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AI and Machine Learning in Service Management


Special issue call for papers from Journal of Service Management

AI and Machine Learning in Service Management

 
Journal of Service Management Special Issue: AI and Machine Learning in Service Management


Submission deadline for extended abstracts: March 30, 2019
Full paper submissions for invited papers May 15, 2019

Guest Editors

Dr. Kristina Heinonen, Hanken School of Economics, Finland
Dr. Jan Kietzmann, Gustavson School of Business, University of Victoria, Canada
Dr. Leyland Pitt, Beedie School of Business, Simon Fraser University, Canada

Journal of Service Management 2017 Impact factor 3.414; with a 5 year impact factor of 5.407

 

Overview

The Journal of Service Management is calling for submissions for a special issue on “Artificial Intelligence and Machine Learning in Service Management”.
Over the last decade, key technological advances in artificial intelligence (AI) and machine learning have caught the attention of practitioners and researchers who are interested in learning how firms can use these technologies effectively. As a result, relatively general calls for research on AI and machine learning are amassing, both for solid foundations that provide useful and highly citable frameworks and typologies and for more nuanced research of the application of such technologies. AI has to do with the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. Machine learning in turn is a subset of artificial intelligence that often uses statistical techniques to give computers the ability to "learn" (i.e., progressively improve performance on a specific task) with data, without being explicitly programmed to do so.
We propose to add to the emerging body of research by focusing directly on AI and machine learning in the specific context of service management. All types of services are already significantly impacted by AI and machine learning, including R&D, product design, accounting, legal, advertising, logistics, supply chain and post-sale services. Outside of the firm, and in a more general sense, AI and machine learning are reshaping services such as communication, transportation, utilities, banking, insurance and health care, to name only a few. We believe a special issue that concentrates directly on these and other areas can really shed light on the current and future impact of AI and machine learning on services and the way they are managed. With this goal, we encourage either conceptual papers or empirical papers contributing to an enhanced understanding of the impact of these technologies on service management. As a host of activities in services organizations will be affected by these technologies, authors might address issues related to service operations, service delivery systems, human resources management, and service marketing.
Possible topics of interest include, but are not limited to:
AI and machine learning and
•    their impact on competition, service strategies and tactics
•    new service development and innovation
•    their influence on the production/consumption service encounter
•    relationship management and the changing seller-buyer relationship/culture
•    supply chain management
•    value creation in services
•    customer experiences
•    service operations
•    service robotics and automation
•    human resource management
•    ethical issues, privacy and data management

Submission

All papers should be submitted through ScholarOne Manuscript Central online submission system http://mc.manuscriptcentral.com/josm. All manuscripts submitted must not have been published, accepted for publication, or be currently under consideration elsewhere.
Manuscripts should be submitted in accordance with the author guidelines available on the journal home page at http://www.emeraldgrouppublishing.com/products/journals/author_guidelines.htm?id=JOSM
Please make sure you select the special issue “AI and Machine Learning in Service Management” when submitting your manuscript.

The deadline for extended abstracts is March 30, 2019.  and the authors of the selected papers will be invited to submit their full paper on or before  May 15 2019.

Expected publication: Volume 30 2020

Key dates


30 March 2019
Extended abstract deadline
15 May 2019 Full submission deadline
30 July 2019 Authors notified of outcome of first review (reject/revise)
November 2019 Final outcome of accepted manuscripts


Articles submitted should not have been published before in their current (or substantially similar) form and should not be under consideration for publication elsewhere. Please see Emerald's originality guidelines for further details.

Further information

For questions regarding the content of this special issue, please contact the guest editors:

Dr. Jan Kietzmann
jkietzma@uvic.ca

Dr. Leyland Pitt
lpitt@sfu.ca

Dr. Kristina Heinonen
kristina.heinonen@hanken.fi