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Sterk, F.; Heinz, D.; Hengstler, P.; Weinhardt, C. (2023): Reallocating Uncertainty in Incumbent
Firms through Digital Platforms: The Case of Google’s Automotive Ecosystem Involvement.
Proceedings of the 44th International Conference on Information Systems (ICIS 2023).
Acknowledgements:
Acknowledgements: This work has been partially supported by the German Federal Ministry of
Education and Research through the research project “bi.smart” (grant no. 02J19B041).
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Institute of Information Systems and Marketing (IISM)
Kaiserstr. 89
76133 Karlsruhe
Germany
Karlsruhe Service Research Institute (KSRI)
Kaiserstr. 89
76133 Karlsruhe
Germany
Reallocating Uncertainty in Incumbent Firms through Digital Platforms
Forty-Fourth International Conference on Information Systems, Hyderabad 2023
1
Completed Research Paper
Felix Sterk
Karlsruhe Institute of Technology
Karlsruhe, Germany
felix.sterk@kit.edu
Daniel Heinz
Karlsruhe Institute of Technology
Karlsruhe, Germany
daniel.heinz@kit.edu
Petra Hengstler
Karlsruhe Institute of Technology
Karlsruhe, Germany
petra.hengstler@student.kit.edu
Christof Weinhardt
Karlsruhe Institute of Technology
Karlsruhe, Germany
weinhardt@kit.edu
Abstract
This research examines how incumbent firms decide on the degree of involvement of
technology players in their digital strategies, by integrating insights from digital
innovation and digital platform research. We conducted an embedded case study on the
adoption of Googles Android Automotive OS and Google Automotive Services by the
automotive industry, using semi-structured interviews with industry experts and senior
decision-makers. We build on affordance-actualization theory to develop a grounded
model of uncertainty reallocation consisting of five aggregate dimensions: (1) external
digital platform by tech firm, (2) incumbent firm and its goals, (3) uncertainty tradeoffs
and affordance of reallocation, (4) strategic actions by incumbent firm, and (5) short-
and long-term outcomes. Our results provide valuable insights into the selection of non-
binary platform strategies and the effects of various levels of technology firm
involvement. This addition to the knowledge base of the information systems discipline
provides practical guidance for incumbent firms navigating digital transformation.
Keywords: Digital platforms, Digital innovation, Incumbent firms, Uncertainty reallocation
Introduction
The automotive industry is undergoing a significant transformation due to digital technologies that
challenge original equipment manufacturers (OEMs) (Bohnsack et al., 2021; Svahn et al., 2017). By 2030,
modern OEMs aim to generate up to 50% of their profits from recurring digital revenue streams (Römer et
al., 2022). Yet, many are still struggling to adopt a digital-first approach, vital for realizing software-defined
vehicles (Dremel et al., 2017; Svahn et al., 2017). Cars are evolving from status symbols to smartphones on
(Hanelt et al., 2015; Kaiser et al., 2018), with infotainment systems playing a central role (Weiss et
al., 2021). With up to 40% of drivers considering switching brands for superior digital services such as
integrated navigation and entertainment features (Heineke et al., 2020), tech players are in a favorable
position. They leverage their smartphone expertise, using infotainment as a medium to occupy the digital
interface between the driver and the vehicle (Schreieck et al., 2022; Weiss et al., 2021). For example, Google
not only attracts drivers with its navigation application, Google Maps, but offers an operating system (OS)
for entire infotainment suites (Legenvre et al., 2022). This growing proficiency of tech players in automotive
dynamics could relegate OEMs to mere hardware producers, reshaping the industry value chain.
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An incumbent firm is defined as a well-established firm with a significant market share in its industry, often
with long-standing customer relationships and operational processes (Porter, 1985). Most incumbent firms
must revise their business strategies to remain competitive in the digital age, which is currently dominated
by tech players (Hermes et al., 2021; Sebastian et al., 2017). Incumbents, which have years of experience
enhancing their pipeline business models, need to broaden their traditional value-creation logic to include
digital platforms (Marheine et al., 2021; Van Alstyne et al., 2016). However, the pursuit of digital innovation
brings unique challenges, such as lack of expertise, surging costs, and changing customer expectations (Gao
et al., 2022; Oberländer et al., 2021; Sterk et al., 2022). Previous studies have examined how incumbent
firms transition to the platform economy and the required changes to benefit from platform economics
(Sandberg et al., 2020; Sebastian et al., 2017; Svahn et al., 2017). However, they have usually assumed that
incumbents have only two alternatives for platform strategizing: building or joining (Cusumano et al., 2019;
Hein et al., 2020). They overlooked the potential to collaborate, assemble, configure, or contribute to open-
source, white-label, or tech firm-provided platforms (Hermes et al., 2021). Our objective is to explore the
non-binary elements in platform strategy and the impacts of varying levels of tech firm involvement. We
ask: How and why do incumbent firms decide on a certain level of tech player involvement in their digital
strategy?
We conduct an embedded case study (Yin, 2014) focusing on Automotive OS (AAOS) and
its underlying Google Automotive Services (GAS) as the sole locus of our research. Our research is based on
semi-structured interviews with industry experts and senior decision-makers knowledgeable about
digital platforms and their adoption by incumbent OEMs, as well as publicly available information
published from the AAOS inception in May 2017 through April 2023. In the process, we find three distinct
digital strategies that offerings. Through grounded-
theory-based interpretive data analysis (Gioia et al., 2013), we identified uncertainty reallocation as a core
construct and derived five aggregate dimensions that represent the building blocks of a grounded model
(1) external digital platform by tech firm, (2) incumbent firm and its goals, (3) uncertainty tradeoffs and
affordance of reallocation, (4) strategic actions by incumbent firm, and (5) short- and long-term outcomes.
The remainder of this paper is organized as follows: First, we outline the theoretical foundations of
uncertainty in digital innovation processes and boundary resources in digital platforms. Next, we outline
the research method of our case study, followed by the analytical results. Finally, we present a grounded
model of uncertainty reallocation through digital platforms, discuss the implications of our research, and
provide a brief conclusion on its limitations and further research opportunities.
Theoretical Foundations
Uncertainty in Digital Innovation Processes
The digital era introduces numerous uncertainties for incumbent firms (Salmela et al., 2022; Svahn et al.,
2017) as they navigate a volatile, uncertain, complex, and ambiguous (VUCA) environment while redefining
their organizational identity and purpose (Wessel et al., 2021). Uncertainty, defined as
deficiency in any phase or activity of the process, which can be characterized as not definite, not known,
(Kreye et al., 2012, p. 683), or simply, a (Kreye et al., 2012; Ramirez
Hernandez & Kreye, 2021), leads decision makers to have low confidence in predicting future outcomes
resulting from their decisions (Erkoyuncu et al., 2013; Ramirez Hernandez & Kreye, 2021). Unlike risk,
which is defined as a measurable unknown, uncertainty cannot be assigned a probability (Jalonen, 2012).
Uncertainty management throughout the innovation process has been studied in service management and
new product development (Ramirez Hernandez & Kreye, 2021). However, recent research emphasizes its
importance also in digital innovation processes in the context of Information Systems (IS) (Poeppelbuss et
al., 2022). These processes involve decisions under highly variable and uncertain future states, influencing
perceptions of strategic options for structuring, developing, using, and deploying IT artifacts (Kohli &
Melville, 2019; Nambisan, 2017; Nylén & Holmström, 2015). Factors contributing to increased uncertainty
include rapid technological developments, evolving customer demands, internal challenges in
understanding the affordances of digital technologies, determining the level of collaboration with suppliers
and partners, and assessing whether investments in digital innovation will yield the required returns for all
actors involved in the ecosystem (Nambisan, 2017; Poeppelbuss et al., 2022; Svahn et al., 2017).
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We adopt a multidimensional conceptualization of uncertainty (Poeppelbuss et al., 2022; Ramirez
Hernandez & Kreye, 2021), while recognizing the interrelated nature of these dimensions
2013). Ramirez Hernandez and Kreye (2021) distinguish between the unpredictability of the external
environment (environmental uncertainty), the lack of experience with the technologies the organization
intends to adopt and employ (technical uncertainty), the organizational dynamics throughout the change
process (organizational uncertainty), the adequacy of financial, technical, and human resources (resource
uncertainty), and the inability to predict and explain the actions of external related actors (relational
uncertainty). This distinction allows us to delineate the different sources of uncertainty in our study.
Existing research suggests strategies for managing uncertainty by reducing it at its source or coping with it
by minimizing its impact (Poeppelbuss et al., 2022; Simangunsong et al., 2012). Organizations may also
engage in uncertainty reallocation by shifting criticality between uncertainty types (Poeppelbuss et al.,
2022; Ramirez Hernandez & Kreye, 2021). For instance, Poeppelbuss et al. (2022) empirically show how
participation in multi-actor innovation settings can reduce technical and resource uncertainty while
increasing relational uncertainty. In this context, our study explores how external digital platforms, such as
determine strategic actions to actualize and exploit these affordances.
Affordances of Boundary Resources in Digital Platforms
We define a digital platform as including services and contentthat enable
value- (Constantinides et al., 2018,
p.381). Digital platforms can provide technological affordances, which refer to what one individual or
organization with particular capabilities and purposes can or cannot do with (Majchrzak
& Markus, 2013, p. 832). To provide new affordances, digital platforms must possess inherent flexibility,
enabling them to be reconfigured as needed (Hein, Setzke, et al., 2019; Yoo et al., 2010). In addition, the
architecture of digital platforms is characterized by a high degree of modularity, facilitating the integration
of new modules without jeopardizing the entire system (Tiwana et al., 2010).
To design for such affordances, platform owners use boundary resources that enable complementors to
develop products or services on the digital platform (Eaton et al., 2015; Ghazawneh & Henfridsson, 2013;
Hein, Setzke, et al., 2019). Boundary resources can be software tools or rules that serve as the interface for
- (Ghazawneh &
Henfridsson, 2013, p. 174). The concept of boundary resources can be understood as a theoretical device
(Ghazawneh & Henfridsson, 2013) for digital platform owners to balance the tension between retaining
platform control and stimulating the generativity of third-party developers (Tilson et al., 2010). These
resources include technical and social elements, such as application programming interfaces (APIs), and
regulations, incentives, and guidelines, respectively (Aanestad et al., 2019).
Prior research has mainly focused on the boundary resources of digital smartphone platforms (Eaton et al.,
2015; Karhu et al., 2018, 2020). For instance, Eaton et al. (2015) explain
iOS platform change through distributed tuning. This process triggers cascade of adaptations and rejections
in a network of diverse actors and artifacts. Karhu et al. (2018)
identify four functions of boundary resources: defining openness, facilitating, loosening couplings, and
capturing value. Besides research on purely digital ecosystems, research has addressed boundary resources
in Internet of Things (IoT)-based digital platforms (Hein, Weking, et al., 2019; Petrik et al., 2021; Petrik &
Herzwurm, 2020). Our study integrates these research directions through a case study of
automotive platforms, AAOS and GAS, focusing on software-defined vehicles as complex IoT devices.
Specifically, we examine the affordances of boundary resources within AAOS and GAS to understand how
platform owners facilitate generativity for OEMs and third-party developers while retaining control.
Research Method
We use an embedded single-case study approach (Yin, 2014) to und how incumbent firms adapt their digital
strategies in terms of engaging with technology firms in response to them introducing digital platforms to
the market. This section details our case selection, data collection, and data analysis.
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Case Selection. We employ a revelatory single case strategy (Yin, 2014), which includes multiple subunits
of analysis and allows for variation across them to examine previously inaccessible dynamics of a
phenomenon (Yin, 2014). We chose the automotive industry and Googles AAOS along with its underlying
GAS features, such as Google Maps, Google Assistant, and Google Play Store as our case. Our selection was
motivated by the significant IT-driven innovation in the automotive sector, and Googles central role
through AAOS. Unlike alternatives such as Android Auto or Apple CarPlay, AAOS is specifically designed
for direct in-vehicle integration, allowing enhanced interaction with vehicle systems. Due to the increasing
partnerships between OEMs and Google, our study focuses mainly on the extent of Googl to
vehicle functions and data (e.g., AAOS with/without GAS). As embedded subunits within this case, we
analyze the strategic positioning of different incumbent firms regarding solutions
over time. Following a sampling logic that emphasizes subunit diversity (Yin, 2014), we identified three
distinct OEM actualization strategies by analyzing their strategic actions from 2017 to 2023, and used these
as the basis for abstracting knowledge across multiple embedded units of analysis. Figure 1 shows a timeline
of , along with the OEMs strategic positioning.
Figure 1. Case timeline of AAOS and GAS development and adoption by OEMs
Data Collection. Our primary data sources were interviews and archival documents, providing a multi-
faceted view of our case (Yin, 2014). Between June 2021 and April 2023, we interviewed 17 industry experts
and senior decision-makers actively involved in incumbent firms. These interviewees held pivotal roles in
understanding offerings (i.e., AAOS and GAS) and their adoption by automotive OEMs
(see Table 1). The timing of the interviews coincided with significant developments and announcements in
the automotive industry related to Googles offerings. Additionally, our secondary data source,
spanning May 2017 to April 2023, provides a broader historical context prior to the primary data collection
period. Using both convenience and theoretical sampling, we initially reached out to existing contracts in
the automotive industry and subsequently acquired additional interviewees to provide depth on specific
emerging aspects as the study progressed (Bryman, 2016). Participants were selected based on their
professional roles, ranging from technical experts to strategic decision-makers, to ensure an encompassing
perspective on our topic. While a wider pool of potential participants was initially identified, practical
constraints such as availability and sensitivity of the topic determined the final set of interviewees. While
the perspectives of car users were not considered central to the decision-making of incumbent firms, we
recognize their potential value in future studies that seek a broader understanding.
The semi-structured interviews, averaging 53 minutes, were structured around open-ended questions on
pre-defined topics (e.g., value-capturing strategy, data sovereignty, or scalability), conducted by two
authors, and their transcripts were analyzed using MAXQDA software. Our secondary data included 67
publicly available archival documents, such as articles, strategy update reports, and press releases, focusing
strategic activities related to AAOS and GAS between May 2017 and April 2023. By
analyzing this data, we identified 19 strategic activities by either Google or the OEMs (see Figure 1). OEMs
that planned to integrate AAOS or GAS in some way include BMW Group, Ford, General Motors, Honda,
Renault-Nissan-Mitsubishi, Mercedes-Benz, Volkswagen Group, Stellantis, Volvo, and Polestar.
Data Analysis. Following established procedures for inductive data analysis (Gioia, 2021; Gioia et al.,
2013), our analysis began with two authors independently reviewing interview transcripts and documents.
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During this phase, descriptive open and in-vivo codes were assigned to relevant segments to capture a range
of insights related to our research question. To ensure the reliability of our coding, both authors met
regularly to discuss discrepancies and arrive at a shared interpretation. This iterative a pproach fostered a
higher level of inter-coder reliability and ensured the robustness of the concepts and themes derived.
Supported by initial memos (e.g., preliminary diagrams), these team discussions helped reassemble the
data by aggregating clusters of descriptive codes into 46 informant-centered first-order concepts that served
as inferential and explanatory codes that highlighted explanatory patterns in the data. In the second-order
analysis, we further condensed related first-order concepts into 17 more research-centered second-order
themes. Finally, we distilled the second-order themes into five aggregated dimensions and developed a
grounded model. In the latter analytical steps, we the applied affordance-actualization theory (Strong et al.,
2014) as a theoretical lens to explain the conceptual relationships among the constructs.
Industry Sector
Company
Role of Interviewee (Years of Tenure)
Length
Car Manufacturer
OEMCorp1
Product Owner App Store (6)
72 min
Android Automotive Developer (6)
46 min
OEMCorp2
Lead Android Automotive Developer (8)
45 min
OEMCorp3
Senior Project Manager Vehicle Platform (6)
67 min
Project Manager Automotive Software (11)
68 min
OEMCorp4
Product Manager Digital Services (5)
59 min
OEMCorp5
Company Builder Automotive (6)
61 min
OEMCorp6
CEO/CTO Digital Innovation Unit (20)
66 min
Tier-1 Supplier
SupplierCorp1
Senior Android Automotive Developer (5)
51 min
Senior Vice President Engineering (24)
41 min
Product Lead Software-Defined Vehicle (8)
27 min
Product Manager Infotainment (8)
42 min
Business Owner Android Automotive (24)
46 min
SupplierCorp2
Director Navigation Software (13)
58 min
Consulting
ConsultingCorp1
Strategy Consultant Automotive (20)
44 min
ConsultingCorp2
Strategy Consultant Automotive (4)
44 min
Applied Research
ResearchCorp
Senior Automotive Software Architect (8)
62 min
Table 1. Overview of Interviewees
Insights from
In this section, we present analytical insights into how and why incumbent firms reallocate uncertainty by
deciding on the level of tech player involvement in their digital strategy. The focus of our embedded case
study is platform offering (i.e., AAOS and GAS), as Google currently holds the
predominant position in infotainment and operating systems, forcing traditional OEMs to reconsider their
digital strategy. We first describe the affordances of uncertainty reallocation by incumbent firms (i.e.,
carmakers) via the utilization of a tech firms (i.e., Google) external platform and then present findings
regarding the actualization strategies taken by incumbent firms.
Affordance of Uncertainty Reallocation
External Digital Platform by Tech Firm
The influx of tech players into the automotive industry has resulted in a more fragmented competitive
landscape. They provide external digital platforms to penetrate the market for certain areas of the
technology stack, as observed with Google operating system (AAOS) and the accompanying service
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offerings (GAS). Boundary resources play a crucial role and are an indispensable tool for platform owners
to implement digital platform strategies. In the context of Googles digital in-vehicle platform, we identified
boundary resources used to pursue four strategiesscale, capture value, standardize, and facilitate. In the
Figure 2. Data External Digital Platform by Tech Firm
Accelerating scalability via open-source license. Analogous to its smartphone OS, Google has
released AAOS under an open-source license so that OEMs can install AAOS in their cars without involving
Google and without entering into a contractual relationship with Google to make their derivatives of the
OS. The Product Lead of SupplierCorp2 -defined vehicle program pointed out the distinction
-source approach like Linux and having
as the shepherd of the open-In the end, AAOS itself is always
but it does not generate any monetary gains as From a
strategic perspective, the open-source license encourages as many OEMs as possible to integrate AAOS to
scale the ecosystem quickly. ConsultingCorp1summarized this aspect as follows:
open-source is Googls brilliant idea to make carmakers dependent without
directly charging licensing fees. [...] Some OEMs are afraid to work directly with Google due to the
licensing costs and dependency. However, some of them are being convinced because it is possible
to use AAOS open-source, which seems like Linux. This is the Trojan horse that OEMs fall for
because they dont have to pay (Strategy Consultant, ConsultingCorp1).
Capturing value via Google Automotive Services. While AAOS itself is open-source, Google has
developed value-adding software artifacts called Google Automotive Services (GAS) that interact with the
OS, including Google Maps, Google Assistant, and the Google Play Store. To use GAS, implementing OEMs
must enter into a licensing agreement and share proprietary data with Google. According to ResearchCorp
Software Architect, not on acquiring in-vehicle data. From a marketing standpoint, the
user is a more appealing ta primary scaling mechanism depends
on gaining access to user data in order to extract patterns to develop customized online advertising, and
improve the quality of applications such as Google Maps. third monetization mechanism is its Play
Store, which is mandatory for OEMs using GAS and charges a commission fee for third-party applications
hosted there. The Product Owner of OEMCorp1
The most exciting thing, from my point of view, is the business model. Who will earn money with
digital products in the vehicle in the future? If you look at how things have worked in the mobile
phone world, third-party app developers are the only ones earning money directly from digital
products. But who is the only one who gets a revenue share? Its the two big stores, Apple and
Google. The Play Store is one of three apps that come with GAS. And that means that the likelihood
that you as an automotive OEM can still earn money with digital products in the car afterwards
will be diminished.(Product Owner App Store, OEMCorp1).
Enforcing standardization via vehicle hardware abstraction layer. Regardless of whether an
OEM chooses the open-source option or licenses AAOS, the most important requirement for integrating
Android into their cars is the implementation of the vehicle hardware abstraction layer (VHAL). The VHAL
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extends the original Android framework for the automotive context and defines properties, such as
powertrain-related data, that must be supported by all OEMs implementing AAOS. Google enables OEMs
to extend the VHAL and integrate custom, manufacturer-specific properties, giving them control and data
sovereignty over the vehicle data sent to Google. However, according to analysis by s
Strategy Consultant, the authority ultimately remains with Google, as market demand for advanced
applications will force OEMs to share specific vehicle data items with Google and third-party developers:
The belief that the OEM has full control over the VHAL and data is a widespread misconception.
In reality, the OEM can only define supported data, and this poses a challenge as developers are
hesitant to build applications for a platform that is not based on a common foundation of supported
data and functionality. The platform business operates within a merciless economy of scale, and
without external developer support, the OEMs capacity to build customer relationships is severely
limited. This lack of scale and content will cause the standard to fail, as it will not be able to
secure a customer base.(Strategy Consultant, ConsultingCorp1).
Facilitating generativity via APIs, SKD, and client library. The success of Googles expansive
digital ecosystem can be attributed to its robust third-party developer community, which delivers a diverse
set of third-party apps available to end users. Implementing GAS comes with APIs and a software
development kit (SDK) that facilitates app development while guaranteeing a robust payment
infrastructure for all platform transactions through the Google Play Store. GAS provides extensive support
for app developers, including various resources such as tools, test suits, documentation, and collaborative
events (e.g., developer conferences). In addition, AAOS provides a client library called Google Play Services,
which facilitates frequent updates to developer APIs independently of OEMs. Finally, with its established
control mechanisms, Google takes responsibility for excluding undesirable or malicious apps, relieving the
OEM of the burden of ensuring the app quality in the store. s AAOS Business Owner
summarized the similarities and differences to a Linux-based OS for developers as follows:
similarities, but the architecture of Android is different, for example, because of the virtual machine
and the high-level APIs, which are mainly for third-party developers to develop apps . They just
promote it as an app development environment. The documentation for AAOS is not extensive for
he whole architecture and the setup for Android is
just to promote third-party apps (Business Owner Android Automotive, SupplierCorp1).
Incumbent Firm and Its Goals
The ongoing digital transformation is turning cars from status symbols into rolling computing platforms.
This paradigm shift has pushed OEM to re-evaluate their strategic goals, forcing them to make crucial
decisions about their future service offering and digital business models to remain their competitive edge
in the market. By implementing an appropriate digital strategy, OEMs can retain control of their businesses,
avoid commoditization by tech players, continue providing high-quality services to end customers, and tap
into recurring digital revenue streams. We found that OEMs have formulated four overarching goals
concerning their infotainment offering, which we discuss below (see Figure 3).
Figure 3. Data Structure
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Transforming into an ecosystem orchestrator. OEMs want to move from selling physical cars
within a linear value chain to orchestrating service-oriented business ecosystems. Due to the complex
nature of software-defined vehicles, they rely on third-party developers to expand their application
offerings while maintaining quality standards and managing costs efficiently. Implementing in-vehicle app
stores not only enhances the driving experience but also provides an opportunity to earn a significant
revenue share from third-party apps. The ecosystem orchestrator takes on the role of a gatekeeper,
controlling the selection of third-party apps and determining which are ultimately offered in the app store.
The Product Owner of OEMCorp1s app store emphasized the difference between the OEMs existing
business models and the coveted role of an ecosystem orchestrator:
Today, we dont have a platform business model, which means we dont build a two-sided
marketplace but sell products in the pipeline value creation, where we end up enriching the product
more and more through suppliers and sell it once to the customers. In the future, we want to build
a platform ecosystem where third-party developers develop apps for us. As a store provider, we
can set certain rules, such as what is allowed and what is prohibited. We can also ensure that these
rules are adhered to, and we can earn money with [the app store]. But as of today, no one makes
money with apps in cars. (Product Owner App Store, OEMCorp1).
Providing technology-driven service portfolio. An additional goal of incumbent firms is to provide
a value-adding digital app portfolio to meet increasing end user expectations. This includes the integration
of the other digital ecosystems, such as music streaming, into the vehicle, which has become standard
practice. Moreover, OEMs try to improve the performance of other in-vehicle services and reduce the
dependencies on smartphone mirroring, with navigation systems and voice assistants being the most
prominent. For instance, map application providers have the power to influence the driver with targeted
and prominently placed points of interest. With the vast amounts of in-vehicle data generated by sensors
and software, OEMs are looking to create analytical insights about the vehicle, the driver, and their
environment, enabling data-driven business models in areas such as insurance, after-sales, and fleet
management. Appropriately, the Product Owner of OEMCorp1s app store drew an analogy to the
smartphone and confirmed the significant potential underlying digital in-vehicle services:
Nobody can say, but I believe there is.
[...] But in 2005, very few people would have said that many billions of Euros would be turned over
in a quarter via an app store that runs on a mobile phone. And if you look at the possibilities, a
smartphone offers only a fraction of the interfaces and sensors or data that a car theoretically has.
If you take that as a measure of the potential for innovation, the business potential for digital
automotive (Product Owner App Store, OEMCorp1).
Differentiating via customer intimacy. As a third goal, OEMs seek to differentiate themselves
through unique brand identity and direct interaction with the end user via the digital cockpit. Control of the
digital interface, and therefore customer interaction, allows for a differentiated user experience and
improved customer value. In particular, premium carmakers strive to deliver rich digital experiences
seamlessly integrated with their overall brand identity and familiar aesthetics, such as intuitive
touchscreens. However, OEMs must retain control over the user touchpoint and central data to generate
and capitalize on increased satisfaction via brand-exclusive onboard experience. SupplierCorp2s Director
Navigation Software affirmed:
Today, its all about software and the experience you create for your customers, but also the
relationship you build with them. If the big screen in your car belongs to a third party [...] and they
own the direct relationship with the consumer, what is left for the OEM? How can they differentiate
themselves? How are they going to create and monetize value-added services on that platform in
the future? This is not about the operating system, but what they build on top of it, like their
own applications or ecosystem to keep that direct relationship with the consumer and collect and
use data to improve and monetize their products.(Director Navigation Software, SupplierCorp2).
Controlling critical software architecture. Finally, OEMs aim to strengthen their control over key
architectures and standards by expanding capabilities in OS and middleware. Both serve as critical vehicle
components that enable carmakers to integrate essential software-defined features into the vehicles rapidly.
These functionalities include remotely integrating additional battery power or activating seat heating
features through over-the-air updates. However, while OEMs are eager to expand their in-house software
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stack development to avoid external dependencies, lack of expertise, escalating costs, and lack of economies
of scale are putting pressure on them to partner with large tech companies. ResearchCorp
Software Architect added specific reasons for the strong emphasis on in-house development by OEMs:
-effective for the OEM to develop a custom proprietary operating
system. For example, AAOS requires a lot of heavy hardware. [...] Additionally, allowing external
tech players to take responsibility for the further development of the operating system poses
significant risks for the OEM. [...] Utilizing a third-party operating system entails a potential loss
of control over data, as the vendor may try to get as deep into the vehicle as possible.(Senior
Automotive Software Architect, ResearchCorp).
Uncertainty Tradeoffs and Affordance of Reallocation
The rise of digital platforms such as AAOS and GAS presents a significant potential to reduce uncertainty
for legacy carmakers. However, these also increase uncertainty compared to established pre-digital
strategies. In sum, external platforms may not necessarily reduce uncertainties but offer the potential to
reallocate them, requiring incumbents to balance multiple tradeoffs, as illustrated below (see Figure 4).
Figure 4. Data Uncertainty Tradeoffs and Affordance of Reallocation
Uncertainty tradeoff on the operating system. Whether to implement AAOS or build a proprietary
OS is a key consideration for OEMs. Using an external platform such as AAOS provides significant financial
benefits by reducing the need for continuous system updates with each new generation of hardware.
Developing and maintaining in-house technology stacks requires a large financial investment, including the
cost of hiring software developers with the necessary skills. Also, integrating mature off-the-shelf solutions
such as AAOS can improve time-to-market and scalability, especially in the low-volume luxury segment.
On the other hand raises uncertainties, even without the use of
GAS. Since AAOS is likely to become a standard feature in many provider of AAOS
would give them considerable power. They could cease releasing open-source versions of AAOS and offer
new versions under license agreements that require GAS or let the VHAL specifications force OEMs to share
critical vehicle data. A Company Builder from OEMCorp5 commented on this tradeoff as follows:
Implementing AAOS entails considerable uncertainty to OEMs, as it may result in a loss of control
over user data, user behavior, and system usage information. On the other hand, it must be
acknowledged that the automotive industry has yet failed to develop a stable operating system. In
this regard, I believe it is necessary to strike a balance. While this approach may present challenges,
I believe that the benefits of integrating a trusted and well-established operating system outweigh
(Company Builder Automotive, OEMCorp5).
Uncertainty tradeoff on the core application offering. The next critical strategic decision for
OEMs is whether to use GAS or develop and integrate its
vast training data from widespread smartphone use, which makes it difficult to develop navigation services
with comparable real-time geo-information as Google Maps or similar voice recognition capabilities as
Google Assistant. Moreover, many
mode and may demand a built-in version, exposing OEMs with alternative solutions to the threat of losing
customers. Despite the potential benefits, there are downsides to implementing GAS for OEMs, including
losing their digital customer touchpoints and user interactions to Google or limited visibility into data
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exchange. Finally, GAS offers limited customization of
in a reduced impact on brand identity and customer experience. The impact of this uncertainty factor varies
depending audience, as explained by OEMCorp1
differentiation. When using GAS, they have limited control over the user interface and experience
compared to building on plain Android open-source. However, this is not a general argument for
or against GAS; not all OEMs see differentiation in user experience and interface design as a
competitive differentiator, especially volume OEMs with lower-priced vehicles who place less
(Product Owner App Store, OEMCorp1).
Uncertainty tradeoff on the app store business model. When deciding on GAS, carmakers must
consider that it includes the integration of the Google Play Store as the in-car app store. Using GAS reduces
nty by ensuring robust payment mechanisms for all transactions and quality
control for third-party apps. Also, adherence to established standards can reduce threat
of limited app developer engagement and failure to achieve economies of scale. As a result, experts suggest
that the Google Play Store could outpace proprietary alternatives in terms of app quantity, as it facilitates
third-party app development through specific boundary resources (i.e., SDK, APIs, and client library).
However, embedding about its business model, as it prevents
them from pursuing the goal of becoming an ecosystem orchestrator by delegating control over third-party
app selection, user engagement, app sales tracking, and revenue sharing to Google. SupplierCorp1
Business Owner AAOS stressed the strategic options OEMs have regarding in-car app stores:
time when every major manufacturer was trying to develop their own app store. [...]
And how many apps did they have in there? Negligible. That approach has failed. In the second
wave, a few manufacturers started using the Google Play Store instead. However, what are the
others doing? They are looking for third-party app stores, ideally working with other OEMs to
hopefully reach
(Business Owner Android Automotive, SupplierCorp1).
Strategic Actualization Process
Strategic Actions by Incumbent Firm
When integrating Google into an OEMs in-vehicle offering, three actualization strategies have emerged
that involve the uncertainty tradeoffs discussed (see Figure 5). To illustrate the actions taken for each
strategy, we supplement the description of each type with a corresponding real-world example in the form
of a case vignette, also visualizing which architecture components come from Google (grey) and which come
from the OEM. (white) (see Vignette 1-3).
Figure 5. Data Strategic Actions by Incumbent Firm
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Swedish carmaker Volvo Cars and its subsidiary Polestar, both owned by
Chinese carmaker Geely, have been offering cars with built-in AAOS since
2020. Volvo is fully committed to the partnership resulting in all new cars
featuring the whole infotainment system supplied by Google, including
the pre-installed GAS. Thereby, Volvo or Polestar car drivers are
prompted to link their Google accounts. Furthermore, Google and Volvo
are taking their partnership to the next level with the integration of HD
Maps, where Google Maps will use additional car sensor data in real-time
to provide highly detailed and up-to-date road information.
-In Approach
Actions of holistic tech integration strategy. This strategy involves the comprehensive integration
of , in our case both the AAOS and GAS platforms (see Vignette 1:
-in approach). OEMs that adopt this strategy benefit from a rapid go-to-market,
allowing them to focus on their existing core competencies. Regular over-the-air updates of the AAOS base
architecture provided by Google ensure a continuous update of the OS and the pre-installed GAS provide
the OEM with an attractive service offering in exchange for licensing fees and dedicated vehicle data,
With this strategy, OEMs offer their end-
users a seamless experience that they are familiar with from their smartphones, including Google ID login,
the established Android look and feel, and popular Google applications. Google takes care of the app store,
security, and support for app developers, while the OEM takes the role of a complementor, allowing the
tech firm to orchestrate the digital ecosystem, including shaping ecosystem policies and receiving revenue
shares from third-party apps.
Starting in 2023, the BMW Group will be the first German carmaker to
launch an infotainment system based on the open-source variant of
AAOS, called BMW OS 9. This approach excludes permanently installed
GAS applications (e.g., Google Maps), as BMW wants to retain
independence in these areas. BMW also does not use the Google Play
Store and instead tries to build up its own Android-based commercial
ecosystem supported by selected suppliers. Here, BMW integrates
Faurecia Aptoidewhite-label app store, with BMW developing the user
interface to preserve its brand-specific design and experience.
Vignette 2. Illustrating -Source Approach
Actions of isolated tech integration strategy. The second strategy adopted by OEMs is to integrate
the open-source versions of a digital platform (e.g., AAOS), but not to use proprietary platforms and services
(e.g., GAS) in order to avoid becoming too dependent on the external platform providers (e.g., through
contractual agreements or payment obligations with Google) (see Vigne -source
approach). In pursuing this strategy, OEMs need to find alternatives to proprietary services. For example,
for in-car navigation systems and voice assistants, OEMs can either rely on their existing service offerings
or choose between the traditional make or buy binary. For the app store, most OEMs adopting this strategy
procure an Android-based white-label app store from a software vendor to retain the benefits for app
developers while outsourcing the app store development effort and retaining platform control. Compared
to the first strategy, the OEM replaces Google as the orchestrator, gaining the authority to set app store
rules and earn revenue share from third-party applications. The look and feel of the infotainment system
and data sovereignty remain with the OEM using open-source and white-label solutions.
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Mercedes-Benz took a unique approach to its software strategy in 2023.
Instead of choosing an off-the-shelf operating system like AAOS, the firm
developed a proprietary infotainment system called MB.OS. This choice
was made to retain control over customer relationships and data privacy,
and to integrate exclusive car functions. Mercedes is using Faurecia
-label app store, but has also formed a strategic, long-term
alliance with Google to be the first OEM building its own branded
navigation system using in-car data and Google Maps navigation features.
Actions of custom tech integration strategy. Apart from the two strategies of using open-source
platforms such as AAOS with or without proprietary platforms and services (here: GAS), Mercedes-Benz
has exemplified in our case a so far unique third strategy (see Vignette 3),
which relies on a proprietary OS without involvement to retain full control over the base-
layer of software architecture and overall integration. Although GAS is not involved, this strategy includes
the integration of certain Google services in exchange for licensing fees. For example, the OEM integrates
Google Maps, which includes rich location details and real-time and predictive traffic information. Under
this strategy, the OEM integrates specific Google services while maintaining its own brand and design, and
retaining sovereignty over user data. For the app store, the OEM also takes on the role of the platform owner
and uses a white-label solution for the app store. In the case of Mercedes, in order to provide a functional
app store despite the absence of AAOS, a container API is integrated to run Android apps.
Short- and Long-Term Outcomes
The commitment of incumbent OEMs to an actualization strategy, characterized by their degree of tech firm
integration, ultimately leads to different short- and long-term outcomes. In this subsection, we analyze the
(anticipated) outcomes for each of the specified strategies (see Figure 6).
Figure 6. Data Structure - and Long-
Anticipated outcomes of holistic strategy. The holistic tech integration strategy offers early adopters
in the short term a state-of-the-art infotainment system with high recognition value (e.g., due to the
popularity of Android in the smartphone sector) and a time advantage over other OEMs, since white-label
app store providers have to follow GoogleAndroid development. This time advantage is reinforced by
close collaboration with the tech partner, allowing the OEM to be the first to release new services, such as
in our case the next-level navigation feature HD Maps. However, OEMs cede the direct touchpoint with
the end user, along with valuable insights into user engagement with the infotainment system and specific
vehicle data, to Google. In the long run, this approach results in the OEM losing critical infotainment
capabilities and the ability to provide data-driven aftermarket services to various end users (consumer,
business, and government), including the domains of fleet management, driving analytics, and location-
based services. Automotive Software Project Manager highlighted this aspect as follows:
r unique vehicle data-based services that OEMs currently
lack the competence to provide. As a result, OEMs may transform into pure chassis suppliers,
leaving Google to derive services and business models from the data. In the past, car ownership
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was a simple process with limited customer interaction. Now, customers can pay for additional
vehicle functions and personalize their vehicles. Aftersales, for example, is the absolute cash cow of
the automotive industry and involves continuous customer support and the exploration of new sales
channels. By handling this over
(Project Manager Automotive Software, OEMCorp3).
Anticipated outcomes of isolated strategy. short-term outcome of pursuing the isolated
tech integration strategy is to initiate a stable and scalable OS based on the established open-source
standards (here: AAOS), which, due to its open-source nature, is constantly being supplemented by a vast
developer community. In addition, this approach allows for the creation of a proprietary ecosystem that is
mostly independent of the tech firm and gives OEMs control over key differentiators and business model
elements, including data ownership, user interface, and app store orchestration. However, OEMs must find
competitive alternative solutions with equivalent performance to the
to avoid customer churn due to a potentially inferior user experience
digital offerings. Moreover, the long-term viability of working with white-label app store providers as a
genuine alternative to the Google Play Store remains unclear. This approach can only succeed if the
adaptation effort for third-party developers to place their apps in multiple Android-based app stores
remains manageable, and the tech firm continues to provide the necessary boundary resources (e.g.,
APIs). Finally, a Company Builder Automotive from OEMCorp5 stressed that a possible long-term
outcome could be Google using its position of power to gain more access to vehicle data in the future:
In the future, Google may try to get access to as much car sensor data as possible. For years Ive
been discussing using all powers of persuasion that we as an OEM can tap into insanely cool data,
whether from the camera, temperature, or light sensors. Conversely, Google has seen through
this potential of moving sensor stations [i.e., cars] for years because they collect everything that
isnt nailed down with their smartphones. Google may exploit this lock-in effect to get access to
more vehicle sensor data. I have no idea how the OEMs are going to fight this(Company Builder
Automotive, OEMCorp5).
Anticipated outcomes of custom strategy. OEMs that negotiate individual deals with a tech firm
reap the immediate benefits of both strategies discussed so far: leveraging powerful services like Google
Maps, while retaining customer touchpoints, including brand, design, and data sovereignty. The app store-
related outcomes are similar to the second strategy because of the same white-label approach. However,
the peculiarity of this strategy of not using open-source standards such as AAOS and instead developing a
proprietary system result in a high short-term financial expenditure, but also has two critical long-term
consequences. On the one hand, this approach is primarily characterized by the fact that a significant part
of the base system is programmed in-house, thus retaining important software competencies and central
control (e.g., over vehicle data) over the OS. On the other hand, the OEM is responsible for maintaining and
evolving the system, including performance and security updates, over multiple generations of vehicles.
Because of the latter, industry experts, including the Senior Project Manager Vehicle Platform from
OEMCorp3, are skeptical about the long-term viability of a proprietary OS:
ng run. Simply for one reason: it has proven itself! There
are two big options when it comes to touchscreen devices, user interface frameworks, operating
systems, and development environments: iOS and Android. Show me another framework, another
SDK that I can use today, where I can get a good
option anymore to develop it in-(Senior Project Manager Vehicle Platform, OEMCorp3).
Discussion and Conclusion
A Grounded Model of Uncertainty Reallocation in Incumbent Firms
We set out to explore how and why incumbent firms decide on a certain level of tech player involvement in
their digital strategy. We apply affordance-actualization theory as a theoretical lens to develop a grounded
model of uncertainty reallocation in incumbent firms (see Figure 7). In doing so, we combine the insights
gained so far using the five inductively derived aggregate dimensions as building blocks of the model
(1) external digital platform by tech firm, (2) incumbent firm and its goals, (3) uncertainty tradeoffs and
affordance of reallocation, (4) strategic actions by incumbent firm, and (5) short- and long-term outcomes.
Reallocating Uncertainty in Incumbent Firms through Digital Platforms
Forty-Fourth International Conference on Information Systems, Hyderabad 2023
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Figure 7. Grounded Model of Uncertainty Reallocation in Incumbent Firms
By offering a digital platform, tech firms aim to dominate and control specific technology areas in traditional
markets, creating an attractive platform offering for incumbent manufacturers and third-party service
providers while maintaining platform control through boundary resources (Ghazawneh & Henfridsson,
2013). At the same time, incumbent firms are reevaluating their strategic goals in the face of ongoing digital
transformation, forcing them to make critical decisions about investments in technology development and
their intended digital portfolio in the future. The combination of these two aspects, leads to uncertainty
tradeoffs between different dimensions (e.g., technical, resource, and relational uncertainty), but the means
offered by the external platform also provide the affordance to reallocate uncertainty between these
dimensions. Given these different sources of uncertainty, incumbent firms must critically weigh their
u external
digital platforms do not necessarily reduce uncertainty but provide the potential to reallocate it, requiring
incumbents to make a variety of tradeoffs.
On the right side, we illustrate how incumbent firms choose specific strategic actions after perceiving the
affordance of uncertainty reallocation. Their chosen strategy influences their role in the ecosystem and their
future business model. For example, incumbents that opt for holistic integration of the external digital
platform typically adopt rather a contributor role, giving up customer touchpoints and access to user data.
Conversely, the openness of a digital platform may allow incumbents to create platform derivatives and act
as orchestrators. Depending on the strategy, short- and long-term outcomes will result, allowing incumbent
firms to immediately and iteratively evaluate and adjust their actions and, in the long run, also adjust their
strategic goals based on the fit between intended goals and the feedback from actions and outcomes. Finally,
although outside the scope of our empirical study, the entire process is also subject to external factors such
vironment.
Implications, Limitations, and Future Research
Our analytical findings contribute empirical insights into the growing involvement of tech firms in
established industries and provides insights into the decision-making of incumbent firms in this context.
Thus, our findings have theoretical implications. First, through the application of affordance-
actualization theory (Strong et al., 2014), we can theoretically grasp the phenomenon of uncertainty
reallocation in long-standing business ecosystems (e.g., Poeppelbuss et al., 2022; Ramirez Hernandez &
Kreye, 2021). The affordance of uncertainty reallocation arises from the interaction between incumbent
firms and an external digital platform offered by a tech firm. Collaborating with the tech firms enables
incumbent firms to meet their strategic goals, but also exposes them to the risk of being locked into using
(Ghazawneh & Henfridsson, 2013). Furthermore, our research
adds to the current understanding of digital platform affordances (e.g., Beverungen et al., 2021; Hein et al.,
2020; Hein, Setzke, et al., 2019) by introducing the reallocation of uncertainty as a core construct when
incumbent firms respond to external digital platform proposals. We provide empirical evidence that while
incumbent automotive firms share some goals and contextual factors, properties such as resource
availability, customer segments, and organizational structures individually determine the potential of
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Forty-Fourth International Conference on Information Systems, Hyderabad 2023
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external platforms to reallocate uncertainty. This also has implications for recent adaptations of the
uncertainty construct in multi-actor digital innovation settings (e.g., Poeppelbuss et al., 2022). It highlights
the heterogeneity of affordances for uncertainty reallocation when firms face similar external offers, and
underscores the socio-technical nature of uncertainty reallocation processes in a digital innovation context.
Finally, the case of the automotive industry illustrates how the uncertainty surrounding digital
transformation in incumbent firms presents a negative socio-technical antecedent, constraining
organizations from realizing shared and collective affordances for leveraging the smart products properties
in multi-actor settings (Heinz et al., 2022; Herterich et al., 2023).
Our study also has managerial implications. Our findings provide a benchmarking tool for evaluating
strategies relative to the embedded subunits in our case study, illustrating the range of strategic options
that automotive OEMs can pursue using s. For instance, adopting suite
of tools through the holistic strategy secures a time advantage, but may result in giving up control over user
touchpoints and data, potentially leading to a missed opportunity to offer data-driven aftermarket services
independently. The other two approaches, which use Google to a lesser extent, have more flexibility
and monetization potential. However, the isolated strategy risks losing customers who may find the user
experience lacking, and the custom strategy requires sizable financial and human resources. Nevertheless,
it remains uncertain whether establishing an ecosystem around their proprietary (white-labeled) app store
is viable, given digital platform principles such as network effects, scalability, and lock-in effects. We show
that incumbents must compromise on their ambitious goals to remain competitive, and that there is no
universal strategy for involving tech players. Rather, incumbents should carefully assess which technology
and business control points in the ecosystem they need to own, depending on their internal capabilities and
goals. Decision-makers in other industries can benefit from studying the advanced car industry
industrial IoT frameworks to better understand their role in their own ecosystem, and to assess the future
capabilities they will need. This requires careful consideration of which aspects should be developed in-
house, through collaboration with traditional suppliers, or by partnering with dominant tech companies.
Our study has limitations that point to areas for future research. Although we engaged extensively with
industry experts both inside and outside of OEMs, we faced constraints in obtaining interviewees due to the
ongoing strategic exploration of OEMs. To gain a more complete understanding of the organizational
dynamics that affect the sensemaking process described by our theoretical model, our research could be
complemented by in-depth case studies of organizations. Our exploration of this emerging phenomenon
can provide valuable initial observations and insights for such studies, which should include multiple
informants per case and observe the organizations over a longer period of time. Second, limiting our
analysis to may restrict the applicability of our conclusions (Yin, 2014). It is
important to note that our findings are not exhaustive and may not apply to every incumbent firm seeking
to integrate external digital platforms. We see great potential in adapting our theoretical model by
conducting similar studies in different industry contexts (e.g., manufacturing, agriculture, or smart home
platforms) to increase the applicability of our results. Finally, our study focuses on Googles AAOS and GAS
in the Western market, so our findings may not be readily transferable to regions with limited access to
Google services. Future research could examine partnerships with tech players from regions like China,
given the recent shifts in market share in the automotive industry and beyond.
Acknowledgements
This work has been partially supported by the German Federal Ministry of Education and Research through
Karlsruhe Institute of Technology).
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