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Concise & all-inclusive: 24 page summary of articles Digital Transformation Strategy

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A concise summary of all articles of DTS. Through experience and attending the lectures, this summary focusses on the most important aspects and translates difficult concepts into easy-to-understand language so that you can easily remember them. Week 1: Introduction to Digital Transformation Strategy • Adner, R., Puranam, P., & Zhu, F. 2019. What is different about digital strategy? From quanti- tative to qualitative change. Strategy Science, 4(4): 253–261. • Nambisan, S., Wright, M., & Feldman, M. 2019. The digital transformation of innovation and entrepreneurship: Progress, challenges and key themes. Research Policy, 48(8): . • Verhoef, P. C., Broekhuizen, T., Bart, Y., Bhattacharya, A., Qi Dong, J., Fabian, N., & Haenlein, M. 2021. Digital transformation: A multidisciplinary reflection and research agenda. Journal of Business Research, 122: 889–901. Week 2: Strategies for Digital Platforms and Ecosystems • Cennamo, C., & Santalo, J. 2013. Platform competition: Strategic trade-offs in platform markets. Strategic Management Journal, 34(11): 1331–1350. • Shipilov, A., & Gawer, A. 2020. Integrating research on interorganizational networks and eco- systems. Academy of Management Annals, 14(1): 92–121. • Zhu, F., & Iansiti, M. 2012. Entry into platform-based markets. Strategic Management Journal, 33(1): 88–106. Week 3: Digital Governance of Interorganizational Relationships • Hanisch, M., & Goldsby, C. M. 2021. The boon and bane of blockchain: Getting the governance right. California Management Review, forthcoming. • Lumineau, F., Wang, W., & Schilke, O. 2021. Blockchain governance—A new way of organizing collaborations? Organization Science, 32(2): 500–521. Week 4: Big Data and Business Analytics • Chen, Chiang, & Storey. 2012. Business intelligence and analytics: From big data to big impact. MIS Quarterly, 36(4): 1165–1188. • Davenport, T. H. Competing on analytics. Harvard Business Review, 84(1): 98– 107. • McAfee Andrew, & Brynjolfsson Erik. 2012. Big data: The management revolution. Harvard Business Review, 90(10): 60–66. Week 5: Artificial Intelligence and Automation • Agrawal, A., Gans, J., & Goldfarb, A. 2019. Prediction, judgment and complexity: A theory of decision making and artificial intelligence. In A. Agrawal, J. Gans & A. Goldfarb (Eds.), The economics of artificial intelligence: An agenda. Chicago, London: The University of Chicago Press. • Berente, N., Gu, B., & Santhanam, R. 2021. Managing artificial intelligence. MIS Quarterly, 45(3): 1433–1450. • Dixon, J., Hong, B., & Wu, L. 2021. The robot revolution: Managerial and employment conse- quences for firms. Management Science, 67(9): 5586–5605. Week 6: Digital Market Regulation • Martens, B. 2018. The impact of data access regimes on artificial intelligence and machine learning. JRC Digital Economy Working Paper. • Parker, G., Petropoulos, G., & van Alstyne, M. W. 2020. Digital Platforms and Antitrust. SSRN Electronic Journal. • Tirole, J. 2020. Competition and the Industrial Challenge for the Digital Age.

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Week 1 - Article 1: Adner, 2029, What is different about digital strategy? From quantitative
to qualitative change

The article recognizes the increased attention of digital transformation for businesses. It
suggests that’s there is a new wave of digital development for firms which is caused by a
shift from quantitative advancements (like the exponential growth of computing power
(Moore’s law)) to quantitative advancements. The quantitative advancement can be
summarized in: representation, connectivity, aggregation.

Representation: with representation the authors mean that data can be shown in a digital
fashion. It is possible to create huge databases of data which were previously considered
irrelevant/ unimportant. With these databases it is possible to do algorithmic calculations
and extract new type of information. Information not based on the limitations and biases of
the human rationale and descriptive statistics, but on the capability of an algorithm which
can handle vast amount of data to extract predictions based on patterns.

Connectivity: digitization enables connectivity between business parties, thus promoting
network density and network value. The landscape has changed from connectivity-on-
demand to connectivity-by-default. This enables firms to explore new business models which
sometimes cause disruption in a market.

Aggregation: the new ability to combine new types of information the solve complex
problems that were previously impossible to answer based on data.

Combination: together, representation, connectivity and aggregation reinforce each other
dramatically and creates the possibility for new ways to create and deliver value to
customers, radically changing the business landscape. Connectivity and aggregation
decrease transaction costs. Decreased transaction costs increase the number of
transactions; consequently creating more data. In turn, this spurs further investments and
creates a positive feedback loop.
Representation, connectivity, and aggregation cause a positive feedback loop which
enhances the digital transformation radically.

Business sensemaking on an algorithmic world: statistical approaches are being replaced by
machine learning for making data-based decision. This causes opportunities like better
decision-making but also threats like legal and ethical implications.

Conclusion: representation of data, connectivity among firms and aggregation of data
sources will continue to impact businesses and their digital transformation as the interaction
among these three factors will be more pronounced in the future. It will cause firms to
rethink how to create, capture and deliver value to their customers and sometimes disrupt
existing markets. The disruption might cause the creation of new business ecosystems, new
intellectual property, and growth, scale and scope of businesses differently.




1

, Week 1 – Article 2: Nambisan, 2019, The digital transformation of innovation and
entrepreneurship: progress, challenges, and key themes

Article recognizes that there are multiple problems in the business world due to ongoing
digitization. The problems are: ‘data privacy & security in practice’, ‘compartmentation of
research on digital subjects which fails to paint a holistic viewpoint in research’ and the
literature and therefore is not fully understood yet. Lastly, ‘digitization is not only innovation
and entrepreneurship, and can be an operational resource for a firm.’ Authors propose 3 key
overarching themes in digital transformation and try to demonstrate the value of creating a
research scope based on these three themes:

Openness of innovation & entrepreneurship: who can participate in/with the new digital
technology? What can they contribute? How can they contribute? For what results can they
contribute? (actors, inputs, process, output). Openness can be measured on three levels:
individual, organizational, and societal level. While openness due to digitization and the data
it generates allows for new partnerships and value creation, it also creates tension in society.
Firms create products which capture data and then allow consumers to interact on a
platform. From there on it is unclear who owns the data. Is it the firm or is it from the
consumer? This causes tension and should be researched from a societal perspective.
!! 🡪 Paradox of openness: this is the tension between sharing knowledge and protecting
knowledge. Sharing knowledge creates the opportunity to create value while protecting
knowledge is essential for value appropriation.
Affordance of innovation & entrepreneurship: possibilities to create an action offered by
digital technology to its user. (high costs have low action possibility). The concept of
affordance refers to the relationship between a piece of technology and the
individual/organization using it, in relation to their goals.
Generativity of innovation & entrepreneurship: basically, how can digital technology be
used in society to create change. Can it blend/recombine large, varied, unrelated,
unaccredited, and uncoordinated datasets? Generativity refers to the capacity of a
technology to produce violent change driven by a broad and diverse group of users. Digital
technologies are particularly well-suited for generative processes because they are open,
accessible and the ability to be edited and combined in various ways. The ability to combine
technology in a generative way can lead to creative, novel and entrepreneurial endeavors
which might be positive or might be negative for individuals, organizations, and society.

Conclusion: by focusing future research on digital transformation on three themes of
openness, affordances, and generativity, a more holistic view to consider the implications of
digital transformation for innovation and entrepreneurship can be established. three
themes: openness, affordances, and generativity. Openness refers to the nature and degree
of accessibility facilitated by digital technologies in innovation and entrepreneurship.
Affordances refer to the action potential or possibilities offered by a digital tech in relation to
a specific user or use context. Generativity refers to the capacity of technology to produce
unprompted change driven by a diverse group of users. By considering these themes, the
coherence of future research efforts can be enhanced and a more nuanced understanding of
how digital technologies facilitate innovation and entrepreneurship can be developed.




2

, Week 1 – article 3: Verhoef, 2021, Digital transformation: a multidisciplinary reflection and
research agenda.

Articles articulates three phases of digital transformation, identify growth strategies and
necessary capabilities required to successfully transform digitally. High performance requires
a specific organizational structure and specific metrics to calibrate the business. Digital
transformation = a change in how a firm employs digital technologies to develop a new
digital business model that helps to create and appropriate more value for the firm.

Digital transformation is needed because (1) New Technologies: the development of new
technologies based on a digital ecosystem called the world wide web is only growing. (2)
Competition: due to new technologies, the competition is changing dramatically, and
markets are being disrupted. (3) Customer Behavior: is changing as technology has a
profound impact on consumer lives creating a new type of (online) customer journey.

The phases of digital transformation are (1) Digitization: the process of converting analogue
information to digital format so that it can be stored and processed by computers. Often
increases efficiency of current processes but does not affect value creation for firms. (2)
Digitalization: the use of digital technologies to optimize existing business processes through
more efficient coordination or by enhancing customer experiences. It is not solely focused
on cost savings, but also includes process improvements of customer experiences. (3) Digital
Transformation: is a companywide change that leads to the development of new business
models through the implementation of digital technologies. It goes beyond digitization
which is the changing of simple organizational processes and tasks. Digital transformation is
always linked to strategy and the business model (creating, capturing & delivering value). It
therefore has the possibility to create competitive advantages and new core competencies.

Imperatives of Digital Transformation
Digital resources: firms need to develop new digital assets and capabilities to achieve a
digital transformation. E.G. (1) Digital Assets: develop tech/data which leverages existing
firm knowledge and resource to create more value for customers. (2) Digital Agility:
continuous improvement of digital assets and resources. (3) Digital Networking: bring
together and match users to address their mutual needs through a platform. (4) Big Data
Analytics Capability: ability of a firm to acquire and analyze big data for decision-making and
have teams with specific data business skills (analytics, visualization etc). Teams need to be
continuously train analytics teams as techniques become more advanced (4)
Organizational structure: firms with dynamic capabilities, flexible organizational structure/
forms, and separate BU’s are better equipped for digital transformation. It is recommended
to develop new business models in autonomous BU’s which are separate from HQ allowing
for experimentation and quick learning. Avoiding conflicts. To deal with the disruptive nature
of digital technologies, it is recommended to develop new business models in autonomous
business units that are separated from the headquarters, allowing for experimentation,
quick learning, fast responses, and avoiding conflicts. Thereby Quickly testing market
assumptions.
Digital growth Strategies: most prominent growth strategy is the use of digital platforms.
Platforms have high potential due to 2 key drivers: high scalability (economies of scale) and
reinforcing network effects (more sellers attract more buyers). Ansoff matrix shows

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