Understanding Decision-Making to Tackle Complexity in Open Innovation Labs in Government

IF 3.7 Q1 Economics, Econometrics and Finance

Intelligent Systems in Accounting, Finance and Management Pub Date : 2025-09-13 DOI:10.1002/isaf.70017

Ben De Coninck, Stijn Viaene, Jan Leysen

引用次数: 0

Abstract

This article examines the decision-making processes in open innovation labs (OI-labs) in government. Through a qualitative single case study, we explore how the use of causal and effectual reasoning, as dichotomous logics, evolves over time and is manifested in the form of organizational practices to tackle temporal, relational, and cultural complexity. The findings reveal three episodes: the conceptualizing of the lab (predominantly causation), the building of the lab (predominantly effectuation), and the sustaining of the lab (hybrid causation–effectuation). Moreover, shifts in the logic are aimed at addressing different types of complexity, and over time, a hybrid logic emerges.

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理解决策以解决政府开放式创新实验室的复杂性

本文考察了政府开放式创新实验室的决策过程。通过定性的单一案例研究，我们探索因果推理和有效推理的使用，作为二分逻辑，如何随着时间的推移而演变，并以组织实践的形式表现出来，以解决时间、关系和文化的复杂性。研究结果揭示了三个阶段：实验室的概念化（主要是因果关系）、实验室的建设（主要是效果）和实验室的维持（混合因果关系）。此外，逻辑中的转换旨在处理不同类型的复杂性，并且随着时间的推移，出现了混合逻辑。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Intelligent Systems in Accounting, Finance and Management Economics, Econometrics and Finance-Finance

CiteScore

6.00

自引率

0.00%

发文量

期刊介绍： Intelligent Systems in Accounting, Finance and Management is a quarterly international journal which publishes original, high quality material dealing with all aspects of intelligent systems as they relate to the fields of accounting, economics, finance, marketing and management. In addition, the journal also is concerned with related emerging technologies, including big data, business intelligence, social media and other technologies. It encourages the development of novel technologies, and the embedding of new and existing technologies into applications of real, practical value. Therefore, implementation issues are of as much concern as development issues. The journal is designed to appeal to academics in the intelligent systems, emerging technologies and business fields, as well as to advanced practitioners who wish to improve the effectiveness, efficiency, or economy of their working practices. A special feature of the journal is the use of two groups of reviewers, those who specialize in intelligent systems work, and also those who specialize in applications areas. Reviewers are asked to address issues of originality and actual or potential impact on research, teaching, or practice in the accounting, finance, or management fields. Authors working on conceptual developments or on laboratory-based explorations of data sets therefore need to address the issue of potential impact at some level in submissions to the journal.