No Cover Image

Journal article 115 views 5 downloads

Deployment of generative artificial intelligence to enhance organisational resilience: empirical evidence from the logistics industry

Yue Hou, Ahmed Zainul Abideen, Guoqing Zhao Orcid Logo, Xiaoning Chen, Huilan Chen, Sebastian Elgueta

Journal of Decision Systems, Volume: 35, Issue: 1

Swansea University Author: Guoqing Zhao Orcid Logo

  • 71882.VOR.pdf

    PDF | Version of Record

    © 2026 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution License.

    Download (1.16MB)

Check full text

DOI (Published version): 10.1080/12460125.2026.2675048

Abstract

Grounded in dynamic capability theory, this study investigates how generative artificial intelligence (GenAI) adoption enhances organizational resilience through a qualitative single-case design based on 18 semi-structured interviews conducted within a world-leading logistics company. Our findings p...

Full description

Published in: Journal of Decision Systems
ISSN: 1246-0125 2116-7052
Published: Informa UK Limited 2026
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa71882
first_indexed 2026-05-11T16:44:24Z
last_indexed 2026-06-12T13:21:06Z
id cronfa71882
recordtype SURis
fullrecord <?xml version="1.0"?><rfc1807><datestamp>2026-06-11T14:29:47.3024854</datestamp><bib-version>v2</bib-version><id>71882</id><entry>2026-05-11</entry><title>Deployment of generative artificial intelligence to enhance organisational resilience: empirical evidence from the logistics industry</title><swanseaauthors><author><sid>2ff29aa347835abe2af6d98fa89064b4</sid><ORCID>0009-0003-9537-9016</ORCID><firstname>Guoqing</firstname><surname>Zhao</surname><name>Guoqing Zhao</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2026-05-11</date><deptcode>CBAE</deptcode><abstract>Grounded in dynamic capability theory, this study investigates how generative artificial intelligence (GenAI) adoption enhances organizational resilience through a qualitative single-case design based on 18 semi-structured interviews conducted within a world-leading logistics company. Our findings provide novel insights into how GenAI supports resilience across the disruption lifecycle. First, we identify nine key dimensions of organizational functioning strengthened by GenAI adoption, including enhanced risk prediction, early warning alerts, real-time movement tracking, performance analytics, and action recommendations during the preparation; the provision of feasible action plans during the response; and continuous monitoring against planned performance through to the recovery. Second, these functional benefits are translated into individual- and organizational-level capabilities. At the individual level, GenAI strengthens sensemaking, decision-making capability, and flexibility. At the organizational level, it enhances cross-functional synchronization, proactive preparedness, and resource optimization. The interaction and collective alignment of these multi-level capabilities enable organizations to strengthen their resilience.</abstract><type>Journal Article</type><journal>Journal of Decision Systems</journal><volume>35</volume><journalNumber>1</journalNumber><paginationStart/><paginationEnd/><publisher>Informa UK Limited</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>1246-0125</issnPrint><issnElectronic>2116-7052</issnElectronic><keywords>Generative artificial intelligence, organizational resilience, logistics industry, single case study, dynamic capability theory</keywords><publishedDay>21</publishedDay><publishedMonth>5</publishedMonth><publishedYear>2026</publishedYear><publishedDate>2026-05-21</publishedDate><doi>10.1080/12460125.2026.2675048</doi><url/><notes/><college>COLLEGE NANME</college><department>Management School</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>CBAE</DepartmentCode><institution>Swansea University</institution><apcterm>SU Library paid the OA fee (TA Institutional Deal)</apcterm><funders>Swansea University</funders><projectreference/><lastEdited>2026-06-11T14:29:47.3024854</lastEdited><Created>2026-05-11T17:36:18.7680105</Created><path><level id="1">Faculty of Humanities and Social Sciences</level><level id="2">School of Management - Business Management</level></path><authors><author><firstname>Yue</firstname><surname>Hou</surname><order>1</order></author><author><firstname>Ahmed Zainul</firstname><surname>Abideen</surname><order>2</order></author><author><firstname>Guoqing</firstname><surname>Zhao</surname><orcid>0009-0003-9537-9016</orcid><order>3</order></author><author><firstname>Xiaoning</firstname><surname>Chen</surname><order>4</order></author><author><firstname>Huilan</firstname><surname>Chen</surname><order>5</order></author><author><firstname>Sebastian</firstname><surname>Elgueta</surname><order>6</order></author></authors><documents><document><filename>71882__36944__be99ade8efad4a34be8b392f64d56cf5.pdf</filename><originalFilename>71882.VOR.pdf</originalFilename><uploaded>2026-06-11T14:27:43.7113076</uploaded><type>Output</type><contentLength>1215570</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><documentNotes>&#xA9; 2026 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution License.</documentNotes><copyrightCorrect>true</copyrightCorrect><language>eng</language><licence>http://creativecommons.org/licenses/by/4.0/</licence></document></documents><OutputDurs/></rfc1807>
spelling 2026-06-11T14:29:47.3024854 v2 71882 2026-05-11 Deployment of generative artificial intelligence to enhance organisational resilience: empirical evidence from the logistics industry 2ff29aa347835abe2af6d98fa89064b4 0009-0003-9537-9016 Guoqing Zhao Guoqing Zhao true false 2026-05-11 CBAE Grounded in dynamic capability theory, this study investigates how generative artificial intelligence (GenAI) adoption enhances organizational resilience through a qualitative single-case design based on 18 semi-structured interviews conducted within a world-leading logistics company. Our findings provide novel insights into how GenAI supports resilience across the disruption lifecycle. First, we identify nine key dimensions of organizational functioning strengthened by GenAI adoption, including enhanced risk prediction, early warning alerts, real-time movement tracking, performance analytics, and action recommendations during the preparation; the provision of feasible action plans during the response; and continuous monitoring against planned performance through to the recovery. Second, these functional benefits are translated into individual- and organizational-level capabilities. At the individual level, GenAI strengthens sensemaking, decision-making capability, and flexibility. At the organizational level, it enhances cross-functional synchronization, proactive preparedness, and resource optimization. The interaction and collective alignment of these multi-level capabilities enable organizations to strengthen their resilience. Journal Article Journal of Decision Systems 35 1 Informa UK Limited 1246-0125 2116-7052 Generative artificial intelligence, organizational resilience, logistics industry, single case study, dynamic capability theory 21 5 2026 2026-05-21 10.1080/12460125.2026.2675048 COLLEGE NANME Management School COLLEGE CODE CBAE Swansea University SU Library paid the OA fee (TA Institutional Deal) Swansea University 2026-06-11T14:29:47.3024854 2026-05-11T17:36:18.7680105 Faculty of Humanities and Social Sciences School of Management - Business Management Yue Hou 1 Ahmed Zainul Abideen 2 Guoqing Zhao 0009-0003-9537-9016 3 Xiaoning Chen 4 Huilan Chen 5 Sebastian Elgueta 6 71882__36944__be99ade8efad4a34be8b392f64d56cf5.pdf 71882.VOR.pdf 2026-06-11T14:27:43.7113076 Output 1215570 application/pdf Version of Record true © 2026 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution License. true eng http://creativecommons.org/licenses/by/4.0/
title Deployment of generative artificial intelligence to enhance organisational resilience: empirical evidence from the logistics industry
spellingShingle Deployment of generative artificial intelligence to enhance organisational resilience: empirical evidence from the logistics industry
Guoqing Zhao
title_short Deployment of generative artificial intelligence to enhance organisational resilience: empirical evidence from the logistics industry
title_full Deployment of generative artificial intelligence to enhance organisational resilience: empirical evidence from the logistics industry
title_fullStr Deployment of generative artificial intelligence to enhance organisational resilience: empirical evidence from the logistics industry
title_full_unstemmed Deployment of generative artificial intelligence to enhance organisational resilience: empirical evidence from the logistics industry
title_sort Deployment of generative artificial intelligence to enhance organisational resilience: empirical evidence from the logistics industry
author_id_str_mv 2ff29aa347835abe2af6d98fa89064b4
author_id_fullname_str_mv 2ff29aa347835abe2af6d98fa89064b4_***_Guoqing Zhao
author Guoqing Zhao
author2 Yue Hou
Ahmed Zainul Abideen
Guoqing Zhao
Xiaoning Chen
Huilan Chen
Sebastian Elgueta
format Journal article
container_title Journal of Decision Systems
container_volume 35
container_issue 1
publishDate 2026
institution Swansea University
issn 1246-0125
2116-7052
doi_str_mv 10.1080/12460125.2026.2675048
publisher Informa UK Limited
college_str Faculty of Humanities and Social Sciences
hierarchytype
hierarchy_top_id facultyofhumanitiesandsocialsciences
hierarchy_top_title Faculty of Humanities and Social Sciences
hierarchy_parent_id facultyofhumanitiesandsocialsciences
hierarchy_parent_title Faculty of Humanities and Social Sciences
department_str School of Management - Business Management{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}School of Management - Business Management
document_store_str 1
active_str 0
description Grounded in dynamic capability theory, this study investigates how generative artificial intelligence (GenAI) adoption enhances organizational resilience through a qualitative single-case design based on 18 semi-structured interviews conducted within a world-leading logistics company. Our findings provide novel insights into how GenAI supports resilience across the disruption lifecycle. First, we identify nine key dimensions of organizational functioning strengthened by GenAI adoption, including enhanced risk prediction, early warning alerts, real-time movement tracking, performance analytics, and action recommendations during the preparation; the provision of feasible action plans during the response; and continuous monitoring against planned performance through to the recovery. Second, these functional benefits are translated into individual- and organizational-level capabilities. At the individual level, GenAI strengthens sensemaking, decision-making capability, and flexibility. At the organizational level, it enhances cross-functional synchronization, proactive preparedness, and resource optimization. The interaction and collective alignment of these multi-level capabilities enable organizations to strengthen their resilience.
published_date 2026-05-21T06:02:22Z
_version_ 1868490858696802304
score 11.109323

Similar Items