Adoption of Big Data Analytics in Supply Chain Management

Alsadi, Amin K.; Alaskar, Thamir Hamad; Mezghani, Karim

doi:10.4018/ijisscm.2021040105

Cited by 17 publications

(13 citation statements)

References 54 publications

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“…Indeed, Big Data analytics provide new and different insights on improving the performance of supply chains [51][52][53][54]. Specifically, big data analytics can be used to improve decision-making and solve various problems that may arise in supply chain channels [55] as well as improve supply chain performance, because the supply chain is highly dependent on information [56].…”

Section: Introductionmentioning

confidence: 99%

Green Intellectual Capital and Green Supply Chain Performance: Does Big Data Analytics Capabilities Matter?

Al-Khatib¹,

Shuhaiber

2022

Sustainability

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In light of global environmental concerns growing, environmental awareness within firms has become more important than before, and many scholars and researchers have argued the importance of environmental management in promoting sustainable organizational performance, especially in the context of supply chains. Thus, the current study aimed at identifying the impact of the components of green intellectual capital (green human capital, green structural capital, green relational capital) on green supply chain performance in the manufacturing sector in Jordan, as well as identifying the moderating role of big data analytics capabilities. To achieve this aim, we developed a conceptual model of Structural Equation Modelling-Partial Least squares and tested through the Smart-PLS software on a sample of 438 respondents. Empirical results showed that each of the components of green intellectual capital and big data analytics explains 71.1% of the variance in green supply chain performance and that all components of green intellectual capital have a statistically significant impact on green supply chain performance. The results also revealed that the relationship between green relational capital and green supply chain performance is moderated through big data analytics capabilities. Finally, this study made a theoretical and managerial implications to the supply chain literature and industry.

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Section: Introductionmentioning

confidence: 99%

Green Intellectual Capital and Green Supply Chain Performance: Does Big Data Analytics Capabilities Matter?

Al-Khatib¹,

Shuhaiber

2022

Sustainability

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“…Alidrisi (2021) from Saudi Arabia proposed a BDA platform for determination of the effect of green supply chain management (GSCM) in the adoption of SCF. Alsadi et al (2021) from Saudi Arabia assessed the organizational factors which are important for the implementation of BDA in supply chain management (SCM). A theoretical model was developed by Shokouhyar et al (2020) in Iran for comprehending the effect of BDA on SSC.…”

Section: A Brief Description Of Bda-sscm Studiesmentioning

confidence: 99%

An exploration into the factors influencing the implementation of big data analytics in sustainable supply chain management

Tambuskar¹,

Jain²,

Narwane

2023

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PurposeWith big data (BD), traditional supply chain is shifting to digital supply chain. This study aims to address the issues and challenges in the way toward the implementation of big data analytics (BDA) in sustainable supply chain management (SSCM).Design/methodology/approachThe factors that affect the implementation of BDA in SSCM are identified through a widespread literature review. The PESTEL framework is used for this purpose as it covers all the political, economic, social, technological, environmental and legal factors. These factors are then finalized by means of experts' opinion and analyzed using structural equation modeling (SEM).FindingsA total of 10 factors are finalized with 31 sub-factors, of which sustainable performance, competitive advantage, stakeholders' involvement and capabilities, lean and green practices and improvement in environmental performance are found to be the critical factors for the implementation of BDA in SSCM.Research limitations/implicationsThis research has taken up the case of Indian manufacturing industry. It can be diversified to other geographical areas and industry sectors. Further, the quantitative analysis may be undertaken with structured or semi-structured interviews for validation of the proposed model.Practical implicationsThis research provides an insight to managers regarding the implementation of BDA in SSCM by identifying and examining the influencing factors. The results may be useful for managers for the implementation of BDA and budget allocation for BDA project.Social implicationsThe result includes green practices and environmental performance as critical factors for the implementation of BDA in SSCM. Thus the research establishes a positive relationship between BDA and sustainable manufacturing that ultimately benefits the environment and society.Originality/valueThis research addresses the challenges in the implementation of BDA in SSCM in Indian manufacturing sector, where such application is at its nascent stage. The use of PESTEL framework for identifying and categorizing the factors makes the study more worthwhile, as it covers full spectrum of the various factors that affect the strategic business decisions.

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“…The TOE framework is, also, considered a solid theoretical basis and a well-defined analytical framework, backed with strong empirical basis to study the phenomena of technology adoption [ 20 , 22 ]. As a result, this framework has been widely adopted in previous empirical studies, either as the sole framework or combined with other theories, to identify the critical drivers of the adoption and assimilation of various types of technological innovations, such as e-business [ 66 , 71 ], RFID [ 47 , 103 ], ERP [ 16 , 95 ], cloud computing [ 32 , 56 ], BDA [ 10 , 51 ] and mobile commerce [ 11 , 76 , 79 ].…”

Section: Theoretical Background Research Model and Hypothesis Develop...mentioning

confidence: 99%

“…Top management support involves top managers’ level of awareness, commitment, and engagement toward introducing technological innovation (e.g., m-commerce) [ 33 , 46 , 77 , 98 ]. This support is expressed in the mission of the business, the willingness to take risks and the establishment of a supportive organizational environment for the technological adoption [ 10 , 22 ].…”

Section: Theoretical Background Research Model and Hypothesis Develop...mentioning

confidence: 99%

Drivers of mobile commerce adoption intention by Saudi SMEs during the COVID-19 pandemic

Alaskar

Alsadi

2023

Futur Bus J

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Grounded in the technology-organization-environment framework, this paper investigates critical drivers of mobile commerce (m-commerce) adoption intention by SMEs in Saudi Arabia, a developing country in transition, during the COVID-19 pandemic. A quantitative approach was adopted in this study for data collection and analysis. A proposed research model was tested and validated using PLS-SEM on data collected using a structured questionnaire from a sample of 171 Saudi SMEs located in the capital city of Riyadh. The findings reveal that top management support, environmental uncertainty and perceived benefits are the critical drivers of m-commerce adoption intention. However, perceived costs do not influence firms’ intentions to adopt m-commerce. This study contributes to a better understanding of m-commerce adoption intention in developing countries, particularly in Saudi Arabia. Both theoretical and practical implications of interest can be derived from this study.

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Adoption of Big Data Analytics in Supply Chain Management

Cited by 17 publications

References 54 publications

Green Intellectual Capital and Green Supply Chain Performance: Does Big Data Analytics Capabilities Matter?

Green Intellectual Capital and Green Supply Chain Performance: Does Big Data Analytics Capabilities Matter?

An exploration into the factors influencing the implementation of big data analytics in sustainable supply chain management

Drivers of mobile commerce adoption intention by Saudi SMEs during the COVID-19 pandemic

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