Cluster Dynamics Measure:
[Emerging Hot Spot Analysis of the US Computer Industry from 1974 to 2014]
I (Min Jung Kim), Myles Shaver, and Russell Funk have introduced a measure that quantifies the dynamics of industry clusters, which we call . Calculating our measure of cluster dynamics consists of three steps: (1) measuring cluster concentration levels, (2) identifying trends in concentration levels, and (3) quantifying characteristics of those trends. tells us, for each cluster trend, the degree to which concentration is changing.
Codes
* README.txt (Download)
* Notes for Code Users: Please cite two following papers.
1) Min Jung Kim, Myles Shaver, and Russell Funk. Forthcoming. "From Mass to Motion: Conceptualizing and Measuring the Dynamics of Industry Clusters," Strategic Management Journal
2) Jushan Bai and Pierre Perron. 2003. "Computation and Analysis of Multiple Structural Change Models,"
Journal of Applied Econometrics, (18) 1-22.*
*The trend identification part of Code #2 has been built largely based on the codes by Bai and Perron (2003).
Code #1. Measuring cluster concentration levels (Step 1)
- Matlab code: Concentration_levels.m (Download)
- Input file #2:
- Input file #3:
- Input file #1:
Total number of the focal industry establishments (or employees) in a year.
● Example: Total number of U.S. Semiconductor establishments by year, from 1974 to 2016. Download)
01
Total number of population in a year-region
● Example: Total number of U.S. population by CBSA and year, from 1974 to 2016. Download)
Total number of establishments (or employees) in a year-region.
● Example: Total number of U.S. Semiconductor establishments in CBSA 35620—New York-Newark-Jersey City, NY- NJ-PA—by year, from 1974 to 2016. Download)
Concentration levels of industry activities in a year-region
(Example: Z-scores calculated based on the total number of U.S. Semiconductor establishments in CBSA 35620—New York-Newark-Jersey City, NY- NJ-PA—by year, from 1974 to 2016, from 1974 to 2016. Download*)
- Input file #1:
* Input files for Code #2 are consistent with output files from Code #1.
02
Code #2: Identifying trends in concentration levels and then quantifying characteristics of those trends
(Steps 2 & 3)
Paper
“From Mass to Motion: Conceptualizing and Measuring the Dynamics of Industry Clusters,” Forthcoming, Strategic Management Journal
Min Jung Kim, Myles Shaver, and Russell Funk. (Paper is available here)
An extensive body of research examines concentration levels (i.e., “mass”) of industry clusters; however, little attention is paid to their dynamics (i.e., “motion”). Understanding cluster dynamics is important because how clusters change over time may have implications for firm strategies and outcomes that are not attributable to cluster mass alone. To advance scholarship, we derive a theoretically grounded measure of cluster motion. Applying this measure to data on establishments in the U.S. computer and semiconductor industries, we document the dynamic nature of clusters both within and across regions. We demonstrate that our measure of cluster motion is distinct from cluster mass. Furthermore, we document that regions rarely follow stylized descriptions of cluster life cycles, which underscores the importance of measuring and investigating cluster dynamics.