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10.1108/tqm-02-2021-0036

PurposeThe main objective of this paper is to study the role of supply chain performance (SCP) as a mediator between big data-driven supply chain (BDDSC) and firm sustainable performance.

Big data-driven supply chain and performance: a resource-based view

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10.1108/jeim-03-2020-0101

Practical implicationsThe results provide important managerial insights for CBE companies to sustain their competitive advantages by improving their performances through IT and SCI practices throughout the upstream and downstream data-driven supply chain.

Impact of information technology on supply chain integration and company performance: evidence from cross-border e-commerce companies in China

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10.1108/tqm-12-2020-0303

PurposeThe paper aims to explore the various dimensions of human factor relevant for integrating data-driven supply chain quality management practices (DDSCQMPs) with organizational performance.

Reinforcing the significance of human factor in achieving quality performance in data-driven supply chain management

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10.5220/0010474107510758

This paper presents the preliminary results of the systematic empirically based development of a conceptual reference framework for data-driven supply chain collaboration based on the process model for empirically grounded reference modelling by Ahlemann and Gastl.

A Conceptual Reference Framework for Data-driven Supply Chain Collaboration

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10.1007/s11192-021-04060-4

In the narrow mapping, however, only the following clusters with a clear business-management focus emerge: (i) Data-driven methods in management in general and data-driven supply chain management in particular, (ii) Data-driven operations research analyses with different business administration/management focuses, (iii) Data-driven methods and processes in economics and finance, and (iv) Data-driven methods in Information Systems.

The effect of web of science subject categories on clustering: the case of data-driven methods in business and economic sciences

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Data Driven Supply
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What is/are Data Driven Supply?

Data Driven Supply - PurposeThe main objective of this paper is to study the role of supply chain performance (SCP) as a mediator between big data-driven supply chain (BDDSC) and firm sustainable performance. [1] Practical implicationsThe results provide important managerial insights for CBE companies to sustain their competitive advantages by improving their performances through IT and SCI practices throughout the upstream and downstream data-driven supply chain. [2] PurposeThe paper aims to explore the various dimensions of human factor relevant for integrating data-driven supply chain quality management practices (DDSCQMPs) with organizational performance. [3] This paper presents the preliminary results of the systematic empirically based development of a conceptual reference framework for data-driven supply chain collaboration based on the process model for empirically grounded reference modelling by Ahlemann and Gastl. [4] In the narrow mapping, however, only the following clusters with a clear business-management focus emerge: (i) Data-driven methods in management in general and data-driven supply chain management in particular, (ii) Data-driven operations research analyses with different business administration/management focuses, (iii) Data-driven methods and processes in economics and finance, and (iv) Data-driven methods in Information Systems. [5]