Christian Versloot, Maria Iacob and Klaas Sikkel
Utility strikes have spawned companies specializing in providing a priori analyses of the underground. Geophysical techniques such as Ground Penetrating Radar (GPR) are harnessed…
Abstract
Utility strikes have spawned companies specializing in providing a priori analyses of the underground. Geophysical techniques such as Ground Penetrating Radar (GPR) are harnessed for this purpose. However, analyzing GPR data is labour-intensive and repetitive. It may therefore be worthwhile to amplify this process by means of Machine Learning (ML). In this work, harnessing the ADR design science methodology, an Intelligence Amplification (IA) system is designed that uses ML for decision-making with respect to utility material type. It is driven by three novel classes of Convolutional Neural Networks (CNNs) trained for this purpose, which yield accuracies of 81.5% with outliers of 86%. The tool is grounded in the available literature on IA, ML and GPR and is embedded into a generic analysis process. Early validation activities confirm its business value.
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María Laura Ponisio, Klaas Sikkel, Lourens Riemens and Pascal van Eck
The purpose of this paper is to present an approach to support understanding of inter‐organisational systems.
Abstract
Purpose
The purpose of this paper is to present an approach to support understanding of inter‐organisational systems.
Design/methodology/approach
The approach combines two types of graphical snapshots of relevant properties of each organisation, based on concrete data. The first type of snapshot provides a bird's eye view of the network that enables matching partners to form groups based on similarity. The second type of snapshot can be used to compare and contrast the information technology (IT) portfolio of partners to assess the extent to which each portfolio is ready to meet the needs of the inter‐organisational system. The approach has been applied in a case study that analysed E‐CUSTOMS, a large distributed system that connects the customs organisations of a number of member states of the European Union. The approach has been validated by showing the results to experts in the E‐CUSTOMS project, who confirmed the findings.
Findings
An approach based on quantifiable and non‐quantifiable data that combines two visualisation techniques was used. The graphical snapshots obtained by applying this approach showed similarities and differences between countries that indicate opportunities and challenges in IT integration.
Practical implications
The approach provides a semi‐automatic method to understand inter‐organisational systems. If in need of successful co‐operation in groups within an inter‐organisational network, this approach will help the expert to ask the right questions.
Originality/value
An understanding of inter‐organisational systems is necessary, as co‐operation in inter‐organisational networks usually requires considerable up‐front investments in IT specific for this co‐operation.
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Three decades of academic and professional discourse on HR technologies (HRTs) have produced continued disagreement over construct definitions and research streams that are highly…
Abstract
Three decades of academic and professional discourse on HR technologies (HRTs) have produced continued disagreement over construct definitions and research streams that are highly fragmented. These realities suggest that greater consistency in meanings is sorely needed if we are to integrate and upgrade knowledge in this area. This chapter draws on the findings of a systematic research review to properly define the content domains of human resource information systems (HRIS), virtual human resources (virtual HR), electronic human resource management (e-HRM), and business-to-employee (B2E) systems. An integrative synthesis was performed on 242 system-level writings that appeared in the literature from 1983 to 2017. The weight of the evidence strongly supports treating HRIS, virtual HR, e-HRM, and B2E systems as independent, complimentary constructs. While the first three comprise a firm’s HRT system, the fourth construct is more appropriately positioned in the business-collaborative system. The sample was further evaluated with an analytic framework to detect patterns of practice in research designs. This revealed that much more attention has been focused on system actions and outcomes than on attitudes and system characteristics. Different units of analysis were well represented aside from trans-organizational studies. Finally, a case is made for better contextualizing HRT research by recognizing differences in assimilation stage, functional penetration, and collective proficiency. These factors are rarely mentioned, let alone studied, raising additional concerns about measurement error. Detailed suggestions are offered on ways to incorporate them. Together, these materials should promote more sophisticated and generalizable assessments of technology, improving our ability to understand its impacts.