How the Use of Big Data Analytics Affects Value Creation in Supply Chain Management

Chen, Daniel Q.; Preston, David; Swink, Morgan

doi:10.1080/07421222.2015.1138364

Cited by 578 publications

(706 citation statements)

References 72 publications

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“…They should analyze their advantages, then focus on the field that would bring the maximum value to them [6,28], and by combining big data techniques and handling the dynamic information outside and inside of them, optimize allocation of resources to promote their competitive edge [27]. Moreover, Manyika et al recommend manufacturing corporations to make different strategies in diverse staged market.…”

Section: Taskmentioning

confidence: 99%

“…1. Integrating and analyzing the demand data, inventory data and market data to make more valid decision in the highly unstable marketing environment [27]. 2.…”

Section: Technologymentioning

confidence: 99%

“…Optimizing production planning or obtain new business opportunities [26] Optimizing service or division of customers [3] Reducing the cost and flaws of product, or optimizing product design [3] Marketing management Optimizing after-sales service [3] Human resource management Improving the accuracy of online recruitment [27] Challenges Technology Data management Cannot apply and manage data effectively [28] Data technology…”

Section: Environmentmentioning

confidence: 99%

“…In summary, enterprises could apply the big data and relevant techniques to gain market insight, guarantee the variation of demand [26], and change the operating strategy and business models to optimize the abilities of marketing, production, service and human resource [27]. But meanwhile, in the context of big data, many domains of enterprises are faced with a large number of challenges because of the features of big data, such as big size, multiple types, timeliness, uncertainty and so on.…”

Section: The Opportunities In the Big Data Eramentioning

confidence: 99%

“…1. Using data about the market, they can comprehend the highly unstable market environment, get more accurate information of market demand, and then optimize allocation of resources and adjust production plans [27], or create new business opportunities [26]. 2.…”

Section: The Opportunities In the Big Data Eramentioning

confidence: 99%

See 4 more Smart Citations

Influence of Big Data on Manufacturing Industry and Strategies of Enterprises: A Literature Review

Zhao

Yang

2017

MATEC Web Conf.

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Abstract. Along with the rapid development of information technologies, such as cloud computing, mobile internet and internet of things, and the promotion of IT application, all kinds of data are generated and accumulated rapidly in various ways, big data era is coming, in which enterprises are faced with both opportunities and unprecedented challenges. Various processes, from decision making to operation and from designing to marketing, are being influenced by big data in manufacturing industry. This paper, according to the nature and features of big data, analyzes and extends a classical model of organizational change, Leavitt's model of organizational change, in order to explore the ways for enterprises to cope with challenges and seize chances of development in big data era. Then, using the extended Leavitt's model, opportunities and challenges derive from big data are combed, and approaches to making use of big data and coping with big data are generalized from five perspectives, including task, structure, people, technology and environment.

show abstract

Section: Taskmentioning

confidence: 99%

“…1. Integrating and analyzing the demand data, inventory data and market data to make more valid decision in the highly unstable marketing environment [27]. 2.…”

Section: Technologymentioning

confidence: 99%

Section: Environmentmentioning

confidence: 99%

Section: The Opportunities In the Big Data Eramentioning

confidence: 99%

Section: The Opportunities In the Big Data Eramentioning

confidence: 99%

See 3 more Smart Citations

Influence of Big Data on Manufacturing Industry and Strategies of Enterprises: A Literature Review

Zhao

Yang

2017

MATEC Web Conf.

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Navigating circular economy: Unleashing the potential of political and supply chain analytics skills among top supply chain executives for environmental orientation, regenerative supply chain practices, and supply chain viability

Bag

Rahman

2023

Bus Strat Env

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In a changing business environment, firms encounter significant challenges to fulfill sustainable development goals. However, firms can make substantial progress by adopting regenerative approaches grounded in circular economy principles, enabling them to effectively pursue sustainable development objectives such as responsible production and consumption (goal 12), climate action (goal 13), and the preservation of life on land (goal 15). However, there is a scarcity of research studies that offer guidance to top supply chain (SC) executives, aiming to enhance their environmental focus and enhance the SC viability through regenerative SC practices. This study employed the philosophical perspective of the natural resource‐based view. Advancing the SC literature, it tested a theoretical model to investigate the relationship between the political skills and SC analytics skills of top SC executives and the environmental orientation of SCs. Additionally, it examined the direct and indirect (via regenerative SC) relationships between a firm's environmental orientation and SC viability. This study also tested the moderating role of a firm's artificial intelligence‐driven big data analytics culture in these relationships. Applying a mixed‐methods approach, the study derived a theoretical model to link the aforementioned constructs. Apart from a qualitative investigation, data were also collected through a questionnaire‐based survey from 375 samples. The results indicated that the relationship between the political skills and SC analytics skills of top SC executives toward the environmental orientation of SCs is significant. Furthermore, they indicated that a firm's environmental orientation is positively related to a regenerative SC, which in turn enhances SC viability. The findings also provided evidence that a firm's AI‐driven big data analytics culture enhances the strength of these relationships. The current study extends the knowledge base by integrating the two unique concepts of digitalization and circular economy.

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The role of interorganizational collaboration and digital technologies in the implementation of circular economy practices—Empirical evidence from manufacturing firms

Schöggl,

Stumpf,

Baumgartner

2023

Bus Strat Env

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Interorganizational collaboration and the use of new digital technologies, such as artificial intelligence (AI), big data analytics, internet of things (IoT), or blockchain technology, are regarded as key enablers in implementing sustainability and circular economy‐oriented practices. While this is reflected in a few conceptual and case studies, statistical analyses on the topic are rare. No study so far has focused on collaboration, and digital technologies have only been studied in isolation. Therefore, the purpose of this study is to investigate the effect of interorganizational collaboration practices on a firm's circular economy practices and on outcomes (sustainability performance and economic performance), as well as the potentially facilitative role of new digital technologies on both. The research is based on a deductive approach, using a random sample of 112 Austrian manufacturing companies. The study employs partial least squares structural equation modeling (PLS‐SEM), features a multiple‐respondent design, and uses the dynamic capabilities view as a theoretical foundation. The study finds that interorganizational collaboration practices have a strong positive effect on the implementation of sustainability and CE practices, while the use of new digital technologies and general dynamic capabilities do not. The use of digital technologies positively affects only interorganizational collaboration, while general dynamic capabilities serve as an antecedent for both the use of digital technologies and interorganizational collaboration. Regarding the outcomes of CE implementation, the study finds a positive impact on firm‐level sustainability and economic performance. From a theoretical point of view, the study provides a new perspective on the prerequisites for successful CE implementation, highlights the importance of collaboration, and contextualizes the role of new digital technologies and dynamic capabilities. From a practical point of view, based on the positive outcomes found, the study supports arguments in favor of company engagement in CE activity. It also serves to motivate purposive digitization and systems thinking in order to create efficient CE collaboration networks.

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How the Use of Big Data Analytics Affects Value Creation in Supply Chain Management

Cited by 578 publications

References 72 publications

Influence of Big Data on Manufacturing Industry and Strategies of Enterprises: A Literature Review

Influence of Big Data on Manufacturing Industry and Strategies of Enterprises: A Literature Review

Navigating circular economy: Unleashing the potential of political and supply chain analytics skills among top supply chain executives for environmental orientation, regenerative supply chain practices, and supply chain viability

The role of interorganizational collaboration and digital technologies in the implementation of circular economy practices—Empirical evidence from manufacturing firms

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