scholarly journals Modeling and data analytics in manufacturing and supply chain operations

2021 ◽  
Author(s):  
Weiwei Chen ◽  
Siyang Gao ◽  
Michael Pinedo ◽  
Lixin Tang
Keyword(s):  
Supply Chain ◽  
Data Analytics

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.

An examination of the importance of big data analytics in supply chain agility development

2018 ◽  
Vol 41 (10) ◽  
pp. 1201-1219 ◽  
Author(s):  
Santanu Mandal
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Technology Management ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Technical Knowledge ◽  
Content Type ◽  
Relational Knowledge ◽  
Management Knowledge ◽  
Business Knowledge

Purpose This paper aims to investigate the influence of big data analytics (BDA) personnel expertise capabilities in the development of supply chain (SC) agility. Based on extant literature, the study explores the role of BDA technical knowledge, BDA technology management knowledge, BDA business knowledge and BDA relational knowledge in SC agility development. Furthermore, the author also explores the inter-relationships among these four BDA personnel expertise capabilities. Design/methodology/approach An expert team consisting of IT practitioners (with a minimum experience of five years) were chosen to comment and modify the established scale items of the constructs used in the study. Subsequently, the measures were further pre-tested with 61 students specializing in computer science and information technology. The final survey was mailed to 651 IT professionals with a minimum experience of five years or more in an allied field. Repeated follow-ups and reminders resulted in 176 completed responses. The responses were analysed using partial least squares in SmartPLS 2.0.M3. Findings Findings suggested that BDA technology management knowledge, BDA business knowledge and BDA relational knowledge are prominent enablers of SC agility. Furthermore, BDA technology management knowledge is an essential precursor of BDA technical knowledge and BDA business knowledge. Originality/value The study is the foremost in addressing the importance of BDA personnel expertise capabilities in the development of SC agility. Furthermore, it is also the foremost in exploring the inter-relationships among the BDA personnel expertise capabilities.

Optimal supply chain performance

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Keyword(s):  
Supply Chain ◽  
Data Analytics ◽  
Business Performance ◽  
Design Methodology ◽  
Dynamic Capabilities ◽  
Internal Dynamic ◽  
Content Type ◽  
Combining Data ◽  
Pertinent Information ◽  
Practical Implications

Purpose This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies. Design/methodology/approach This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context. Findings Companies can enhance their supply chain by combining data analytics and the digitization of activities. Manager focus on internal dynamic capabilities and effectiveness of data acquisition and utilization increases the possibility of improved operational and business performance. Originality/value The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

Causality seafood processing circular supply chain capabilities in qualitative data analytics

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ming-Lang Tseng ◽  
Thi Phuong Thuy Tran ◽  
Kuo-Jui Wu ◽  
Bing Xue ◽  
Xiaobo Chen
Keyword(s):  
Supply Chain ◽  
Hierarchical Structure ◽  
Data Analytics ◽  
Qualitative Data ◽  
Action Planning ◽  
Management Control ◽  
Content Type ◽  
Fuzzy Delphi ◽  
Seafood Processing ◽  
Circular Design

PurposeThis study establishes a set of seafood processing circular supply chain capabilities (CSCCs) in Vietnam using qualitative data analytics. This study specifies the interrelationships and hierarchical structure comprising six aspects and 24 criteria for the seafood processing circular supply chain in Vietnam.Design/methodology/approachFuzzy Delphi method is used to confirm the validity. Fuzzy set theory is used to deal with the complexity and uncertainties from the qualitative information. The decision-making trial and evaluation laboratory method is used to examine the interrelationships among attributes. The analytical network process segregates (or displays) the capabilities in a hierarchical structure.FindingsThe results show that management control and technological capability dominate in circular design, circular sourcing, circular production and resource recovery. In practices, the strategic planning, action planning, information technology and technological facilities are important to seafood processing industry.Originality/valueThe CSCCs are pivotal in establishing a concrete foundation for the execution of circular supply chain management, with the aim of optimizing resource utilization and eliminating waste; however, prior studies have lacked a focus on the capability associated interrelationships and hierarchical structure in qualitative data analytics.

Adoption of Big Data Analytics in Supply Chain Management

2021 ◽  
Vol 14 (2) ◽  
pp. 88-107
Author(s):  
Amin Khalil Alsadi ◽  
Thamir Hamad Alaskar ◽  
Karim Mezghani
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Top Management ◽  
Management Support ◽  
Chain Management ◽  
Top Management Support ◽  
Intention To Adopt

Supported by the literature on big data, supply chain management (SCM), and resource-based theory (RBT), this study aims to evaluate the organizational variables that influence the intention of Saudi SCM professionals to adopt big data analytics (BDA) in SCM. A survey of 220 supply chain respondents revealed that both top management support and data-driven culture have a high significant influence on their intention to adopt BDA. However, the firm entrepreneurial orientation showed no significant effect. Also, the findings revealed that supply chain connectivity positively moderates the link between top management support and intention. This study contributes to the practical field, offering valuable insights for decision makers considering BDA adoption in SCM. It also contributes to the literature by helping minimize the research gap in BDA adoption in the Saudi context.

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