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The data sharing conundrum: revisiting established theory in the age of digital transformation
Supply Chain Management ( IF 11.263 ) Pub Date : 2024-04-29 , DOI: 10.1108/scm-07-2023-0362
Giovanna Culot , Guido Orzes , Marco Sartor , Guido Nassimbeni

Purpose

This study aims to analyze the factors that drive or prevent interorganizational data sharing in the context of digital transformation (DT). Data sharing appears as a precondition for companies to capture emerging opportunities in supply chain management and for product-related servitization; however, there are ongoing concerns, and data are often perceived as the “new oil.” It is thus important to gain a better understanding of the determinants of firms’ decisions.

Design/methodology/approach

The authors develop an embedded case study analysis involving 16 firms within an extended supply network in the automotive industry. The authors focus on the peculiarities of the new context, as opposed to elements highlighted by research prior to the advent of the latest technologies. Abductive reasoning is applied to the theoretical foundations of the resource-based view, resource dependence theory and the complex adaptive systems perspective.

Findings

Data sharing is largely underpinned by factors identified prior to DT, such as data specificity, dependence dynamics and protection mechanisms and the dynamism of the business context. DT, however, can influence the extent of data sharing. New factors concern complementarities whenever data are pooled from different sources and digital platforms, as well as different forms of data ownership protection.

Originality/value

This study stresses that data sharing in the context of DT can be explained through established theoretical lenses, providing the integration of elements accounting for new technological opportunities.



中文翻译:

数据共享难题:重新审视数字化转型时代的既定理论

目的

本研究旨在分析数字化转型 (DT) 背景下推动或阻止组织间数据共享的因素。数据共享似乎是公司抓住供应链管理和产品相关服务化新兴机遇的先决条件;然而,仍然存在一些担忧,数据通常被视为“新石油”。因此,更好地了解企业决策的决定因素非常重要。

设计/方法论/途径

作者开展了一项嵌入式案例研究分析,涉及汽车行业扩展供应网络中的 16 家公司。作者关注的是新环境的特殊性,而不是最新技术出现之前研究强调的要素。归纳推理应用于资源基础观、资源依赖理论和复杂自适应系统观点的理论基础。

发现

数据共享在很大程度上受到DT之前确定的因素的支撑,例如数据特异性、依赖性动态和保护机制以及业务环境的动态性。然而,DT 可以影响数据共享的程度。当数据从不同来源和数字平台汇集时,新的因素涉及互补性,以及不同形式的数据所有权保护。

原创性/价值

这项研究强调,数字技术背景下的数据共享可以通过既定的理论视角来解释,从而提供新的技术机会的要素整合。

更新日期:2024-04-27
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