Winning the Hardware Software Game book Winning the Hardware-Software Game

Using Game Theory to Optimize the Pace of New Technology Adoption

Innovators of new technology systems requiring users to combine both hardware and software components often face delays in adoption of their new systems.  Users will not buy the hardware until enough software or content is available, while at the same time software providers will not provide content until enough users have adopted the new system.  This book examines the dynamics of this adoption process and provides methods for optimizing the pace of adoption of new technology systems.     Read more...

technology adoption

  • 2 Often Overlooked Factors that Impede Adoption of New Technologies

    A lot of great new technologies are introduced into the marketplace, only to flounder and fail to be adopted by users. In many cases, users’ failure to adopt new technologies is due technology providers’ failure to consider two important factors: ecosystem completeness and switching costs.

    Ecosystem Completeness

    Every technology introduced into the market offers users a particular value-in-context; that is, the technology enables users to generate value under specific conditions.

    Take, for example, an cellphone. For users to be able to generate value from a cellphone, they must have

    1. An cellphone,
    2. A charged battery (e.g., access to electricity services)
    3. Connection services (including a phone number), and
    4. Other people to call.

    All four of these pieces must be present simultaneously for the cellphone to provide value to the user. Conversely, if any of those four pieces is missing, then the cellphone provides no value.

  • An Overview of the Market for Driverless Cars

    Two Potential Market Outcomes

    Complementary Infrastructure Requirement

    Benefits of Self-Driving Cars

    Costs of Self-Driving Cars

    Winners

    Losers

    System Evolution

     

    Driverless (autonomous) vehicles is one of the hottest topics being discussed in the news lately. Some writers have been touting the enormous benefits adoption of driverless cars will bring, emphasizing the utopian scenario associated with the new technology. Others have noted the large industries dislocations their adoption will create, emphasizing the dystopian scenario. This analysis is my attempt to better understand what the market for driverless cars will entail.

     

    Two Potential Market Outcomes

    There have been two general market scenarios bandied about in discussions of autonomous vehicles:

    • Personal Self-Driving Cars (PSDC): In this scenario people generally own their own vehicles, but instead of people doing the driving, the vehicles drive themselves. This market outcome would yield a vehicle environment that looks relatively similar to the one that exists today, except that cars would have no drivers.
    • Shared Self-Driving Cars (SSDC): In this scenario people don’t own their own vehicles. Instead, third-party providers of transportation services own fleets of driverless vehicles, which people hail when they need to go somewhere. In other words, the SSDC scenario conflates autonomous vehicle with peer-to-peer (or sharing) technologies. This market outcome would yield a vehicle environment that is radically different from the one that exists today.
  • Are Device – Content Systems Moving Towards Compatibility or Incompatibility?

    Public vs. Private Information on the Internet

    Does Hardware Drive Software, or Vice Versa?

    Why Have Past Consortia for Compatibility Failed, and Why Would DECE Now Succeed?

    So Are Device-Content Systems Moving Toward Compatibility or Incompatibility?

     

    There are two trends occurring in the digital world that seem to be at odds with one another.  The first is that towards incompatible hardware/device – software/content ecosystems and the other is towards compatible ecosystems.

  • Bitcoin: Wave of the Future or Flash in the Pan?

    Essential Requirements of a Currency

    Essential Functions of a Currency

    Essential Characteristics of a Currency

    About Bitcoin

    What Is Bitcoin?

    Advantages of Bitcoin relative to Other Currencies

    Disadvantages of Bitcoin relative to Other Currencies

    Will Bitcoin Survive as a Global Currency?

    Does Bitcoin Satisfy the Essential Requirements of a Currency?

    Does Bitcoin Suffer from Fatal Disadvantages?

    Conclusions

    Useful Articles

    Bitcoin is one of the hottest new technologies on the scene. It started out as a niche tool for cyberpunks and anarchists to use to conduct online transactions. However, it has become increasingly embraced by more mainstream users, as global financial crises and massive amounts of government increases in money supplies have continued to wreak havoc on people’s trusts in the traditional financial systems. Some extol Bitcoin as the future of global currency, while others write it off as a speculative bubble and are quick to predict its impending demise. So which is it? Wave of the future or flash in the pan?

  • Creating a Competitive Edge by Inducing New Technology Adoption in Sub-Networks

    Inducing Adoption of New Technologies by Network Members

    Creating Sub-Network Competitive Advantage

     

    A recent article in the NYT, “E-Records Get a Big Endorsement” by Steve Lohr, describes how hospitals are seeking a competitive edge” by offering subsidies to doctors to join the hospitals’ digital networks:

  • Do We Shape Technology, or Does Technology Shape Us?

    I have always thought about technology as a tool that we develop and improve and customize and adapt to use to help us do whatever it is we want to do faster and easier and better. In other words, we shape and control technology.

    However, recently I’ve come to realize that, rather than simply us controlling technology, technologyactually shapes and controls us.

    Consider the example of clocks. Over time, we have developed and improved and customized and adapted clocks to meet our needs. We have huge clocks in watchtowers and churches that tell time for masses of people. We have wall clocks that tell time for organizations, and grandfather clocks that tell time for households, and watches and alarm clocks that tell time for us personally. And we customize all these clocks and watches to be more functional or more decorative to suit our needs and personalities. Clearly, it must be true that we shape and control clocks and watches.

  • Electric Vehicles and Social Welfare

    Terminology/Technical Information

    Players in the Electric Vehicle Game

    Current Stages of Adoption of Electric Vehicles

    Advantages and Disadvantages of Electric Vehicles

    Energy Inputs and Emissions Costs of Electric Vehicles

    Should the Construction of Electric Charging Stations be Subsidized by the Public?

     

     

    A recent article in the WSJ, “U.S. Utilities Push the Electric Car” by Cassandra Sweet, notes that electric companies nationwide are seeking to charge electricity consumers extra fees to fund construction of electric vehicle charging stations by the electric companies. The rationale is that having more charging stations available will speed adoption of electric vehicles by consumers, thereby leading to fewer pollutant emissions, and thus higher air quality for everyone.

    Should all electricity consumers be required to pay the construction costs of electric vehicle charging stations?

    The answer to this question requires understanding the underlying distribution of the private and social costs and benefits associated with manufacture and use of conventional versus electric vehicles.

  • For Smartphone Profitability, Focus on Software Beats Hardware

    A recent NYT article, ‘Why Japan’s Cellphones Haven’t Gone Global” by Hiroko Tabuchi, presents a dichotomy in the Japanese cellphone market: while the technology is extremely advanced, the market has evolved in such a way as to effectively isolate the Japanese market from the rest of the world. This will become increasingly problematic for Japanese suppliers (of both hardware and software/content/services), since the Japanese market is shrinking.

  • Has the Time for Electric Cars Finally Come?

    A recent article in the NYT, “Sites to Refuel Electric Cars Gain a Big Dose of Funds” by Nelson D. Schwartz,described the latest development in the evolution of the market for electric cars:

    Better Place, the closely watched start-up that hopes to create vast networks of charge spots to power electric cars, is set to receive a vote of confidence on Monday, in the form of $350 million in new venture capital.  Although Better Place will most likely require billions more in financing, this investment is an important step for the company...

  • How Do We Defend Against Rogue Drones?

    I’ve been reading a lot about drones, and the more I read, the more I’m convinced they’re going to cause a lot of problems, for everyone – citizens, businesses, and government alike.

     

    Here’s some background information that lays out some relevant issues.

     

    •  Drones are available to anyone.

    Drones are cheap to buy, and they can be built from off-the-shelf parts (see, for example “Building a Drone vs Buying One – Which is Best?”). So while the government could theoretically “require” people to register drones, there’s no way to enforce that requirement.

     

    •  It is difficult to identify drone owners and thus their intent.

    In this sense, drones are similar to cyberattacks. In “Marching off to cyberwar,” The Economist indicates that

    A cyberattack on a power station or an emergency-services call centre could be an act of war or of terrorism, depending on who carries it out and what their motives are.

  • Is Apple's Ecosystem Successful Because of or In Spite of Apple?

    Does Apple Dominate the MP3 Player & Smartphone Markets?

    Apple iPod & iPhone Sales Timeline

    How Did Apple Manage the Growth of Its Ecosystem to Create Value?

    Would Even More Value Have Been Created If Apple’s System Had Been Open?

     

    A recent article in Newsweek, “Think Really Different” by Daniel Lyons, laments the fact that Apple’s ecosystem is a closed system, which represents paradigm shift from the prior, open system the PC industry and post-Internet world had evolved into:

  • Is the Autonomous Vehicle Ecosystem in Balance?

    The Technology Triangle

    Years ago I attended a meeting on intellectual property (IP). One of the speakers, a sharp IP attorney named Pat Ellison, gave a talk, which greatly resonated with me. He said that a successful technology requires a balance between technology, business, and law, as represented by the triangle in Figure 1. (I recently contacted Pat about the origin of this idea and he said he was fairly sure that the idea was developed collaboratively with others, but he couldn’t remember who the other contributors were.) Very succinctly, descriptions for the requirements are:

    • Technology: The technology must work well.
    • Business: The technology must be cost effective, that is, is must able to be manufactured and sold for a profit.
    • Law: The legal and regulatory underpinnings of the technology, including intellectual property foundations and liability issues, must be sound.

    A successful technology will exhibit balance in each of the three areas in the sense that if any of the three is too weak – the technology doesn’t function well, the technology cannot be sold for a profit, and/or the intellectual property is invalid or ineffective or other regulatory issues have not been settled – then the technology will not become commercially successful.

    Figure 1

    balance1

  • Overview of Technology System Dynamics

    This is a presentation I’m preparing for “Tech Startup Conference: Artificial Intelligence” being held on September 26, 2017.

    1. Issues Covered

    • Adoption of New Technology Systems: What does it take for new technologies to become successfully adopted in the marketplace? Why do some technologies become adopted while others do not?
    • Value Creation: How do the components of the system combine to create value for the different players? Can the environment be changed so that the system will create more value?
    • Value Extraction: How much value does each player extract? In particular, are players extracting as much value from the system as they can?
  • Playing the e-Book Game

    The e-Book Pricing Battle

    The following is a brief history of the e-book pricing battle that has been taking place. The passage quotes heavily from three articles:

    “Publishers, Amazon in Flux in e-Book Pricing Fray” by Phil Wahba and Alexandria Sage, Reuters  

    “Amazon Looking Foolish in e-Book Flap” by Therese Poletti, MarketWatch

    “Cost of an E-Book Will Be Going Up” by Motoko Rich and Brad Stone, NYT

    Being first to market, Amazon established a $9.99 e-book pricing model.

    Amazon was first on the market with an electronic book (e-book) reader (e-reader), the Kindle.  Being first to market and having a large market presence together provided Amazon with enough leverage vis-à-vis publishers as to be able to establish a low, fixed sales price of $9.99 for all sales of e-books to Kindle users. This single, low, fixed price for all books is analogous to Steve Job’s iTunes music store pricing model, which initially sold all songs for 99 cents each.

  • Playing the Food Technology Game

    Introduction

    The players in the Food Technology Game include

    • Government
    • Farmers
    • Food Companies (Brands)
    • Retailers (Grocery Stores and Restaurant)
    • Consumers

    Government establishes standards and regulations, which affect the price, health, and safety of food supplied by Farmers, Food Companies, and Retailers.

    Farmers have different technologies available to them for increasing the productivity of their food supplies, such as machinery, chemicals, genetically engineering, and information/communication technologies.

    When it comes to demand for food, Consumers care to greater or lesser extents about

    • Low Price
    • Convenience
    • High Quality
    • Healthy Food
    • Moral or Sustainable Food

    That is, Consumers have different preferences over the use of certain technologies by Farmers, Food Companies and Retailers. Furthermore, Consumers’ preferences are dynamic – they change over time – in response both to new information and to social influences.

    Aside from the re-engineering costs, there are also time lags associated with changing the formulations of food supplies by Farmers, Food Companies, and Retailers.

    Given

    • The changing nature of Consumers’ preferences,
    • Together with the costs of changing food supplies,

    Farmers, Food Companies, and Retailers must choose which types of food to supply, based on their expectations of the quantity and longevity of demand for different food types by Consumers.

    This analysis examines these different dynamics in the Food Technology Game.

  • Playing the Mobile Payments Game v.1 (Pre-Mobile): 1950 – 2010ish

    A copy of the full analysis can be downloaded by clicking on the link at the bottom of this blog entry.

     

    The establishment of the general-purpose credit card system (in the US) is, for all intents and purposes, the basis upon which the mobile payment systems game is based.  The use of credit to pay for purchases of goods and services actually goes way back – nearly 3,000 years ago to ancient Babylon and Egypt. However, the use of general-purpose credit cards (as opposed to particular store credit cards) in the US started in 1950. The players in this initial credit card game included (i) the Banks or Credit Card Companies who issued the cards, (ii) Users who used credit cards issued by the Credit Card Companies to purchase goods and services from Merchants, and (iii) Merchants who accepted credit cards from Users as a form of payment for goods and services.  Over the next 60 years or so, the game between these three sets of players remained essentially unchanged.

  • Playing the Mobile Payments Game v.2: 2010ish - 2015

    A copy of the full analysis can be downloaded by clicking on the link at the bottom of this blog entry.

     

    In Part 1 of this analysis, I described the pre-mobile payments game, which involved Users, Merchants, and Credit Card Companies. I also disussed three significant features of the pre-mobile game: (i) Credit card fraud is a huge cost for Credit Card companies; (ii) The Credit Card Companies introduced a new credit card system in 2005 that is contactless and more secure than the current system, but the new technology has been slow to become adopted in the US; and (iii) High credit card fees have generated resentment from (Users and) Merchants toward the Credit Card Companies, and in 2012 the Merchants established a consortium, MCX, to develop an alternative payment system that would bypass the credit card system.

     Version 2 of the Mobile Payments Game starts after the introduction of smartphones. The widespread adoption and use of smartphones has paved the way for the development and recent introduction of mobile payment systems. It seems reasonable to assume that since smartphones enable mobile payment systems, eventually, Users will come to expect their smartphones to offer that capability. What this means is that any smartphone provider who hopes to gain widespread market share of their handsets will have to offer a mobile payments system. Of course, in theory, a smartphone provider can always offer someone else’s mobile payment system on his handsets – say, Apple could offer a Google-designed system for use on iPhones – but this would be a foolish move strategically for major systems providers. They would be passing up an extremely valuable opportunity for generating revenues, data, product differentiation, and/or general promotion of proprietary (branded) technology ecosystems.

    Since Apple and Google currently provide the majority of smartphone operating systems, and since the two behemoths seem to have developed a need to compete in every possible market, it should come as absolutely no surprise that Apple and Google have been developing their own mobile payment systems. Also, based on the tremendous antipathy that has been developing for decades by Merchants against Credit Card Companies, it’s also logical that Merchants have been developing a mobile payment system that will bypass the Credit Card Companies. The last group of early mobile payment systems developers is the Mobile Carriers.  The Mobile Carriers probably figured that since they have direct access to smartphone Users through their mobile services offerings, it would make sense for this relationship to serve as a means of them getting their finger in the humongous consumer credit card payments pie, if at all possible.

  • Playing the Mobile Payments Game v.3: 2015 - Present

    A copy of the full analysis can be downloaded by clicking on the link at the bottom of this blog entry.

     

    The latest version of the Mobile Payment Systems Game started in early 2015, with two significant changes in the structure of the Game.  First, the Mobile Carriers surrendered to Google. And second, Samsung entered into the game with its acquisition of a technology company that provides an alternative to Google Wallet. PayPal also joined the Game, allying itself with the Merchants, though this is a less-significant change than the other two. The structure of the game is presented in Figure 5.

  • Playing the Open Source AI Game, Part 1

    AI Basics

    Definition

    Why Now?

    The Controversy

    The Letter

    Current AI Ecosystem

    Categorization of AI Technologies

    Organization of Companies in the AI Ecosystem

     

     A copy of the full analysis can be downloaded by clicking on the link at the bottom of this blog entry.

     

    OpenAI, the organization recently cofounded by Elon Musk, has been receiving a lot of press lately. The company was introduced as follows:

    OpenAI is a non-profit artificial intelligence research company. Our goal is to advance digital intelligence in the way that is most likely to benefit humanity as a whole, unconstrained by a need to generate financial return.

    Since our research is free from financial obligations, we can better focus on a positive human impact. We believe AI should be an extension of individual human wills and, in the spirit of liberty, as broadly and evenly distributed as possible.

    Two issues in particular have been generating most of the attention surrounding the founding of the new organization:

    • OpenAI will focus its research on discoveries that will have positive benefits for society; and
    • OpenAI will be open source, that is, its discoveries will be freely available to all.

    Recent advancements in AI have enabled researchers to provide valuable new products and services in the marketplace, and the promise of continuing advancements suggest that even more valuable discoveries are on the horizon. As such, what motivations lay behind the decision of Elon Musk and his cofounders to make their new organization open source, rather than establishing it as a for-profit company? They have said that their intent is to provide discoveries that benefit humanity. But are the founders really as altruistic as they, themselves, and the media have made them out to be?

    This analysis is an attempt to better understand the dynamics underlying the AI ecosystem so as to better understand what motivated the founders of OpenAI to designate the organization as open source and whether or not there may be other agendas out there besides pure altruism.

  • Playing the Open Source AI Game, Part 2

    Generating Value from AI Systems

    Essential Components

    Feedback Loops

    Stated Benefits of Open Source Systems

    Focus on Projects that Benefit Humanity

    Mitigate Power of Single Entity

    Benefit From and Improve the Technology

    Attract Elite Researchers

    Why Do I Think OpenAI Was Established As Open Source?

    The More Obvious/Discussed Justifications

    The Less Obvious/Discussed Justification

     

    In Part 1 of this analysis, I provided some background information on AI as a foundation for the discussion. In this part of the analysis I continue on to discuss why I think Elon Musk designated OpenAI as an open source entity.

    A copy of the full analysis can be downloaded by clicking on the link at the bottom of this blog entry. 

     

    Generating Value from AI Systems

    Essential Components

    I’ve mentioned several times throughout the analysis that AI technology involves three essential components: IA algorithms (software), AI platforms (hardware), and big data. In this section I describe the nature and use of these components in more detail.

    I like the way Neil Lawrence describes the AI system in “OpenAI won't benefit humanity without data- sharing.” He uses the analogy of cooking, where AI algorithms are the recipes, the data are the ingredients, and the platform is the stove or oven.

    Anyone who has tried to come up with an original recipe will tell you that it generally needs to be tweaked before you come out with the ideal output. Similarly, researchers design AI algorithms, test and train them by running data through them, then tweak them to improve their performance.

    Generally speaking, the better cooks are those with more experience, and they tend to be the ones who come up with the best recipes. Of course, occasionally unknown or unpracticed chefs come up with excellent recipes, but that’s not the norm. Similarly in AI, the better, more experienced researchers are the ones who will probably generate most of the advancements in AI. However, that does not preclude the possibility that some unknown savants will be able to come up with advanced solutions on their own.

    Also, in cooking, better ingredients produce better dishes. Similarly, in AI, higher quality data lead to better results – as the saying goes, garbage in, garbage out. At the same time, AI algorithms become more accurate (trained) as they run more data. This means that having access to larger volumes of data will generate more accurate algorithms. So when it comes to data, both volume and quality are important.

    Finally, when cooking, the sizes of the ovens constrain the volume of food that can be produced. Similarly, with AI algorithms that need to run through large volumes of data to become properly trained, larger, more efficient hardware systems produce results much more quickly than do smaller systems.