Beyond the Beginning
Unveiling the Evolutionary Paths of Startups Using Dynamic Classification
Thursday, 13. June 2024
Creative Destruction: Out with the Old, in with the New
Schumpeter characterized creative destruction as innovations in the manufacturing process that increase productivity, describing it as the …
… «process of industrial mutation that incessantly revolutionizes the economic structure from within, incessantly destroying the old one, incessantly creating a new one.»
— Joseph Schumpeter (1942)
Digital Disrupt: How Netflix’s Success demonstrates the Effectiveness of Business Model Innovation
Securing the Future: Navigating the Evolutionary Path of Business Models for sustainable Growth
Blockbuster’s Digital Demise: How Failing to Adapt Led to Bankruptcy (Dynamics of competitive structures)
Constructive destruction: What has to be changed?
[…] it is not that kind of competition [price, ed] which counts but the competition from the new commodity, the new technology, the new source of supply, the new type of organization – competition which commands a decisive cost or quality advantage and which strikes not at the margins of the profits and the outputs of the existing firms but at their foundations and their very lives.»
— Joseph Schumpeter (1942)
Business Model Canvas
Value Proposition Canvas
Research Objective: An evolutionary approach to Business Model Innovation & Value Proposition Development
Market structure map: Spatial representation of firms’ competitive positions relative to one another based on some measure of their competitive relationships (DeSarbo et al. 1993).
- Such maps typically capture static snapshots in time. Yet, competitive positions tend to change.
Firms’ trajectories: Evolutionary paths of firms’ positions over time relative to all other firms in a market based on their value proposition
Defining a Startup’s unique Value Proposition: How to identify Core Value?
Approach
- Static: Venture Capital Databases (Crunchbase, Pitchbook, … )
- Dynamic: Natural language processing and historical websites (WayBack Machine)
How they faced a Digital Transformation: Changes in Netflix’s business model over time
Handling Noisy Data Part 1:
Extracting Key Noun Phrases for Essential Insight
Unlike simplistic keywords, nounphrases transcend single words, comprising compound expressions that encapsulate the essence of the text more comprehensively
Tools: SpaCy (nounchunk library) & Custom Algorithmus
Handling Noisy Data Part 2:
Leveraging Embeddings for Similarity Calculations
Handling Noisy Data Part 3:
Clustering with Candidate Keyphrases
- Cluster Crunchbase & Pitchbook Description Embeddings, which are describing value propositions
- Use corresponding medoids/centroids (k=300) as ultimate truth anchors
- Find appropriate similarity threshold as cutoff for website embeddings
Handling Noisy Data Part 4:
Consolidating Unique Embeddings for Value Propositions
Mapping Moments: Unveiling competitive positions through Time-Indexed Pairwise Similarity Measures
Proof of Concept: Exploring Competitive Landscapes with the EvoMap Algorithm
Exploring the Role of Pivotal Shifts: Driving Force or Outcome Variable?
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B1: The Evolutionary Path
B2: Websites: Perceived value proposition
- Value propositions are derived from the descriptions that firms provide to the market through their websites
- This contrasts with existing industry classification schemes, which often rely on external assessments
- By this, we capture a more dynamic and internally generated perspective of their industry affiliations, potentially offering a richer understanding of their positioning and evolution over time
Start-up Roadmap: The Myth of the Linear Path
1st Goal: Keyphrase Extraction
