the decision-making in the automotive industry and what barriers a business analysis can help to overcome.

According to Ghauri et al. (2020), research methods in business studies can be divided into two broad categories – qualitative and quantitative methods, which, of course, also apply to other fields of knowledge. For this study, we chose quantitative methods, namely, working with and analyzing numerical data. All our decisions in the business game can be quantified, which can be seen in Round logs, therefore, they translate into outcomes in a rather straightforward manner. There is no doubt that every method has its drawbacks: for instance, qualitative studies cannot draw large enough samples (Bell et al., 2018). On the other hand, quantitative studies do not provide insight into complex concepts such as motivation and emotions (Bell et al., 2018). However, narrowing down the scope of this study was a must; therefore, to maintain a necessary level of detail, we forewent qualitative methods.

Data Search and Collection

Data search and collection were vital to the robustness of the present research. The quality of data determines the quality of research findings, which is why it is important to ensure its relevance and accuracy (Whitney et al., 1998). Even with the help of the best statistical methods, it is nigh on impossible to gain meaningful insights into a problem at hand and inform business decisions. As mentioned before, this study almost exclusively uses quantitative, numerical data. The data utilized for the present research can be roughly put into two categories: external and internal.

External data are primarily presented in the literature review section: it entails scientific data, major business reports and white papers in the automotive industry, and country statistics. In the context of this study, external data help to put the analyzed problems in a larger context (Goicoechea & Fenollera, 2012). They make it possible to understand our company’s position on the market and in relationship to others. In turn, internal data not only supports the purpose of research but also allows for tailored decisions (Gareche et al., 2019). While broad trends affecting all players in the market do exist, no two companies are the same (Evans, 2017). Therefore, internal data are reflective of unique needs and challenges as well as the progress that a company is experiencing.

The rise of digital technologies made data search and collection easier than ever but at the same time, led to a vast amount of information noise (Sun et al., 2019). Sources of data are abundant, and the question arises as to which sources to trust and which to avoid. Our team complied with the basic guidelines for academic writing and only used reliable sources such as peer-reviewed scholarly publications and official statistical data (“Referencing,” n.d.). The preferred search engines were Google Scholar and the University of Liverpool online library for external data. As for internal data, it was sourced strictly from the Business Game portal.

The Process and Analysis of Business Game

Game Process and Roles

It is essential to note that the project team consisted of ten people, each of whom was assigned a certain role. After discussing the overall views on the game, it was decided to divide the team into five departments, which included marketing, sales, products, human resources, and finance. The division of labor was established in a way that it emphasized each person’s individual strengths. Since marketing was the main scope of my responsibility, it was within my primary tasks to analyze the market segmentation, market share, product price, and gross profit of competitors in the market (Nazir & Shavarebi, 2019). In addition, I also worked closely with the products department to control the production in response to market trends. At the end of each round, we had a group discussion where we evaluated our results and adjusted a strategy. We found that brainstorming for possible solutions helped us advance our strategy.

Business Analysis

Business Game Analysis

The given part provides an analysis of Rounds 5,9, and 12 as they were decisive in the overall success of the simulation. The sales during rounds 1-4 were underwhelming since our team has not completely understood the rules of the game. However, after the fourth round, following a group discussion, we started paying more attention to the customer preference survey of vehicle options that were displayed in market perception as seen in Table 2. For this reason, for the fifth round, we adjusted our care options according to the customer preference survey on popularity factors. As a result, we performed better in the fifth round – that was also when we introduced the fifth model car in order to limit the profitability of our competitors.

Table 2. Popularity Factors

Popularity Factors

In this simulation, teams are competing for market share, which means that they are selling similar products but trying to make them more attractive through differentiation and price leadership. Competitor analysis was critical to understand how we could tip the market dynamics in our favor. After the first four rounds, I discovered that the teams with relatively high gross profit were mostly occupying the luxury market segment because of the higher price for this type of vehicle. Yet, focusing on the luxury market segment poses its own set of risks as its share is not significant. Nevertheless, I considered it a blue ocean market – an untapped territory fills of potential, as shown in figure 2.

The number of models in round 4
Figure 2. The number of models in round 4

We made a decision to invest in the luxury market at a small cost, and prevent the other competing teams from making more sales through price leadership, which is one of Porter’s primary strategies (Bhatia, 2016). For instance, as seen in Table 3, G2T8 sold a total of 14,567 cars for 100,000 pounds, and, thus, took up a market share of 2.46%. Our team set a lower price (70,000 pounds) and produced 10,000 – less than the competitor’s team. Because of a smaller quantity of produced cars, we were able to achieve an optimally lower cost input. It was due to the lower price and superior configuration that we were able to limit the sales volume of this team in this market segment. Therefore, the G2T8’s market share in the luxury segment ended up being lost to us, and we were able to limit the G2T8’s total profit by shrinking its market share.

Table 3. The number of models in round 4

The number of models in round 4

Table 4 shows the results of our fifth round, where our team sold 9,607 cars. In other words, it means that almost all of our FTG-5 are sold as shown in Figure 3, and the luxury model of G2T8 has experienced a significant decline in sales. Therefore, our strategy can be considered an effective one. Since the effect of the fifth round was relatively good, our team kept the same car setting for Rounds 6, 7, and 8, only occasionally changing production quantity but no other options. Concurrently, other groups took risks changing their car models. In contrast, the results of our team were predictably stable, without any significant surges.

Table 4. The company report of FTG in round 5

The company report of FTG in round 5

 G2T8 luxury model sales in round 5
Figure 3. G2T8 luxury model sales in round 5

By Round 9, I started looking for more data to inform our decisions. By analyzing the market data of other groups, I found that G2T4 and G2T8 have the same characteristics. Those two groups were the leaders as their product sales volume was much higher as compared to the rest of the team. What captured my attention though is that apparently G2T4 and G2T8 did not capitalize on price leadership since their prices were much higher than those of other teams. Actually, not only prices were greater but also so were their sales and margins.

I concluded that those teams must have gone down the differentiation path. My assumptions were confirmed by their car model data: the teams invested in the option, design, and research and development. By that time, it had dawned on me that our team never took the key perception factors into consideration (KPF) (Table 5). KPF provided another valuable source of data to drive business decisions. As seen in Table 5, our models were underperforming as per criteria such as speed (21% vs ideal 75%) and green technology (11% vs 65%). Our team was confronted with a dilemma as we somehow had to balance key perception factors, customer preference, and cost. We took a risk by focusing on key perception factors, simultaneously raising the price, though not higher than the two leading teams.

Table 5. Key perception factors

Key perception factors

Unfortunately, when the results came out, the car sales were very poor. The new figures proved that the key perception factors did not have a great impact on car sales. To recover from the loss, for Rounds 10 and 11, we made some adjustments to the configuration of the car but did not bring the price down. The results of these two rounds were not good either, and, at this point, our team felt lost. In other words, it means that the confidence and motivation of team members are greatly affected in such situations.

What helped our situation is studying the data from competitors, especially given that G2T4 and G2t8 were still in high sales. We set the car’s configuration to be similar to the G2T4 or G2T8 since their three models of market model 6, 12, 13 were selling well and generated high profits. Their success did not mean that their models were perfect; most likely, our competitors succeeded in strategic management. Therefore, in the process of modifying the car set, different team members looked at different kinds of reports. Finally, our team kept the more reasonable options in the two group models.

Meanwhile, our team also added some new configurations, and then we set the price lower than the two groups. In the end, our data result in the 12th round is better than before, which is why we stayed true to the same strategy for Round 13. Below are plots that depict the relationship between price and sales volume for each of the models (see Appendix A for raw data). As seen in Figures 4-8, one can observe that there is a relationship between price and sales volume, but the impact of price on sales volume is not so significant. Considering that KPF and price are similar, it can be assumed that the main factor affecting sales volume is customer preference. At the same time, price, KFP and other factors have a combined effect on the overall market.

Summary of Strategic Decision Making

By analyzing the game report, one can see that the decision-making process needs to consider the company strategy, market strategy, and operational strategy. Analyzing the internal links between these strategies helps the company allocate resources to achieve the expected goals (Jenkins & Williamson, 2015). As the core objective of the team, corporate strategy provides the direction for both marketing strategy and operational strategy. According to the actual market situation, the market strategy gives the company the target and market positioning at different stages. Operational strategy is the implementation method to realize the market strategy and the company strategy. It helps the team to move closer to the core goal by allocating the company’s resources and adjusting the production plan.

 FTG1 Price vs. Sales
Figure 4. FTG1 Price vs. Sales
FTG2 Price vs. Sales
Figure 5. FTG2 Price vs. Sales
FTG3 Price vs. Sales
Figure 6. FTG3 Price vs. Sales
FTG4 Price vs. Sales
Figure 7. FTG4 Price vs. Sales
FTG5 price vs Sales
Figure 8. FTG5 price vs Sales

Results Analysis from My Msc Field

SWOT Analysis. In accordance with my individual topic, it was important to apply some of the most commonly used business analysis tools to make sense of the business game. The SWOT analysis looks as follows:

  • Strengths. We had a team with a wide range of roles and were able to allocate human resources in an efficient manner. As a team, we were able to streamline our communication to make the best of our discussions. Our company tapped into various market segments of the European automotive industry, therefore, diversifying its portfolio and building up resilience. With the help of research and development, five models were introduced to meet customer diverse preferences.
  • Weaknesses. Due to the difference in time zones, communication was not always in sync. In addition, our team didn’t analyze all the game reports for each round, we merely focused on some reports that we considered being more important. Therefore, our gross profit growth in rounds 1 to 4 is relatively slow.
  • Opportunities. The luxury market segment gave us an opportunity to discover a blue ocean, and through the analysis of competitors’ products, we were able to provide customers with more competitive products.
  • Threats. Just like in the real world, the car market is oversaturated and competitive. In the decision-making process, it is difficult to make key perception factors and customer preference surveys reach the expected level. Thus, our team needs to use the method of controlling variables in order to observe the factor that influences the sales volume the most. In other words, our team will eventually experience at least one failed decision.

PESTEL Analysis. Below is the PESTEL analysis of the business game that also helped us make decisions:

  • Political factor was a mostly overlooked part in this game because these policies usually do not directly affect the company’s car production. For example, in the news bulletin from Round 1, OPEC will discuss the current decline in oil revenues and future increases in oil prices. It means that gasoline prices are likely to rise, and therefore, sales of high-emission vehicles may be affected.
  • Economic factors included the competitiveness of the market and its significance in the global arena. The change of exchange rate and inflation rate in the game brings challenges to the control of production cost and adjustment of the product price
  • Social factors helped us realize the changing customer persona since they are able to select from a variety of options. The sales trend change of different models can be found in the Market Prediction report, which is crucial for the new round of production plan setting.
  • Technology can directly affect product sales, and each round of the Market Perception report includes an analysis of the requirements for technical options for each model, which means that we had to keep up with our competitors in terms of research and development.
  • The environment was of little concern in the context of the game; though, we took into account consumer preference for green technology.
  • One should be aware that legal factors can directly affect a company’s operations. For example, in the Round 1 and 8 games, the cost of materials for all manufacturers will increase by 1% next year due to new government safety regulations. The increase of cost will lead to a decrease in profit; therefore, the team needs to consider adjusting the production plan in order to maintain the company’s profit margin and sales.

Critical Reflection

Business analysis is essentially a survival tool: it allows companies to stay afloat during turbulent times. Blackler and Regan (2009) outline two different approaches to change: maintain company strategy or adjust company strategy according to market changes. In the case of the former approach, managers see the market situation as primarily stable. They put a lot of effort into upholding the status quo while changes are seen as local, incidental. Typically, managers who follow the conservative approach dislike change: to them, it is an unfortunate aberration that disrupts their plans. Hayes (2017) believes that change is an indispensable feature of the market. Managers who follow change will not resist market change because they know how to make the most of it. According to the wrong decisions made by our team in the process of running the game, we can find that the development of the automobile industry is accompanied by the constant changes in the market, and these changes are great challenges and opportunities for the company’s strategic decisions and development.

As a team, we had not been able to start seeing tangible improvements until we accepted the changing nature of the simulation and the need to act in the now. We learned that even if one is lucky to formulate a successful strategy, one should not count on it being as effective in the long term because of the changing conditions of the market. Looking back, I realize that we made a mistake by not utilizing all the data available to us such as customer preferences surveys. For this reason, our decisions during the first few rounds were largely uninformed and not supported by business analysis. In contrast, as some of the advantages of our strategy, I would like to point out our ability to analyze competitors, take reasonable risks, and discover untapped market segments – the so-called “blue oceans.”


Customer evolving preferences and tight competition are two truths that an automotive company needs to take into account and let them inform its decisions. The decision-making process in car manufacturing and distribution is complex, multi-layered, and often impeded by issues boiling down to poor communication and a lack of decision support with a company. For this study, I hypothesized that business analysis tools would enhance our team’s success, in competing against others. Over the course of the game, we had mixed results and experienced ups and downs. However, it came to my attention that whenever we focused on utilizing precise and relevant data as well as conducting competitor analysis, we were able to make progress. Hence, I conclude that business analysis is indeed not only a useful but a critical tool. It is necessary for facing fierce competition during market turbulence and getting ahead not just by making a perfect product but by being nimble strategists.


ACEA. (2020). Competitiveness, market and economy. Web.

ACEA. (2020). EU car sales forecast 2020: Record drop of 25% expected this year, says ACEA. Web.

Al-Fayad, F. S. (2018). The perception of Japanese cars by market: Saudi Arabia and The United States and the value versus price proposition. Archives of Business Research, 6(12), 1-10. Web.

Aris, I. B., Sahbusdin, R. K. Z., & Amin, A. F. M. (2015). Impacts of IoT and big data to the automotive industry. In 2015 10th Asian Control Conference (ASCC) (pp. 1-5). IEEE.

Bell, E., Bryman, A., & Harley, B. (2018). Business research methods. Oxford University Press.

Bhatia, J. (2016). Porter’s Five Forces industry analysis of the Indian passenger car industry. Pacific Business Review International, 8(7), 113-123.

Blackler, F., & Regan, S. (2009). Intentionality, agency, change: Practice theory and management. Management Learning, 40(2), 161-176. Web.

Bonab, A.F. (2017). The development of competitive advantages of brand in the automotive industry (Case Study: Pars Khodro Co). The Journal of Internet Banking and Commerce, 1-15.

DePoy, E., & Gitlin, L. N. (2019). Introduction to research e-book: Understanding and applying multiple strategies. Elsevier Health Sciences.

Dietl, H., Royer, S., & Stratmann, U. (2009). Value creation architectures and competitive advantage: Lessons from the European automobile industry. California Management Review, 51(3), 24-48. Web.

Doz, Y., & Prahalad, C.K. (2013). Quality of management: An emerging source of global competitive advantage? In N. Hood & J. E. Vahlne (Eds.), Strategies in global competition (RLE International Business): Selected papers from the Prince Bertil Symposium at the Institute of International Business (pp. 345-368). Routledge.

European Automobile Manufacturer Association. (2020). Key figures. Web.

Evans, J. R. (2017). Business analytics. Pearson.

Farhana, M., & Bimenyimana, E. (2015). Design-driven innovation as a differentiation strategy: In the context of the automotive industry. Journal of Technology Management & Innovation, 10(2), 24-38. Web.

Fleisher, C.S., & Bensoussan, B.E. (2003). Strategic and competitive analysis: Methods and techniques for analyzing business competition. Prentice-Hall.

France – flash report, sales volume, 2019. Web.

Gareche, M., Hosseini, S.M., & Taheri, M. (2019). A comprehensive literature review in competitive advantages of businesses. International Journal of Advanced Studies in Humanities and Social Science, 6(4), 312-329.

Goicoechea, I., & Fenollera, M. (2012). Quality management in the automotive industry. DAAAM International Scientific Book, 619-632.

Goodwin, P., & Wright, G. (2014). Decision analysis for management judgment (5th ed.). John Wiley & Sons.

Gupta, S., Malhotra, N. K., Czinkota, M., & Foroudi, P. (2016). Marketing innovation: A consequence of competitiveness. Journal of Business Research, 69(12), 5671-5681.

Hayes, J. (2018). The theory and practice of change management. Palgrave.

Holmes, F. (2020). How will Europe’s automotive industry recover from COVID-19? Automotive World. Web.

Holweg, M. (2008). The evolution of competition in the automotive industry. In G. Parry & A. Graves (Eds.), Build to order (pp. 32-54). Springer.

Holweg, M., Davies, P., & Podpolny, D. (2009). The competitive status of the UK automotive industry. Picsie Books.

IHS. (2015). Five critical challenges facing the automotive industry. A guide for strategic planners [PDF document]. Web.

Jenkins, W., & Williamson, D. (2015). Strategic management and business analysis. Routledge.

Koptyug, E. Leading car brand market shares by new registrations April 2020. Statista. Web.

Lademann, A., & Partner Gesellschaft for Unternehmens und Kommunalberatung mbH. (2001). Customer preferences for existing and potential sales and servicing alternatives in automotive distribution. Web.

Laux, J. M. (1992). The European automobile industry. Twayne Pub.

Leonte, A., & Orszaghova, L. (2013). The competitiveness of the European automotive industry [PDF document]. Web.

Magretta, J. (Eds). (1999). Managing in the new economy: A Harvard Business Review book. Harvard Business School Press.

Meredith, J. R., Shafer, S. M., & Mantel, S. J. (2017). Project management: A strategic managerial approach (10th ed.). John Wiley & Sons.

Nazir, N. M., & Shavarebi, K. (2019). A review of the global automotive industry’s competitive strategies. World Journal of Science, Technology and Sustainable Development, 16(4), 1-10. Web.

Number of cars sold worldwide between 2010 and 2020. Web.

Referencing. (n.d.). Web.

Rugraff, E. (2012). The new competitive advantage of automobile manufacturers. Journal of Strategy and Management, 5(4), 407-419. Web.

Sissoko, T. M., Jankovic, M., Paredis, C. J., & Landel, E. (2018). An empirical study of a decision-making process supported by simulation in the automotive industry. In International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (p. V007T06A018). American Society of Mechanical Engineers.

Statista Research Department. (2020). Leading car companies’ monthly UK market share 2020. Web.

Sun, Y., Kadota, I., Talak, R., & Modiano, E. (2019). Age of information: A new metric for information freshness. Synthesis Lectures on Communication Networks, 12(2), 1-224.

The International Institute for Business Analysis. (2012). The guide to the business analysis body of knowledge™ [PDF document].

Wagner, I. YTD market share of selected car manufacturers in Europe 2020. Statista. Web.

Whitney, C.W., Lind, B.K., & Wahl, P.W. (1998). Quality assurance and quality control in longitudinal studies. Epidemiologic Reviews, 20(1), 71-80.

Winck, B. (2019). The auto industry is shrinking as the world reaches ‘peak car’ — and it’s dragging down the entire global economy. Business Insider. Web.

Yannick, L. (2004). The challenges of the European automotive industry at the beginning of the 21st century. Cahiers du GRES, 8, 1-10.

Find out your order's cost