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How and When do New Technologies Become Economically Feasible

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These slides contrast two processes by which new technologies become economically feasible. Some technologies become economically feasible as advances in science facilitate the creation of new concepts and improvements in the resulting technologies. Other technologies become economically feasible as improvements in electronic components (e.g., Moore's Law), smart phones, and the Internet experience improvements.

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How and When do New Technologies Become Economically Feasible

  1. 1. A/Prof Jeffrey Funk Division of Engineering and Technology Management National University of Singapore For information on other technologies: see http://www.slideshare.net/Funk98/presentations or Exponential Change: What drives it? What does it tell us about the future? http://www.amazon.com/Exponential-Change- drives-about-future-ebook/dp/B00HPSAYEM/ref=sr_1_1?s=digital-text&ie=UTF8&qid=1399871060&sr=1-1&keywords=exponential+change
  2. 2.  Some new technologies destroy both an existing economic system and create a new one (Schumpeter, 1942)  These technologies  provide significantly higher economic value than do old ones  enable dramatic improvements in economic productivity and thus living standards (e.g., Solow (1957)  create winners and losers at individual, firm, and country level  have a large impact on our ecological and social environment  Over last 20 years, Apple, Google, Amazon, and Microsoft have enabled creative destruction  What is the long-term evolutionary process by which opportunities become economically feasible? Many Terms: Technological Discontinuities, Radical or Disruptive Innovations, Creative Destruction
  3. 3. Diffusion (and Obsolescence) are the Last Stages of Creative Destruction: What Happens before Diffusion Occurs? What is Happening Here?
  4. 4. http://www.theatlantic.com/technology/archive/2012/04/the-100-year-march-of-technology-in-1-graph/255573/ Real World Examples of Diffusion
  5. 5. What Happens Before Diffusion Starts?  How do new technologies become economically feasible?  What is the long term evolutionary process by which they become economically feasible?  And thus diffuse and cause creative destruction?  We can distinguish between economic feasibility and the organizational and regulatory challenges of implementing new technologies  Technologies (or Systems Composed of Them) that Experience Rapid Improvements are more Likely to Become Economically Feasible than are Slowly Improving Technologies
  6. 6. Rate of Improvement ExtentofImprovementNeeded Small Large Slow (e.g., <5% Fast >10% Technologies that Experience Rapid Improvements are more Likely to Become Economically Feasible Now or Probably Very Soon Probably Never Within 5 to 15 Years? Within 5-15 Years?
  7. 7. Session Technology 1 Objectives and overview of course 2 How do improvements in cost and performance occur? 1) Creating materials that better exploit physical phenomena; 2) Geometrical scaling 3 What is process by which new technologies become economically feasible? 4 Future of ICs and Electronic Systems 5 Sensors, MEMs, and the Internet of Things 6 Bio-Electronics, DNA Sequencers, and Health Care 7 Lighting, Lasers, Displays 8 Human-Computer Interfaces, Wearable Computing 9 IT and Transportation 10 Nanotechnology and Superconductivity 11 Feedback on Group Slides 12-13 Group Presentations This is Third Session of MT5009
  8. 8. Outline  Supply and demand curves and economic feasibility  Two models of technology change  Model of Invention  Silicon Valley Model (Improvements in components lead to emergence of new systems)  Billion Dollar Startup Club  Problems with over-emphasizing model of invention: Predictions made by MIT’s Technology Review  Myths of technology change  S-Curves for performance  Slowdowns in old technologies lead to improvements in new technologies  Learning and Experience Curves  A-U Model
  9. 9. Quantity (Q) Price (P) q p What do Demand and Supply Curves Mean and what do they have to do with Diffusion? Demand Supply
  10. 10. What are some problems with last Slide?
  11. 11. What are some problems with last slide?  Previous slide assumes performance is unimportant  In reality, performance is important  Market evaluates products and services in terms of price and a variety of performance dimensions  Difficult to represent multiple dimensions on a two- dimension graph, so most graphs only show price and quantity  Many use the term value proposition to capture price and all dimensions of performance
  12. 12. Simple Definition of Value Proposition Value to the target market Benefits to the target market Price to the target market = Relative to A simple and clear statement of what the new technology provides and that the existing technology does not: better performance, features, or price Such a statement involves performance (including features) and cost
  13. 13. Superior Value Propositions  Might involve lower price  Higher performance  Speed, ease of Use  Durability, portability  Maintainability  Reliability, Aesthetics  Specific Features  Your projects should consider many aspects of value  But for this session, let’s simplify the discussion and just focus on performance and price
  14. 14. Quantity (Q) Performance (P) q p In terms of performance, What do Demand and Supply Curves Mean and what do they have to do with Diffusion? Supply Demand
  15. 15. Price, Performance, and Demand  Price and performance determine the amount of demand and supply  Rising performance often leads to growing demand  Falling price often leads to growing demand  What changes over time and how do these curves look before there is a market (i.e., no commercial production)?  When performance is too low?  Or when price is too high?  How can we represent these dynamics with supply and demand curves?
  16. 16. Quantity (Q) Price (P) q p Diffusion often starts in segments/users that are willing to pay more for products and services than are other segments/users Demand Curve Supply Curve Typical movement of supply curve over time Typical movement of demand curve over time
  17. 17. Quantity (Q) Price (P) q p Maximum Threshold of Price: the maximum price that the market will pay for a new technology Demand Curve Supply Curve Typical movement of supply curve over time
  18. 18. Quantity (Q) Performance (P) q p Sometimes, diffusion starts in segments/users that have lower performance expectations than other segments/users Supply Curve Demand Curve Typical movement of supply curve over time?
  19. 19. Quantity (Q) Performance (P) Minimum Threshold of Performance: the minimum performance the market will accept for a new technology Supply Curve Demand Curve Typical movement of supply curve over time
  20. 20. Whether we Focus on Performance or Price  Demand and supply curves help us think about important issues  Impact of falling price or increasing performance on demand  Levels of performance and price that are needed before a technology becomes economically feasible  Other factors impact on diffusion such as standards, regulations, and organizational issues  Demand and supply curves can also help us to think about the first  Products to diffuse  First value propositions  First designs  Markets to accept this diffusion  First customer segments  First customers within segments  First sales channels
  21. 21. But What Drives Changes in Supply Curves?  The second session focused on  Creating materials that better exploit physical phenomena  Geometrical scaling  Some technologies directly experience improvements through these two mechanisms while others indirectly experience them through improvements in specific “components”  Let’s place these improvements in a larger context  What is the long term evolutionary process by which new technologies become economically feasible?
  22. 22. Outline  Supply and demand curves and economic feasibility  Two evolutionary models of technology change  Model of Invention  Silicon Valley Model (Improvements in components lead to emergence of new systems)  Billion Dollar Startup Club  Problems with over-emphasizing model of invention: Predictions made by MIT’s Technology Review  Myths of technology change  S-Curves for performance  Slowdowns in old technologies lead to improvements in new technologies  Learning and Experience Curves  A-U Model
  23. 23. What was the process by which these opportunities emerged?  Did they emerge through process of  Invention  Commercialization  Diffusion?  This is most widely described process in economics, emphasized by Joseph Schumpeter, Nathan Rosenberg, Giovanni Dosi, Brian Arthur, and others  Science (new explanations of natural or artificial phenomena) plays critical role in this process  Facilitates creation, demonstration, commercialization, and improvement of a concept and product design  Did advances in science play critical role in emergence of opportunities exploited by billion dollar startup club?
  24. 24. What was the process by which these opportunities emerged? (2)  Or did they emerge through a different process?  Improvements in components, particularly those that are defined as General Purpose Technologies (Paul David, Timothy Bresnahan, Manuel Trajtenberg, Elhanan Helpman), enable new products, systems, and services  For example, improvements in integrated circuits enabled new forms of computers, mobile phones, and other electronic products  More broadly speaking, improvements in ICs, lasers, glass fiber, and computers enabled improvements in Internet, which enabled new forms of content, services, and access devices (e.g., mobile phones) to emerge* See for example, http://www.slideshare.net/Funk98/when-do-new-technologies- become-economically-feasible-the-case-of-electronic-products
  25. 25. All of these Models Involve Technological Discontinuities (significant changes in design)  This term is widely used in courses on technology management  Disruptive and radical innovations are discontinuities  One reason discontinuities are discussed is because  Incumbents often fail to effectively commercialize them and thus lose substantial market share in the new technology  Thus discontinuities represent large opportunities for new entrants  It is also important to understand the concept that forms the basis for the technology  One reason is because this helps us understand the potential for improvements
  26. 26. Consider Two Types of Technological Discontinuities Within Four Types of Innovations Reinforced Overturned Core Concepts Unchanged Changed LinkagesBetweenCore ConceptsandComponents Incremental Innovation Modular Innovation Architectural Innovation Radical Innovation Source: Henderson and Clark (1990)
  27. 27. Henderson and Clark’s Innovation Framework Applied to Ceiling Fans Reinforced Overturned Core Concepts Unchanged Changed LinkagesBetweenCore ConceptsandComponents Improvements in Blade or Motor Design Completely new form of motor Portable Fans Air Conditioners
  28. 28. Steam-powered fire engine Technological Discontinuities: What was change in concepts? Old Technology New Technology, i.e., Discontinuity Early Benz (1894) Wright Brothers (1904) Gliders (19th Century)
  29. 29.  Which model can best help us to find new opportunities?  Each model has its advantages and disadvantages  Let’s look at each model  Then we will use the billion dollar startup club to understand the relative importance of these models  Recent startups (still private) with valuations of greater than $1Billion  http://graphics.wsj.com/billion-dollar-club/  Which models help us understand how the opportunities emerged?  Multiple models may be applicable to a specific opportunity Returning to Four Models of Technology Change
  30. 30. Outline  Supply and demand curves and economic feasibility  Four models of technology change  Model of Invention  Silicon Valley Model (Improvements in components lead to emergence of new systems)  Disruptive model of technology change  Billion Dollar Startup Club  Problems with over-emphasizing model of invention : Predictions made by MIT’s Technology Review  Myths of technology change
  31. 31. http://judithcurry.com/2013/05/15/pasteurs-quadrant/ Model of Invention Includes basic science New Products and Services Social Benefits Includes Invention
  32. 32. Different People, Different Terms  Research (Basic, Applied) and Development  Science, Technology, Commercialization  Invention (proof of concept), Innovation (commercialization of discontinuity/concept), Diffusion of discontinuity/concept  Technological Discontinuity: based on new concept that comes from advances in science (sometimes called radical or disruptive innovation)  Scientific, technical, and economic feasibility  In any case, technologies proceed through stages of scientific, technical and economic feasibility  advances in science often continue throughout these stages and contributes towards improvements
  33. 33.  Advances in science play a key role  First step in process by which new technology becomes  Scientifically feasible  Technically feasible  Economically feasible  Science  provides basis for technology (including invention) and how it works (concept or paradigm) (Dosi, 1982)  facilitates refinement and improvement of concepts and prototypes (Arthur, 2007, 2009)  resulting in cost and performance trajectories (Dosi, 1982; Funk and Magee, 2015) Model of Invention
  34. 34.  Engineers and Scientists focus on this model  Mostly consider technologies that involve advances in science  Ignore other technologies that might be considered trivial in terms of advances in science (e.g., smart phone, tablet computer)  Example presented later on MIT’s Technology Review  Many scientists focus on scientific feasibility when they discuss future  Michio Kaku: The Future of the Mind, Physics of the Future, Physics of the Impossible  Peter Diamandis: Abundance Model of Invention
  35. 35.  Examples of technologies for which model of invention provides important insights  Bio-technology  Organic light emitting diodes (OLEDs)  Organic transistors and solar cells  Quantum dot solar cells and displays  New forms of non-volatile memory, carbon nano-tubes  Superconductors, quantum computers, graphene,  Holograms, nano-fiber and particles (see following slides)  Patent literature heavily emphasizes linear model  Science measured with papers  Innovation measured with patents Model of Invention
  36. 36. 0.1 1 10 100 1000 1985 1990 1995 2000 2005 Green Yellow Blue White Lumens/Watt Why might costs fall as luminosity per Watt rises? start of commercial production Luminosity Per Watt for Organic Light Emitting Diodes
  37. 37. 0.000001 0.0001 0.01 1 100 1980 1985 1990 1995 2000 2005 2010 Mobility of Single Crystal and Polycrystalline Organic transistors Single crystal Poly crystalline Mobility(cm2xsec) Start of Commercial Production Why might costs fall as mobility rises?
  38. 38. 1998 2002 2006 2010 2014 Organic Quantum Dots Efficiency of Organic and Quantum Dot Solar Cells 25% 5% 0% Efficiency Why might costs fall as efficiency rises? Perovskite solar cells now have about 20% efficiency but without any commercial production
  39. 39. 1990 1995 2000 2005 2010 2015 Red Blue Orange Yellow Green Efficiency of Quantum Dot Displays for Different Colors 10% 1% .1% .01% Efficiency Start of Commercial Production Why might costs fall as efficiency rises?
  40. 40. 0.001 0.1 10 2001 2003 2005 2007 2009 2011 2013 Phase Change RAM Ferro Electric RAM Magnetic RAM Resistive RAM Number of Memory Bits (Gb) per RAM (Random Access Memory) Chip StorageCapacityperChip(Gb) Why do costs fall as storage capacity rises?
  41. 41. 0.01 0.1 1 10 100 0.01 0.1 1 10 100 1995 2000 2005 2010 2015 Density with Inconsistent Feature Size Density with Consistent Feature Size Density(CarbonNanotubes(permicrometer) Purity(%Contaminant) Purity (left axis) and Density (right axis) of Carbon Nano Tubes for Transistors. Density is for Consistent and Inconsistent Feature Size Purity Start of Production
  42. 42. 100 1000 10000 100000 2003 2005 2007 2009 2011 $/kilomps-meter Start of Commercial production Cost per kiloamps-meter for Superconducting Cable
  43. 43. 1 10 100 1000 1985 1990 1995 2000 2005 2010 2015 YBaCuO BiSr CuO Current (Amps) x Length (km) for Two Types of Superconducting Cables AmpsxLength Start of commercial production Why might costs fall as current x length increases
  44. 44. 0.001 0.01 0.1 1 1 10 100 1000 1990 1995 2000 2005 2010 2015 Bit Energy (left axis) and Clock Period (right axis) for Super- conducting Josephson Junctions BitEnergy(FemtoJoules) ClockPeriod(PicoSeconds) Clock Period Bit Energy Start of commercial production Why do costs fall as speeds increase and energy consumption falls?
  45. 45. 0.001 0.1 10 1000 100000 1998 2002 2006 2010 2014 Relaxation Time Coherence Time Cavity Lifetime QuBit Lifetime for Several Definitions of "Lifetime" Lifetime(nanoseconds) Start of Commercial Production
  46. 46. 1 10 100 1000 10000 2004 2006 2008 2010 2012 2014 The Number of Bits per QuBit Lifetime NumberofBits Start of Commercial Production
  47. 47. 1 10 100 1000 2000 2004 2008 2012 NumberofBits Number of Qubits in Quantum Computers (mostly prototypes) Start of Commercial Production
  48. 48. Who Improved These Technologies?  Many of the improvements were implemented by university researchers  Primarily motivated by publications and perhaps also patents and forming firms  Others were implemented by startups and corporate labs of large firms (e.g., IBM, Samsung)  Motivated partly by publications and mostly by firm’s desire to commercialize new technologies
  49. 49. How were these Technologies Improved? (1)  Creating new materials  Ones with higher luminosity per Watt (both OLEDs and Quantum dots)  Ones that convert more sunlight to electricity (Organic, Quantum Dot, and Perovskite Solar Cells)  Ones with higher mobility (organic transistors)  Ones with higher critical temperatures, magnetic fields, and current densities (superconductors)  New materials also require new processes, so each of these new materials required new processes
  50. 50. How were these Technologies Improved? (2)  New processes (really a subset of creating new materials)  Higher purity and density of carbon nano-tubes  Longer Qubit lifetimes and number of Qubits per lifetime  When the material is fixed, the improvements primarily come from changes in processes  Reducing the feature size of memory cells or Josephson Junctions  Non-volatile memory  Superconducting Josephson Junctions  This also requires changes in both product and process design. Smaller feature sizes involve new product designs and they require new processes in order to achieve the smaller feature sizes
  51. 51. Outline  Supply and demand curves and economic feasibility  Two models of technology change  Model of Invention  Silicon Valley Model (Improvements in components lead to emergence of new systems)  Billion Dollar Startup Club  Problems with over-emphasizing model of invention: Predictions made by MIT’s Technology Review  Myths of technology change  S-Curves for performance  Slowdowns in old technologies lead to improvements in new technologies  Learning and Experience Curves  A-U Model
  52. 52.  Some components such as integrated circuits experience very rapid improvements (Funk, 2013; Funk and Magee, 2015)  These improvements enable new forms of systems, such as computers, mobile phones, other electronic products to emerge  (Bresnahan and Trajtenberg, 1995; Funk, 2013)  Rapidly improving components with many applications are often called general purpose technologies by economists  (David, 1989; Bresnahan and Trajtenberg, 1995; Helpman, 2003; Lipsey et al, 2005)  Internet is considered general purpose technology by most economists  For new systems  costs and/or performance depend primarily on components  This was discussed in session 2 Improvements in Components Enable New Systems to Emerge
  53. 53. Laptops MP3 Players Calculators Video Set-top boxes E-Book Readers Digital Games Web Browsers Digital TV Watches Mobile Digital Cameras Smart Phones Example: Better Integrated Circuits Make New Forms of Electronic Products Economically Feasible MT5009 focuses on the future
  54. 54. Internet has Experienced Rapid Improvements  In speed, bandwidth and cost  These improvements have enabled new forms of  Content: from text to pictures, videos, flash content  Software: from assembly code to higher level languages  Cloud computing and Big Data  Advertising, pricing, recommendation techniques  Similar things have occurred with mobile networks and phones
  55. 55. Outline  Supply and demand curves and economic feasibility  Two models of technology change  Model of Invention  Silicon Valley Model (Improvements in components lead to emergence of new systems)  Billion Dollar Startup Club  Problems with over-emphasizing model of invention: Predictions made by MIT’s Technology Review  Myths of technology change  S-Curves for performance  Slowdowns in old technologies lead to improvements in new technologies  Learning and Experience Curves  A-U Model
  56. 56.  Global Startups (sometimes called Unicorns)  valuations over $1 Billion  still private (no IPO yet)  have raised money in past four years  at least one venture capital firm as investor  122 firms as of 25 September 2015  With 21 other startups that recently exited (IPOs, acquisitions or decreasing value), total of 143 firms  High valuations mean investors believe these firms offer something valuable, unique, hard to copy  Some of them will  lead to “creative destruction”  have $100 Billion plus market capitalizations in the future, like the strongest hi-tech startups: Apple, Google, Amazon, and Microsoft Wall Street Journal’s Billion Dollar Startup Club
  57. 57. Company Latest Valuation Total Equity Funding Last Valuation Uber $51.0 billion $7.4 billion August 2015 Xiaomi $46.0 billion $1.4 billion December 2014 Airbnb $25.5 billion $2.3 billion June 2015 Palantir $20.0 billion $1.6 billion October 2015 Snapchat $16.0 billion $1.2 billion May 2015 Didi Kuaidi $16.0 billion $4.0 billion September 2015 Flipkart $15.0 billion $3.0 billion April 2015 SpaceX $12.0 billion $1.1 billion January 2015 Pinterest $11.0 billion $1.3 billion February 2015 Dropbox $10.0 billion $607 million January 2014 WeWork $10.0 billion $969 million June 2015 Lufax $9.6 billion $488 million March 2015 Theranos $9.0 billion $400 million June 2014 Spotify $8.5 billion $1.0 billion April 2015 DJI $8.0 billion $105 million May 2015 Zhong An Online $8.0 billion $934 million June 2015 Meituan $7.0 billion $1.1 billion January 2015 Square $6.0 billion $495 million August 2014 Stripe $5.0 billion $290 million July 2015 ANI Technologies (Ola Cabs) $5.0 billion $903 million September 2015 Snapdeal $5.0 billion $911 million August 2015 Stemcentrx $5.0 billion $250 million September 2015 Zenefits $4.5 billion $596 million May 2015 Cloudera $4.1 billion $670 million March 2014 Dianping $4.0 billion $1.4 billion March 2015 The Top 25 Firms as of 25 September, 2015
  58. 58. Category U.S. Europe China India Other Total Software 38 1 2 41 E-Commerce 12 3 9 2 2 28 Consumer Internet 18 6 7 2 4 37 Financial 7 4 3 1 15 Hardware 7 2 1 10 BioTech, Bio- Electronics 7 1 8 Energy 2 2 Space 1 1 Retail 1 1 Total 92 14 22 6 9 143 Number of Startups, by Category and Country Most are Internet Related (122) Note: some of the startups were redefined and the smaller categories were combined, based on the descriptions by the Wall Street Journal and other sources
  59. 59. 0 5 10 15 20 25 30 before 2001 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Number of Startups Founded by Year and Category software consumer internet e-commerce financial hardware healthcare
  60. 60. What was the process by which these opportunities emerged?  Did they emerge through process of  Invention; Commercialization; Diffusion?  Science (new explanations of natural or artificial phenomena) facilities improvements in technology and often the creation of new concept  Or did they emerge through a different process?  Improvements in components enable new products, systems, and services  For example, improvements in integrated circuits enabled new forms of computers, mobile phones, and other electronic products
  61. 61. Methodology  Which of these processes enabled the opportunities to emerge that were exploited by the billion dollar startup club?  Invention and advances in science  Examine the U.S. patents held by members of startup club and scientific papers cited by the patents  Scientific papers are defined as papers published in journals that are in science citation index  Contrast papers in physical and life science journals with those in engineering (e.g., IEEE) and computer science (e.g., Association of Computing Machinery) journals  Compare importance of scientific papers across categories
  62. 62. Methodology (2)  Which of these processes enabled the opportunities to emerge that were exploited by the billion dollar startup club?  Improvements in components  By reading descriptions provided by the Wall Street Journal and other sources, what number of startups can be defined as Internet related startups or in general those that benefit from improvements in ICs?  Define sub-categories for each category of Internet-related startups  Explain how improvements in components, particularly those that can be defined as general purpose technologies, enabled these opportunities to emerge?
  63. 63. Category Total Number Percentage of Startups with Patents ≥ 1 patent ≥ 10 patents ≥ 50 patents Software 41 63% 29% 7.3% E-Commerce 28 3.4% 3.4% 0% Consumer Internet 37 23% 17% 0% Financial 15 6.6% 6.6% 6.6% Hardware 10 90% 70% 20% BioTech, Bio- Electronics 8 88% 50% 0% Energy 2 100% 100% 50% Space 1 100% 0% 0% Retail 1 0% 0% 0% Total 143 39% 23% 4.9% Percentage of Startups All, by Numbers of Patents
  64. 64. Category Total Number Percentage of Startups with Patents ≥ 1 patent ≥ 10 patents ≥ 50 patents Software 38 66% 32% 7.9% E-Commerce 12 8.3% 8.3% 0% Consumer Internet 18 39% 28% 0% Financial 7 14% 14% 14% Hardware 7 86% 72% 28% BioTech, Bio- Electronics 7 86% 56% 0% Energy 2 100% 100% 50% Space 1 100% 0% 0% Total 92 54% 34% 7.6% Percentage of U.S. Startups, by Numbers of Patents
  65. 65. Category Total Number of startups Percentage of Startups with Patents Citing Scientific Papers (SPs) Citing ≥ 1 SP Citing ≥ 10 different SPs Citing ≥ 50 different SPs Software 41 27% 2.5% 0% E-Commerce 28 0% 0% 0% Consumer Internet 37 2.7% 0% 0% Financial 15 0% 0% 0% Hardware 10 50% 0% 0% BioTech, Bio- Electronics 8 88% 75% 75% Energy 2 50% 50% 0% Space 1 0% 0% 0% Retail 1 0% 0% 0% Total 143 18% 5.6% 4.2% Percentages of All Startups, by Numbers of Scientific Papers Cited in Patents
  66. 66. Category Total Number Percentage of Startups with Patents Citing Scientific Papers (SPs) Citing ≥ 1 SP Citing ≥ 10 different SPs Citing ≥ 50 different SPs Software 38 28% 7.5% 0% E-Commerce 12 0% 0% 0% Consumer Internet 18 0% 0% 0% Financial 7 0% 0% 0% Hardware 7 63% 0% 0% BioTech, Bio- Electronics 7 88% 75% 75% Energy 2 50% 50% 0% Space 1 0% 0% 0% Total 92 23% 7.6% 5.4% Percentages of U.S. Startups, by Numbers of Scientific Papers Cited in Patents
  67. 67. Few Startups have Patents that Cite Scientific Paper  Only 4.2% of all startups have patents that cite 50 or more different papers  Only 5.6% of all startups have patents that cite 10 or more different papers  Even for U.S. startups, the percentages are low  Only 5.4% of U.S. startups have patents that cite 50 or more different papers  Only 7.6% of U.S. startups have patents that cite 10 or more different papers
  68. 68. Startups for a Few Categories Have Patents that Cite Scientific Papers  75% of BioTech/Bio-Electronic startups had patents that cited more than 50 scientific papers  One of two (50%) of energy startups had patents that cited more than 10 scientific papers  All of these startups are U.S. startups  In comparison  Only 7.3% of the software startups  None of the e-commerce, consumer Internet, or hardware startups  had patents citing 10 or more scientific papers
  69. 69. Pure Science vs. Engineering and Computer Science  The BioTech/Bio-Electronics and energy startups had patents that cited papers in pure scientific journals  Physics  Chemistry  Biology  Only one startup outside of these categories cited papers in pure scientific journals  Palantir, a software startup  It cited more than 10 scientific papers including Nucleic Acids Research and Bioinformatics
  70. 70. Summary  Advances in science did not directly play an important role in the emergence of opportunities exploited by startups  Few scientific papers cited in patents  Of the few papers cited in patents, they were mostly for startups in Bio-Tech/Bio-Electronic category  Few science-based products  No carbon nanotubes, graphene, nano-particle, quantum dot, superconductor, display, lighting, new forms of integrated circuits, membranes, or quantum computers  https://www.youtube.com/watch?v=yesyhQkYrQM  These types of science-based technologies are emphasized by engineering schools
  71. 71. Summary (2)  Thus, traditional process (invention, commercialization and diffusion) does not explain how opportunities emerged  Few science-based prototypes  Few improvements in performance and cost for these new prototypes driven by advances in science  What about improvements in components?  Can they explain the emergence of opportunities that were exploited by startups?  Let’s look at the startups for each category, beginning with e-commerce
  72. 72. Sub- Category Number Names of Firms Clothing and Accessories 9 Fanatics, Vancl, Gilt Groupe, Mogujie, JustFab, LaShou, Zalando, Global Fashion Group, Lazada Broad Variety of Products 7 Flipkart, Contextlogic, Snapdeal, Coupang, Koudai Shopping, Quikr, JD.com Furniture, Interior Design 5 Home24, Honest Co, FarFetch, Wayfair, Fab Other Specialty Sites 5 Warby Parker, Blue Apron, Beibei, Pluralsight, We Work Discount coupons 2 Coupons.doc, Meituan Total 28 Number of E-Commerce Startups by Sub-Category
  73. 73. What Enabled these Opportunities?  Fifteen of 28 startups focus on fashion related products  clothing, accessories, furniture, and interior design.  Although music, videos, books, electronic products dominated early online sales in U.S. and elsewhere, fashion related products have experienced rapid growth in online sales over the last 10 years  their U.S. sales were 50% higher than those of music, videos, books, electronic products in 2013  Improvements in Internet speed and bandwidth  Enabled more complex and aesthetically pleasing web pages and thus fashion related opportunities (see below)  Enabled new users and thus new opportunities The Ongoing Evolution of US Retail, Journal of Economic Perspectives, Ali Hortacsu and Chad Syverson, Vol 29, No 4, pp. 89-112
  74. 74. The Ongoing Evolution of US Retail, Journal of Economic Perspectives, Ali Hortacsu and Chad Syverson, Vol 29, No 4, 2015 pp. 89-112 Furniture, Sporting Goods, Clothing Fashion, clothing, furniture E-Commerce Changed from Digital Products to Fashion, Clothing, Furniture
  75. 75. Increases in Speed Enable Increases in Web Page Size And Number of Objects (pictures, videos, flash files)
  76. 76.  Large number of 28 startups in two largest emerging economies and are mobile related  9 from China and 2 from India  16 of them primarily depend on access from mobile phones  Both these trends consistent with improvements in Internet and Internet-related devices  As cost and performance of Internet improved, Internet diffusion spread to countries such as China and India and to new access devices such as mobile phones  Smart phone-targeted services attract young people and other fashion-conscious shoppers to the Internet and this impacts on popularity of fashion-related products Two Other Key Trends
  77. 77. Sub-Category Number Names of Firms Ride Sharing 7 Uber, Didi Dache, Kuaidi Dache, Ola Cabs, Lyft, Grabtaxi, BlaBla Car Food (delivery, restaurant search) 6 Delivery Hero, Zomato, Instacart, Hello Fresh, Ele.me, Dianping Audio/Video 6 Spotify, Shazam, Pinterest, Snapchat, KIK Interactive, Tango Games, Digital Entertainment 5 Kabam, Garena Online, Fan Duel, Draft Kings, Legendary Entertainment Social Networking 5 Houzz, NextDoor, Eventbrite, Lamabang, Vox Media Hotels 2 Airbnb, Tujia Health Care 2 Oscar Healthcare, ZocDoc Other 5 Rocket Internet, Yello Mobile, APUS, BuzzFeed Total 37 Number of Consumer Internet Startups by Sub-Category
  78. 78. What Enabled these Opportunities?  All 37 provide services that were not available during early years of Internet (late 1990s and early 2000s)  because Internet did not have sufficient bandwidth and/or mobile phones did not have sufficient capability  This is particularly true of startups that were founded in China or India or that depend on mobile phones  9 from China or India  25 of 37 services mostly depend on smart phones and often on smart phone apps  this includes all ride sharing, food, and hotel-related services, and most audio/video, social networking, and other services
  79. 79. What Enabled these Opportunities? (2)  Taxi apps (e.g., Uber) have become most famous of these apps  Also food (delivery, restaurant search), audio/video (music photos), some games, social networking (specialized sites)  Many of these startups can also be defined as members of the demand or sharing economy  Taxi, food services, Airbnb, Tujia  Consumers are paying for services that provide taxis, food, and hotels on demand and all of these services clearly require mobile phones
  80. 80. http://www.wsj.com/articles/in-china-fast-food-fight-turns-to-delivery-1439130011
  81. 81. Sub-Category Number Names of Firms Sales, Human Resource, Inventory Enterprise software 14 Shopify, Apttus, Coupa, Qualtrics, Zenefits, Automattic, CloudFlare, InsideSales.com, Sprinklr, Deem, AppDynamics, Slack, Medalia, Domo Security software 5 Tanium, Good Technology, Lookout, Okta, Zscaler Database, data storage software 6 Nutanix, Simplivity, MarkLogic, PureStorage, MongoDB, Actifio Big Data Software and Services 4 Palantir, Cloudera, Hortonworks, MuSigma Online Ad Software 3 InMobi, AppNexus, IronSource Cloud storage 2 Dropbox, Box Software Dev. Tools 2 Twilio, Github Other Tools 3 DocuSign, Evernote, New Relic Integration Platforms 1 MuleSoft Internet of Things Platform 1 Jasper Technologies Total 41 Number of Software Startups by Sub-Category
  82. 82. What Enabled these Opportunities?  All these opportunities involve cloud computing  Cloud computing emerged as improvements in Internet speed and bandwidth occurred  Various types of enterprise, software, software development and other tools, and platforms are accessed or downloaded via cloud by organizations and to lesser extent individuals  Organizations use software for internal use or on website. This includes enterprise software for human resources, sales, marketing, operations, human resources  Purchase Big Data services or use cloud storage services  Economic feasibility of these opportunities depended on improvements in Internet bandwidth and speed
  83. 83. What Enabled these Opportunities? (2)  Most of these opportunities involve big data  Big data is broad term for data sets so large or complex that traditional data processing techniques are inadequate  It tests much more complex models with many more independent variables than does traditional data analysis  It emerged as improvements in Internet speed and bandwidth occurred  Organizations purchase  big data software and services  software services for sales, human resource, inventory enterprise software suppliers that includes big data functions
  84. 84. What Enabled these Opportunities? (3)  Organizations purchase big data software/services  Purchase big data results through services or do big data internally with software or services from  Palantir, Cloudera, MuSigma, Hortonworks  Use data base software from  Nutanix, Actifio, Simplivity, MarkLogic, PureStorage, MongoDB  Organizations also purchase software services for sales, human resource, inventory enterprise software suppliers that includes big data functions  this includes Shopify, Apttus, Coupa, Deem, AppDynamics, Sprinklr, Qualtrics, InsideSales.com  Opportunities emerged as improvements in Internet speed and bandwidth occurred
  85. 85. What Enabled these Opportunities? (4)  Improvements in Internet speed and bandwidth along with emergence of cloud computing and big data caused other opportunities to emerge  Security has become more important  Tanium, Good Technology, Lookout, Okta, Zscaler  Online ads have become more sophisticated, both in presentation and delivery  InMobi, AppNexus, IronSource  Software development and integration have become more expensive and important  Twilio, Github, MuleSoft
  86. 86. What Enabled these Opportunities? (5)  Five of the 41 software startups (InMobi, Good Technology, Lookout, Evernote, Twilio) also depended on emergence and diffusion of smart phones such as iPhone and Android phones  Emergence of these phones and networks depended on improvements in microprocessors, flash memory, and displays  What’s Next? To be discussed in Session 4 See for example, http://www.slideshare.net/Funk98/when-do-new-technologies-become-economically-feasible-the-case-of-electronic- products
  87. 87. Sub- Category Number Names of Firms Peer-to peer lending 5 Lufax, Prosper Marketplace, Social Finance, Funding Circle, Lending Club Mobile payment 4 Stripe, One97 Communications, Adven, Square E-commerce Payment 2 Powa and Klarna Other 4 Zhong an Online (insurance), Hanhua Financial (credit guarantor), Credit Karma (credit scores), Sunrun (solar leasing) Total 15 Number of Financial Startups by Sub-Category
  88. 88. What Enabled these Opportunities?  Peer-to peer lending and “other” financial startups have benefited from emergence of  Cloud Computing  Big Data  Web sites that specialize in peer-to peer loans offer loans to customers, considered too risky by banks  set rates using special algorithms and these rates are often lower than those offered by loan sharks  Improvements in Internet bandwidth and speed helped create more sophisticated websites  that could assemble credit histories and credit scores of potential borrowers through Big Data  Similar things happened with “other” and one “e-commerce”  Decisions about credit guarantees, credit scores, insurance, solar leasing, and one e-commerce payments (Klarna) are based on Big Data
  89. 89. What Enabled these Opportunities? (2)  Feasibility of e-commerce payment services have benefited from increasing market for e-commerce, which has benefited from improvements in Internet  Feasibility of mobile payment services have benefited from improvements in mobile phones  including growth in text messaging services in early 2000s  emergence and growth of smart phones in last seven years  Global opportunities  7 in U.S.  4 in Europe  3 in China  1 in India  What’s Next? Discussed some in Session 4
  90. 90. Hardware Related Startups  All ten hardware startups provide electronic products  They are not placed into sub-categories  since each of them provides a different type of electronic product  Smart phones, rugged cameras, drones  Wearable health, augmented reality glasses  Storage hardware, audio headphones, assisted vision  Gaming mouse, smart thermostats  All of these opportunities depended on improvements in electronic components
  91. 91. Other Startups  Other startups depended less on improvements in electronic components than did above ones  Energy, space, and retail startup do not benefit greatly from improvements in electronic components  Only four of eight 8 bio-tech/bio-electronic startups might benefit from rapid improvements in components, including electronic components  Theranos, Intarcia, Proteus Digital Health, 23andMe  Four other startups (Moderna, Stemcentrix, Adaptive BioTechonlogies, CureVaC) offer drugs (bio-tech)  The drug related products involve advances in science, and this is consistent with data on patents and papers presented above
  92. 92. Summary  Most startups exploited opportunities that benefited from improvements in electronic components, which experience rapid improvements  Internet bandwidth, cost, and speed  Integrated circuits, lasers, photo-sensors, computers  These improvements in electronic components enabled improvements in Internet speed and bandwidth and emergence of new forms of  Internet content  Services  Software  121 of 143 are Internet related  10 are related to electronic hardware
  93. 93. What’s Next: Much of this will continue with some changes  Many new ones discussed in Session 4  Software: cloud computing, enterprise software, big data, online ads, security, database  e-commerce: more fashion, cosmetics, drugs, food and beverages  Consumer internet: Taxi (Session 9), social networking, food, games, music, hotels  Financial services: P2P lending, mobile payment, micro-financing  Hardware: Phones, drones, wearable computing  Improvements in components such as ICs (Moore’s Law)  Greater use of smart phones, other mobile devices  Improvements in online Internet experience  More social networking  Growth of Internet in new countries: China, India, and other countries
  94. 94.  Internet of Things (Session 5)  Better and cheaper ICs, MEMS, transceivers (WiFi, Bluetooth), and energy harvesters are enabling all mechanical products to be connected to Internet  Which products can benefit the most from being attached to Internet?  Big Data services and software will also emerge and they will probably become the biggest opportunities  Who will provide these services and software?  Wearable Computing and Health Care (Sessions 6, 7, 8)  Better and cheaper bio-sensors, ICs, MEMS and displays are enabling more health care related wearable computing  Big Data services and software will also emerge and will likely provide most of the opportunities Two Big Opportunities For more info, see: http://www.slideshare.net/Funk98/presentations
  95. 95. Let’s Connect Everything to the Internet For more info, see: http://www.slideshare.net/Funk98/ presentations
  96. 96. The next step in computing – after smart phones and tablets One big market for wearables will be health care – monitoring various parts of your body For more info, see: http://www.slideshare.net/Funk98/ presentations
  97. 97. For your projects  Can you better explain the types of software, e- commerce, consumer internet, or financial services that will likely emerge in the next few years?  Focus on one of the categories and explain the types of technological changes that are changing the economics and thus enabling better software, e- commerce, consumer internet, or financial services to emerge  Can you use this analysis to explain the types of changes that will likely occur in the sub-categories?  Will some sub-categories become more or less important?  Will there be new sub-categories?  Or will there be new categories?
  98. 98. Outline  Supply and demand curves and economic feasibility  Two models of technology change  Model of Invention  Silicon Valley Model (Improvements in components lead to emergence of new systems)  Billion Dollar Startup Club  Problems with over-emphasizing model of invention: Predictions made by MIT’s Technology Review  Myths of technology change  S-Curves for performance  Slowdowns in old technologies lead to improvements in new technologies  Learning and Experience Curves  A-U Model
  99. 99. For the remaining slides  Problems with over-emphasizing the linear model: Predictions made by MIT’s Technology Review  See predicting breakthrough technologies……  http://www.slideshare.net/Funk98/presentations/2  Myths of Technology Change  http://www.slideshare.net/Funk98/presentations/3

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