Linkages between big data analytics, circular economy, sustainable supply chain flexibility, and sustainable performance in manufacturing firms

2021 ◽  
pp. 1-15
Author(s):  
T. C. Edwin Cheng ◽  
Sachin S. Kamble ◽  
Amine Belhadi ◽  
Nelson Oly Ndubisi ◽  
Kee-hung Lai ◽  
...  
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Circular Economy ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Manufacturing Firms ◽  
Sustainable Supply Chain ◽  
Chain Flexibility ◽  
Sustainable Performance ◽  
Supply Chain Flexibility

The role of capabilities in shaping sustainable supply chain flexibility and enhancing circular economy-target performance: an empirical study

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Surajit Bag ◽  
Muhammad Sabbir Rahman
Keyword(s):  
Supply Chain ◽  
Circular Economy ◽  
Data Analytics ◽  
Sustainable Supply Chain ◽  
Chain Flexibility ◽  
Content Type ◽  
Mediating Role ◽  
Supply Chain Flexibility ◽  
Target Performance ◽  
Analytics Capability

Purpose A circular economy is a popular approach considered by many firms to address sustainable development goals strategically. Literature indicates that collaborative relationships among supply chain partners facilitate circular economy practices. However, there is a dearth of studies in lower-middle-income countries indicating the unique challenges industries face whilst practising circular economy principles and how the challenges can be overcome. To address the calls of previous researchers, this study aims to explore the following relationships: engagement and alliance capability whilst data analytics capability plays a mediating role; the relationship between alliance and data analytics capability with sustainable supply chain flexibility whilst industry dynamism is considered as a moderating variable and the relationship between sustainable supply chain flexibility and circular economy-target performance. Design/methodology/approach A cross-sectional survey was performed and data was collected from 760 employees of Indian firms. Covariance-based structural equation modelling was applied to perform the path analysis to determine a firm’s capabilities in shaping sustainable supply chain flexibility and enhancing circular economy target performance. Findings Drawing upon dynamic capability theory, it was first established that engagement capability has a positive and significant influence on alliance capability, whilst data analytics capability played a partial mediating role. Second, it was established that alliance capability and data analytics capability significantly affect sustainable supply chain flexibility, whilst industry dynamism played a moderating role. Finally, it was clear that sustainable supply chain flexibility had a significant and positive effect on circular economy target performance, ultimately enhancing sustainability. Originality/value This study advances the circular economy literature by recommending that firms must consider some critical operational level capabilities to develop their dynamic capability, i.e. sustainable supply chain flexibility, to better meet the competitive market conditions in turbulent business environments.

A systematic literature review with bibliometric analysis of big data analytics adoption from period 2014 to 2018

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zeeshan Inamdar ◽  
Rakesh Raut ◽  
Vaibhav S. Narwane ◽  
Bhaskar Gardas ◽  
Balkrishna Narkhede ◽  
...  
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Literature Review ◽  
Bibliometric Analysis ◽  
Systematic Literature Review ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Sustainable Supply Chain ◽  
Content Type ◽  
Future Direction

PurposeThe volume of data being generated by various sectors in recent years has increased exponentially. Consequently, professionals struggle to process essential data in the current competitive world. The purpose of the study is to explore and provide insights into the Big Data Analytics (BDA) studies in different sectors.Design/methodology/approachThis study performs a systematic literature review (SLR) with bibliometric analysis of BDA adoption (BDAA) in the supply chain and its applications in various sectors from 2014 to 2018. This paper focuses on BDAA studies have been carried out across different countries and sectors. Also, the paper explores different tools and techniques used in BDAA studies.FindingsThe benefits of adopting BDA, coupled with a lack of adequate research in the field, have motivated this study. This literature review categorizes paper into seven main areas and found that most of the studies were carried out in manufacturing and service.Practical implicationsThis research insight and observations can provide practitioners and academia with guidance on implementing BDA in different sustainable supply chain sectors. The article indicates a few remarkable gaps in the future direction and trends regarding the integration of BDA and sustainable supply chain development.Originality/valueThe study derives a new categorization of BDA, which investigates how data is generated, organized, captured, interpreted and evaluated to give valuable insights to manage the sustainable supply chain.

scholarly journals Big Data Analytics in Sustainable Supply Chain Management: A Focus on Manufacturing Supply Chains

2021 ◽  
Vol 13 (13) ◽  
pp. 7101
Author(s):  
Joash Mageto
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Supply Chains ◽  
Data Analytics ◽  
Social Issues ◽  
Big Data Analytics ◽  
Sustainable Supply Chain ◽  
Chain Management ◽  
Sustainable Supply Chain Management

Sustainable supply chain management has been an important research issue for the last two decades due to climate change. From a global perspective, the United Nations have introduced sustainable development goals, which point towards sustainability. Manufacturing supply chains are among those that produce harmful effluents into the environment in addition to social issues that impact societies and economies where they operate. New developments in information and communication technologies, especially big data analytics (BDA), can help create new insights that can detect parts and members of a supply chain whose activities are unsustainable and take corrective action. While many studies have addressed sustainable supply chain management (SSCM), studies on the effect of BDA on SSCM in the context of manufacturing supply chains are limited. This conceptual paper applies Toulmin’s argumentation model to review relevant literature and draw conclusions. The study identifies the elements of big data analytics as data processing, analytics, reporting, integration, security and economic. The aspects of sustainable SCM are transparency, sustainability culture, corporate goals and risk management. It is established that BDA enhances SSCM of manufacturing supply chains. Cyberattacks and information technology skills gap are some of the challenges impeding BDA implementation. The paper makes a conceptual and methodological contribution to supply chain management literature by linking big data analytics and SSCM in manufacturing supply chains by using the rarely used Toulmin’s argumentation model in management studies.

Impact of big data analytics capabilities on supply chain sustainability

2020 ◽  
Vol 17 (1) ◽  
pp. 33-57 ◽  
Author(s):  
Sajjad Shokouhyar ◽  
Mohammad Reza Seddigh ◽  
Farhad Panahifar
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Sustainable Supply Chain ◽  
Self Assessment ◽  
Pharmaceutical Supply Chain ◽  
Content Type ◽  
Different Dimensions ◽  
The Relationship

Purpose The purpose of this paper is to develop a theoretical model to explain the impact of big data analytics capabilities (BDAC) on company’s supply chain sustainability (CSCS). The secondary objective of the study is to assess the relationship between different dimensions of supply chain sustainability and companies’ BDAC. Design/methodology/approach This research was carried out by conducting a survey among 234 pharmaceutical companies in Iran (a case study of Iran), using a standard questionnaire of BDAC and United Nations (UN) online self-assessment on supply chain sustainability. However, the respond of managers of 188 companies were usable in this research. Smart PLS3 was used to employ partial least squares method to examine the validity and reliability of the measurement and structural model. Findings The results of this study demonstrate that BDAC have a strong impact on both pharmaceutical supply chain sustainability, and the dimensions including vision, engage and internal. It is found that the relationships between BDAC and the other dimensions of supply chain sustainability including expect, scope and goals are not significant but positive. Research limitations/implications Research on the relationship between BDAC and CSCS, especially in the pharmaceutical supply chain, is scanty, and this gap is highlighted in developing countries and the pharmaceutical supply chain that plays a prominent role in public health. This paper discusses several important barriers to forming a sustainable supply chain and strong BDA capabilities. Practical implications This paper could be a guide to managers and consultants who are involved in big data analytics and sustainable development. Since UN urges companies do the online self-assessment, the results of this paper would be attractive and useful for UN global compact specialists. Originality/value No study has directly measured the relation between BDAC and CSCS and different dimensions of CSCS, using a comprehensive survey throughout all pharmaceutical companies in Iran. Moreover, this research assesses the different dimensions of BDA capabilities and supply chain sustainability. This paper represents the facts about situation of sustainability of pharmaceutical supply chain and BDAC in these companies, and discloses several related issues that are serious barriers to forming a sustainable supply chain and strong BDAC. In addition, this paper provided academic support for UN questionnaire about CSCS and used it in the survey.

Managing supply chain resources with Big Data Analytics: a systematic review

2017 ◽  
Vol 21 (3) ◽  
pp. 177-200 ◽  
Author(s):  
Marcelo Werneck Barbosa ◽  
Alberto de la Calle Vicente ◽  
Marcelo Bronzo Ladeira ◽  
Marcos Paulo Valadares de Oliveira
Keyword(s):  
Systematic Review ◽  
Big Data ◽  
Supply Chain ◽  
Data Analytics ◽  
Big Data Analytics

The role of big data analytics capabilities in bolstering supply chain resilience and firm performance: a dynamic capability view

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohamad Bahrami ◽  
Sajjad Shokouhyar
Keyword(s):  
Risk Management ◽  
Big Data ◽  
Supply Chain ◽  
Firm Performance ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Content Type ◽  
Supply Chain Resilience ◽  
Management Culture

PurposeBig data analytics capability (BDAC) can affect firm performance in several ways. The purpose of this paper is to understand how BDA capabilities affect firm performance through supply chain resilience in the presence of the risk management culture.Design/methodology/approachThe study adopted a cross-sectional approach to collect survey-based responses to examine the hypotheses. 167 responses were collected and analyzed using partial least squares in SmartPLS3. The respondents were generally senior IT executives with education and experience in data and business analytics.FindingsThe results show that BDA capabilities increase supply chain resilience as a mediator by enhancing innovative capabilities and information quality, ultimately leading to improved firm performance. In addition, the relationship between supply chain resilience and firm performance is influenced by risk management culture as a moderator.Originality/valueThe present study contributes to the relevant literature by demonstrating the mediating role of supply chain resilience between the BDA capabilities relationship and firm performance. In this context, some theoretical and managerial implications are proposed and discussed.

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