scholarly journals Digital Transformation Model, Based on Grounded Theory

2021 ◽  
Vol 9 (36) ◽  
pp. 275-284
Author(s):  
Abbas Khamseh ◽  
Mohammad Ali Mirfallah Lialestani ◽  
Reza Radfar
2021 ◽  
Vol 258 ◽  
pp. 02024
Author(s):  
Aleksandr Kozlov ◽  
Anna Smirnova ◽  
Irina Zaychenko ◽  
Yevhenii Shytova ◽  
Joanna Kalkowska

This paper is devoted to researching the major aspects of the digital transformation of the logistical field. Provided are the suggestions for constructing logistical process stakeholder interaction models. One of the major trends in digital logistics is platform solutions that will come to replace specialized digital solutions. Based on this trend, authors provide the 3-level model of stakeholder interaction on the logistical platform which could form the foundation of a future platform solution architecture. The creation of the logistical platform is the next step in the digital transformation of logistics which aims to create a unified logistical ecosystem.


2021 ◽  
Vol 13 (2) ◽  
pp. 52
Author(s):  
Guillermo Rodríguez-Abitia ◽  
Graciela Bribiesca-Correa

Industry 4.0 and Society 5.0 are reshaping the way organizations function and interact with the communities they serve. The massive penetration of computer and network applications forces organizations to digitalize their processes and provide innovative products, services, and business models. The education market is suffering changes as well, but universities seem slow to react. This paper proposes the application of an integrated digital transformation model to assess the maturity level that educational institutions have in their digital transformation processes and compares them to other industries. Particular considerations to address when using the model for higher-education institutions are discussed. Our results show that universities fall behind other sectors, probably due to a lack of effective leadership and changes in culture. This is complemented negatively by an insufficient degree of innovation and financial support.


2021 ◽  
Vol 3 ◽  
pp. 27
Author(s):  
Valérie Rocchi ◽  
Daniel Brissaud

Industry 4.0 is a promising concept that allows industries to meet customers’ demands with flexible and resilient processes, and highly personalised products. This concept is made up of different dimensions. For a long time, innovative digital technology has been thought of as the only dimension to succeed in digital transformation projects. Other dimensions have been identified such as organisation, strategy, and human resources as key while rolling out digital technology in factories. From these findings, researchers have designed industry 4.0 theoretical models and then built readiness models that allow for analysing the gap between the company initial situation and the theoretical model. Nevertheless, this purely deductive approach does not take into consideration a company’s background and context, and eventually favours one single digital transformation model. This article aims at analysing four actual digital transformation projects and demonstrating that the digital transformation’s success or failure depends on the combination of two variables related to a company’s background and context. This research is based on a double approach: deductive and inductive. First, a literature review has been carried out to define industry 4.0 concept and its main dimensions and digital transformation success factors, as well as barriers, have been investigated. Second, a qualitative survey has been designed to study in-depth four actual industry digital transformation projects, their genesis as well as their execution, to analyse the key variables in succeeding or failing. 46 semi-structured interviews were carried out with projects’ members; interviews have been analysed with thematic content analysis. Then, each digital transformation project has been modelled regarding the key variables and analysed with regards to succeeding or failing. Investigated projects have consolidated the models of digital transformation. Finally, nine digital transformation models have been identified. Industry practitioners could design their digital transformation project organisation and strategy according to the right model.


2017 ◽  
Vol 3 (2) ◽  
pp. 525-528
Author(s):  
Kathrin Bartelheimer ◽  
Hendrik Teske ◽  
Rolf Bendl ◽  
Kristina Giske

AbstractDuring radiotherapy, posture changes and volume changing deformations like growing or shrinking tissue result in anatomical deformations. The basis for investigating the impact of such deformations on dose uncertainties, are model-based tools for deformation analysis. In this context, we propose a transformation model based on the information of CT-images, which allows an on-the-fly calculation of voxel volumes. Our model is based on the concept of the chainmail algorithm and describes deformation on voxel-level. With an exemplary input of a set of landmark pairs, generated by a kinematic head-and-neck skeleton model, CT-images (512x512x126 voxel) can be deformed with an on-the-fly volume calculation in less than 70s. The volume calculation delivers insight into model-characteristic volume changes and is a prerequisite for implementing tissue growth and shrinkage.


Author(s):  
Nima Torbati ◽  
Ahmad Ayatollahi

Image registration is regarded as an important component of medical procedures. The present study aimed to introduce a new transformation model based on dual-tree complex wavelet transform (DT-CWT). To this aim, parametric registration methods was revised based on the function expansion theory and the gradient descent algorithm was used to introduce a general formulation for transformation models based on spatio-spectral transforms. Then, the performance of the proposed method was evaluated on a public dataset of 3D real magnetic resonance images (MRI) and compared with the transformation model based on wavelets. Finally, the performance of the proposed method was compared with the current state-of-the-art methods (IRTK, SyN and SPM-DARTEL). Based on the experimental results, the proposed method could deliver superior registration performance compared with the previous methods.


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