Reviewing the applications of artificial intelligence in sustainable supply chains: Exploring research propositions for future directions

Naz, Farheen; Agrawal, Rohit; Gunasekaran, Angappa; Majumdar, Abhijit; Luthra, Sunil

doi:10.1002/bse.3034

Cited by 57 publications

(16 citation statements)

References 136 publications

(179 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Also, these organizational capabilities that exploit big data can exploit the available external resources that can attract opportunities for environmental cooperation among all stakeholders such as suppliers and major customers (Sharma et al, 2022). Big data can also be used to restructure supply and demand more accurately, improving the efficiency of the transportation process (Lee, 2017;Seyedan and Mafakheri, 2020;Wang et al, 2016;Zhong et al, 2017) leading to a reduction in the use of compounds that use substances harmful to the environment (Naz et al, 2022). The advanced predictive tools provided by big data analytics can explore the sources of potential risks concerning the environmental aspect and thus these tools can work to discover these sources before falling into any potential problems or disasters in the future that could lead to the destruction or failure of green supply chains (Papadopoulos et al, 2017).…”

Section: Theoretical Framework and Hypotheses Developmentmentioning

confidence: 99%

See 1 more Smart Citation

Big data analytics capabilities and green supply chain performance: investigating the moderated mediation model for green innovation and technological intensity

Al-Khatib¹

2022

BPMJ

View full text Add to dashboard Cite

PurposeThis study investigates the impact of big data analytics capabilities on green supply chain performance. Moreover, it assesses the mediating effect of the green innovation and moderating effect of technological intensity.Design/methodology/approachThis study is based on primary data that were collected from the food and beverages manufacturing sector operating in Jordan. A total of 420 samples were used for the final data analysis. Data analysis was performed via structural equation modeling (SEM) using SmartPLS 3.3.9.FindingsThe results of the data analysis supported a positive relationship between big data analytics capabilities and the green supply chain performance as well as a mediating effect of green innovation. It was confirmed that technological intensity moderated the relationship of green innovation on green supply chain performance.Research limitations/implicationsThe study faced many limitations such as the method of collecting primary data, which relied on a questionnaire only and the use of cross-sectional data, as well as studying one context and in one country.Practical implicationsThe findings can guide managers and policymakers in the Jordanian food and beverage manufacturing sector on how to manage organizational capabilities related to big data analytics to enhance green supply chain performance and improve green innovation in these firms.Originality/valueThis study developed a theoretical and empirical model to investigate the relationship between big data analytics capabilities, green innovation, technological intensity and green supply chain performance. This study offers new theoretical and managerial contributions that add value to the supply chain management and innovation literature by testing the moderated mediation model of these constructs in the food and beverages manufacturing sector in Jordan.

show abstract

Section: Theoretical Framework and Hypotheses Developmentmentioning

confidence: 99%

“…, 2016; Zhong et al. , 2017) leading to a reduction in the use of compounds that use substances harmful to the environment (Naz et al. , 2022).…”

Section: Theoretical Framework and Hypotheses Developmentmentioning

confidence: 99%

Big data analytics capabilities and green supply chain performance: investigating the moderated mediation model for green innovation and technological intensity

Al-Khatib¹

2022

BPMJ

View full text Add to dashboard Cite

show abstract

“…The keyword statistics were developed to examine the most popular keywords in the headings of articles and the keyword section to comprehend the key conceptual trend established by current research (Agrawal et al, 2022). The cluster-based network of keywords developed using VOS viewer is shown in Fig.…”

Section: Abstracttatisticsmentioning

confidence: 99%

“…The bibliometric analysis aids in gaining a complete grasp of a research area and identifying prominent scholars and fresh areas for future research. A bibliometric analysis aids in the analysis of statistics for publications published in a speci c eld (Agrawal et al, 2022). A bibliometric technique, according to scholars, is a cross-disciplinary way for effectively mapping the directions and issues addressed during the growth of a eld of study (Tandon et al, 2021).…”

Section: Bibliometric Analysismentioning

confidence: 99%

Blockchain Technology for Sustainable Supply Chains: A Network Cluster Analysis for Future Research Propositions

Yadav

Luthra

Garg

2023

Preprint

Self Cite

View full text Add to dashboard Cite

Achieving the sustainable goals of the United Nations requires improving supply chain sustainability. BlockChain Technology (BCT) has attracted attention on a global level with the ability to transform supply chain management and sustainability efforts. Recognizing this, this study investigates how BCT plays a role in a Sustainable Supply Chain (SSC). The current study looks into the importance of BCT in order to move supply networks toward sustainability by performing bibliometric analysis, and network cluster analysis. Through the literature review, the current literature was analyzed and future research directions were concluded. We begin our study by selecting 297 papers on the relevant subject by applying various filters to the Web of Science (WoS) database. Influential individuals, journals, and organizations in this field were identified using bibliometric analysis. A network analysis was performed to identify influential co-author, and keywords, and for page rank, and cluster analysis. The network analysis revealed ten distinct study clusters, and ten propositions were suggested from the analysis of these clusters. Additionally, a conceptual framework for the research was proposed can advise managers, practitioners, and, researcher communities on the key trends and topics. Further, to guide research scholars in this field, thirty-three future research directions were suggested.

show abstract

“…Film and television production theory is a theoretical set of montage, lens combination, material editing, and other theories as stated by Naz [11]. Its solution set is the best combination of various film and television production theories, which has the characteristics of sparsity and integration and can be used for nonlinear analysis of film and television works.…”

Section: Film and Television Production Eorymentioning

confidence: 99%

Study Film and Television Postproduction and Innovation Strategy Based on an Artificial Intelligence Algorithm

Han

Shen

2022

Mobile Information Systems

View full text Add to dashboard Cite

In the process of choosing the best scheme in the artificial intelligence algorithm, it is impossible to accurately judge the nonlinear relationship between the innovation strategy and the film and television postproduction scheme. An improved artificial intelligence algorithm based on the integration of dynamic factors and the artificial intelligence algorithm is proposed to reduce the disturbance ability of the artificial intelligence algorithm and improve the analysis level of film and television postproduction and innovation strategy. Firstly, the initial innovation strategy set of the production set is established by using dynamic factors, which makes it discrete and reduces the influence of the scheme selection error on the results. Then, the production set is divided into dynamic subproduction sets by using the film and television production theory, and each subproduction set seeks its own parallel innovation strategy. Finally, under the guidance of film and television production theory, each subproduction set shares the matching of optimal solutions. Through MATLAB simulation analysis and verification, the improved dynamic artificial intelligence algorithm can improve the accuracy of judging the innovation strategy of film and television works in an uncertain environment and shorten the convergence time of global feature solution and is superior to the original selection method of film and television production strategy. In addition, under that condition the initial weight scheme and the threshold scheme are set. The artificial intelligence algorithm is used to analyze the innovation strategy selection of youth idol works. The results show that under different film and television production requirements, the innovation strategy selection judgment of the artificial intelligence algorithm is accurate and superior to the original film and television production strategy selection method, which further verifies the effectiveness of the artificial intelligence algorithm proposed in this paper.

show abstract

Reviewing the applications of artificial intelligence in sustainable supply chains: Exploring research propositions for future directions

Cited by 57 publications

References 136 publications

Big data analytics capabilities and green supply chain performance: investigating the moderated mediation model for green innovation and technological intensity

Big data analytics capabilities and green supply chain performance: investigating the moderated mediation model for green innovation and technological intensity

Blockchain Technology for Sustainable Supply Chains: A Network Cluster Analysis for Future Research Propositions

Study Film and Television Postproduction and Innovation Strategy Based on an Artificial Intelligence Algorithm

Contact Info

Product

Resources

About