Data or Business First?—Manufacturers’ Transformation Toward Data-driven Business Models

被引:0
作者
Stahl B. [1 ,2 ,3 ]
Häckel B. [1 ,2 ,3 ]
Leuthe D. [1 ,2 ,3 ]
Ritter C. [1 ,3 ]
机构
[1] Research Center Finance & Information Management, Augsburg
[2] University of Applied Sciences Augsburg, Augsburg
[3] Branch Business & Information Systems Engineering of the Fraunhofer FIT, Alter Postweg 101, Augsburg
来源
Schmalenbach Journal of Business Research | 2023年 / 75卷 / 3期
关键词
Data analytics; Data-driven business models; Data-driven services; Enterprise architecture; L60; Manufacturing; O14; O32;
D O I
10.1007/s41471-023-00154-2
中图分类号
学科分类号
摘要
Driven by digital technologies, manufacturers aim to tap into data-driven business models, in which value is generated from data as a complement to physical products. However, this transformation can be complex, as different archetypes of data-driven business models require substantially different business and technical capabilities. While there are manifold contributions to research on technical capability development, an integrated and aligned perspective on both business and technology capabilities for distinct data-driven business model archetypes is needed. This perspective promises to enhance research’s understanding of this transformation and offers guidance for practitioners. As maturity models have proven to be valuable tools in capability development, we follow a design science approach to develop a maturity model for the transformation toward archetypal data-driven business models. To provide an integrated perspective on business and technology capabilities, the maturity model leverages a layered enterprise architecture model. By applying and evaluating in use at two manufacturers, we find two different transformation approaches, namely ‘data first’ and ‘business first’. The resulting insights highlight the model’s integrative perspective’s value for research to improve the understanding of this transformation. For practitioners, the maturity model allows a status quo assessment and derives fields of action to develop the capabilities required for the aspired data-driven business model. © 2023, The Author(s).
引用
收藏
页码:303 / 343
页数:40
相关论文
共 116 条
[1]  
Appelbaum S.H., Socio-technical systems theory: an intervention strategy for organizational development, Management Decision, 35, 6, pp. 452-463, (1997)
[2]  
Astill J., Dara R.A., Campbell M., Farber J.M., Fraser E.D., Sharif S., Yada R.Y., Transparency in food supply chains: A review of enabling technology solutions, Trends in Food Science & Technology, 91, pp. 240-247, (2019)
[3]  
Azkan C., Iggena L., Moller F., Otto B., Towards design principles for data-driven services in industrial environments, Proceedings of the 54th Hawaii International Conference on System Sciences, (2021)
[4]  
Baltuttis D., Hackel B., Jonas C.M., Oberlander A.M., Roglinger M., Seyfried J., Conceptualizing and assessing the value of Internet of things solutions, Journal of Business Research, 140, pp. 245-263, (2022)
[5]  
Baskerville R., Baiyere A., Gregor S., Hevner A., Rossi M., Design science research contributions: Finding a balance between artifact and theory, Journal of the Association for Information Systems, 19, 5, pp. 358-376, (2018)
[6]  
Baxter G., Sommerville I., Socio-technical systems: From design methods to systems engineering, Interacting with Computers, 23, 1, pp. 4-17, (2011)
[7]  
Becker J., Knackstedt R., Poppelbuss J., Developing maturity models for IT management, Business & Information Systems Engineering, 1, 3, pp. 213-222, (2009)
[8]  
Bergman R., Abbas A.E., Jung S., Werker C., de Reuver M., Business model archetypes for data marketplaces in the automotive industry, Electronic Markets, 32, 2, pp. 747-765, (2022)
[9]  
Bertolini M., Mezzogori D., Neroni M., Zammori F., Machine learning for industrial applications: A comprehensive literature review, Expert Systems with Applications, 175, (2021)
[10]  
Beverungen D., Muller O., Matzner M., Mendling J., vom Brocke J., Conceptualizing smart service systems, Electronic Markets, 29, 1, pp. 7-18, (2019)