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MISQ Workshop, Leuven, Belgium, August 2015
Towards A Better Measure of
Business Proximity:
Topic Modeling for Industry In...
MISQ Workshop, Leuven, Belgium, August 2015 2
Business proximity: motivation
MISQ Workshop, Leuven, Belgium, August 2015 2
Business proximity: motivation
• To measure firms’ dyadic relatedness in spac...
MISQ Workshop, Leuven, Belgium, August 2015 2
Business proximity: motivation
• To measure firms’ dyadic relatedness in spac...
MISQ Workshop, Leuven, Belgium, August 2015 2
Business proximity: motivation
• To measure firms’ dyadic relatedness in spac...
MISQ Workshop, Leuven, Belgium, August 2015 3
Our Big Data approach
MISQ Workshop, Leuven, Belgium, August 2015 3
Our Big Data approach
• Our approach: a unified framework that integrates
MISQ Workshop, Leuven, Belgium, August 2015 3
Our Big Data approach
• Our approach: a unified framework that integrates
• M...
MISQ Workshop, Leuven, Belgium, August 2015 3
Our Big Data approach
• Our approach: a unified framework that integrates
• M...
MISQ Workshop, Leuven, Belgium, August 2015 3
Our Big Data approach
• Our approach: a unified framework that integrates
• M...
MISQ Workshop, Leuven, Belgium, August 2015 3
Our Big Data approach
• Our approach: a unified framework that integrates
• M...
MISQ Workshop, Leuven, Belgium, August 2015 3
Our Big Data approach
• Our approach: a unified framework that integrates
• M...
MISQ Workshop, Leuven, Belgium, August 2015 3
Our Big Data approach
• Our approach: a unified framework that integrates
• M...
MISQ Workshop, Leuven, Belgium, August 2015 3
Our Big Data approach
• Our approach: a unified framework that integrates
• M...
MISQ Workshop, Leuven, Belgium, August 2015 3
Our Big Data approach
• Our approach: a unified framework that integrates
• M...
MISQ Workshop, Leuven, Belgium, August 2015 4
Main contributions
MISQ Workshop, Leuven, Belgium, August 2015 4
Main contributions
1. Propose a transformative data-analytic
framework for u...
MISQ Workshop, Leuven, Belgium, August 2015 4
Main contributions
1. Propose a transformative data-analytic
framework for u...
MISQ Workshop, Leuven, Belgium, August 2015 4
Main contributions
1. Propose a transformative data-analytic
framework for u...
MISQ Workshop, Leuven, Belgium, August 2015 5
Roadmap
1. CrunchBase Data
2. Data-Analytics based Business Proximity
3. Emp...
MISQ Workshop, Leuven, Belgium, August 2015 6
Roadmap
1. CrunchBase Data
2. Data-Analytics based Business Proximity
3. Emp...
MISQ Workshop, Leuven, Belgium, August 2015
CrunchBase data
7
• CrunchBase: open database (“Wikipedia”) of high-tech indus...
MISQ Workshop, Leuven, Belgium, August 2015
Data: networked business
8
MISQ Workshop, Leuven, Belgium, August 2015
Data: networked business
8
• M&A: 1689 total
• cross-state: 62.6%
• cross-sect...
MISQ Workshop, Leuven, Belgium, August 2015
Data: networked business
8
• M&A: 1689 total
• cross-state: 62.6%
• cross-sect...
MISQ Workshop, Leuven, Belgium, August 2015
Data: networked business
8
• M&A: 1689 total
• cross-state: 62.6%
• cross-sect...
MISQ Workshop, Leuven, Belgium, August 2015 9
Roadmap
1. CrunchBase Data
2. Data-Analytics based Business Proximity
3. Emp...
MISQ Workshop, Leuven, Belgium, August 2015
Our approach on business proximity
10
MISQ Workshop, Leuven, Belgium, August 2015
Our approach on business proximity
• Objectives: data-driven, scalability, fine...
MISQ Workshop, Leuven, Belgium, August 2015
Our approach on business proximity
• Objectives: data-driven, scalability, fine...
MISQ Workshop, Leuven, Belgium, August 2015
Our approach on business proximity
• Objectives: data-driven, scalability, fine...
MISQ Workshop, Leuven, Belgium, August 2015
Our approach on business proximity
• Objectives: data-driven, scalability, fine...
MISQ Workshop, Leuven, Belgium, August 2015
Our approach on business proximity
• Objectives: data-driven, scalability, fine...
MISQ Workshop, Leuven, Belgium, August 2015
Our approach on business proximity
• Objectives: data-driven, scalability, fine...
MISQ Workshop, Leuven, Belgium, August 2015
Our approach on business proximity
• Objectives: data-driven, scalability, fine...
MISQ Workshop, Leuven, Belgium, August 2015
Business proximity from topic model
• Business proximity pb(i,j) between firms ...
MISQ Workshop, Leuven, Belgium, August 2015
Business topic model
Per-word
business topic
assignment
Observed
business
desc...
MISQ Workshop, Leuven, Belgium, August 2015
LDA topic model with CrunchBase
13
Click here for the complete list of 50 topi...
MISQ Workshop, Leuven, Belgium, August 2015 14
Roadmap
1. CrunchBase Data
2. Data-Analytics based Business Proximity
3. Em...
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
Towards a better measure of business proximity: Topic modeling for industry intelligence
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Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 1 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 2 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 3 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 4 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 5 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 6 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 7 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 8 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 9 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 10 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 11 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 12 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 13 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 14 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 15 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 16 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 17 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 18 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 19 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 20 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 21 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 22 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 23 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 24 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 25 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 26 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 27 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 28 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 29 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 30 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 31 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 32 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 33 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 34 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 35 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 36 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 37 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 38 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 39 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 40 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 41 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 42 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 43 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 44 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 45 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 46 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 47 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 48 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 49 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 50 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 51 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 52 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 53 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 54 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 55 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 56 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 57 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 58 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 59 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 60 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 61 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 62 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 63 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 64 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 65 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 66 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 67 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 68 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 69 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 70 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 71 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 72 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 73 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 74 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 75 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 76 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 77 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 78 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 79 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 80 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 81 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 82 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 83 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 84 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 85 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 86 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 87 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 88 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 89 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 90 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 91 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 92 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 93 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 94 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 95 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 96 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 97 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 98 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 99 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 100 Towards a better measure of business proximity: Topic modeling for industry intelligence Slide 101
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Towards a better measure of business proximity: Topic modeling for industry intelligence

  1. 1. MISQ Workshop, Leuven, Belgium, August 2015 Towards A Better Measure of Business Proximity: Topic Modeling for Industry Intelligence 1 August 13th 2015 Zhan (Michael) Shi Gene Moo Lee* Andrew B. Whinston Arizona State University University of Texas at Arlington University of Texas at Austin * presenter
  2. 2. MISQ Workshop, Leuven, Belgium, August 2015 2 Business proximity: motivation
  3. 3. MISQ Workshop, Leuven, Belgium, August 2015 2 Business proximity: motivation • To measure firms’ dyadic relatedness in spaces of product, market, and technology • Essential in competitive/industry intelligence • Building block in strategy/industrial organization fields
  4. 4. MISQ Workshop, Leuven, Belgium, August 2015 2 Business proximity: motivation • To measure firms’ dyadic relatedness in spaces of product, market, and technology • Essential in competitive/industry intelligence • Building block in strategy/industrial organization fields • Existing methods • Common industry membership (Wang and Zajac 2007) • Patent holdings (Stuart 1998, Mowery et al. 1998) • Geographic distance (Mitsuhashi and Greve 2009)
  5. 5. MISQ Workshop, Leuven, Belgium, August 2015 2 Business proximity: motivation • To measure firms’ dyadic relatedness in spaces of product, market, and technology • Essential in competitive/industry intelligence • Building block in strategy/industrial organization fields • Existing methods • Common industry membership (Wang and Zajac 2007) • Patent holdings (Stuart 1998, Mowery et al. 1998) • Geographic distance (Mitsuhashi and Greve 2009) • These approaches have strong data requirement • Typically scarce for early stage high-tech startups
  6. 6. MISQ Workshop, Leuven, Belgium, August 2015 3 Our Big Data approach
  7. 7. MISQ Workshop, Leuven, Belgium, August 2015 3 Our Big Data approach • Our approach: a unified framework that integrates
  8. 8. MISQ Workshop, Leuven, Belgium, August 2015 3 Our Big Data approach • Our approach: a unified framework that integrates • Machine learning (LDA topic model)
  9. 9. MISQ Workshop, Leuven, Belgium, August 2015 3 Our Big Data approach • Our approach: a unified framework that integrates • Machine learning (LDA topic model) • Statistical network model (ERGM)
  10. 10. MISQ Workshop, Leuven, Belgium, August 2015 3 Our Big Data approach • Our approach: a unified framework that integrates • Machine learning (LDA topic model) • Statistical network model (ERGM) • Big Data technologies (Cloud, NoSQL, Condor)
  11. 11. MISQ Workshop, Leuven, Belgium, August 2015 3 Our Big Data approach • Our approach: a unified framework that integrates • Machine learning (LDA topic model) • Statistical network model (ERGM) • Big Data technologies (Cloud, NoSQL, Condor) • Outperforming existing approaches
  12. 12. MISQ Workshop, Leuven, Belgium, August 2015 3 Our Big Data approach • Our approach: a unified framework that integrates • Machine learning (LDA topic model) • Statistical network model (ERGM) • Big Data technologies (Cloud, NoSQL, Condor) • Outperforming existing approaches • Automatic processing (vs. manual inspection)
  13. 13. MISQ Workshop, Leuven, Belgium, August 2015 3 Our Big Data approach • Our approach: a unified framework that integrates • Machine learning (LDA topic model) • Statistical network model (ERGM) • Big Data technologies (Cloud, NoSQL, Condor) • Outperforming existing approaches • Automatic processing (vs. manual inspection) • Dynamic industry definition (vs. static)
  14. 14. MISQ Workshop, Leuven, Belgium, August 2015 3 Our Big Data approach • Our approach: a unified framework that integrates • Machine learning (LDA topic model) • Statistical network model (ERGM) • Big Data technologies (Cloud, NoSQL, Condor) • Outperforming existing approaches • Automatic processing (vs. manual inspection) • Dynamic industry definition (vs. static) • Finer granularity (vs. discrete)
  15. 15. MISQ Workshop, Leuven, Belgium, August 2015 3 Our Big Data approach • Our approach: a unified framework that integrates • Machine learning (LDA topic model) • Statistical network model (ERGM) • Big Data technologies (Cloud, NoSQL, Condor) • Outperforming existing approaches • Automatic processing (vs. manual inspection) • Dynamic industry definition (vs. static) • Finer granularity (vs. discrete) • Relaxed data requirement (vs. patent, location)
  16. 16. MISQ Workshop, Leuven, Belgium, August 2015 4 Main contributions
  17. 17. MISQ Workshop, Leuven, Belgium, August 2015 4 Main contributions 1. Propose a transformative data-analytic framework for understanding dynamic startup landscape
  18. 18. MISQ Workshop, Leuven, Belgium, August 2015 4 Main contributions 1. Propose a transformative data-analytic framework for understanding dynamic startup landscape 2. Construct an explicit network structure for understanding firm interactions
  19. 19. MISQ Workshop, Leuven, Belgium, August 2015 4 Main contributions 1. Propose a transformative data-analytic framework for understanding dynamic startup landscape 2. Construct an explicit network structure for understanding firm interactions 3. Implement a BI for competitive intelligence in U.S. high-tech industry
  20. 20. MISQ Workshop, Leuven, Belgium, August 2015 5 Roadmap 1. CrunchBase Data 2. Data-Analytics based Business Proximity 3. Empirical Validation 4. Empirical Application on M&A Analysis 5. Industry Intelligence System 6. Conclusion and implication
  21. 21. MISQ Workshop, Leuven, Belgium, August 2015 6 Roadmap 1. CrunchBase Data 2. Data-Analytics based Business Proximity 3. Empirical Validation 4. Empirical Application on M&A Analysis 5. Industry Intelligence System 6. Conclusion and implication
  22. 22. MISQ Workshop, Leuven, Belgium, August 2015 CrunchBase data 7 • CrunchBase: open database (“Wikipedia”) of high-tech industry • Data collection time: April 2013 ~ April 2015 • 24,382 U.S. high-tech companies (1.4% public, 5.7 years old) • HQ location, CB-defined industry sector, key personnels, M&A, investments, business summary • States: CA, NY, MA, TX (stats page) • Industries: software, web, e-commerce, ad, mobile
  23. 23. MISQ Workshop, Leuven, Belgium, August 2015 Data: networked business 8
  24. 24. MISQ Workshop, Leuven, Belgium, August 2015 Data: networked business 8 • M&A: 1689 total • cross-state: 62.6% • cross-sector: 63.6% • top 10 buyers: 14.3% (skewed)
  25. 25. MISQ Workshop, Leuven, Belgium, August 2015 Data: networked business 8 • M&A: 1689 total • cross-state: 62.6% • cross-sector: 63.6% • top 10 buyers: 14.3% (skewed) • Investments: 531 total
  26. 26. MISQ Workshop, Leuven, Belgium, August 2015 Data: networked business 8 • M&A: 1689 total • cross-state: 62.6% • cross-sector: 63.6% • top 10 buyers: 14.3% (skewed) • Investments: 531 total • Job mobility: 19K total
  27. 27. MISQ Workshop, Leuven, Belgium, August 2015 9 Roadmap 1. CrunchBase Data 2. Data-Analytics based Business Proximity 3. Empirical Validation 4. Empirical Application on M&A Analysis 5. Industry Intelligence System 6. Conclusion and implication
  28. 28. MISQ Workshop, Leuven, Belgium, August 2015 Our approach on business proximity 10
  29. 29. MISQ Workshop, Leuven, Belgium, August 2015 Our approach on business proximity • Objectives: data-driven, scalability, finer granularity, little data requirements 10
  30. 30. MISQ Workshop, Leuven, Belgium, August 2015 Our approach on business proximity • Objectives: data-driven, scalability, finer granularity, little data requirements • Approach: topic modeling [Blei et al. 2003] 10
  31. 31. MISQ Workshop, Leuven, Belgium, August 2015 Our approach on business proximity • Objectives: data-driven, scalability, finer granularity, little data requirements • Approach: topic modeling [Blei et al. 2003] • unsupervised learning to discover latent “topics” from a large collection of documents 10
  32. 32. MISQ Workshop, Leuven, Belgium, August 2015 Our approach on business proximity • Objectives: data-driven, scalability, finer granularity, little data requirements • Approach: topic modeling [Blei et al. 2003] • unsupervised learning to discover latent “topics” from a large collection of documents 10 24K company descriptions
  33. 33. MISQ Workshop, Leuven, Belgium, August 2015 Our approach on business proximity • Objectives: data-driven, scalability, finer granularity, little data requirements • Approach: topic modeling [Blei et al. 2003] • unsupervised learning to discover latent “topics” from a large collection of documents 10 LDA 24K company descriptions
  34. 34. MISQ Workshop, Leuven, Belgium, August 2015 Our approach on business proximity • Objectives: data-driven, scalability, finer granularity, little data requirements • Approach: topic modeling [Blei et al. 2003] • unsupervised learning to discover latent “topics” from a large collection of documents 10 LDA Industry-wide topics 24K company descriptions
  35. 35. MISQ Workshop, Leuven, Belgium, August 2015 Our approach on business proximity • Objectives: data-driven, scalability, finer granularity, little data requirements • Approach: topic modeling [Blei et al. 2003] • unsupervised learning to discover latent “topics” from a large collection of documents 10 LDA Industry-wide topics Company’s topics 24K company descriptions
  36. 36. MISQ Workshop, Leuven, Belgium, August 2015 Business proximity from topic model • Business proximity pb(i,j) between firms i and j • Cosine similarity of topic vectors Ti and Tj • Range: 0 (no commonality) ~ 1 (same business components) 11
  37. 37. MISQ Workshop, Leuven, Belgium, August 2015 Business topic model Per-word business topic assignment Observed business descriptions Business topics Per-firm business topics distrib. Topic parameter Proportions parameter K: # topics D: # companies N: # words
  38. 38. MISQ Workshop, Leuven, Belgium, August 2015 LDA topic model with CrunchBase 13 Click here for the complete list of 50 topics Video/music Energy Sports Healthcare
  39. 39. MISQ Workshop, Leuven, Belgium, August 2015 14 Roadmap 1. CrunchBase Data 2. Data-Analytics based Business Proximity 3. Empirical Validation 4. Empirical Application on M&A Analysis 5. Industry Intelligence System 6. Conclusion and implication

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