Utilizing Artificial Intelligence for Stakeholder Engagement and Social Innovation in Addressing Climate Change: A Conceptual Framework and Future Research Agenda

Surajit Bag; Susmi Routray; Santosh Kumar Srivastava; David Roubaud; Abla Chaouni Benabdellah; Oksana Grebinevych

doi:10.4018/JGIM.366588

Utilizing Artificial Intelligence for Stakeholder Engagement and Social Innovation in Addressing Climate Change: A Conceptual Framework and Future Research Agenda

Surajit Bag
, Susmi Routray
, Santosh Kumar Srivastava
, David Roubaud
, Abla Chaouni Benabdellah
, Oksana Grebinevych

Research output: Contribution to journal › Article › peer-review

8 Citations (Scopus)

Abstract

This study employs Systematic Literature Review (SLR) and thematic analysis to explore the topics of Artificial Intelligence (AI), Stakeholder Engagement (SE) and social innovation. To enhance methodological rigor, the study integrated literature analysis and social media analysis to recognize topics within texts using Latent Dirichlet Allocation (LDA), an unsupervised machine learning method. The study highlights AI's influence on social engagement, aligning with diffusion theory, stressing the need to emphasize AI's benefits for faster adoption.

Original language	English
Journal	Journal of Global Information Management
Volume	32
Issue number	1
DOIs	https://doi.org/10.4018/JGIM.366588
Publication status	Published - Jan 2024
Externally published	Yes

Keywords

Artificial Intelligence
Change, Social Innovation
Climate
Grand Societal Challenges
Information Management
Stakeholder Engagement

ASJC Scopus subject areas

Business and International Management
Computer Science Applications
Strategy and Management
Management Science and Operations Research
Information Systems and Management

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.4018/JGIM.366588

Cite this

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title = "Utilizing Artificial Intelligence for Stakeholder Engagement and Social Innovation in Addressing Climate Change: A Conceptual Framework and Future Research Agenda",

abstract = "This study employs Systematic Literature Review (SLR) and thematic analysis to explore the topics of Artificial Intelligence (AI), Stakeholder Engagement (SE) and social innovation. To enhance methodological rigor, the study integrated literature analysis and social media analysis to recognize topics within texts using Latent Dirichlet Allocation (LDA), an unsupervised machine learning method. The study highlights AI's influence on social engagement, aligning with diffusion theory, stressing the need to emphasize AI's benefits for faster adoption.",

keywords = "Artificial Intelligence, Change, Social Innovation, Climate, Grand Societal Challenges, Information Management, Stakeholder Engagement",

author = "Surajit Bag and Susmi Routray and Srivastava, \{Santosh Kumar\} and David Roubaud and Benabdellah, \{Abla Chaouni\} and Oksana Grebinevych",

year = "2024",

month = jan,

doi = "10.4018/JGIM.366588",

language = "English",

volume = "32",

journal = "Journal of Global Information Management",

issn = "1062-7375",

publisher = "IGI Publishing",

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}

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T2 - A Conceptual Framework and Future Research Agenda

AU - Bag, Surajit

AU - Routray, Susmi

AU - Srivastava, Santosh Kumar

AU - Roubaud, David

AU - Benabdellah, Abla Chaouni

AU - Grebinevych, Oksana

PY - 2024/1

Y1 - 2024/1

N2 - This study employs Systematic Literature Review (SLR) and thematic analysis to explore the topics of Artificial Intelligence (AI), Stakeholder Engagement (SE) and social innovation. To enhance methodological rigor, the study integrated literature analysis and social media analysis to recognize topics within texts using Latent Dirichlet Allocation (LDA), an unsupervised machine learning method. The study highlights AI's influence on social engagement, aligning with diffusion theory, stressing the need to emphasize AI's benefits for faster adoption.

AB - This study employs Systematic Literature Review (SLR) and thematic analysis to explore the topics of Artificial Intelligence (AI), Stakeholder Engagement (SE) and social innovation. To enhance methodological rigor, the study integrated literature analysis and social media analysis to recognize topics within texts using Latent Dirichlet Allocation (LDA), an unsupervised machine learning method. The study highlights AI's influence on social engagement, aligning with diffusion theory, stressing the need to emphasize AI's benefits for faster adoption.

KW - Artificial Intelligence

KW - Change, Social Innovation

KW - Climate

KW - Grand Societal Challenges

KW - Information Management

KW - Stakeholder Engagement

UR - https://www.scopus.com/pages/publications/85214419276

U2 - 10.4018/JGIM.366588

DO - 10.4018/JGIM.366588

M3 - Article

AN - SCOPUS:85214419276

SN - 1062-7375

VL - 32

JO - Journal of Global Information Management

JF - Journal of Global Information Management

IS - 1

ER -

Utilizing Artificial Intelligence for Stakeholder Engagement and Social Innovation in Addressing Climate Change: A Conceptual Framework and Future Research Agenda

Abstract

Keywords

ASJC Scopus subject areas

UN SDGs

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