36.3 Take-off Disruption

Marginal Prob vs. Hazard of Death (what is the conditional probability of dying conditional on you are alive)

Sometimes we study takeoff instead of sales of new products because new products either takeoff or die, wee dont’ see flat salles. (managerial implication: invest if takeoff)

We have to wait at least till the peak of the hazard function (5 years)

Pervasiveness of disruption: US

36.3.1 Disruptive Technologies

  • Companies stay too close to their current customers, without accounting for future ones.

  • For each industry, there is performance trajectory that help track new technology performance in comparison with old ones’.

    • Sustaining technology: maintain the rate of improvement

    • Disruptive technology:

  • Solution to cultivate disruptive technologies:

    • Is the technology disruptive or sustaining?

    • What is the strategic significance of the disruptive technology?

    • Where is the initial market for the disruptive technology?

    • There should be a separate organization or business that handle disruptive technology

36.3.2 (Peter N. Golder and Tellis 1997) takeooff

  • Key issues:

    • How long does it typically take a product to take off?

    • Is there a takeoff pattern?

    • Can we predict takeoff?

  • If the baseline sales is small, it takes a large increase in sales to takeoff, but if the baseline sales is big, it takes only a small increase in sales to takeoff. Hence, there is a threshold for takeoff

  • Definition of takeoff: “the first year in which an individual category’s growth rate relative to base sales crosses this threshold.” (p. 256) or “the point of transition from the introductory stage to the growth stage of the product file cycle.” (p. 257)

    • Metric: the first large increase in sales in the new category (still don’t quite understand)
  • Operational definition of takeoff: “threshold for takeoff as a plot of the percentage increase in sales relative to its base sales that demarcates the takeoff.” (p. 259)

  • Independent variables: price, year of introduction, market penetration (percentage of households that have purchased a new product), and controls (product specific, and economic variables)

  • Found:

    • price at takeoff is lower than price at the introduction stage

    • Average time to takeoff is 6 years

    • penetration at takeoff is 1.7%

    • Products usually takeoff around 3 price points: $1000, $500, $100

  • Model: Cox’s proportional hazard mode

\[ h_i(t) = h(t; z_{it}) = h_0 (t) \times e^{z_{it} \beta} \]

where

  • \(h_0(t)\) is the baseline hazard function

  • \(z_{it}\) are the independent variables

  • \(\beta\) is the same for all categories (questionable choice)

  • Do not include unbosomed heterogeneity because each event is unique (non repeated)

Samples:

  1. 11 consumer durables (usually studied in diffusion research)
  2. 10 recently introduced consumer durables
  3. 10 categories during the review process.

Model performance

  • \(U^2\) measure reduction in uncertainty

  • Forecasts: (1) at introduction (2) one year ahead

36.3.3 (Chandy and Tellis 2000) Incumbent’s curse

  • Present this paper
  • Definition: “A radical product innovation is a new product that incorporates a substantially different core technology and provides substantially higher customer benefits relative to previous products in the industry” (Chandy and Tellis 1998).
  • Theory of S-curves: figure 1
  • Reasons incumbents don’t like radical innovations:
    • Perceived incentives: prospect theory (incumbents stand to lose, innovators stand to gain)

    • Organizational filter: resources are invested in important tasks that yield money.

    • Organizational routines: repetitive tasks are very efficient.

    • Opportunities of incumbents: market capabilities (customer knowledge, customer franchise, market power)

  • Size and incumbency are positively correlated
    • Theory of (bureaucratic) inertia: it’s hard to get new idea through a large firm because of filtering and screening + no incentives to do so.

    • Opportunities of large firms: financial and technical capabilities

  • There are more nonincumbents (i.e., small firms) as innovators in the US than other countries (e.g., Japan, or Western Europe) because of (1) institution (2) culture
  • Historical analysis: 1 author + 9 assistants over 4 years
  • Sample frame:
    • Product classes: consumer durables + office products

    • High unit sales (> 1 mil) (from Predicasts)

    • Radically new technology: (1) identify the most significant product innvoaitosn in each product category (2) 3 experts rate the radicalness

  • Measures
    • Radical innovation means (1) differences in core technology: utilizing a distinct core technology (2) superiority in user benefits:gives a lot more value to the customer than the first product in the same category.

    • Firm size: employees, sales volumn, value of asset from Moody’s Industrial Manual and S&P manual, for private firms: company directories - Industrial laboratories Directory, Edison Electric Light Co.

    • Innovator (firm that first commercialized the radical innovation) and incumbent (firms that sell previous generation product on the introduction date)

  • Results: 64 out of 93 innovations have data.
  • Categorical Analysis:
    • Large firms are more likely to be incumbents

    • Small firms were more radical in their innovation before the World War 2, large firms are radical in their innovation recently.

    • US innovators are from non-incumbent. Before the World War II, the US innovation were likely to come from smaller firms, but recent US innovation tend to come from large firms.

  • Multivariate
    • While larger organizations have historically introduced fewer innovative inventions, the tendency in recent years has been the polar opposite.

    • In recent years, US corporations have developed more radical ideas than non-US firms.

  • Further Analyses
    • Relevant Population: Large firms account for a significantly higher proportion of radical innovations when compared to its total number of firms in the economy. In any product class (incumbent vs. non), the number of incumbent is much smaller than non incumbents, but incumbents still account for half of the nubmer of radical innovations.

    • Alternative measure of firm size

    • Radical Innovator: but what if incumbents can be early entrants?

36.3.4 (Tellis, Stremersch, and Yin 2003) International Takeoff

  • 137 products across 10 categories inn 16 countries

  • Parametric hazard model

  • Takeoff in Europe (e.g., 6 years after introductionn) is different from those in US

  • Time-to-takeoff varies by countries and categories

  • Not much evidence for the effect of culture and economic factors on inter-country differences in time-to-takeoff

  • Use waterfall strategy when going international.

  • Countries with less uncertainty avoidance will have greater adoption

  • Countries with higher education will have greater adoption

36.3.5 (Hauser, Tellis, and Griffin 2006)Review on Innovation

5 fields

  • Consumer response to innovation

  • Organzattion and innovation

  • Market entry strategies

  • prescriptive technique for product development processes

  • Defense against market entry

36.3.6 (Chandrasekaran and Tellis 2008) Global Takeoff

  • 16 products in 31 countries

  • Parametric hazard model

  • Economic variable (developed vs. developing) (isn’t this kinda contradict (Tellis, Stremersch, and Yin 2003), product types (work vs. fun), cultural clusters, calendar time can affect takeoff time

  • Takeoff is getting shorter over time

36.3.7 (Sood and Tellis 2011) Predict takeoff

36.3.8 (M. Zhang and Luo 2016) Restaurant survival from Yelp

References

———. 2008. “Global Takeoff of New Products: Culture, Wealth, or Vanishing Differences?” Marketing Science 27 (5): 844–60. https://doi.org/10.1287/mksc.1070.0329.
Chandy, Rajesh K., and Gerard J. Tellis. 1998. “Organizing for Radical Product Innovation: The Overlooked Role of Willingness to Cannibalize.” Journal of Marketing Research 35 (4): 474. https://doi.org/10.2307/3152166.
———. 2000. “The Incumbent’s Curse? Incumbency, Size, and Radical Product Innovation.” Journal of Marketing 64 (3): 1–17. https://doi.org/10.1509/jmkg.64.3.1.18033.
———. 1997. “Will It Ever Fly? Modeling the Takeoff of Really New Consumer Durables.” Marketing Science 16 (3): 256–70. https://doi.org/10.1287/mksc.16.3.256.
Hauser, John, Gerard J. Tellis, and Abbie Griffin. 2006. “Research on Innovation: A Review and Agenda forMarketing Science.” Marketing Science 25 (6): 687–717. https://doi.org/10.1287/mksc.1050.0144.
———. 2011. “Demystifying Disruption: A New Model for Understanding and Predicting Disruptive Technologies.” Marketing Science 30 (2): 339–54. https://doi.org/10.1287/mksc.1100.0617.
Tellis, Gerard J., Stefan Stremersch, and Eden Yin. 2003. “The International Takeoff of New Products: The Role of Economics, Culture, and Country Innovativeness.” Marketing Science 22 (2): 188–208. https://doi.org/10.1287/mksc.22.2.188.16041.
Zhang, Mengxia, and Lan Luo. 2016. “Can User Generated Content Predict Restaurant Survival: Deep Learning of Yelp Photos and Reviews.” SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3108288.