Human Factor in Information Systems Development and Management

A special issue of Big Data and Cognitive Computing (ISSN 2504-2289).

Deadline for manuscript submissions: closed (31 July 2024) | Viewed by 16213

Special Issue Editors


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Guest Editor
Institute of Psychology, University of Wrocław, 50-137 Wrocław, Poland
Interests: research methodologies; ICT in transition economies; ICT for development; business statistics; business psychology

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Guest Editor
Department of Business Intelligence in Management, Wroclaw University of Economics and Business, 53-345 Wrocław, Poland
Interests: knowledge grid; knowledge validation and verification; knowledge management; expert system applications; artificial intelligence and database technology; distance and open learning

Special Issue Information

Dear Colleagues,

The significance of the “human factor” is beginning to dawn on software vendors, and though difficult and intangible to measure by nature, the human factor is starting to be seen for what it is: the core of an information system (IS). Yet, in many cases, the collaboration and communication with the users is still ineffective or simply neglected.

Nowadays, information systems are fuelled by large datasets and embedded with artificial intelligence (AI) capabilities driven by machine learning (ML) methods and techniques. The requirements formulated toward modern software systems have considerably changed, imposing novel challenges and vast opportunities. However, while organizations are rushing to deploy AI solutions, the voice of users often seems faint.

Moreover, with the proliferation of information systems (ISs) in both business and personal applications increasing, the growing research interest across diverse disciplines in the human factor is unsurprising. Although many studies have been devoted to addressing the role of the human factor in IS development and management, one can notice the vastly different circumstances due to the COVID-19 pandemic.

In the current situation, COVID-19 has appeared as a real challenge; however, it has also presented an opportunity to tackle a plethora of issues related to work processes, procedures and policies. Therefore, decision makers need to adapt and apply new way of managing communication and collaboration with IS users.

In summary, this Special Issue of the Big Data and Cognitive Computing journal aims to collect and disseminate actual state-of-the-art research regarding the role and impact of the human factor in information system development and management.

Dr. Paweł Weichbroth
Dr. Jolanta Kowal
Dr. Mieczysław Lech Owoc
Guest Editors

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Published Papers (3 papers)

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Research

30 pages, 2117 KiB  
Article
Towards a Refined Heuristic Evaluation: Incorporating Hierarchical Analysis for Weighted Usability Assessment
by Leonardo Talero-Sarmiento, Marc Gonzalez-Capdevila, Antoni Granollers, Henry Lamos-Diaz and Karine Pistili-Rodrigues
Big Data Cogn. Comput. 2024, 8(6), 69; https://doi.org/10.3390/bdcc8060069 - 13 Jun 2024
Viewed by 1410
Abstract
This study explores the implementation of the analytic hierarchy process in usability evaluations, specifically focusing on user interface assessment during software development phases. Addressing the challenge of diverse and unstandardized evaluation methodologies, our research develops and applies a tailored algorithm that simplifies heuristic [...] Read more.
This study explores the implementation of the analytic hierarchy process in usability evaluations, specifically focusing on user interface assessment during software development phases. Addressing the challenge of diverse and unstandardized evaluation methodologies, our research develops and applies a tailored algorithm that simplifies heuristic prioritization. This novel method combines the analytic hierarchy process framework with a bespoke algorithm that leverages transitive properties for efficient pairwise comparisons, significantly reducing the evaluative workload. The algorithm is designed to facilitate the estimation of heuristic relevance regardless of the number of items per heuristic or the item scale, thereby streamlining the evaluation process. Rigorous simulation testing of this tailored algorithm is complemented by its empirical application, where seven usability experts evaluate a web interface. This practical implementation demonstrates our method’s ability to decrease the necessary comparisons and simplify the complexity and workload associated with the traditional prioritization process. Additionally, it improves the accuracy and relevance of the user interface usability heuristic testing results. By prioritizing heuristics based on their importance as determined by the Usability Testing Leader—rather than merely depending on the number of items, scale, or heuristics—our approach ensures that evaluations focus on the most critical usability aspects from the start. The findings from this study highlight the importance of expert-driven evaluations for gaining a thorough understanding of heuristic UI assessment, offering a wider perspective than user-perception-based methods like the questionnaire approach. Our research contributes to advancing UI evaluation methodologies, offering an organized and effective framework for future usability testing endeavors. Full article
(This article belongs to the Special Issue Human Factor in Information Systems Development and Management)
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24 pages, 2389 KiB  
Article
The Extended Digital Maturity Model
by Tining Haryanti, Nur Aini Rakhmawati and Apol Pribadi Subriadi
Big Data Cogn. Comput. 2023, 7(1), 17; https://doi.org/10.3390/bdcc7010017 - 17 Jan 2023
Cited by 21 | Viewed by 11189
Abstract
The Digital Transformation (DX) potentially affects productivity and efficiency while offering high risks to organizations. Necessary frameworks and tools to help organizations navigate such radical changes are needed. An extended framework of DMM is presented through a comparative analysis of various digital maturity [...] Read more.
The Digital Transformation (DX) potentially affects productivity and efficiency while offering high risks to organizations. Necessary frameworks and tools to help organizations navigate such radical changes are needed. An extended framework of DMM is presented through a comparative analysis of various digital maturity models and qualitative approaches through expert feedback. The maturity level determination uses the Emprise test of the international standard ISO/IEC Assessment known as SPICE. This research reveals seven interrelated dimensions for supporting the success of DX as a form of development of an existing Maturity Model. The DX–Self Assessment Maturity Model (DX-SAMM) is built to guide organizations by providing a broad roadmap for improving digital maturity. This article presents a digital maturity model from a holistic point of view and meets the criteria for assessment maturity. The case study results show that DX-SAMM can identify DX maturity levels while providing roadmap recommendations for increasing maturity levels in every aspect of its dimensions. It offers practical implications for improving maturity levels and the ease of real-time monitoring and evaluating digital maturity. With the development of maturity measurement, DX-SAMM contributes to the sustainability of the organization by proposing DX strategies in the future based on the current maturity achievements. Full article
(This article belongs to the Special Issue Human Factor in Information Systems Development and Management)
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23 pages, 4084 KiB  
Article
Locating Source Code Bugs in Software Information Systems Using Information Retrieval Techniques
by Ali Alawneh, Iyad M. Alazzam and Khadijah Shatnawi
Big Data Cogn. Comput. 2022, 6(4), 156; https://doi.org/10.3390/bdcc6040156 - 13 Dec 2022
Cited by 2 | Viewed by 2262
Abstract
Bug localization is the process through which the buggy source code files are located regarding a certain bug report. Bug localization is an overwhelming and time-consuming process. Automating bug localization is the key to help developers and increase their productivities. Expanding bug reports [...] Read more.
Bug localization is the process through which the buggy source code files are located regarding a certain bug report. Bug localization is an overwhelming and time-consuming process. Automating bug localization is the key to help developers and increase their productivities. Expanding bug reports with more semantic and increasing software understanding using information retrieval and natural language techniques will be the way to locate the buggy source code file, in which the bug report works as a query and source code as search space. This research investigates the effect of segmenting open source files into executable code and comments, as they have a conflicting nature, seeks the effect of synonyms on the accuracy of bug localization, and examines the effect of “part-of-speech” techniques on reducing the manual inspection for appropriate synonyms. This research aims to approve that such methods improve the accuracy of bug localization tasks. The used approach was evaluated on three Java open source software, namely Eclipse 3.1, AspectJ 1.0, and SWT 3.1; we implement our dedicated Java tool to adopt our methodology and conduct several experiments on each software. The experimental results reveal a considerable improvement in recall and precision levels, and the developed methods display an accuracy improvement of 4–10% compared with the state-of-the-art approaches. Full article
(This article belongs to the Special Issue Human Factor in Information Systems Development and Management)
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