Discovering Sustainable Business Partnerships through a Deep Learning Approach to Maximize Potential Value

Author:

Lee Donghun1,Kim Jongeun1,Song Seokwoo2ORCID,Kim Kwanho1ORCID

Affiliation:

1. Department of Industrial and Management Engineering, Incheon National University, Incheon 22012, Republic of Korea

2. Department of Supply Chain & Management Information Systems, Weber State University, Ogden, UT 84403, USA

Abstract

Discovering sustainable business partnerships is crucial for small and medium-sized companies, where they can realize potential value through operational resources and abilities. Prior studies have mostly focused on predicting and developing new business partners using various machine learning techniques or social network analyses. However, effectively estimating potential benefits from business partnerships is much more valuable to companies. Therefore, this study proposes a method which combines deep learning and network analyses to estimate the potential value of business partnerships for companies. To demonstrate the effectiveness of the proposed method, we expand business partnerships between companies and assess potential value derived from the parenthesis using business transaction data collected from the Republic of Korea. The results suggest that companies can gain more potential value from extended networks when compared to previous ones. Furthermore, potential value results show clear distinctions between industries. Our findings provide evidence that small and medium-sized companies can experience significant benefits by establishing adequate business partnerships.

Funder

Incheon National University (International Cooperative) Research

Korea Institute of Energy Technology Evaluation and Planning

Ministry of Trade, Industry & Energy, Republic of Korea

Publisher

MDPI AG

Subject

Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Building and Construction

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