Big data in operations and supply chain management: current trends and future perspectives

Lamba, Kuldeep; Singh, SP

doi:10.1080/09537287.2017.1336787

Cited by 161 publications

(114 citation statements)

References 46 publications

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“…Also it works as a practical decision support means for examining competing decision alternatives along the chain as well as environmental assessment. Lamba and Singh [50] focused on decision making aspect of supply chain process and mentioned that data-driven decision-making is gaining noteworthy importance in managing logistics activities, process improvement, cost optimization, and better inventory management. Sahal et al [67] and Xu and Duan [80] showed the relation of cyber physical systems and stream processing platform for Industry 4.0.…”

Section: Literature Reviewmentioning

confidence: 99%

Current landscape and influence of big data on finance

2020

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In the age of technological innovation, various types of data are available with the advance of information technologies, and data is seen as one of the most valuable commodities in managing automation systems [13, 68]. In this sense, financial markets and technological evolution have become related to every human activity in the past few decades. Big data technology has become an integral part of the financial services industry and will continue to drive future innovation [12]. Financial innovations are also considered the fastest emerging issues in financial services. More specifically, they cover a variety of financial businesses such as online peer-to-peer lending, crowd-funding platforms, SME finance, wealth management and asset management platforms, trading management, crypto-currency, money/remittance transfer, mobile payments platforms, and so on. All of these services create thousands of pieces of data every day. Therefore,

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Section: Literature Reviewmentioning

confidence: 99%

Current landscape and influence of big data on finance

2020

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“…Rajesh (2016) presents a prediction model to forecast supply chain resilience performance and to test it. For an extensive literature review, see (Lamba and Singh 2017). Tan et al (2015) propose an analytic infrastructure to assist firms to capture the potential of supply chain innovation afforded by data.…”

Section: Analytics and Data Managementmentioning

confidence: 99%

“…With the highest values on in-degree (12) and betweenness centrality (3108), the article from Hazen et al (2014) contributes to the data quality problem within the supply chain management context. Lamba and Singh (2017) see a lack of data analytics techniques and works which can suggest the practical implementation of BD. For future research, it is suggested one consult, for example, Sivarajah et al (2017).…”

Section: Analytics and Data Managementmentioning

confidence: 99%

Research streams on digital transformation from a holistic business perspective: a systematic literature review and citation network analysis

et al. 2019

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Digital transformation (DT) has become a buzzword, triggering different disciplines in research and influencing practice, which leads to independent research streams. Scholars investigate the antecedents, contingencies, and consequences of these disruptive technologies by examining the use of single technologies or of digitization, in general. Approaches are often very specialized and restricted to their domains. Thus, the immense breadth of technologies and their possible applications conditions a fragmentation of research, impeding a holistic view. With this systematic literature review, we aim to fill this gap in providing an overview of the different disciplines of DT research from a holistic business perspective. We identified the major research streams and clustered them with co-citation network analysis in nine main areas. Our research shows the main fields of interest in digital transformation research, overlaps of the research areas and fields that are still underrepresented. Within the business research areas, we identified three dominant areas in literature: finance, marketing, and innovation management. However, research streams also arise in terms of single branches like manufacturing or tourism. This study highlights these diverse research streams with the aim of deepening the understanding of digital transformation in research. Yet, research on DT still lacks in the areas of accounting, human resource management, and sustainability. The findings were distilled into a framework of the nine main areas for assisting the implications on potential research gaps on DT from a business perspective.

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“…Big data sources may be harnessed for predictive analytics (Ilie-Zudor et al, 2015;Waller and Fawcett, 2013) to provide insights for a number of supply chain management challenges including predictive facility layout optimisation, identification of qualitative and quantitative criteria related to suppliers and preferred supplier and carrier selection (Lamba and Singh, 2017).…”

Section: Big Data In Business Operations and Logisticsmentioning

confidence: 99%

Creation of unstructured big data from customer service

Bhattacharjya

Ellison

Pang

et al. 2018

IJLM

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Purpose-Customer service provision is a growing phenomenon on social media and parcel shipping companies have been among the most prominent adopters. This has coincided with greater interest in the development of analysis techniques for unstructured big data from social media platforms, such as the micro-blogging platform, Twitter. Given the growing use of dedicated customer service accounts on Twitter, this paper investigates the effectiveness with which parcel shipping companies use the platform. Design/methodology/approach-This paper demonstrates the use of a combination of tools for retrieving, processing and analysing large volumes of customer service related conversations generated between parcel shipping companies and their customers in Australia, United Kingdom and the United States. Extant studies using data from Twitter tend to focus on the contributions of individual entities and are unable to capture the insights provided by a holistic examination of the interactions. Findings-This study identifies the key issues that trigger customer contact with parcel shipping companies on Twitter. It identifies similarities and differences in the approaches that these companies bring to customer engagement and identifies opportunities for using the medium more effectively. Originality/value-The development of consumer-centric supply chains and relevant theories require researchers and practitioners to have the ability to include insights from growing quantities of unstructured data gathered from consumer engagement. This study makes a methodological contribution by demonstrating the use of a set of tools to gather insight from a large volume of conversations on a social media platform.

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Big data in operations and supply chain management: current trends and future perspectives

Cited by 161 publications

References 46 publications

Current landscape and influence of big data on finance

Current landscape and influence of big data on finance

Research streams on digital transformation from a holistic business perspective: a systematic literature review and citation network analysis

Creation of unstructured big data from customer service

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