Skip to Main Content
Article navigation
Purpose

The purpose of this paper is to identify key factors that influence the decision to adopt computerized numerical control (CNC) and direct numerical control (DNC) machines, material working lasers and robots (specific advanced manufacturing technologies – AMT) using the theory of planned behavior (TPB) as the underlying framework.

Design/methodology/approach

Firms that had recently adopted a shop floor manufacturing technology were surveyed. Structural equation modeling was used to analyze the 123 responses.

Findings

The TPB explained a substantial amount of variance in behavioral intentions to adopt an AMT. As proposed, attitude towards adoption and subjective norms significantly influence a decision maker. However, perceived behavioral control did not have a significant impact on intentions. The TPB was shown to be an effective predictor of technology adoption in a specific context.

Research limitations/implications

Single respondents were used – future research might include multiple respondents. Though sufficient statistical power was realized, there was a relatively low response rate – future research may pre‐screen potential respondents to ensure eligibility.

Practical implications

Primary implications include: adopters may be willing to tolerate a difficult adoption process in order to realize significant competitive benefits; suppliers of AMT may want to develop greater customer knowledge to influence adoption decisions; and champions of AMT adoption may want to proactively influence the opinions of other key stakeholders.

Originality/value

The research context was controlled by focusing on a specific type of AMT. Further, actual technology adoption decisions were investigated. Most applications of the TPB assume that the “intentions” to “behavior” relationship holds.

You do not currently have access to this content.
Don't already have an account? Register

Purchased this content as a guest? Enter your email address to restore access.

Please enter valid email address.
Email address must be 94 characters or fewer.
Pay-Per-View Access
$41.00
Rental

or Create an Account

Close Modal
Close Modal