Social Economic And Legal Framework Report

Social Economic and Legal Framework

Running head: SOCIAL ECONOMIC AND LEGAL FRAMEWORK
Social Economic and Legal Framework
Name of the Student
Name of the University
Author Note

1SOCIAL ECONOMIC AND LEGAL FRAMEWORK
Table of Content
1. Introduction............................................................................................................................3
2. Literature Review on knowledge economy and various drivers of economic change...........5
Concept of knowledge Economy...........................................................................................5
Macro- economic dimensions of business.............................................................................6
Demographic and socio-economic shifts.............................................................................12
Technological drivers of change..........................................................................................15
3. Impact of legal framework and political factor....................................................................17
Role of political factors in the economic development and its implication on Tesla..........17
Implications of ‘sharing economy’ for Tesla.......................................................................18
Formal and informal legal systems and anti-trust laws and social economy development. 19
4. Conclusion and Recommendation........................................................................................19
Recommendation..................................................................................................................20
References................................................................................................................................22

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Executive summary
This research report provides a detailed analysis of socio economic and legal framework
creating colossal impact on business today. It is essentially important to learn how technology
disruption is actually affecting the socio-economic and legal environment across globe. To
analyse this growing impact of disruptive technology on socio-economic and legal
environment, Tesla Motor’s disruptive technologyhas been analysed in the report. The
findings indicate that Although Tesla with its disruptive business model is going to penetrate
the market with its electronic car models, Tesla may observe that Technology-driven trends
are most likely to revolutionise how the big players in the sector respond to changing
customer behaviour, build partnership as well as drive transformational change. Tesla faces
the challenges of shared economy services in the car manufacturing sector. The industry
might observe enormous skills gap in relation to AI and Machine language. Tesla, besides its
automated business model development, should focus on the skills development programs for
the employees.

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1. Introduction
This research report presents a detailed analysis of socio economic and legal
framework which creates significant impact on businesses today. It has been identified that
business environment is highly dynamic in nature and technology has been the major driver
in market dynamics. Undoubtedly, technology advances have significantly changed the
business environment across the globe because every business today incorporates technology
in its operation, product and all other aspects of the business. As the rate of technology
adoption in business is rapidly increasing, there is an emerging shift in socio economic and
legal environment associated with the business. Rapid growth in technology emerges as
technology disruption which is actually changing the shape of socio economic and legal
framework.
Consequently, business practices in contemporary market place are following new
pattern. According to Pandit, et al. (2018), disruptive technology is most likely to play a
great role in enhancing the quality of life of people, global economies and business model of
the organizations. It has also been identified that a disruptive technology which also changes
the product that once was generally expensive as well as complicated but now with the
disruptive technology, production of resources is quite easy and affordable. In this context,
Gao et al. (2016), commented that at a point when the innovation that has the potential to
change the growth of the industry, longstanding organizations mostly consider it to be
unattractive and it is not something which the customers need. It is also estimated that profit
margin are not adequate to address the enormous technology expense.
Subsequently, the emerging innovation is often overlooked. Another business after
sometime, manages to go with innovation in the market place. This means once disruptive
innovation grows, even the small scale innovation growingly raise technology performance

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on the elements of mainstream consumers. Therefore, it is essentially important to learn how
technology disruption is actually affecting the socio-economic and legal environment across
globe. Thus, to analyse this growing impact of disruptive technology on socio-economic and
legal environment, real world business scenario has been considered in the analysis. The
analysis has been performed on Tesla Motor’s disruptive technology.
Tesla Motor:
It has been identified that Tesla is one such brand in the car manufacturing sector that
takes the quest for next-level technology as well as sustainability to another level.
Throughout the disruptive innovation, it has been identified that Tesla’s automotive start-up
is mostly having a good year and in September, the organization expects to start shipping its
all electronic Model 3 to non-employee consumers, who, by now logged 500,000 pre-orders
(Chen and Perez 2018). The report published in 2019 indicates the fact that even though there
is a growing success in Tesla’s model, its stocked is jumped taking the 14 years of old start-
up’s valuation to over $53 billion, which is steps ahead of other US car manufacturer.
However, despite such rocket-growth, Tesla alone lost nearly two billion dollars in the past
two years. Nonetheless, Van den Steen (2015) commented that even though there have been
some financial loss, in the field of disruption, the organization Tesla by stepping in the high
end market as a sustaining innovation is most likely to face powerful, established incumbents
like BMW and Mercedes. In this context, Eggers and Eggers (2011) commented that Tesla is
actually approaching the market with its resources process and profit formula by developing a
hybrid model. Thus, it can be mentioned that quest for being disruptive is uninterrupted in
Tesla’s journey.
As put forward by Mangram (2012), socio-economic trends have high impact on Tesla’s
business model because increasing price of fossil fuels and affordability rate of people enable

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Tesla to come up with the idea of incorporating disruptive technology. It is noted that since
the launch of smart-phone, it is quite certain that customers are most likely to adapt to
complex and expensive technology if the technology is able to make their lives easier than
before. In business, it is mostly treated as user value convenience and ease. It is noted that
such core values bought up the technology-based cultural items of 21st century. So, it can be
mentioned that businesses today often translate such priorities into future technology and
need of the society. It is worth mentioning that Tesla in the Automotive sector leverage the
opportunity for core restructuring. The large tech giant like Tesla not only consider product
purchaser when developing strategies and business model, it should take users and groups
into account as they are affected by commotion issues. Phute (2016) mentioned it has been
decades long automobile sector shifted attention from conventional technical agenda to social
commodity. It is worth stating that social participation, landscape and cities are shaped by
such personal mobility. In this context, Oltra and Saint Jean (2009) young as well as
technically savvy generation played the major role in transforming the automotive sector to a
greater extent. Thus, Tesla’s popularity lies in the fact that the organisation mostly focus on
the use of utility of the vehicles rather than the mass production in order to make people’s
live easer. It can he also mentioned that Tesla’s business model will incorporate
unprecedented change with respect to far reaching effect it might have on the industry. It is
also noted that in spite of falling inventory, vehicles sales may invariably increase. It is also
noted that Tesla in the automotive industry is most likely to start to invest less in product
range.

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2. Literature Review on knowledge economy and various drivers of
economic change
Concept of knowledge Economy
As put forward by Peters (2007) knowledge economy is a sort of economy in which
the manufacture of goods and services is fundamentally based on knowledge-intensive
activities. On the contrary, Amidon (2009) mentioned that in knowledge economy is a
significant portion of economic growth as well as employment is the outcome of knowledge-
intensive activities. Authors of this study have also mentioned that a knowledge-intensive
activity may also include a set of collection, analysis and series of information. For example,
Tesla in the automotive sector, manufacture electronic vehicles by installing AI-enabled
technologies and through the manufacturing, the organization contributes to employment
opportunities in US with the increase of 19%.
This means Tesla effectively understands the gaps in the market that due to increasing rate of
carbon emission and demand of mobility, the organization needs to manufacture a sustainable
vehicle that contributes to economic balance. On the contrary, Godin (2008) mentioned that
success in knowledge requires significant level of commitment of both workers as well as
organizations to learn and brush up skills, expertise that can help to apply innovation and
become innovative; thereby, the knowledge-based business may involve educational
institution and science and technology based organisation. Tesla is one such information
based organization whose most of the products are derived from scientific and technological
research. For example, Tesla’s model 3 is embedded with AI technologies. On the contrary,
Smith (2002) stated that increasing growth of economic knowledge is more of a part of larger
modifies the production of tangible goods in developed nations towards the intangible goods
and services.

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Macro- economic dimensions of business
It has been identified that the automotive sector is one of the major industrial as well
as economic force worldwide and it makes almost 69 million vehicles and trucks. Thus, the
sector has a direct relation with economy behaviour. As put forward by Birnleitner and
Student (2013), in spite of the fact that several large corporations have issues with the
overcapacity as well as low profitability, the car manufacturing sector retains potential
influence and importance. Jullien and Pardi (2013) argued that economy environment in the
21st century has been dynamic in nature, which significantly affects the business to a larger
extent. There have been some drivers of economies that enable the changes in the economy
and create further impact on business.
As put forward by Gao et al. (2016), United State comeback with the economic recovery
because jobs in many sector have been created which significantly pushes the unemployment
down to pre-crisis level dropped to 5.0 %. Technology-driven trends are most likely to
revolutionise how the big players in the sector respond to changing customer behaviour, build
partnership as well as drive transformational change. As put forward by Tellis (2006),
economy today is dramatically changing and this is It is driven by the government supported
developments in the emerging sector, increase of new technologies, consumers’ shifts in
preferences and changing policies of sustainability. This means that these forces certainly
Creates the path for four disruptive technology based trends especially in the car
manufacturing sector like the popularity autonomous driving, diverse mobility, electrification
and connectivity. As put forward by Hardman et al. (2013), a many industry players and
experts believe in the fact that there is a number of trends which are most likely to reinforce
and accelerate one another and here automotive sector is ripe for disruption. As put forward
by Zapata and Nieuwenhuis (2010) as per the global understanding of game-changing
disruption already on the horizon, there lacks an integrated point of view on how the sector

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may look in 10 to 15 years as the consequence of such change. Thus, Tesla being the
significant part of 2020 automotive revolution focussing on the scenario about the changes
appearing and how the changes are most likely affect conventional vehicle manufacturing,
suppliers and new potential players.
As put forward by Dwivedi, Srivastava and Srivastava (2017), the automotive revenue
pool is most likely to enhance and diversity towards the on demand mobility services as well
as data driven-services. Consequently, the scenario may create up to $1.5 trillion or more
than 30% in the possible revenue in 2030. According to Pilkington, Dyerson and Tissier
(2002), Tesla’s automotive revenue pool is most likely to maximize as well as vary towards
the on-demand automobile services as well as data-driven services.
Figure 1: High End Disruption
(Source: Danneels 2004)

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Furthermore, Furthermore, Ferràs-Hernández, Tarrats-Pons and Arimany-Serrat (2017) stated
vehicles would become the primary platform for passengers and drivers due to later
autonomous technology and connectivity. Thus, the scholars argue that such pace of
innovation particularly in technology based system may require the cars to be updated. In this
context, Dijk, Wells and Kemp (2016) arguably mentioned the fact that since the shared
mobility solutions within a limited life cycle becomes more general and common, customer
are most likely to become aware of technology advances. This may further enhance the
demands for upgradability in privately used vehicles.
On the contrary, Pandit et al.(2018) mentioned that in spite of the shift towards the
shared mobility, sales of vehicles could most likely to grow, it can be seen at a lower rate (2%
per year). It is observed that overall international sales is most likely to continue but the
growth on an annual basis is estimated to decrease by 3.6% over the last five years to around
2% by 2030. Therefore, it is expected that even the high-end market of Tesla is also going to
provide a decrease in its sales. It is noted that such decrease is significantly driven by some
major micro-economic factors along with the rise of emerging mobility services like e-
hailing. Furthermore, it has also been identified that nee mobility services might lead to a
certain decline in private sales vehicles but such decline may be offset by enhanced sales in
some shared vehicles. This needs to be replaced quite often because of the higher utilisation.
As put forward by Dachs, Stehrer and Zahradnik (2014changing customer preferences,
tightening regulations, as well as technological breakthrough contribute to a fundamental
shift in individual mobility approach. This means it can be mentioned that the rate of rapid
use of multiple model of transportation on an individual level is relatively high.
Consequently, conventional business model of car sales can be utilised or achieved by on
demand automobile solutions by the drivers in dense and populated cities of the world. As put
forward by Ülengin et al. (2014), buyers today usually treat the cars as the purpose vehicles

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and moreover in the coming future such group of buyers would prefer more flexibility to
develop solutions for the purpose, on demand mobility via smart-phones. Conversely, Gopal
and Thakkar (2016) stated there can be a new segments of specialised vehicles driven by
customers’ growing habit of using tailored solutions. It can be stated that in the coming days,
markets for vehicles may be developed for e-hailing services. Vehicles developed for greater
utilization and greater mileage. Therefore, it can be mentioned that such shift in consumer
shifts can affect the sales and manufacturing rends of Tesla, as Tesla only focus on privately
owned cars for high-end markets but rapid changes in consumer preferences and availability
of other alternative choices can affect Tesla’s business.
Consequently, this shift to diverse mobility solutions which is up to one out of ten
new cars sold in 2030 can be a shared vehicle and this can directly decrease the sales of
private-use vehicles. Thus, in order to measure the outcome on a scale, Amighini and Franco
(2013) mentioned that more than 30% miles driven in new cars sold can be from the shared
mobility. On the contrary, Eggers and Eggers (2011) mentioned that trends in the urban areas
may replace the nation because the most relevant section dimension that counts mobility
behaviour and the opportunities of automotive revolution across the world. Dijk, Wells and
Kemp (2016) commented that understanding where the opportunities of coming future lies
needs more in-depth view of the mobility markets than the easy state once before. Thus, it is
highly important to segment such markets by the urban type based fundamentally on the
density of the population, economic development and prosperity. Authors of the above study
have also mentioned the fact that across all sort of segments, customer preferences, policy
regulations as well as availability of price of emerging business model may significantly
diverge. In response to this statement, Hardman et al. (2013) provided an example of the
scenario – in London ownership of car is already being significant burden for a large
percentage of population because of high congestion fees, lack of parkin tariff and several

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other factors. On the contrary, Gao et al. (2016) mentioned that particularly in the rural areas,
particularly, the state of Lowa in United State, private-car use may remain the most preferred
means of transportation till now. This sort of city thereby becomes the major indicator for the
mobility behaviour by replace the conventional regional perception on the automobile
market. Tellis (2006) also mentioned the fact that by 2030 the major large city like New York
is most likely to have much more in common with the market compared Shanghai.
On the contrary, Zapata and Nieuwenhuis (2010) mentioned that once technological
as well as regulatory issuers have been addressed because almost 15% of new vehicles sold in
2030 could be autonomous. In this context, Dwivedi, Srivastava, and Srivastava (2017)
mentioned that vehicles that are completely autonomous need to be commercially available
before the onset of 2020. Authors of this study have also stated the fact that advanced driver-
assistance system (ADAS) may play a great role in making the regulators, customers, and
corporations for the middle term scenario of cars that are being over-controlled by drivers. It
can be further mentioned that the introduction of such system in the market demonstrates that
primary challenges that imped faster market penetration include pricing, customer
understanding, safety and security. Furthermore, in relation to technological readiness, the
major tech players and start-ups could most play a great role particularly in the development
of autonomous vehicles. In this context, Pilkington, Dyerson and Tissier (2002) commented
that stiff regulations and acceptance rate of customers may represent excessive hurdles for the
autonomous vehicles. Nonetheless, such barriers are resolved; the autonomous cars provide
tremendous values for customers.
Conversely, Dijk, Wells and Kemp (2016) mentioned the fact that electronic vehicles
tend to become viable and the most competitive, nonetheless, the speed of such adoption
could vary strongly at the regional range. It is noted that stiffer regulations on emission,

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lower battery cost, more broadly available as increasing customer acceptance and charging
infrastructure may create new and strong status of penetration of EV in the near future.
As a result, it can be mentioned that electrified vehicles are expected to derive increasing
percentage of market share from traditional vehicles. In this context, Chen and Perez (2018)
mentioned that as the cost of battery potentially decrease to $150 to $200 per kilowatt-hour
over the coming decade, EV is most likely to achieve the level of competitiveness in cost
with the traditional vehicles. This will certainly create the most vital catalyst for market
development. SimultaneouslySimultaneously, it is necessary to point out that a large
percentage of electrified vehicles may include a larger proportion of hybrid vehicles. On the
basis of this findings, it can be mentioned that by 2020, internal combustion engine would be
more relevant. According to Van den Steen (2015), under a complex and diversified mobility,
incumbent players may be forced to depend upon multiple fronts and this eventually
cooperate with other players in the sector. As put forward by Ingle and Phute (2016), a
pattern-based shift to mobility service with the presence of new players could invariably
force the conventional car manufacture to compete in different markets. This means that the
mobility players like Tesla enhances the complexity of the competitive landscape. On the
contrary, it is worth mentioning that conventional car manufacturers in the sector is most
likely to face continuous pressure to minimize the cost, enhance the efficiency of fuel,
minimise emission and become more capital-efficient which is most likely to end up shifting
the market positions in the developing automotive sector. This will potentially lead to
different forms of partnership among the incumbent players in the market. Besides this fact,
Pandit et al. (2018) mentioned that the major software proficiency is rapidly becomes one of
the most vial differentiating aspects for the sector, for different domain areas, connectivity
and infotainment. In addition to this, the authors of this study have also stated the fact that as

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the vehicles have increasingly become intergrade into shaped world, the car manufactures are
running out of choices but to take part in the new mobility ecosystem.
Demographic and socio-economic shifts
Human Capital: As put forward by Gao et al. (2016), the human capital that people bring to
the workplace including skills, knowledge and ideas can significantly drive innovation,
productivity enhancements as well as economic growth. According to this author, employees
associated with the business setting can move from place to place but the regions must have
to enhance their quality of life. In response to this statement, Tellis (2006) mentioned that
mix of skills and occupation can become increasingly necessary to the economic well-being
of the province, quality of life influencing economic development.
Financial capital: According to Hardman et al. (2013) investment significantly influences
the growth and increased private investment that are made with respect to ongoing markets or
new scope to create new jobs as this will eventually generate earning locations.
Specialisation and Trade: As put forward by Dwivedi et al. (2017) business in some
particular areas are most likely to capitalise on the efficiencies as well as productivity
advantages to categorise sales for the buyers in own regions. It is often noted that such
regions may be able to gain benefits from the trade to an extent in which they are quite able
to concentrate on the product categories for local inputs, technology and natural resources as
these are the fundamental base for the business.
As put forward by Danneels (2004), China’s economy was a tenth the size of US and in 2019
it becomes two-thirds as big and thereby, in 20130 it is expected to become bigger than 10%.
When it comes to geography and economy, it is noted that the developing nation like India is
most likely leapfrog Japan and Germany to be holding the third position in the global ranks.
In this context, Dijk, Wells and Kemp (2016) mentioned that automation as well as digital

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economy is most likely to boost productivity for some significant source of advantages.
Eggers, and Eggers (2011) argued that threat of climate change can loom. On the contrary,
the On the contrary, the path to development is followed by some success stories because
Korea and Japan are going to follow the same path. Conversely, Birnleitner and Student
(2013) stated that from Beijing to Brasila, all often experience the right amalgamation of
smart investment, new talents, capacity of innovation and effective governance can be
challenging to implement. Hence, Jullien, and Pardi (2013) arguably stated the fact that
disruptive forces, like protectionism to climate change create the scope for considerable
influence on low and middle class economies. The report on emerging economies as well as
disruptive drivers blame the forces narrowing the paths for development and significantly
change the pattern of winners and failures in global economy.As per the report provided by
Amighini and Franco (2013), specific performance measures found on the disrupters that
involves protectionism, automation, digitalisation and climate change demonstrates the type
of economies presently at the verge of being threatened and this can significantly seize the
opportunities.
As put forward by Wells (2013) low and middle class economies are conventionally
disorganised to address the coming disruption. Thus, it can be mentioned that if there is no
striving response forged at both national and global level, scenario shifting from low to
middle and eventually to high earning range can be interrupted. Moreover, it can decrease
further. Therefore, Dachs, Stehrer and Zahradnik (2014) arguably mentioned the fact that
scope for trade and growing trade can back the annual GDP growth at 2.7% in the coming
decades. Consequently, if the market lacks such drivers, economy is most likely to decrease
to 1.4%.
Trade as prosperity driver

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Birnleitner and Student (2013) Birnleitner and Student (2013) argued that the origin of many
of the change is phasing out the global financial system which is often traced in 2 separate
sources like trade and Technology. It has identified that trade is being run without the
agreement and the rules of the game or without any sort of compensation for the failure, the
scenario can lead to protectionist. According to Chen and Perez (2018) the consequences of
US and China Trade can be of $1.2 trillion which spreads the impact across the world.
Conversely, Dwivedi, Srivastava and Srivastava (2017) UK’s withdrawal from EU and
increasing tariff on the imports of vehicles can also be challenging. This means that GDP is
often threatened due to US-China trade war, Brexit and other related disputes and this will
have high impact on the economy. On the contrary, Gao et al. (2016) mentioned that due to
ongoing trade war, China is most likely to face the barriers in economies. UK’s departure
from EU is a constant threat to economy as it breaks the ties with world’s largest free trade
zone.On the contrary, the late developers like Vietnam which focuses on following exporters’
path to growth. This means that path to global market is approaching close and thereby, the
development becomes a harder attempt.
Technological drivers of change
Rise of Robots:
It is also noted that automation delivers and speeds up the growth in productivity as
well as profits at the cost of enhanced job security. As put forward by Tellis (2006), by 2030
almost 14% of the global workforce might have to look for new jobs. This scenario
significantly indicates the fact that rapid growth in Artificial Intelligence as well as machine
learning, growing the range of responsibilities can be automated, while minimizing the cost.
The scenario can push the number up. This means that results for advanced economies can be
further polarized in earning along with increasing division between high-skills and low skills
bar. Particularly, for rising market, the lower remuneration can significantly minimize the

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incentive to automate but certainly, this does not indicate the risk of disruption remains low.
Pilkington, Dyerson and Tissier (2002) also agreed to the fact that automation is growingly
high and it is approaching the point at which a considerable share of low-value added effort
can be done by machinery, by undermining the inexpensive advantages of economically
developing market. (Ferràs-Hernández, Tarrats-Pons and Arimany-Serrat (2017) also agreed
to the fact that combination of globalisation and automation resulted in premature
deindustrialisation in low and middle-income economies and this significantly prevents the
path to growth. On the contrary, according to the viewpoints of economists on composition of
labour markets, indicate the fact that high-income economies is most likely to deal with direct
risk from automation. In addition to this, Oltra and Saint Jean (2009) mentioned that the
ability to increase the benefits and reduce the cost of automation may also depend on policy
choices. To understand the trends of economies here, measure of workforce flexibility and
skills, spend on workforce training, support and the share of population with proper
education. Mangram (2012) mentioned the fact that markets with increasing share of workers
in routine jobs, limited spending on support for the displaced workers as well as small
university-educated population can face the greatest risks. Nonetheless, the findings of the
stated paper does not capture all relevant factors related to work. For example, Japan deals
with increasing pressure to automation but Japan reaps benefits from the competitiveness of
its robotic sector and labour market conventions that highlights low unemployment.
Digital Divide
As put forward by Jullien and Pardi (2013) digital divide is significantly driven by the
increasing reduction in the cost of the digital economy holds and communication, outpace the
dramatic increase in productivity. Internationally, almost 4 billion people are significantly
connected to the internet and this means almost 4 out of 5 are online. Particularly, in
emerging and developing economies, rate of internet use is at 45% and it is increasing

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hurriedly. This means, it can be added that impact of economy is far reaching and
particularly, digital platform like China’s Taobao align entrepreneurs to new consumers,
which empowers both sides of transactions along with the high extent of transparency. In
response to this statement, Wells (2013) mentioned that an enormous increase in data flow is
being driven which is often called as ‘third unbundling’. This happens because the trends
have the potential for the services which needs to be done by the parties across the borders
besides the actions of manufacturing. In this context, Dachs, Stehrer and Zahradnik (2014)
mentioned that digitization holds the scope for the pace of greater productivity, along with
the potential for middle and low class income economies to speed up the development
process. Furthermore, the digital economy index and published by Bloomberg clarifies
evaluation of five dimensions such as quality of business engagement and internet
infrastructure, governments and households. This means that measures can include the
mobile and broadband connection speed and number and share of population that are active
online.
3. Impact of legal framework and political factor
Role of political factors in the economic development and its implication on Tesla
As put forward by Beeson (2014), political stability and instability is often reflected on the
economic development of the organization. It can be mentioned that continuous political
clash between US and Middle East is creating tension among the developing nations and
thereby, the economy is highly affected. In this context, Spolaore and Wacziarg (2013)
commented that United State economy appeared to be coming out of its decade-long slough
2018 with the strongest growth considering the financial crisis. Consequently, the
unemployment decreased to the lowest possible rate and the labour market sudden bloomed
with employment opportunities. Therefore, the manufacturing which was supposed to be the
dying sector, can have the best year. Thus, Tesla’s invention towards the disruptive

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technology and stabilise the demands of disruptive technology based and private owned cars
is uninterrupted. Moreover, China and United State involved in the competitive tariff as
Trump administration sought to change longstanding trade practices between world’s two
largest economies. Consequently, Tesla holds the opportunity to reinforce its financial
performance with the incentives provided by governments. However, Platteau (2015) argued
that Tesla’s manufacturing can be affected due to the coming change in House of
Representatives control, after November election that can develop power for the first
democrats legislative, and this may affect the scenario in 2020.
Implications of ‘sharing economy’ for Tesla
On the basis of the above findings, it can also be mentioned that growing pace of
implementation and adoption can be determined by the communication customers pull,
regulatory pressure which may strongly differ at local and regional and local level. Chen and
Perez (2018) mentioned that by 2030, the share of electrified vehicles is most likely to range
from 10 to 50% of new vehicle sales. This means that implementation can be highest in the
dense regions that are economically developed with tighter control in regulation and customer
incentives. This means that sales penetration of Tesla may be slower in small towns and
particularly in the rural areas with limited range of charge infrastructure as well as increasing
dependency rate. It can be mentioned that through the continuous enhancement and
advancement in technology of battery and expense, while the local differences may become
pronounced. Besides, the above stated picture, it can also be added that sharing economy can
directly affect the sales of Tesla because the major automotive players due to shifting the
paradigm to mobility as a service with the integrated force of new entrants in the market, can
significantly force the conventional market players Tesla to join the competition on multiple
options. Mobility providers like Uber and the tech giants Google will certainly increase the
competition in the landscape. Thus, it can be mentioned that the conventional car

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manufacturer like Tesla that faces the continuous pressure to minimise the cost, enhance fuel
efficiency, minimise pressure will squeeze and Tesla may shift its market position in the
developing automotive sector.
Formal and informal legal systems and anti-trust laws and social economy
development
According to ongoing pace of change in the automotive space as well as related
technologies, which is combined with regulatory scrutiny as well as recent development in
trade, the global car manufacturing sector can estimate the possible risks and barriers in 2020.
Foley’s Automotive Industry Team developed the report that examines what the legal
landscape can look in the coming years. It can be highlighted that increased pace of the
launch of advance technologies as well as software integrated into new cars may create new
sort of risks for Tesla. In this context, Dwivedi et al. (2017) commented that as the purpose
of liability shift away from human drivers as well as towards electrical system component can
brings risk for Tesla. On the contrary, Gao et al. (2016) mentioned that few large Anti-Trust
cases have been introduced in US lately and total enforcement activity can be slower
compared to previous eras but it can be mentioned that there is large scope of potential cases.
Dwivedi, Srivastava and Srivastava (2017) mentioned that United State Anti-Trust regulators
is a significant threat to US innovators, and the especially the companies like Tesla that runs
business in the global markets. The risk is quite possible to occur because European Union
penalized Google $5 billion in 2018 which is a great amount of lost capital which can have
created consumer value instead.
4. Conclusion and Recommendation
The above presented analysis state the fact that even though Tesla with its disruptive
business model is going to penetrate the market with its electronic car models, the

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organization is most likely face certain challenges. Firstly, Technology-driven trends are
most likely to revolutionise how the big players in the sector respond to changing customer
behaviour, build partnership as well as drive transformational change. Economy today is
dramatically changing and this is triggered by the development mostly in accelerated increase
of advance technologies, emerging markets, policies of sustainability and change in customer
preferences. In addition, as per the global understanding of game-changing disruption already
on the horizon, there lacks an integrated perspective on how the sector may look in 10 to 15
years as the consequence of such change. Therefore, Tesla being the significant part of 2020
automotive revolution focussing on the scenario about the changes appearing and how the
changes are most likely affect conventional vehicle manufacturing, suppliers and new
potential players. By 2030 almost 14% of the global workforce might have to look for new
jobs. This scenario significantly indicates the fact that rapid growth in Artificial Intelligence
as well as automated machine learning and task range increase can be effective in cost
minimization.
Recommendation
Skill Development:
Findings indicate that the fact that automotive sector is most likely face employment
crisis because the whole sector is going to be automated in the coming years. To beat this
challenge, Tesla needs to focus on skills development. For example, if car manufacturing
sector is applying machine language in its cars, employees of Tesla needs to be provided with
machine language training in which the employees will learn how machine language is being
implemented in the car manufacturing and how it is being operated. As the automated
scenario indicates that if employees are not trained to join the race, there will be a significant
skills gap.

21SOCIAL ECONOMIC AND LEGAL FRAMEWORK
Joint-venture business to beat shared economy:
Given the findings presented above, shared economy can affect the sales of privately
owned cars manufactured by Tesla. To beat this challenge, Tesla needs to change its focus
from high-end markets and join the race of the shared service to deal with economy. This
means the organization can come in joint-venture with incumbent players like Uber, or any
other car manufacturer. As per the new venture, Tesla will provide vehicles to meet the
demands of shared economy services in the sector. This will enable the brand to defeat the
sales challenges. This recommendation is feasible because the car manufacturer Hyundai and
Uber together have manufactured flight taxi as the shared economy service.

22SOCIAL ECONOMIC AND LEGAL FRAMEWORK
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