Toward sustainability: using big data to explore the decisive attributes of supply chain risks and uncertainties

Wu, Kuo‐Jui; Liao, Ching‐Jong; Tseng, Ming‐Lang; Lim, Ming K.; Hu, Jiayao; Tan, Kim Hua

doi:10.1016/j.jclepro.2016.04.040

Cited by 191 publications

(103 citation statements)

References 70 publications

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“…It has emerged as both a strategic and operational tool that may bring fundamental changes to supply chain sustainability and innovation [21]- [24]. Big data and predictive analytics are one of the fastest evolving fields due to the convergence of Internet of Things (IoT), cloud computing, and fast-cycling mobile devices [25].…”

Section: Cutting Edge Technologies: Big Data and Predictive Analyticsmentioning

confidence: 99%

Effects of Dynamic Capabilities on Frugal Innovation: A Conceptual Framework for Sustainable Supply Chain Application

Rodríguez¹,

Cunha²

2018

dtetr

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Recently, supply chain operations have been influenced by three concepts such as sustainable supply chain, dynamic capabilities, and disruptive innovation. First, sustainability has become a necessary goal for businesses and a powerful strategy for competitive advantage. Sustainable innovations along the supply chain are increasingly important regarding firm competitiveness to respond to rapid changes in the market. Secondly, disruptive innovations are particularly adopted by firms, because they aim to provide product or process to a new set of customers (or customers with new sets of requirements). Big data and predictive analytics are one of them and may have the ability to generate considerably more business and social value while significantly reducing the use of scarce resources. This disruptive innovation could improve the ability to help with the sustainability of sourcing decisions, and reduce environmental footprint are increasingly recognized. Thirdly, developing dynamic capabilities such as absorptive capacity both in firms and in supply chains are also integral to responding to dynamic markets and customer needs. Dynamic capabilities are collective resources (financial and technical assets coordinated with knowledge and competencies) which are essentially change-oriented, helping firms redeploy and reconfigure. Any innovation (whether process or product oriented) must then rely on such capabilities. The main objective of this paper is to develop a conceptual framework through a literature review, to identify the features of disruptive innovations applied to the sustainable supply chain, and to analyze the role of dynamic capabilities. We will focus on how certain dynamic capabilities such as absorptive capacity affect the impact of the utilization of big data analytics on sustainable supply chain on frugal processes, which has not been investigated in depth.

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Section: Cutting Edge Technologies: Big Data and Predictive Analyticsmentioning

confidence: 99%

Effects of Dynamic Capabilities on Frugal Innovation: A Conceptual Framework for Sustainable Supply Chain Application

Rodríguez¹,

Cunha²

2018

dtetr

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“…Wu [19] proposed using the fuzzy and grey Delphi methods to identify a set of reliable attributes and, based on these attributes, transforming big data to a manageable scale to consider their impacts. Meinshausen et al [11] demonstrated linear model and Gaussian model of variable selection consistency in higher dimensional case.…”

Section: Literature Reviewmentioning

confidence: 99%

Attribute Selection Method based on Objective Data and Subjective Preferences in MCDM

Ma¹,

Yi²,

Qu³

et al. 2018

INT J COMPUT COMMUN

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Decision attributes are important parameters when choosing an alternative in a multiple criteria decision-making (MCDM) problem. In order to select the optimal set of decision attributes, an analysis framework is proposed to illustrate the attribute selection problem. Then a two-step attribute selection procedure is presented based on the framework: In the first step, attributes are filtered by using correlation algorithm. In the second step, a multi-objective optimization model is constructed to screen attributes from the results of the first step. Finally, a case study is given to illustrate and verify this method. The advantage of this method is that both external attribute data and subjective decision preferences are utilized in a sequential procedure. It enhances the reliability of decision attributes and matches the actual decision-making scenarios better.

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“…Wu et al [124] implemented fuzzy DEMATEL to identify the factors that affected an automobile company's green supply chain performance. In order to assess supply chain risks and uncertainties towards sustainability in an electronics supply chain, Wu et al [126] employed a novel method based on big data analysis, fuzzy DEMATEL and grey DEMATEL techniques. With regards to this, they identified a set of attributes over fuzzy Delphi and grey Delphi techniques and transformed big data to a manageable scale in order to examine their impacts.…”

Section: Fuzzy Dematelmentioning

confidence: 99%

Environmentally Concerned Logistics Operations in Fuzzy Environment: A Literature Survey

et al. 2017

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Abstract:Growing environmental awareness coupled with stricter governmental regulations has fueled the need for integrating sustainability into supply chain and logistics activities. Accordingly, recent studies in the literature have emphasized the significance of environmentally concerned logistics operations (ECLO). Research in the broad area of ECLO encompasses a wide range of topics including sustainable supply chain, green supply chain, closed-loop supply chain, low-carbon logistics, and waste management. In this paper, a comprehensive content analysis and area review is presented. Over 800 papers published between 1994 and 2017 in peer-reviewed journals, proceedings, and book chapters are utilized. These papers are analyzed in consecutive stages after being reviewed under a structural dimension process that addresses the fields of environmentally concerned logistics operations. Following the state-of-the-art review, a detailed analysis of ECLO research with a special emphasis on fuzzy applications is provided. The findings clearly indicate that the fuzzy multi-criteria decision making technique is a frequently used hybrid method, whereas fuzzy sets theory and other fuzzy hybrid techniques identify a gap in the related literature. This paper provides further critical analysis and other research suggestions in order to clarify these gaps and offer additional research perspectives. This information may provide extensive data that will enable future researchers to fill these gaps within this field.

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Toward sustainability: using big data to explore the decisive attributes of supply chain risks and uncertainties

Cited by 191 publications

References 70 publications

Effects of Dynamic Capabilities on Frugal Innovation: A Conceptual Framework for Sustainable Supply Chain Application

Effects of Dynamic Capabilities on Frugal Innovation: A Conceptual Framework for Sustainable Supply Chain Application

Attribute Selection Method based on Objective Data and Subjective Preferences in MCDM

Environmentally Concerned Logistics Operations in Fuzzy Environment: A Literature Survey

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