This paper presents a strategic reference model for data-driven supply chain collaboration (SCC) designed based on the principles of design science research and the process model for empirically grounded reference modelling. Increasingly competitive and global supply networks require the wider application of collaborative supply chain management. Thus, the different aspects of SCC, including inter-organizational exchange of data and knowledge as well as the integration of novel technologies such as artificial intelligence are essential factors for organizational growth. This paper attempts to fill the gap of a missing overview of this field by providing the results of the development of a comprehensive framework of data-driven SCC. Due to the interdisciplinary focus and approach combining information systems, design science and management research, the paper contributes to the academic debate by providing a macro level perspective on the topic of SCC and a conceptualization and categorization of data-driven SCC. Furthermore, this paper presents a valuable contribution to practice and supply chain processes in organizations across sectors by delivering an adaptable strategic reference framework for application in collaborative processes.
机构:
Fraunhofer Austria Research GmbH, Theresianumgasse 7, Vienna
Vienna University of Economics and Business, Welthandelsplatz 1, ViennaFraunhofer Austria Research GmbH, Theresianumgasse 7, Vienna
Birkmaier A.
Imeri A.
论文数: 0引用数: 0
h-index: 0
机构:
Vienna University of Economics and Business, Welthandelsplatz 1, ViennaFraunhofer Austria Research GmbH, Theresianumgasse 7, Vienna
Imeri A.
Reiner G.
论文数: 0引用数: 0
h-index: 0
机构:
Vienna University of Economics and Business, Welthandelsplatz 1, ViennaFraunhofer Austria Research GmbH, Theresianumgasse 7, Vienna