Data for "Dynamic Capabilities for AI-Enabled Exploration: Antecedents, Mechanisms, and Innovation Outcomes"

Study Overview:
The study examines how technological, organizational, and environmental (TOE) factors enable firms to develop AI-related dynamic capabilities (Sensing Capability and AI-Enabled Exploration) and how these capabilities drive innovation performance. The research integrates the TOE framework with the Dynamic Capabilities View (DCV) and tests a serial mediation model with moderation.
Sample:
Survey data were collected from 245 senior and middle managers in Saudi Arabian firms across multiple industries, including Telecommunications & IT, Energy & Manufacturing, Banking & Finance, Public Sector, and Retail & Services.
Contents:

CSV Data File: Contains anonymized survey responses measuring seven constructs: Government Support (GS1-GS3), Organizational Readiness (OR1-OR3), Technology Compatibility (TC1-TC3), Competitive Pressure (CP1-CP3; note: CP1 was dropped during analysis due to low factor loading), Sensing Capability (SC1-SC3), AI-Enabled Exploration (AIE1-AIE4), and Innovation Performance (IP1-IP4). All items were measured on a 7-point Likert scale. Firm size and industry sector are also included.
R Script: Complete PLS-SEM analysis code using the seminr package, including measurement model validation, structural model assessment, serial mediation analysis, and moderation analysis with 5,000 bootstrap subsamples.

Ethical Considerations:
All data have been anonymized. Respondents provided informed consent.