Identifying the value of data analytics in the context of government supervision: Insights from the customs domain

Rukanova, Boriana; Tan, Yao‐Hua; Slegt, Micha; Molenhuis, Marcel; Rijnsoever, Ben van; Migeotte, Jonathan; Labare, Mathieu L. M.; Plecko, Krunoslav; Çağlayan, Bora; Shorten, Gavin; Meij, Otis van der; Post, Suzanne

doi:10.1016/j.giq.2020.101496

Cited by 23 publications

(20 citation statements)

References 27 publications

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“…From a technological perspective, future solutions feature the growing convergence of several general purpose technologies (Alt, 2021). Among the examples are blockchain technologies that create new distributed infrastructures with automated procedures based on smart contracts (Segers et al, 2019), the use of internet-of-things (IoT) and mobile technologies such as smart containers and drones (Heijmann et al, 2020) as well as the application of various forms of data analytics to automatically detect anomalies and the like (Rukanova et al, 2021). At the same time, the projects have shown that IT is a necessary enabler, but not a sufficient ingredient for successful interorganizational process (re)design.…”

Section: Background Detailsmentioning

confidence: 99%

How to organize for AI? An interview with Yao-Hua Tan

Alt

2021

Electron Markets

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Section: Background Detailsmentioning

confidence: 99%

How to organize for AI? An interview with Yao-Hua Tan

Alt

2021

Electron Markets

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“…price data for specific products) available on eCommerce platforms [see e.g. 15,16,18]. These data analytics approaches aim to obtain additional external (non-customs) data to help customs cross validate customs declarations and identify possible undervaluation of goods.…”

Section: Customs Interactions With Ecommerce Platforms In the Context...mentioning

confidence: 99%

eCommerce Platforms Evaluation Framework for Government

Rukanova

Tan

Ubacht

et al. 2021

Lecture Notes in Computer Science

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The international trade flow of e-commerce goods have reached unprecedented volumes. Ensuring undisrupted flow of cross-border eCommerce goods has become one of the top priorities for customs administrations around the world. Customs has a role in safeguarding public values such as safety and security, revenue collection, and stimulation of the economy. Customs administrations are now looking into innovative ways to be able to fulfil their duties for controlling the trade flows while at the same time not hindering trade. But in a broader sense, other government agencies also have responsibilities for safeguarding public values such as product and consumer safety or sustainability and are currently confronted with these eCommerce flows. While eCommerce is a phenomenon that is widely studied in business literature, it is largely unexplored both in research and practice how governments can understand and engage with these eCommerce developments. In this study we focus on the issue revenue collection related to cross-border eCommerce goods. Empirically, our paper builds on insights from the PROFILE EU project, which focuses on the use of data analytics for customs. Theoretically we build on research on control mechanisms in eCommerce platforms and digital trade infrastructures. We present an eCommerce platforms evaluation framework for customs. The evaluation framework consists of two distinct perspectives (i.e. a data analytics and a partnership perspective) that customs can explore when defining their engagement strategies with eCommerce platforms. We limited our study to the interactions of customs with eCommerce platforms and the issue of revenue collection. Further research can study the safeguarding of a wider range of public values by a range of government organisations to account for effects of the vast growth in international flows of goods via eCommerce platforms, such as monitoring product safety and sustainability effects.

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“…Cai et al [2] specifically discuss the issue of data quality in the era of big data and identify several challenges, namely: (1) difficulty of data integration due to diversity of data sources and complex data structures; (2) the difficulty to judge data quality in a reasonable time due to the tremendous volumes; (3) fast changing time of data which adds requirements for processing time; and (4) lack of unified data quality standard. However, apart from these more technical aspects, research has argued that there is a need for understanding of value of big data and analytics performed on this data [5,6,15].…”

Section: Related Research On Data Quality Big Data Value Of Data and ...mentioning

confidence: 99%

Using Business Data in Customs Risk Management: Data Quality and Data Value Perspective

Hofman

Migeotte

Labare

et al. 2021

Lecture Notes in Computer Science

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With the rise of data analytics use in government, government organizations are starting to explore the possibilities of using business data to create further public value. This process, however, is far from straightforward: key questions that governments need to address relate to the quality of this external data and the value it brings. In the domain of global trade, customs administrations are responsible on the one hand to control trade for safety and security and duty collection and on the other hand they need to facilitate trade and not hinder economic activities. With the increased trade volumes, also due to growth in eCommerce, customs administrations have turned their attention to the use of data analytics to support their risk management processes. Beyond the internal customs data sources, customs is starting to explore the value of business data provided by business infrastructures and platforms. While these external data sources seem to hold valuable information for customs, data quality of the external data sources, as well as the value they bring to customs need to be well understood. Building on a case study conducted in the context of the PROFILE research project, this contribution reports the findings on data quality and data linking of ENS customs data with external data (BigDataMari) and other customs (import declaration) data and we discuss specific lessons learned and recommendations for practice. In addition, we also develop a data quality and data value evaluation framework applied to customs as high-level framework to help data users to evaluate potential value of external data sources. From a theoretical perspective this paper further extends earlier research on value of data analytics for government supervision, by zooming on data quality.

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Identifying the value of data analytics in the context of government supervision: Insights from the customs domain

Cited by 23 publications

References 27 publications

How to organize for AI? An interview with Yao-Hua Tan

How to organize for AI? An interview with Yao-Hua Tan

eCommerce Platforms Evaluation Framework for Government

Using Business Data in Customs Risk Management: Data Quality and Data Value Perspective

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