Systemic innovation and project learning: from firm to ecosystem learning capability

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The forced march of carmakers towards electrification

Apart some first movers, such as Toyota and Honda with hybrids in the 2000s or Renault, Nissan, Tesla with Battery Electric Vehicles (BEV) in the 2010s, global players are not moving towards electrification on their own will. They are constrained by a global set of increasingly stringent environmental regulations including:
1. Reduction of the level of greenhouse gas emissions3 (GHG – CO2) leading to the definition of a maximum threshold, e.g. 95 gCO2 /km in 2021 in Europe,
2. Reduction of the level of pollutants emissions (particulate matter, nitrogen oxides, unburnt hydrocarbons and carbon monoxide) also leading to the definition of maximum thresholds, such as Euro6d in Europe for the latest applicable regulation,
3. Electric vehicles mandate imposing a minimum percentage of sales of electrified vehicles such as 12% by 2020 in China or 22% in 2025 in California (plus nine other states representing 30% of new car sales in USA),
4. Worldwide internal combustion engines vehicles (ICEV) banning or phasing out initiatives (Burch and Gilchrist, 2018) whose first concrete impacts should be visible 2025 onwards,
5. The objective of carbon neutrality by 2050, resulting from the Paris Agreement which, given the length of time the car fleet is used, means a total ban on the sale of new internal combustion cars by 2035.
Therefore, in the next fifteen years, the automotive industry must definitively switch from ICEVs to electric vehicles (EVs). While different technological strategies4 have been observed and decisions to go to electrification have expanded over the past two decades, there appears to have been a general movement toward BEVs over the past three to four years.
Reuters 5 estimated that 29 car manufacturers have invested about $300 billion in electrification, showing that the industry has definitely taken the plunge. In fact, all global players announce the arrival on the market of BEVs and Bloomberg6 has identified 500 EV models on the market by 2022.
As far as market shares, under the effect of COVID19, in the first half of 2020 compared to 2019, passenger car sales collapsed worldwide, falling 28% while EV sales fell only 14%. In China, New Energy Vehicles (NEV) sales fell 42% compared to 20% for the overall vehicle market, due to lower subsidies and stricter technical requirements7. However, in Europe, in the second quarter of 2020 compared to 2019, where the market declined by more than 50%, rechargeable car sales increased by 53.3% to reach a market share of 7.2%8 thanks to proactive subsidy policies, especially in France.
In its global outlook 20209, the International Energy Agency highlights that even if global electric passenger car sales are sluggish in 2019, although better than in 2018, the global stock has now exceeded 7 million vehicles underpinned by policies that “… have set clear, long-term signals to the auto industry and consumers that support the transition in an economically sustainable manner for governments”. On its side, prior to the current crisis, Bloomberg5 expected sales of 8.5 million EVs by 2025 tripling in 2030 up to 26 million and considers, in its latest forecast10, that “The long-term trajectory has not changed, but the market will be bumpy for the next three years.”

 What are the impacts of electrification on the automotive industry?

Therefore, this thesis is based on a very strong initial conviction strengthened by concrete facts: The scaling up of EVs is ongoing, with the ICEVS to EVs tipping point expected to occur around 2035, although the ramp-up is delayed because of COVID-19! This leads to formulate an empirical question: how is the automotive industry managing this transition from internal combustion vehicles to electric vehicles? What are the impacts of the technological evolutions linked to electrification on the structure of this industry?
This empirical question is in line with the rich tradition of academic work on the question of the relationship between technological change and industry dynamics summarized by Nelson as follows “… firm and industry structure ‘coevolve’ with the technology” (1994, p. 47). Elaborating on this stream of research allows us to formulate the initial question of this thesis as follows: « Technological breakthrough and dynamics of an industry, the transition towards electromobility case ».

An initial question founded on strategic theories

All the research work of this stream highlights the importance of distinguishing between two types of technological innovation: incremental innovation, which is a succession of minor changes that improve the performance of a design, and radical innovation, which, on the contrary, involves fundamentally different design rules and scientific principles.
Abernathy and Utterback (1978, p. 42) have shown how these two types of innovation, although opposite to each other, can combine to contribute to « A Transition from Radical to Evolutionary Innovation » or how the introduction of a radical innovation can lead to the emergence of a dominant design that will then be regularly optimized by a succession of incremental innovations. They also explain that the emergence of a dominant design leads to the creation of a mass manufacturing industry, of which the automotive industry is one of the most emblematic examples.
However, noting that these two notions are insufficient to describe all cases of innovation, Henderson and Clark (1990), by emphasizing the importance of the relationships between the different components (the interfaces) within a technical solution, added the notions of modular innovation (overturned core concepts of a solution with unchanged interfaces) and architectural innovation (reinforced core concepts of a solution with changed interfaces). They add (1990, p. 12) “The essence of an architectural innovation is the reconfiguration of an established system to link together existing components in a new way”. As, for incumbent companies in the mass production industry, which tend to remain in the dominant field of design (Abernathy and Utterback, 1978), the bulk of the innovation focuses on components whose interrelationships are defined within the framework of a stabilized product architecture, they conclude that, when faced with architectural innovation, incumbent companies may have two main problems: (1) recognizing that an innovation is of architectural type and (2) having the capacity to implement it.
On their side, Bowen and Christensen (1995) have described sustaining and disruptive technologies, the latter being characterized by the proposition of an offer whose performance characteristics are below the usual expectations of customers; here again, the differentiation between these two concepts has made it possible to contribute to the study of the importance of technology management choices on business dynamics. Indeed, they have shown that many established companies, that had ignored these disruptive technologies because they were focused on their own customers’ satisfaction, have seen their market share decrease or even be reduced to zero when these technologies, thanks to their rapid performance progression, have allowed new entrants either to capture their traditional customers or to create new markets. Finally, it is worth mentioning that a disruptive innovation can only emerge because there are potential customers who are willing to accept lower performance than that appreciated by dominant customers because it meets their specific expectations (Kim and Mauborgne, 2005).
In his analysis of the reaction of incumbent firms to new technologies, Nelson indicates that, in a phase of stabilized dominant design, they are focused on optimizing their business processes and infers: « this suggests that established firms may have considerable difficulty in adjusting, in gaining control of needed different capabilities, when important new technologies that have the potential to replace prevailing ones come into being » (Nelson, 1993, p. 54). He, thus, confirms the difficulties encountered by incumbent companies faced with the introduction of a new technology whatever its nature.
When Porter, in his paper focusing on the competitiveness of firms, states « Everything a firm does involves technology of some sort » (1985a, p. 62), he emphasizes the importance of technology in the functioning of firms, but also makes it very clear that any technological change is important, not intrinsically, but because it changes the competitiveness of a firm; he also explains that the impact of a value-creating technology goes far beyond the firm that developed it, since its diffusion within an industry can greatly contribute to changing both its structure and its attractiveness.
These theoretical frameworks, which are important for understanding and studying the emergence of an innovative technology, have very often been used only at the level of a company, whereas a systemic innovation must be deployed in an ecosystem, well beyond the perimeter of a single company: its benefits “can be realized only in conjunction with related, complementary innovations” (Chesbrough and Teece, 1996, p. 128) developed by a set of external actors playing their part (Afuah and Bahram, 1995; Tushman and Anderson, 1986). This statement refers to the notion of complementarity and co-specialization of offers (Teece, 1986), i.e. the fact that the players in the ecosystem develop different, non-generic offers, which cannot be obtained simply through the market, the combination of which brings value. A systemic disruption can also be defined as a transition that combines four characteristics : (i) the level of radicalism in the disruption introduced; (ii) the extent and heterogeneity of the scope of the players they mobilize; (iii) the scale of the projects; (iv) the speed of the expected transitions (Maniak et al., 2014b; Midler and von Pechmann, 2019; von Pechmann et al., 2015).
The introduction of electric traction has already been described as a systemic disruption (von Pechmann et al., 2015), which is correct insofar as the cost and range performance of an electric vehicle is still below that of a combustion vehicle, or as being systemic because its success requires the intervention, within an ecosystem, of many actors with complementary and co-specialized offers (Teece, 1986) such as energy suppliers, electric batteries, charging systems (Donada and Attias, 2015; Donada and Perez, 2018; Vazquez et al., 2018). Finally, there is also the question of whether the integration of high-voltage electric battery and electric propulsion systems into a vehicle is an area of architectural innovation and, if so, whether established manufacturers are able to seize this opportunity.
The concept of industry architecture is also part of the theoretical framework that needs to be mobilized; broadening the concept of bilateral relationships, which refers to the highly centralized way in which companies manage their value chains through numerous dyads of parallel buyer-supplier relationships (Porter, 1985a; Williamson, 1985), Jacobides et al. (2006, p. 1205) synthetize the notion of industry architecture as “Thus, industry architectures provide two templates, each comprising a set of rules: (1) a template defining value creation and division of labor, i.e. who can do what (2) a template defining value appropriation and division of surplus, or revenue, i.e. who gets what”. An industry architecture emerges in the early days of the industry, shaped by product design decisions (Baldwin and Clark, 2000), by regulations, industry standards, technology or, generally speaking, interfaces (Jacobides et al., 2006; Jacobides and MacDuffie, 2013; Jacobides and Winter, 2005), as well as knowledge and technical capabilities of firms (Zirpoli and Camuffo, 2009). The ability to act, vis-à-vis the end customer, as a guarantor and responsible party for the quality of the products and compliance with regulations relating to safety and health issues is also a fundamental characteristic of a focal firm in an industry architecture, especially in the automotive industry (Jacobides and MacDuffie, 2013). The consolidation of a dominant design contributes greatly to shaping the architecture of an industry, and indeed dominant design and industrial architecture are highly interdependent and mutually reinforcing (Abernathy and Utterback, 1978; Jacobides, 2006; Tushman and Anderson, 1986).

The automotive industry is and remains resilient

Building on these strategic theories, several authors have argued that the automotive industry is particularly resilient and that automakers have the means to keep control of the industry (Jacobides et al., 2016; Jacobides and MacDuffie, 2013; MacDuffie and Fujimoto, 2010; Wells and Nieuwenhuis, 2012). To support their assertion, they state that carmakers act as system integrators because they drive innovation, product strategy and higher value-added manufacturing segments (Gereffi et al., 2005). As it includes the assembly and final inspection of the complete automotive system, they thus retain control of the most strategic assets. De facto, they are then the only ones able to respond to the trend towards integral design imposed by increasingly stringent regulations (Fujimoto, 2017; MacDuffie, 2013) as well as to act as guarantors of quality for end customers and compliance with regulations relating to safety and health issues (Jacobides et al., 2006 ; Jacobides et Mac Duffie, 2013). They are at the top of a hierarchical value chain that they control (Wells and Nieuwenhuis, 2012) and guide future developments. Moreover, the architecture of this industry, after numerous outsourcing operations in the late 1990s, has now been stable for many years (Donada, 2013; Jacobides and MacDuffie, 2013; MacDuffie and Fujimoto, 2010). Finally, mastering the relationship with the customer, through a vehicle distribution and repair network, offering services (financing, insurance, maintenance, to name a few) or the ability to guarantee quality and compliance with regulations relating to safety and health issues (Jacobides et al., 2006; Jacobides and MacDuffie, 2013), is certainly one of the major reasons explaining the dominant position of carmakers.
While some authors, prior to the EV scale-up that is currently taking place, predicted that vehicle electrification will not change this long-lasting situation (Jacobides et al., 2006; Jacobides and MacDuffie, 2013), this assertion deserves to be re-examined since electrification radically transforms the technological core of conventional mobility which is the oldest fundamental of the dominant design of the automotive industry.
It is therefore to answer this theoretical question « Will the scale-up of electric vehicles (EV) disrupt the architecture of the automotive industry? », that this thesis begins with an empirical study. The analysis focuses on how the electric traction value chain is constructed, and more specifically: « the current strategic choices (observable in early 2020) of car manufacturers, namely to manufacture, buy or ally, to develop electric vehicles as well as the two main systems of electric traction, namely those of the high-voltage battery and electric propulsion ». For each car manufacturer observed, there are three units of analysis: the manufacture of electric vehicles, the value chain of the high-voltage battery system (a key component, both from a technical and economic point of view) and that of the electric propulsion system. This study includes both incumbent (cumulating roughly 70% of the global market share) and new entrants (EVs top selling companies), all global players from different countries of origin, to determine whether or not seniority in the automotive sector or regional/national conditions have an influence on their strategy.
This empirical study shows that the elements put forward to explain the resilience of the automotive industry are, to date, confirmed:
1. The ability to achieve integral design (Fujimoto, 2017 ; MacDuffie, 2013), the design agility linked to the continuous integration of product evolutions (Wells and Nieuwenhuis, 2012), and the persistence of operational routines (Zirpoli and Camuffo, 2009), effectively enable car manufacturers to master the design and production of electric traction systems as well as to produce electric and thermal vehicles on the same assembly lines (Alochet and Midler, 2019),
2. Their hierarchical mastery of the value chain and the rules of its operation (Wells and Nieuwenhuis, 2012), allows them to treat suppliers of electric traction system components, new entrants or established Tier 1 suppliers, as commodity suppliers11 ,
3. Their capacity to deploy the stringent regulations to reduce CO2 and pollutants emission still assert themselves as guarantors of the quality of the final product (Jacobides et al., 2006; Jacobides and MacDuffie, 2013),
4. In doing so, they exploit the powerful business model that has supported this industry for almost a century and the deeply rooted cultural, social status that makes the automobile the preferred means of individual mobility (Wells and Nieuwenhuis, 2012).
The results of this study apply to all the global manufacturers observed, regardless of their country of origin, even if some of them, which started later in the development of BEVs, have entered into cooperation, with electric traction specialists or other carmakers, to catch up with the market.
As far as the two new entrants are concerned, BYD, which comes from the battery industry, is highly integrated on the axis of electric traction systems. On its side, Tesla, which is recognized as a disruptive new player, has developed vertical integration strategies that Henry Ford would have no trouble recognizing as an early automotive practice. As a result, in terms of value chain management, they have both followed in the footsteps of installed manufacturers.
This study is the first result to be credited to this thesis, as it is the first contribution to a wide-ranging empirical validation of the hypothesis of resilience of the historic architecture of the automotive industry to the rise of electrification.
Beyond this observation of stability which confirms, to date, the theoretical framework based on the strategy paradigm, another theoretical framework makes it possible to put forward different hypotheses for the future dynamics of this industry.
It is based on the double helix model, introduced by Fine and Whitney (1996), : « the double helix illustrates the oscillation in supply chain structure between vertical / integral and horizontal / modular » (Fine, 2009, p. 216).
While car manufacturers rely, in the short term, on their integration capabilities, a second stage of electrification could be envisaged, leading electric traction specialists to manufacture high-voltage battery and electric propulsion systems instead of car manufacturers.
Three major arguments can be put forward in favor of this hypothesis
1. The heavy and continuous trend towards de-verticalization and outsourcing of the automobile industry during the 20th century (Fourcade and Midler, 2005, 2004; Sako, 2003; Sako and Murray, 1999) which has led suppliers to produce between 70 and 75% of the value of a vehicle,
2. The superior modularity of electric traction compared to thermal traction which favors an outsourcing and specialization effect,
3. The ability of electric traction specialists, thanks to greater series effects, to achieve production cost and quality levels that are much more efficient than those of manufacturers.
In this new context, suppliers of high-voltage battery and electric propulsion systems could take over a significant share of the industry’s activity and value without destabilizing the industry’s overall architecture, as it is already the case for « big » modules (seats, cockpit, etc.).
Fine’s work is inspired by the microelectronics industry, where the speed of change in major components, makes it possible to reshuffle the cards at the speed of Moore’s law. He indicates (2009) that the same phenomena are also occurring in highly capital-intensive sectors such as the automotive industry, but at a slower pace because Very-large-scale integration (VLSI) design is significantly different from mechanical design (Whitney, 1996).
However, this movement is not yet visible for at least two reasons. Firstly, because, for carmakers, faced with the massive conversion of their internal combustion engine plants, in-house manufacturing of high-voltage battery or electric propulsion systems makes it possible to cushion the impact of electrification on jobs in a context where a redundancy strategy, combined with massive outsourced supplies, would be difficult to justify socially and politically.
Secondly, the battery system, including its power management strategy, has a major impact on the performance of an EV, whether in terms of range, maximum speed, charging speed or overall energy efficiency. Even if the intrinsic performance of the cell, the basic electro-chemical component of a battery pack, is important to meet the criteria mentioned above, it requires, above all, strong automotive design skills, such as weight optimization, cooling system design, electrical and thermal risk management, system integration, etc… On the other side, as all the improvements of the last decade have been done in the dominant design of liquid lithium ion technology, electrochemistry specialists haven’t had a chance, so far, to impose their technological pace to carmakers. Consequently, in the current state of knowledge12 of both battery suppliers and carmakers, the latter are in the best position to achieve this.
The obvious conclusion is that electrification, even if it modifies the design of a vehicle, is not enough to cause a destabilization of the industry. This conclusion calls for a new empirical question “Could the current situation of resilience of the automotive industry change over time?”

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Table of contents :

1.1. The forced march of carmakers towards electrification
1.2. What are the impacts of electrification on the automotive industry?
1.2.1. An initial question founded on strategic theories
1.2.2. The automotive industry is and remains resilient
1.3. What is the future of this industry made of?
1.3.1. The momentum of the automotive industry
1.3.2. An exploration of future mobility services
1.4. A theoretical pivoting induced by this new research question
1.5. An international benchmark about innovative mobility services
1.5.1. An original empirical framework
1.5.2. Ten cases in a nutshell
1.5.3. Characterizing the study cases
1.5.4. Uncovering three ideal types
1.5.5. Could the emergence of each ideal type destabilize the architecture of the industry?
1.6. Systemic innovation and project learning
1.7. From product-centric innovation to service-centric innovation
1.8. The influence of public environmental regulations on the automotive industry: a comparison between Europe and China
1.9. Methodology: description of an interactive research trajectory
2. Outline of the thesis
3. ESSAY 1: Will the scale-up of electric vehicles (EV) disrupt the architecture of the automotive industry?
3.1. Introduction
3.2. Literature review
3.2.1. An empirical question, in line with the rich tradition of research on the relationship between technology and industrial dynamics
3.2.2. A resilience hypothesis of the current industry architecture supported by strategic theories
3.3. Methodology
3.3.1. Architecture of the automotive industry
3.3.2. Theoretical sampling
3.3.3. Case definition
3.3.4. Framework
3.3.5. Data collection
3.4. Empirical study of the electric traction value chain
3.4.1. Observation of the vehicle production system
3.4.2. Observation of the battery system value chains
3.4.3. Observation of electric powertrain system value chains
3.4.4. Summary of the role of the actors
3.5. Discussion
3.5.1. Observation of the current situation
3.5.2. Description of the redistribution dynamic
3.5.3. Description of the disruption dynamic
3.6. Conclusion and future research issues
3.7. Annexes
3.7.1. BMW study case
3.7.2. BYD Study case
3.7.3. Daimler Study case
3.7.4. FCA Study case
3.7.5. Ford Study case
3.7.6. GM Study case
3.7.7. Honda Study case
3.7.8. Hyundai Study case
3.7.9. Nissan Study case
3.7.10. PSA Study case
3.7.11. Renault Study case
3.7.12. Tesla Study case
3.7.13. Toyota Study case
3.7.14. VW Study case
4. ESSAY 2: Automobile industry, towards an electric autonomous mobility service industry? A sociotechnical transition-based approach
4.1. Introduction
4.2. The automotive industry, on the move towards an industry of connected, autonomous, shared and electrified mobility services?
4.3. Literature review, identifying a framework to study the automotive industry transition
4.3.1. A resilience hypothesis of the current industry architecture supported by strategic theories
4.3.2. The paradigm of Socio-Technical Transitions
4.4. Analytical frameworks to study the electromobility transition
4.4.1. A global MLP framework for electromobility study
4.4.2. A framework for specifying the direction and intensity of the automotive industry transition to mobility services
4.5. Research design
4.5.1. Designing an international research
4.5.2. Theoretical sampling
4.5.3. Case definition
4.5.4. Analytical Framework and methodology
4.6. Results presentation
4.6.1. Ten initiatives in a nutshell
4.6.2. Characterizing the orientation and radicality of the innovations
4.6.3. Characterizing the role of the social actors activating the transition
4.7. Discussion: what could happen?
4.7.1. The transition of auto industry to an electric, autonomous connected and shared mobility: Towards three possible MaaS models?
4.7.2. Making the transition happen: the role of the key players towards ideal types
4.8. Conclusion and future research
5. ESSAY 3: Systemic innovation and project learning: from firm to ecosystem learning capability
5.1. Introduction
5.2. Context: the automotive mobility momentum, 2020-2035 the end of a century automobile paradigm
5.3. Literature review, research question and theoretical framework
5.4. Methodology
5.4.1. Choice of the industry
5.4.2. Theoretical sampling
5.4.3. Designing an international research
5.4.4. Case definition
5.4.5. Framework
5.5. Preliminary results on 3 projects
5.5.1. Characterizing the mobility solution ambition
5.5.2. Characterizing the ecosystem composition and structure
5.5.3. Characterizing the internal learning process of the project: mitigating the technical, financial, systemic and performance risks in bottleneck management
5.5.4. Characterizing the project to project learning in ecosystem project context ..
5.6. Discussion
5.6.1. Projects as key playground for systemic innovation and nascent ecosystems
5.6.2. Ecosystem identity and innovation orientation
5.6.3. Managing the inside project learning: risk strategy and leadership in the ecosystem
5.6.4. Systemic innovation and project to project learning
5.6.5. Systemic innovation and project learning efficiency: public authorities as systemic innovation project learning leaders?
5.7. Conclusion
6. ESSAY 4: How do servitization impact on project management? Some examples from the emergence of MaaS
6.1. Introduction
6.2.1. Coupling product and services
6.2.2. Impact of servitization on product-oriented innovation project management
6.2.3. Management of a product-oriented innovation project
6.2.4. Characterization of service vs product design domain
6.3. Methodology
6.3.1. The transition of auto industry to MaaS: an emblematic case of product centric to service centric innovation management
6.3.2. A case study methodology
6.3.3. A framework to describe the mobility service initiatives
6.4. Results presentation
6.4.1. Three cases in a nutshell
6.4.2. How does it impact the nature of the relation between product and service at design level?
6.4.3. What is the impact on product validation?
6.4.4. What is the impact on the governance of project?
6.5. Discussion
6.6. Conclusive remarks
7. ESSAY 5: Are Chinese regulations shaping the worldwide EVs industry?
7.1. Introduction
7.2. Literature review, building a theoretical framework to study governance of regulations
7.3. Methodology, characterizing the dynamics of regulation
7.3.1. A relevant TEF instantiation to support our study
7.3.2. Empirical field of study
7.3.3. Data collection
7.4. European regulations, driven by achieving strong reductions of emissions’ levels
7.4.1. Description of emission regulations and their dynamics over time
7.4.2.A fair competition-oriented governance of regulation
7.5. Chinese NEV regulations, constant adaptation towards the growth of the market
7.5.1. Description of EV regulations and their dynamics over time
7.5.2. A regulation governance to develop an industry sector
7.6. Discussion
7.7. Conclusion
7.8. Appendices
7.8.2. List of policies addressing the allocation of subsidies related to battery system and vehicle performances
7.8.3. List of policies addressing the construction of the NEV industry
8.1. Empirical results
8.2. Theoretical contributions
8.3. Managerial Contributions
8.4. The dialectic of empirical questioning and theoretical frameworks
8.5. Limitations


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