Title
Towards An Understanding Of Technology Fit And Appropriation In Business Networks: Evidence From Blockchain Implementations
Abstract
Existing information systems research thoroughly explains how task-technology fit and appropriation affect performance on an individual or group level. This was appropriate for many years, as technology is typically used to fulfill a certain task on these levels. Today, however, companies are tightly interconnected and rely on business networks to develop, produce, and deliver products and services. They collaboratively engage in joint implementation and utilization of new technologies that are applied and integrated into their business processes. These technologies, such as the newly introduced blockchain technology, operate across business networks and, thus, unfold their benefits not only on an individual or group level, but ideally on a network level. On this level, though, knowledge of the application and performance of information technology is still scarce. To drive the performance of technology in such networks, we investigate the impact of fit and technology appropriation on a network level. Due to the technology's expected impact and characteristics, we select blockchain technology to explore potential factors, impacting fit, appropriation and, in turn, performance. We draw upon a set of interviews with experts that have implemented blockchain solutions in large business network settings. Based on our analysis, we propose a comprehensive model elevating the Fit-Appropriation Model to a network level. We contribute to the general understanding of technology utilization and performance by extending existing theory to a network-level perspective. Using insights on blockchain implementations as our empirical base, we also provide guidance to business leaders, intending to connect their partners through blockchain technology.
Year
DOI
Venue
2021
10.1007/s10257-020-00485-1
INFORMATION SYSTEMS AND E-BUSINESS MANAGEMENT
Keywords
DocType
Volume
Blockchain technology, Business network, Fit-appropriation, IOIS performance
Journal
19
Issue
ISSN
Citations 
1
1617-9846
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Stefan Seebacher100.68
Ronny Schüritz201.01
Gerhard Satzger39923.89