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To mind IT or not to mind IT

Authors: Boriana Rukanova; Helle Zinner Henriksen;

To mind IT or not to mind IT

Abstract

Purpose – The objective of this research is to study the significance of technology – as a driver as well as a barrier – for e-customs implementation. E-customs is seen here as a subset of e-government because it deals with digital government-to-business interaction.Design/methodology/approach – The study applies the syntegration process (Beer, 1994) as a method of knowledge exchange among a heterogeneous group of people involved in e-customs implementation. The research methodology is therefore a qualitative, explorative and inductive search for drivers and barriers.Findings – The data suggest that technology is seen more as a means rather than an end in relation to e-customs implementation. Legal, regulatory and policy factors, as well as human and organizational factors are suggested to be of similar importance.Research limitations/implications – The study demonstrates the strength in applying more interpretative research approaches to less explored domains. It highlights that practitioners perceive certain variables, which are less obvious to the traditional research-driven models, to be of importance.Practical implications – The results should be applied with care, bearing in mind that our conclusions are based on a single syntegration process. The robust foundation of the Living Lab as a platform for collaboration (beyond the syntegration workshop) suggests that the insights can provide useful input to practitioners who need to implement an e-customs solutions. It provides a more balanced view because data are generated from a heterogeneous group of stakeholders involved in e-customs implementation.Originality/value – The process of data collection deviates from the more traditional case study where the design of the study guides the data collection.

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Keywords

Open Systems, Government, Business Planning, Communication Technologies

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
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