Data on the impact of business analytics, knowledge retention, and dynamic capabilities on competitive advantage in electronic commerce

Published: 27 November 2023| Version 1 | DOI: 10.17632/tws55hmygt.1
Dian Alanudin,


This article introduces a dataset comprising 327 surveyed electronic commerce firms in Indonesia, aiming to evaluate their competitive advantage. Following a resource-based view (RBV) framework, the dataset encompasses four dimensions of business analytics, three dimensions related to knowledge retention, three dimensions of dynamic capability, and two dimensions supporting the competitive advantage construct. Using Smart PLS software to process and analyze the data. Additionally, the survey captures word cloud data of crucial factors for initiating business analytics in the firms. Firm-level characteristics are identified to unveil organizational competitive performance through knowledge retention and dynamic capability. The dataset incorporates essential factors needed by companies across various dimensions and sub-components with critical attributes. In total, the dataset comprises four main constructs, 12 dimensions, and 57 questions. The dataset is versatile and can be utilized under different theoretical approaches, such as Resource-Based View (RBV), Knowledge-Based View Management (KBV), dynamic capability, change management, innovation, other strategic management theories, or other information technology (IT) and Information system (IS) research.


Steps to reproduce

Using Smart PLS Software


Universitas Indonesia Fakultas Ekonomi, Universitas Indonesia Departemen Manajemen


e-Commerce, Knowledge Management, Strategic Management, Competitive Advantage, Competitive Advantage in Strategic Analysis, Dynamic Capability, Business Analytics