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How a 4-Day Work Week and Remote Work Affect Agile Software Development Teams 6th

How a 4-Day Work Week and Remote Work Affect Agile Software ...

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6th International Conference on Lean and Agile Software Development (LASD)

作者： Topp, Julia Hille, Jan Hendrik Neumann, Michael Moetefindt, David Univ Appl Sci & Arts Hsch Hannover Ricklinger Stadtweg 120 D-30459 Hannover Germany Agile Move Ackerstr 16 D-30851 Langenhagen Germany

ISBN: (纸本)9783030942380;9783030942373

Context: Agile software development (ASD) sets social aspects like communication and collaboration in focus. Thus, one may assume that the specific work organization of companies impacts the work of ASD teams. A major change in work organization is the switch to a 4-day work week, which some companies investigated in experiments. Also, recent studies show that ASD teams are affected by the switch to remote work since the Covid 19 pandemic outbreak in 2020. Objective: Our study presents empirical findings on the effects on ASD teams operating remote in a 4-day work week organization. Method: We performed a qualitative single case study and conducted seven semi-structured interviews, observed 14 agile practices and screened eight project documents and protocols of agile practices. Results: We found, that the teams adapted the agile method in use due to the change to a 4-day work week environment and the switch to remote work. The productivity of the two ASD teams did not decrease. Although the stress level of the ASD team member increased due to the 4-day work week, we found that the job satisfaction of the individual ASD team members is affected positively. Finally, we point to affects on social facets of the ASD teams. Conclusion: The research community benefits from our results as the current state of research dealing with the effects of a 4-day work week on ASD teams is limited. Also, our findings provide several practical implications for ASD teams working remote in a 4-day work week.

关键词： Agile methods Agile software development Remote work 4-day work week Alternative work schedule Covid 19

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Democratizing Enterprise AI Success Factors and Challenges: A Systematic Literature Review and a Proposed Framework 18th

Democratizing Enterprise AI Success Factors and Challenges: ...

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18th European, Mediterranean, and Middle Eastern Conference on information Systems (EMCIS)

作者： Kaddoumi, Tarek Tambo, Torben Aarhus Univ Birk Centerpk 15 DK-7400 Herning Denmark

ISBN: (纸本)9783030959470;9783030959463

To democratize or not to democratize, this is not the problem anymore for the enterprises that consider democratizing their enterprise AI practice;the problem that these enterprises face nowadays, is how to successfully democratize their enterprise AI. In this paper we conduct a systematic literature review to provide an in-depth analysis of the success factors and the challenges of democratizing the artificial intelligence practices in the enterprises, we also build on this review and propose a framework for the enterprise AI democratization that suggests a set of the success factors and challenges. The research design of this paper is to conduct a systematic literature review by including 41 papers as an initial set of studies for review;we screen the papers and implement inclusion and quality checks on these studies, and we qualify 15 papers for the final review. The key findings of this paper, from the systematic literature review, list a set of success factors and challenges that enterprises should consider to strengthen or to avoid. We propose these factors in a form of proposed framework suggesting four categories: strategy, enterprise architecture, data, and trust. Because of the publication specification and limitation, we limited the scope of our primary studies to a limited set to match the constraints and limitations. The paper includes implications for the academic literature review and the extraction of factors that can impact the process of the enterprise artificial intelligence democratization, and the need to increase the awareness of the enterprise AI practices in order to overcome the challenges that might prevent enterprises from having a successful enterprise AI. While there are some efforts to assess and review the success factors and challenges of the AI practices in general, one of the major findings of the literature review conducted is that there is evident research gap in the literature on the perception and associated factors of artificia

关键词： Enterprise Emerging technologies Artificial intelligence Enterprise architecture Intelligent enterprise

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Applying and Evaluating the KYKLOS Method 15th

Applying and Evaluating the KYKLOS Method

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15th IFIP WG 8.1 Working Conference on the Practice of Enterprise Modelling (PoEM)

作者： Koutsopoulos, Georgios Andersson, Anna Stirna, Janis Henkel, Martin Stockholm Univ Dept Comp & Syst Sci POB 7003 S-16407 Kista Sweden

ISBN: (纸本)9783031214875;9783031214882

Organizations are dealing with a continuous need to adapt to their dynamic environments by changing their business capabilities. KYKLOS is a recently developed modeling method aiming to provide methodological and tool support for the phenomenon of capability change in organizations. This paper reports on a case study used to demonstrate and evaluate KYKLOS. The case study has been performed in a company in the ERP system consulting domain, and the results have been used to evaluate the method using two groups of evaluators, a business user group and a group of modeling experts. The paper reports the insights and findings that validate and motivate future research about the method and the different perspectives between the two groups of evaluators.

关键词： Capability management Method evaluation Enterprise modeling Change management

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Technology Acceptance of MS Teams Among University Teachers During COVID-19 18th

Technology Acceptance of MS Teams Among University Teachers ...

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18th European, Mediterranean, and Middle Eastern Conference on information Systems (EMCIS)

作者： Smolinski, Pawel Robert Szostakowski, Marcin Winiarski, Jacek Univ Gdansk Gdansk Poland Univ Gdansk Doctoral Sch Humanities & Social Sci Gdansk Poland Univ Gdansk Dept Business Informat Sopot Poland

ISBN: (纸本)9783030959470;9783030959463

The choice of software for implementing online learning has always been one of the fundamental problems in education sciences. Efficiency and quality of education largely depend on the properties of the tool (software) that the teacher uses. The COVID-19 pandemic has led to the rise in numbers of users of e-learning tools. Decision makers had to choose which available product their corporation, university or school would use. After several months of widespread implementation of different e-learning software, users are ready to give an evaluation. The aim of this paper is to provide such evaluation on MS Teams, which can be obtained by applying Technology Acceptance Models. Among the set of Technology Acceptance Models developed in science and verified in practice, the Unified Theory of Acceptance and Use of Technology (UTAUT) deserves special attention due to its flexibility and large predictive power. We propose an enriched UTAUT model for MS Teams, which adds two new variables to the original: Product Superiority (PS) and System Comprehensiveness (SC). This paper presents the development of Technology Acceptance Models as a software evaluation method, followed by the presentation of hypotheses and description of the research method used. The research was carried out using the questionnaire distributed among university teachers from northern Poland. We present the analysis of the results along with the conclusions formulated on their basis. At the end, we highlight the interpretative limitations and indicate further research directions.

关键词： Technology acceptance UTAUT model MS teams Education e-learning

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Designing an Ontology for Human Rights Violations Documentation Through Practitioner Input and information Infrastructure Theory 15th

Designing an Ontology for Human Rights Violations Documentat...

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15th IFIP WG 8.1 Working Conference on the Practice of Enterprise Modelling (PoEM)

作者： Lindeberg, Joran Henkel, Martin Stockholm Univ Dept Comp & Syst Sci Stockholm Sweden

ISBN: (纸本)9783031214875;9783031214882

Human rights groups of varying sizes collect information about human rights violations. Managing this information in a structured way is a challenging task, particularly since many human rights groups have limited budgets. This paper presents the initial work with requirements elicitation leading to the design of OntoRights - a domain ontology for human rights violations documentation that aims at helping human rights organisations to structure their documentation. To ensure that the ontology was grounded in practice, two interconnected surveys of manuals and practitioners were conducted. Moreover, the design used information infrastructure theory to increase the ontology's potential uptake. The resulting ontology extends the legal core ontology UFO-L and is represented in OntoUML. As a demonstration, it was instantiated twice: in a fictitious and in a real case.

关键词： Ontology-driven conceptual modeling Human rights Requirements elicitations information infrastructures Unified Foundational Ontology (UFO) OntoUML OntoRights

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Naive Bayes Based Classifier for Credit Card Fraud Discovery 18th

Naive Bayes Based Classifier for Credit Card Fraud Discovery

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18th European, Mediterranean, and Middle Eastern Conference on information Systems (EMCIS)

作者： Ogundokun, Roseline Oluwaseun Misra, Sanjay Fatigun, Olufunmilayo Joyce Adeniyi, Jide Kehinde Landmark Univ Dept Comp Sci Omu Aran Nigeria Ostfold Univ Coll Dept Comp Sci & Commun Halden Norway Agr & Rural Management Training Inst Directorate Financial Serv Ilorin Nigeria

ISBN: (纸本)9783030959470;9783030959463

As financial services and operations expand, financial fraud is on the rise. Despite the use of preventative and security measures to reduce monetary fraud, criminals are constantly acquiring and developing new ways to circumvent fraud detection systems, posing a challenge to quantitative methods and predictive approaches. As a result, new methodologies must be researched and tested to leverage the insights gained from the study to assist further incorrect fraud forecasting and the establishment of fraud discovery schemes with extra measures to alleviate distrustful events. Naive Bayes (NB) is a significant Machine Learning (ML) classifier that is not yet explored in the literature, unlike the use of common ML techniques like Decision Tree (DT), Random Forest (RF), Artificial Neural Network (ANN), and the likes. This paper, therefore, explores the use of a technique yet to be employed for credit card fraud detection (CCFD) namely Naive Bayes. The classifier was compared using a confusion matrix for performance matrices like accuracy, precision, recall, f-measure, and ROC-AUC. It was discovered that NB outperformed most of the ML classifiers employed in state-of-the-art compared with an accuracy of 97.99%, recall of 98.02%, the precision of 99.97%, f-measure 98.98%, and FPR of 0.1971.

关键词： Naive Bayes Classification Machine learning Credit card fraud detection Credit card

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Towards an Ontology Network in Finance and Economics 11th

Towards an Ontology Network in Finance and Economics

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11th Enterprise Engineering Working Conference (EEWC)

作者： Amaral, Glenda Sales, Tiago Prince Guizzardi, Giancarlo Free Univ Bozen Bolzano CORE KRDB Bolzano Italy Univ Twente Serv & Cybersecur Enschede Netherlands

ISBN: (纸本)9783031115202;9783031115196

Finance and economics are wide domains, where ontologies are useful instruments for dealing with semantic interoperability and information integration problems, as well as improving communication and problem solving among people. In particular, reference ontologies have been widely recognized as powerful tools for representing a model of consensus within a community to support communication, meaning negotiation, consensus establishment, as well as semantic interoperability and information integration. In domains like economics and finance, which are too large and complex to be represented as a single, large and monolithic ontology, it is necessary to create an ontological framework, built incrementally and in an integrated way, as a network. Therefore, in this paper we introduce OntoFINE, an Ontology Network in Finance and Economics that organizes and integrates knowledge in the realm on finance and economics, serving as a basis to several applications. We discuss the development of OntoFINE and present some of its applications.

关键词： Ontology Network Money Value Trust Risk Economic Exchanges

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Assessment of Machine Learning Classifiers for Heart Diseases Discovery 18th

Assessment of Machine Learning Classifiers for Heart Disease...

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18th European, Mediterranean, and Middle Eastern Conference on information Systems (EMCIS)

作者： Ogundokun, Roseline Oluwaseun Misra, Sanjay Sadiku, Peter Ogirima Adeniyi, Jide Kehinde Landmark Univ Omu Aran Dept Comp Sci Omu Aran Nigeria Ostfild Univ Coll Dept Comp Sci & Commun Halden Norway Univ Ilorin Dept Comp Sci Ilorin Nigeria

ISBN: (纸本)9783030959470;9783030959463

Heart disease (HD) is one of the utmost serious illnesses that afflict humanity. The ability to anticipate cardiac illness permits physicians to deliver better knowledgeable choices about their patient's wellbeing. Utilizing machine learning (ML) to minimize and realize the symptoms of cardiac illness is a worthwhile decision. Therefore, this study aims to analyze the effectiveness of some supervised ML procedures for detecting heart disease in respect to their accuracy, precision, fl-score, sensitivity, specificity, and false-positive rate (FPR). The outcomes, which were obtained using python programming language were compared. The data employed in this investigation came from an open database of the National Health Service (NHS) heart disease which originated in 2013. Through the machine learning (ML) technique, a dimensionality reduction technique and five classifiers were employed and a performance evaluation between the three classifiers- principal component analysis (PCA), decision tree (DT), random forest (RF), and support vector machine (SVM). The NHS database contains 299 observations. The system was evaluated using confusion matrix measures like accuracy, precision, fl-score, sensitivity (TPR), specificity, and FPR. It is concluded that ML techniques reinforce the true positive rate (TPR) of traditional regression approaches with a TPR of 98.71% and f-measure value of 68.12%. The true positives rate which is the same as the sensitivity was used to evaluate the accuracy of the classifiers and it was deduced that the PCA + DT outperformed that of the other two with a sensitivity of 98.71% and since the value is on the high side, this implies that the classifier will be able to accurately detect a patient with HD in his or her body.

关键词： Machine learning Heart disease Confusion matrix Classification Dimensionality reduction

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SafeCross - VCA Based Road Traffic Regulations Compliance Detection 14th

SafeCross - VCA Based Road Traffic Regulations Compliance De...

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14th PLAIS EuroSymposium on Digital Transformation (PLAIS)

作者： Szklarczyk, Rafal Nikodem, Joanna Falat, Pawel Foks, Konrad Caputa, Marcin Szklarczyk, Anna Univ Bielsko Biala Ul Willowa 2 PL-43309 Bielsko Biala Poland Elmontaz Sp zoo Ul Ks Pr St Slonki 54 PL-34300 Zywiec Poland Mech Net Sp Zoo Ul Pilsudskeigo 42 1 PL-43300 Bielsko Biala Poland

ISBN: (纸本)9783031230110;9783031230127

The present paper introduces the concept of video content analysis based system for road traffic regulations compliance monitoring at unguarded railway crossings. The described system named SafeCross is currently being developed by the consortium of Elmontaz Sp. z o. o. (ltd.) and University of Bielsko-Biala. Recently it gained the final phase of development. The technical goals have been achieved and some work results are available.

关键词： SafeCross Road traffic surveillance VCA Road traffic AI analysis

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Technology as Driver, Enabler and Barrier of Digital Transformation: A Review 18th

Technology as Driver, Enabler and Barrier of Digital Transfo...

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18th European, Mediterranean, and Middle Eastern Conference on information Systems (EMCIS)

作者： Tsiavos, Vasilis Kitsios, Fotis Univ Macedonia Dept Appl Informat Thessaloniki Greece Hellen Open Univ Sch Social Sci Parodos Aristotelous 18 Patras 26335 Greece

ISBN: (纸本)9783030959470;9783030959463

In recent years, organizations and researchers have become increasingly interested in digital transformation. Technology has found its way into the lives of customers, but at the same time is disrupting industries by enabling organizations, that have embraced it, to gain more and more competitive advantages. However, technology is only one factor of a successful digital transformation strategy, where culture, management, human resources etc. also play an important role. While digital transformation has been researched over the years from multiple points of view, limited studies have focused in detail on the impact of technology on digital transformation. Questions such as how fast an organization should adapt to the evolution of technology, which technologies should be preferred and finally, in which cases technology might delay the digital transformation process, remain unanswered. The present paper aims to fill this gap by conducting a systematic literature review of 74 related articles, based on the Webster & Watson methodology, followed by a concept analysis of technology related themes in digital transformation. The results of the analysis reveal that technology does not only act as an enabler or driver of digital transformation, but can also be a barrier of it. While we contribute with our paper to the research body in digital transformation, at the same time, we identify potential research gaps that leave space for further investigation.

关键词： Digital transformation Technology Industry 4.0

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