Navigating the digital landscape: communication visibility and entrepreneurial opportunity identification

Abstract

Purpose

With the advent of digital platforms, entrepreneurs have been able to communicate and share information in visible environments. By focusing on the visibility aspect of digital platform in a resource-constrained economy, this study aims to propose a conceptual model for exploring entrepreneurial opportunity identification. Furthermore, this study delves into the moderating influence of entrepreneurial alertness on opportunity recognition.

Design/methodology/approach

A research model is constructed using the theory of communication visibility to investigate how message transparency and network translucence affect the identification and development of entrepreneurial opportunities, with additional exploration of the moderating influence of entrepreneurial alertness. A questionnaire survey is conducted with 152 Iranian founder-entrepreneurs to test the proposed conceptual model. The research model’s constructs are analyzed using the partial least squares structural equation modeling method.

Findings

The results confirm that communication visibility impacts both aspects of entrepreneurial opportunity identification. In addition, this study reveals the distinctive moderating effects of entrepreneurial alertness on the relationship between message transparency and the creation and discovery of entrepreneurial opportunities, while finding no significant effect on network transparency and opportunity identification.

Originality/value

This paper stands out for its originality in collecting data from an emerging market. Besides, it explores the association between entrepreneurs’ communication dimensions and the recognition of new opportunities at the intersection of digital platforms and entrepreneurship literature. Furthermore, it empirically illustrates the moderating role of entrepreneurial alertness in the relationships between communication visibility and opportunity identification, contributing significantly to existing research.