Firm Profiling and Competition Assessment - A Design Science Approach

Extensive efforts have been made by both academics and practitioners to understand inter-firm competitive relationship owing to its profound impacts on multiple key business goals, e.g., company benchmarking, marketing strategy planning, and talent acquisition. However, it has never been an easy task to fully characterize firms and assess the competitive relationship among them mainly due to the challenge of information heterogeneity. In this regard, we propose a novel IT artifact for firm profiling and inter-firm competition assessment guided by Information System Design Theory (ISDT). We start by constructing a Heterogeneous Occupation Network (HON) using employees’ occupation details and education attainments. Then we adopt a Methpath2Vec-based heterogeneous network embedding model to learn firms’ latent profiles (embeddings). Using the firm embeddings as input, we train multiple supervised classifiers to assess the competitive relationship among the firms. Following the logic of design as a search process, we demonstrate the utility of our IT artifact with extensive experimental study and in-depth discussions. Our study also reveals that employees’ occupation and education information significantly contribute to the identification of the focal firm’s potential competitors.

Hao (Howard) ZHONG
Hao (Howard) ZHONG
Assistant Professor | Scientific Co-director of MSc in Big Data and Business Analytics