Leveraging Generative Artificial Intelligence to Enhance Carbon
Performance in Supply Chains Through Green Product Innovation
and End-of-Life Product Management: AI-Driven Carbon
Performance

J 2025

Leveraging Generative Artificial Intelligence to Enhance Carbon Performance in Supply Chains Through Green Product Innovation and End-of-Life Product Management: AI-Driven Carbon Performance

SHARIQ, Syed Muhammad; Roman ŠPERKA; Saqib SHAMIM and Hassan ALI

Basic information

Original name

Leveraging Generative Artificial Intelligence to Enhance Carbon Performance in Supply Chains Through Green Product Innovation and End-of-Life Product Management: AI-Driven Carbon Performance

Authors

SHARIQ, Syed Muhammad; Roman ŠPERKA; Saqib SHAMIM and Hassan ALI

Edition

BUSINESS STRATEGY AND THE ENVIRONMENT, New Jersey, WILEY, 2025, 0964-4733

Other information

Language

English

Type of outcome

Article in a journal

Field of Study

50200 5.2 Economics and Business

Country of publisher

United States of America

Confidentiality degree

is not subject to a state or trade secret

References:

URL

Impact factor

Impact factor: 13.300 in 2024

Organization unit

School of Business Administration in Karvina

DOI

https://doi.org/10.1002/bse.70384

UT WoS

001631553000001

Keywords in English

business intelligence; carbon performance; end-of-life product management; generative artificial intelligence; green product innovation; organizational information processing theory

Abstract

In the original language

This study illustrates how organizations reconcile their information processing capabilities with uncertainty within the supply chain (SC) through generative artificial intelligence (GAI) to achieve carbon performance (CP). A quantitative research methodology is applied, and 155 responses from manufacturing firms are analyzed through structural equation modeling (SEM) for hypothesis testing. The findings suggest that GAI for process automation and cognitive engagement has a positive influence on business intelligence (BI), whereas end-of-life (EOL) product management mediates the relationship between green product innovation (GPI) and CP. This study contributes to the SC context, focusing on GAI and BI in mitigating uncertainties within SCs to foster GPI and improve CP. This study highlights actionable frameworks for leveraging digital technologies in sustainable SCs by addressing technological challenges and integrating green innovation practices.

Cite

SHARIQ, Syed Muhammad; Roman ŠPERKA; Saqib SHAMIM and Hassan ALI. Leveraging Generative Artificial Intelligence to Enhance Carbon Performance in Supply Chains Through Green Product Innovation and End-of-Life Product Management: AI-Driven Carbon Performance. BUSINESS STRATEGY AND THE ENVIRONMENT. New Jersey: WILEY, 2025, vol. 2025, December, p. 1-17. ISSN 0964-4733. Available from: https://doi.org/10.1002/bse.70384.

@article{89243,
   author = {Shariq, Syed Muhammad and Šperka, Roman and Shamim, Saqib and Ali, Hassan},
   article_location = {New Jersey},
   article_number = {December},
   doi = {https://doi.org/10.1002/bse.70384},
   keywords = {business intelligence; carbon performance; end-of-life product management; generative artificial intelligence; green product innovation; organizational information processing theory},
   language = {eng},
   issn = {0964-4733},
   journal = {BUSINESS STRATEGY AND THE ENVIRONMENT},
   title = {Leveraging Generative Artificial Intelligence to Enhance Carbon Performance in Supply Chains Through Green Product Innovation and End-of-Life Product Management: AI-Driven Carbon Performance},
   url = {https://onlinelibrary.wiley.com/doi/10.1002/bse.70384},
   volume = {2025},
   year = {2025}
}

TY  - JOUR
ID  - 89243
AU  - Shariq, Syed Muhammad - Šperka, Roman - Shamim, Saqib - Ali, Hassan
PY  - 2025
TI  - Leveraging Generative Artificial Intelligence to Enhance Carbon Performance in Supply Chains Through Green Product Innovation and End-of-Life Product Management: AI-Driven Carbon Performance
JF  - BUSINESS STRATEGY AND THE ENVIRONMENT
VL  - 2025
IS  - December
SP  - 1-17
EP  - 1-17
PB  - WILEY
SN  - 09644733
KW  - business intelligence
KW  - carbon performance
KW  - end-of-life product management
KW  - generative artificial intelligence
KW  - green product innovation
KW  - organizational information processing theory
UR  - https://onlinelibrary.wiley.com/doi/10.1002/bse.70384
N2  - This study illustrates how organizations reconcile their information processing capabilities with uncertainty within the supply chain (SC) through generative artificial intelligence (GAI) to achieve carbon performance (CP). A quantitative research methodology is applied, and 155 responses from manufacturing firms are analyzed through structural equation modeling (SEM) for hypothesis testing. The findings suggest that GAI for process automation and cognitive engagement has a positive influence on business intelligence (BI), whereas end-of-life (EOL) product management mediates the relationship between green product innovation (GPI) and CP. This study contributes to the SC context, focusing on GAI and BI in mitigating uncertainties within SCs to foster GPI and improve CP. This study highlights actionable frameworks for leveraging digital technologies in sustainable SCs by addressing technological challenges and integrating green innovation practices.
ER  -

SHARIQ, Syed Muhammad; Roman ŠPERKA; Saqib SHAMIM and Hassan ALI. Leveraging Generative Artificial Intelligence to Enhance Carbon Performance in Supply Chains Through Green Product Innovation and End-of-Life Product Management: AI-Driven Carbon Performance. \textit{BUSINESS STRATEGY AND THE ENVIRONMENT}. New Jersey: WILEY, 2025, vol.~2025, December, p.~1-17. ISSN~0964-4733. Available from: https://doi.org/10.1002/bse.70384.

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