| Title |
Linking Digital Servitization and Industrial Sustainability Performance: A Configurational Perspective on Smart Solution Strategies |
| ID_Doc |
73780 |
| Authors |
Kolagar, M; Parida, V; Sjödin, D |
| Title |
Linking Digital Servitization and Industrial Sustainability Performance: A Configurational Perspective on Smart Solution Strategies |
| Year |
2024 |
| Published |
|
| DOI |
10.1109/TEM.2024.3383462 |
| Abstract |
Manufacturing companies are introducing innovative ways to facilitate the sustainable transition of their customers' operations. The emerging literature on digital servitization proposes numerous factors, such as the use of advanced artificial intelligence analytics, orientation toward outcomes, and aligning ecosystem partnerships, which can potentially influence the sustainable performance of industrial customers. However, there is currently a lack of understanding regarding how these factors interact to result in sustainable outcomes. Hence, this study seeks to shed light on these complex relationships by identifying viable smart solution strategy configurations for achieving customer sustainable performance. Drawing on a dataset of 180 Swedish manufacturing firms, this study uses a configurational comparative method-namely, fuzzy-set qualitative comparative analysis-to identify the impact of different configurations of "AI-driven optimization," "outcome orientation," "value co-creation," and "ecosystem orchestration" conditions on the realization of customer sustainable performance. This study has identified five smart solution strategies that empower manufacturers to realize sustainable performance for their customers. Among the five configurational strategies identified, the first configurational strategy appears to be the most prominent, as it is based on an outcome-based approach in which the firm uses its technological expertise and its ecosystem partnerships to take over customer operations. Thus, this study contributes to the ongoing discussion in digital servitization on its enabling role for industrial sustainability practices. |
| Author Keywords |
Artificial intelligence (AI)-driven optimization; digital servitization; ecosystem orchestration; industrial sustainability; smart solutions |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:001204996100005 |
| WoS Category |
Business; Engineering, Industrial; Management |
| Research Area |
Business & Economics; Engineering |
| PDF |
https://ieeexplore.ieee.org/ielx7/17/4429834/10487017.pdf
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