Abstract
Inter-organisational governance is an important enabler for information processing, particularly in relationships undergoing digital transformation (DT) where partners depend on each other for information in decision-making. Based on information processing theory (IPT), the authors theoretically and empirically investigate how governance mechanisms address information asymmetry (uncertainty and equivocality) arising in capturing, sharing and interpreting information generated by digital technologies.
Design/methodology/approach
IPT is applied to four cases of public–private relationships in the Dutch infrastructure sector that aim to enhance the quantity and quality of information-based decision-making by implementing digital technologies. The investigated relationships are characterised by differing degrees and types of information uncertainty and equivocality. The authors build on rich data sets including archival data, observations, contract documents and interviews.
Findings
Addressing information uncertainty requires invoking contractual control and coordination. Contract clauses should be precise and incentive schemes functional in terms of information requirements. Information equivocality is best addressed by using relational governance. Identifying information requirements and reducing information uncertainty are a prerequisite for the transformation activities that organisations perform to reduce information equivocality.
Practical implications
The study offers insights into the roles of both governance mechanisms in managing information asymmetry in public–private relationships. The study uncovers key activities for gathering, sharing and transforming information when using digital technologies.
Originality/value
This study draws on IPT to study public–private relationships undergoing DT. The study links contractual control and coordination as well as relational governance mechanisms to information-processing activities that organisations deploy to reduce information uncertainty and equivocality.
| Original language | English |
|---|---|
| Article number | 7 |
| Pages (from-to) | 1145-1191 |
| Number of pages | 47 |
| Journal | International Journal of Operations & Production Management |
| Volume | 41 |
| Issue number | 7 |
| Early online date | 10 Aug 2021 |
| DOIs | |
| Publication status | Published - 8 Sept 2021 |
Funding
The authors express their gratitude to the research assistants Christina F?ll and Sophie Strijk, who both assisted with analysing and coding the data for both the Rail cases, and to graduate students Megan Ridderhof and Joep van de Water, who???together with the lead author???conducted interviews for the Rail A and Road A cases, respectively. The authors also acknowledge the support of Henk Akkermans, Brenda Espinosa and Saskia Lavrijssen, fellow researchers in the LONGA VIA research project, in developing the study and getting access to the case organisations and during the writing process. Finally, the authors thank all the participants of WION 2020 for their valuable feedback on an earlier version of the paper. This study was supported by the Dutch Research Council (NWO; grant number 439-16-807) and co-financed by Next Generation Infrastructures (NGinfra). This study was supported by the Dutch Research Council (NWO; grant number 439-16-807) and co-financed by Next Generation Infrastructures (NGinfra).