TY - JOUR
T1 - Modeling supply-side dynamics of it components, products, and infrastructure
T2 - An empirical analysis using vector autoregression
AU - Adomavicius, Gediminas
AU - Bockstedt, Jesse
AU - Gupta, Alok
PY - 2012/1/1
Y1 - 2012/1/1
N2 - Prior IS research on technological change has focused primarily on organizational information systems and technology innovation; however, there is a growing need to understand the dynamics of supply-side forces in the introduction of new technologies. In this paper we investigate how the interdependencies among information technology components, products, and infrastructure affect the release of new technologies. Going beyond the ad hoc heuristic approaches applied in previous studies, we empirically validate the existence of several patterns of supply-side technology relationships in the context of wireless networking. We use vector autoregression (VAR) to model the comovements of new component, product, and infrastructure introductions and provide evidence of strong Granger-causal interdependencies. We also demonstrate that substantial improvements in forecasting can be gained by incorporating these cross-level effects into models of technological change. This paper provides some of the first research that empirically demonstrates these cross-level effects and also provides an exposition of VAR methodology for both analysis and forecasting in IS research.
AB - Prior IS research on technological change has focused primarily on organizational information systems and technology innovation; however, there is a growing need to understand the dynamics of supply-side forces in the introduction of new technologies. In this paper we investigate how the interdependencies among information technology components, products, and infrastructure affect the release of new technologies. Going beyond the ad hoc heuristic approaches applied in previous studies, we empirically validate the existence of several patterns of supply-side technology relationships in the context of wireless networking. We use vector autoregression (VAR) to model the comovements of new component, product, and infrastructure introductions and provide evidence of strong Granger-causal interdependencies. We also demonstrate that substantial improvements in forecasting can be gained by incorporating these cross-level effects into models of technological change. This paper provides some of the first research that empirically demonstrates these cross-level effects and also provides an exposition of VAR methodology for both analysis and forecasting in IS research.
KW - Information systems and technology trends
KW - Supply-side forces
KW - Technological change
KW - Technology ecosystems
KW - Technology forecasting
KW - Time series analysis
KW - Vector autoregression
UR - http://www.scopus.com/inward/record.url?scp=84871259473&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84871259473&partnerID=8YFLogxK
U2 - 10.1287/isre.1120.0418
DO - 10.1287/isre.1120.0418
M3 - Article
AN - SCOPUS:84871259473
SN - 1047-7047
VL - 23
SP - 397
EP - 417
JO - Information Systems Research
JF - Information Systems Research
IS - 2
ER -