Data Governance Issues for a Digital Economy

A special issue of Logistics (ISSN 2305-6290).

Deadline for manuscript submissions: closed (15 June 2018) | Viewed by 5173

Special Issue Editor

Poole College of Management, North Carolina State University, Campus Box 7229, Raleigh, NC 27695, USA
Interests: strategic sourcing; supplier development; bioproducts; supply market intelligence; supply chain re-design; logistics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue will focus exclusively on data governance issues faced by supply chain professionals.

Authors are cordially invited to submit papers to Logistics for the 31 March 2018 issue. Manuscripts or papers can be submitted on the following topics

  1. Data Governance and its impact on Supply Chain Analytics
  2. Ways organizations can harness data to drive spend analysis
  3. Approaches to improve data quality in operations, procurement and business planning
  4. Methods to filter and observations on growth of noise while gathering data
  5. Global scenarios, legislation and adoption of block chain/smart contracts/distributed ledgers
Prof. Dr. Robert Handfield
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Logistics is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Data governance
  • Supply chain analytics
  • Data integrity
  • Supply chain systems
  • Cognitive analytics
  • Big data

Published Papers (1 paper)

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Research

20 pages, 831 KiB  
Article
Archetypes of Supply Chain Analytics Initiatives—An Exploratory Study
by Tino T. Herden and Steffen Bunzel
Logistics 2018, 2(2), 10; https://doi.org/10.3390/logistics2020010 - 08 May 2018
Cited by 5 | Viewed by 4673
Abstract
While Big Data and Analytics are arguably rising stars of competitive advantage, their application is often presented and investigated as an overall approach. A plethora of methods and technologies combined with a variety of objectives creates a barrier for managers to decide how [...] Read more.
While Big Data and Analytics are arguably rising stars of competitive advantage, their application is often presented and investigated as an overall approach. A plethora of methods and technologies combined with a variety of objectives creates a barrier for managers to decide how to act, while researchers investigating the impact of Analytics oftentimes neglect this complexity when generalizing their results. Based on a cluster analysis applied to 46 case studies of Supply Chain Analytics (SCA) we propose 6 archetypes of initiatives in SCA to provide orientation for managers as means to overcome barriers and build competitive advantage. Further, the derived archetypes present a distinction of SCA for researchers seeking to investigate the effects of SCA on organizational performance. Full article
(This article belongs to the Special Issue Data Governance Issues for a Digital Economy)
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