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18 pages, 5454 KiB

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Development and Future Trends of Digital Product-Service Systems: A Bibliometric Analysis Approach

by Slavko Rakic, Nenad Medic, Janika Leoste, Teodora Vuckovic and Ugljesa Marjanovic

Appl. Syst. Innov. 2023, 6(5), 89; https://doi.org/10.3390/asi6050089 - 30 Sep 2023

Cited by 7 | Viewed by 3863

As a plan, Industry 4.0 encourages manufacturing companies to switch from conventional Product-Service Systems to Digital Product-Service Systems. Systems of goods, services, and digital technologies known as “Digital Product-Service Systems” are provided to improve consumer satisfaction and business success in the marketplace. Previous studies have looked into various elements of this area for industrial companies and academic institutions. Digital Product-Service Systems’ overall worth and expected course of growth are still ignored. The authors use bibliometric analysis to organize the body of prior knowledge in this discipline and, more significantly, to identify areas for further study in order to cover the literature deficit. The results of the most esteemed authors, nations, and sources in the subject were given by this study. The findings also show that terms like digitization, sustainability, and business have grown in popularity over the previous year. This study also offered insight into how Industry 5.0, a new manufacturing strategy, would include Digital Product-Service Systems. Finally, the findings of this research demonstrate three new service orientations, namely resilient, sustainable, and human-centric, in manufacturing firms. Full article

(This article belongs to the Special Issue Towards the Innovations and Smart Factories)

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39 pages, 964 KiB

Open AccessArticle

Event Log Data Quality Issues and Solutions

by Dusanka Dakic, Darko Stefanovic, Teodora Vuckovic, Marina Zizakov and Branislav Stevanov

Mathematics 2023, 11(13), 2858; https://doi.org/10.3390/math11132858 - 26 Jun 2023

Cited by 1 | Viewed by 3300

Abstract

Process mining is a discipline that analyzes real event data extracted from information systems that support a business process to construct as-is process models and detect performance issues. Process event data are transformed into event logs, where the level of data quality directly impacts the reliability, validity, and usefulness of the derived process insights. The literature offers a taxonomy of preprocessing techniques and papers reporting on solutions for data quality issues in particular scenarios without exploring the relationship between the data quality issues and solutions. This research aims to discover how process mining researchers and practitioners solve certain data quality issues in practice and investigates the nature of the relationship between data quality issues and preprocessing techniques. Therefore, a study was undertaken among prominent process mining researchers and practitioners, gathering information regarding the perceived importance and frequency of data quality issues and solutions and the participants’ recommendations on preprocessing technique selection. The results reveal the most important and frequent data quality issues and preprocessing techniques and the gap between their perceived frequency and importance. Consequently, an overview of how researchers and practitioners solve data quality issues is presented, allowing the development of recommendations. Full article

(This article belongs to the Special Issue Business Analytics: Mining, Analysis, Optimization and Applications)

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17 pages, 633 KiB

Open AccessArticle

Investigating the Key Factors Influencing the Process Innovation Capability in Organizations: Evidence from the Republic of Serbia

by Marina Žižakov, Teodora Vuckovic, Srđan Vulanović, Dušanka Dakić and Milan Delić

Sustainability 2023, 15(10), 8158; https://doi.org/10.3390/su15108158 - 17 May 2023

Cited by 2 | Viewed by 2202

Abstract

Research exploring quality management, knowledge management, and innovations in organizations has received significant attention from academics worldwide, providing different insights. Innovation has been widely seen as an essential organizational performance driver. This study aims to accentuate the importance of quality management and knowledge management and their direct, mediating, and total effect on an organization’s process innovations. The double-reflective second-order construct model was analyzed following the most recent methodology guidelines. Eventually, partial least squares structural equation modeling (PLS-SEM) was used to test the research hypotheses and investigate the relations between the latent factors. The results from 264 Serbian companies that implemented ISO 9001 standard point to quality management’s direct effect on process innovations and knowledge management’s mediating effect on process innovation. Full article

(This article belongs to the Special Issue Standardized Management Systems: Integration, Information, Innovation and Sustainability)

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22 pages, 1147 KiB

Open AccessArticle

The Extended Information Systems Success Measurement Model: e-Learning Perspective

by Teodora Vuckovic, Darko Stefanovic, Danijela Ciric Lalic, Rogério Dionisio, Ângela Oliveira and Djordje Przulj

Appl. Sci. 2023, 13(5), 3258; https://doi.org/10.3390/app13053258 - 3 Mar 2023

Cited by 6 | Viewed by 4547

Abstract

This study investigated the crucial factors for measuring the success of the information system used in the e-learning process, considering the transformations in the work environment. This study was motivated by the changes caused by COVID-19 witnessed after the shift to fully online learning environments supported by e-learning systems, i.e., learning emphasized with information systems. Empirical research was conducted on a sample comprising teaching staff from two European universities: the University of Novi Sad, Faculty of Technical Sciences in Serbia and the Polytechnic Institute of Castelo Branco in Portugal. By synthesizing knowledge from review of the prior literature, supported by the findings of this study, the authors propose an Extended Information System Success Measurement Model—EISSMM. EISSMM underlines the importance of workforce agility, which includes the factors of proactivity, adaptability, and resistance to change, in the information system performance measurement model. The results of our research provide more extensive evidence and findings for scholars and practitioners that could support measuring information system success primarily in e-learning and other various contextual settings, highlighting the importance of people’s responses to work environment changes. Full article

(This article belongs to the Special Issue Information and Communication Technology (ICT) in Education)

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