2026-02-23
Yudhy Setyo Purwanto, Rahmat Gernowo, Dinar Mutiara Kusumo Nugraheni
Mobile Language Learning Applications (MLLAs) are gaining widespread use in higher education because of the flexible nature of practice opportunities with languages. The majority have easy-to-use interfaces, but few enable long-term engagement, retention, and productive learning. There is much empirical work that isolates usability or outcomes singularly without noting how user experience, motivation, and pedagogy intersect in the mobile environment. This study investigates MLLA user experience among university students in Indonesia using a mixed-methods design. Structural Equation Modelling (SEM) was used to investigate the inter-plays of usability, acceptance, engagement, and retention. Qualitative data provided information about user views and context-based limitations. Findings suggest that while overall MLLAs are usable and widely accepted, they tend to lack instructional intensity and intrinsic motivation support. Motivation and perceived usefulness significantly impact engagement, but redundant repetition, superficial individualization, and minimal interaction reduce retention. With reference to TPACK, FRAME, and SDT, the study highlights learner-centered design featuring effective pedagogy, social interaction, and adaptive functionality as being vital. To transcend surface gamification, MLLAs must support deep, long-term language learning. These results provide actionable recommendations for developers and instructors seeking to optimize mobile language learning by synergizing technology, pedagogy, and learner psychology.
2026-01-27
Mateja Gorenc, Janez Likozar
The article discusses the optimization of batch processing in a public institution through the implementation of a proprietary centralized batch management system. The research is based on the analysis of processing log entries from 2018 to 2023 and the implementation of a proprietary information interface developed in C# and connected to an Oracle database. The study highlights the importance of operator roles, structured work orders, and socio-technical alignment between technology and organizational processes. The analysis confirms that advanced planning significantly reduces processing time, thereby improving operational efficiency. However, the impact on overall process success is limited, as reliability appears to depend on additional organizational and infrastructural factors.
2025-12-05
Willy Riyadi, Kurniabudi, Jasmir, Yudi Novianto, Desi Kisbianty, Xaverius Sika
The rapid growth of the Internet of Medical Things (IoMT) has introduced critical cybersecurity challenges, highlighting the need for robust and accurate intrusion detection systems (IDS). This study presents a hybrid machine learning (ML) framework to strengthen intrusion detection in IoMT networks using the CIC-IoMT2024 dataset. The framework combines Information Gain (IG) and Principal Component Analysis (PCA) for feature selection and dimensionality reduction, while SMOTEENN and SMOTETomek are applied to address severe class imbalance. The processed data are classified using Random Forest (RF), K-Nearest Neighbors (KNN), XGBoost (XGB), Multi-Layer Perceptron (MLPC), and Logistic Regression (LR), with hyperparameters optimized through Bayesian Optimization. Performance is evaluated using Accuracy, Precision, Recall, F1-Score, and AUC. Experimental results reveal that the optimized XGB classifier with SMOTEENN achieves a peak accuracy of 99.811%. This top-tier performance surpasses several existing benchmarks, validating the effectiveness of integrating IG-PCA with advanced resampling and optimization strategies. This work contributes a lightweight, scalable, and highly accurate IDS, offering a practical and efficient solution for enhancing security in resource-constrained, next-generation medical IoT systems.
2025-12-05
Sajeda Ben Otman, Sourur Ben Otman, Gökçe Karahan Adalı
Generative Artificial Intelligence (GenAI) is rapidly transforming higher education, yet its impact on learning experiences remains contested. Existing research often isolates either cognitive outcomes (e.g., comprehension, creativity) or affective outcomes (e.g., motivation, engagement), leaving a gap in integrated analyses that also account for heterogeneity across student groups. This study investigates both dimensions simultaneously by examining university students’ perceptions of GenAI, focusing on learning, creativity, motivation, and engagement, alongside perceived risks such as overreliance, ethical concerns, and difficulties in verifying accuracy. Data were collected from 93 students and analyzed through Spearman’s correlations and unsupervised clustering (k-means) with PCA visualization. Findings indicate low to moderate positive correlations between GenAI usage and learning outcomes, particularly problem-solving and motivation. Cluster analysis reveals diverse usage–perception profiles, including paradoxical cases where frequent users report limited cognitive benefit. These results align with Technology Acceptance Model (TAM) and UTAUT assumptions of perceived usefulness and performance expectancy, while also showing that digital literacy moderates these relationships, especially in critical thinking and responsible use. The study contributes by integrating cognitive and affective outcomes, revealing latent profiles beyond averages, and bridging adoption models with responsible AI frameworks. Practical implications highlight the need for AI literacy training, ethical policies, and instructional design to foster effective and responsible GenAI integration in higher education.
2025-11-05
Reza Adyaputra, Khairul Imtihan, Maemun Saleh
Despite continued efforts to digitize public services, many local government websites in emerging contexts still underperform in delivering satisfactory user experiences. This study develops an integrated evaluation framework that combines the ISO 25010 software quality model with the Technology Acceptance Model (TAM) to jointly assess system quality and user acceptance. We analyzed survey data from 524 users in Lombok Tengah, Indonesia, using Partial Least Squares Structural Equation Modeling (PLS-SEM) and Importance Performance Map Analysis (IPMA). The results indicate that functional suitability, usability, and reliability significantly shape perceived usefulness, whereas reliability, security, and performance efficiency drive perceived ease of use. Both perceived usefulness and perceived ease of use positively influence user satisfaction and behavioral intention, with satisfaction emerging as the strongest predictor. IPMA highlights performance efficiency and security as priority areas for improvement. The study contributes to e-government literature by proposing a dual layer model that links system level attributes to user-level perceptions and outcomes, and by translating statistical effects into actionable priorities for local governments seeking to enhance the quality and adoption of digital public services in semi urban developing regions.
2025-09-12
Prathamesh Vijay Lahande
Purpose: The author proposes sixteen Shortest Job First - Machine Learning (SJF-ML) hybrid algorithms, combining the cloud's SJF scheduling algorithm with four ML algorithm categories, with cloud evolution through ML intelligence as the primary objective. The four categories include: SJF-CA, SJF-ELA, SJF-PM, and SJF-RA. The developed SJF-ML algorithms by the author perform pattern recognition of the tasks that are to be computed, to improve decision-making during task computations in the cloud. These sixteen SJF-ML algorithms include: SJF-ADAB, SJF-BAY, SJF-DT, SJF-KNN, SJF-LAS, SJF-LDA, SJF-LGB, SJF-LN, SJF-MLP, SJF-NAV, SJF-PLY, SJF-RDG, SJF-RF, SJF-RBST, SJF-SVM, and SJF-XGB. Performance Metrics: Cost, Time, Energy, and LB are utilized to compare the developed algorithms with baseline SJF, along with comparing them within their respective SJF-ML categories. Dataset: The real-time Google Big Data Task (BDT) dataset, comprising tasks ranging from one hundred to one thousand across nineteen files, was computed using the SJF-ML and SJF algorithms. Experiment: Open-source CloudSim simulator with VM counts of 20, 40, 60, 80, and 100 were utilized to compute the BDTs, outputting results across the considered metrics. Results: The algorithms SJF-XGB and SJF-LN provided the best results, with SJF-DT, SJF-LAS, and SJF-LDA providing poor results. Findings: Hybridization of the cloud's scheduling algorithms with ML provides improved intelligence and performance, resulting in the evolution of the cloud.
2025-06-04
Albana Berisha Qehaja, Edona Berisha Kida
This longitudinal study examines the relationships among job insecurity, life satisfaction, trust in government, and hope during the COVID-19 pandemic across 27 European Union countries. Using data from 8,750 participants collected via the PsyCorona Study, the analysis applies the PROCESS macro (model 6) with 5,000 bootstrapped samples to estimate indirect effects with 95% bias-corrected confidence intervals. Findings reveal that job insecurity significantly reduces life satisfaction, explaining 13.62% of the variance over time. Trust in government mediates this relationship in earlier waves, though its influence diminishes later. Conversely, hope consistently emerges as a strong mediator across all waves, accounting for 24.64% of the variance. Sequential mediation via trust and hope is significant early on but weakens by wave 22. These findings underscore the essential role of government trust and hope in buffering the negative effects of job insecurity and enhancing societal resilience during times of crisis.
2025-05-31
Mahmoud Mohamed, Fayaz Aljuaid
This paper investigates the performance of 5G networks compared to 4G LTE, WiFi, and BLE for transmitting real-time health monitoring data. Using Apple Watch Series 7 and Fitbit Sense devices connected to commercial 5G and 4G networks, our experimental analysis demonstrates that 5G technology offers significant advantages for healthcare monitoring applications. Results show a 62% reduction in latency (8.2ms versus 21.6ms), 83.4% improvement in throughput, and 75% reduction in packet loss compared to 4G LTE networks. The low latency achieved with 5G (8.2ms) is particularly critical for remote cardiac monitoring, where transmission delays directly impact clinical response time. Signal strength correlation analysis reveals that 5G networks maintain performance consistency across varying RSRP levels, with only 16% performance degradation at -110dBm compared to 42% for 4G networks. Our findings confirm that 5G networks provide the reliability and performance required for next-generation real-time health monitoring systems, especially for applications requiring continuous vital sign monitoring and immediate clinical feedback.
2025-04-23
Bekti Suratmanto, Yonathan Dri Handarkho, Andi Wahju Raharjo Emanuel
This study investigates how gamification influences habit formation and repurchase intention in Indonesian e-marketplaces, focusing on key elements such as points, rewards, badges, and challenges. Using the Stimulus-Organism-Response (SOR) model and habit formation theory, the research examines how user engagement drives repeat purchasing behavior. Data were collected from 375 Shopee and Tokopedia users via an online survey, and the hypotheses were tested using Structural Equation Modeling (SEM). The results reveal that gamification significantly enhances customer engagement, which in turn strengthens habitual use and positively impacts repurchase intention. Among the gamification elements, rewards emerged as the most influential driver of repeat purchases, suggesting that incentive-based mechanisms are particularly effective in promoting customer retention. Unlike previous studies that primarily emphasize engagement and loyalty, this research highlights the specific role of gamification in shaping behavioral habits that lead to sustained purchasing. By integrating habit theory into the SOR framework, the study offers a fresh perspective on long-term consumer behavior in digital commerce. These findings have practical implications for e-marketplace platforms seeking to optimize their gamification strategies to maintain engagement and boost sales. Overall, the study emphasizes the importance of habit formation as a key factor in enhancing customer retention through gamification.
2025-04-21
Miro Zdilar
Spreadsheets are one of the most used software systems in business and academia. Since the first introduction of electronic spreadsheets for personal computers in 1979, spreadsheets have significantly evolved. With recent technological advancements and new features added, spreadsheets have become powerful computing platforms capable of complex analysis and modelling. However, numerous publications over the years described cases of spreadsheet errors. In focus of this research paper are spreadsheet errors caused by unauthorized access and modifications of spreadsheets in multi-user environments. Specifically, this paper is structured around formal verification of the novel ABAC4S (Attribute Based Access Control for Spreadsheets) protocol designed for prevention or detection of unauthorized modifications to spreadsheets in multi-user environments. We utilized a model checking approach to verify ABAC4S protocol rules for correctness.
2024-12-18
Amjad Alloush, Ghaida Rebdawi, Mohammad Saeed Abou Trab
The dynamics and patterns of information propagation on online social networks are complex and challenging to model and to predict. This study proposes a novel algorithm for simulating the spread of information on online social networks using a swarm-based approach. The algorithm is based on the firefly algorithm, which incorporates a new term called Vantablack to represent the non-spreader nodes in the network. The proposed algorithm is validated on three real-world datasets extracted from Kaggle.com, covering different topics and domains. The proposed algorithm outperforms other baseline methods in terms of accuracy and efficiency in predicting information diffusion.
2024-12-18
Ayşe Meriç Yazıcı, Ayşegül Özkan
The purpose of this study is to explore the mediating role of organizational trust in the impact of social sustainability on organizational resilience. Using a sample of 441 employees in the energy sector in Istanbul, a structured questionnaire was applied to measure employees' organizational resilience, organizational trust and perceived social sustainability activities. Data analysis was carried out with SPSS and AMOS 24 programs. Factor analysis and structural equation modeling were used in the study. The data analysis based on path modelling confirms the mediating role of organizational trust in the effect of social sustainability on organizational resilience. The findings show that all social sustainability variables significantly affect all organizational trust dimensions, and organizational trust dimensions significantly affect organizational resilience dimensions. Accordingly, organizational trust dimensions and all social sustainability dimensions have a full mediating variable role in the effect of organizational trust dimensions on organizational resilience dimensions. Future research is important to gain a deeper understanding of the relationships between social sustainability, organizational resilience and organizational trust. In particular, studies in specific sectors or cultural contexts can help us better understand how these relationships may vary and how they may shape organizations' strategies.
2024-12-18
Jelena Jardas Antonić, Antonija Srok, Nenad Vretenar
The mass adoption of ICT for online delivery of education due to the COVID-19 pandemic has brought many opportunities but also challenges for the education sector. In this paper, we conducted a scientometric analysis to provide insights into research trends and present bibliometric indicators of 5810 publications on blended learning to contribute to the knowledge base on the use of ICT in education management, during and after the COVID-19 pandemic, from 2020 to 2023. The number of citations and publications increased rapidly. Content analysis of the publications and keyword analysis revealed important and emerging topics such as the challenges and experiences of students, teachers and institutions with blended learning, especially in higher education, from implementation and use to digital literacy, attitudes, performance, self-regulation and learning outcomes. The main journals focused on the use of technology in education and health education. Blended learning has likely moved beyond the pandemic and has become an integral part of management in educational organizations.
2024-12-18
Maha Al-Bayati
The outbreak of Coronavirus (COVID-19), especially SARS-CoV-2, has led to a catastrophic scenario in the course of the world. The cumulative prevalence of COVID-19 was increasing rapidly day by day. Machine learning (ML) and deep learning (DL) can be deployed to facilitate tracking disease, anticipating the increase in epidemic, and hence planning for coverage techniques to control its spread. This work is based on the application of an advanced mathematical model to examine and predict the increase in a pandemic. On the bases of time-series data, an advanced DL model has been implemented to predict the risk of COVID-19 spreading in Iraq. A hybrid approach is presented where two deep learning algorithms; LSTM and GRU are brought up together to achieve good prediction with rewarding levels of (MAE = 0.109), (MAPE = 0.191) and (RMSE = 0.134).
2024-06-16
N Sathya, R Gayathiri
In the realm of investment decisions, the influence of behavioral biases has emerged as a captivating area of exploration. This article embarks on a comprehensive journey through the landscape of behavioral biases in investment choices, delving into their profound impact on financial markets. Contrary to traditional finance theories assuming rationality, a multitude of empirical evidence attests to the pervasive effects of cognitive and emotional biases. Through an extensive literature review, this article elucidates the intricacies of key biases such as overconfidence, loss aversion, anchoring, confirmation bias, herding behavior, disposition effect, framing effects, and regret aversion. By examining the distinct ways these biases distort investors' judgment and decision-making processes, we unveil the often unexpected deviations from rationality. Each bias, rooted in human psychology, can lead to suboptimal investment behaviors, portfolio misalignments, and heightened market volatility. However, recognizing the impact of these biases provides opportunities for transformative insights. As investment professionals, policymakers, and individuals alike comprehend the subtle nuances of behavioral biases, tailored interventions, educational initiatives, and adaptive strategies can be devised to mitigate their adverse effects. This article not only synthesizes the prevailing research but also charts a course for future investigations. The implications of understanding and addressing behavioral biases extend beyond financial realms, offering a bridge between finance and psychology. As interdisciplinary collaboration gains momentum, pathways for future research become evident, beckoning scholars to delve deeper into the uncharted territories of human behavior and its intricate relationship with investment decisions. Through the exploration of these biases and their potential remedies, this article illuminates the evolving landscape of investment decision-making in a world where cognitive fallacies intersect with financial choicest.
2024-06-16
Abdelkader Adla, Mohammed Frendi, Bakhta Nachet
Current supply chain management (SCM) requires the control of physical and information flows in order to satisfy the customer, i.e. deliver the right product to the customer at the right place, at the right time, at the right price and at the lowest cost. SCM is inseparable from traceability which makes reliable the said flows, accelerates the transmission of information on these flows, allows to access a detailed knowledge of the movements, and makes the flows visible. In order to streamline and monitor, if possible, in real time and permanently these logistical processes, we propose the design and implementation of an Ontology-based traceability system based on an architectural model for the physical Internet using computing resources such as Cloud computing, Fog computing and Internet of Things (IoT) to achieve efficiency and sustainability goals. To evaluate our system, we were able to carry out all the queries that the user can express whether he is a customer, a supplier or a manager.
2024-06-16
Avinash Singh, Vikas Pareek, Ashish Sharma
Financial Technology (FinTech) has sparked widespread interest and is fast spreading. As a result of its continual growth, new terminology in this domain has been introduced. The name 'FinTech' is one such example. This term covers a wide range of practices that are repeatedly used in the financial technology industry. This processes were typically accomplished in careers or organizations to supply required services through the use of information technology-based applications. The word covers a wide range of delicate subjects, including security, privacy, threats, cyberattacks, and others. Several cutting-edge technologies, including those associated with a mobile embedded system, mobile networks, mobile cloud computing, big data, data analytics techniques, and cloud computing, among others, must be mutually integrated for FinTech to thrive. To be approved by its users, this new technology must overcome serious security and privacy flaws. This research gives a thorough analysis of FinTech by discussing the present as well as expected confidentiality and safety problems facing the financial sector to protect FinTech. Finally, it examines potential obstacles to ensuring financial technology application security and privacy.
2024-06-16
Alen Lovrenčić
Dear readers, I had the pleasure of preparing the articles published in the Journal of Information and Organizational Sciences in the last four years. This is my issue, and I want to thank all who helped, every one in its way, the Journal to prosper. Firstly, I want to thank the authors who recognized JIOS as a decent journal adequate to publish their paper. Thanks to all the reviewers who helped me to classify received papers and raise the quality of the journal. Many of them were members of the editorial board which I want to address my thanks, too. The advisory board helped me to widen the pull of reviewers. At the end, I want to thank members of the publishing board who invested their time and work to improve the design of the journal and web page, and made it visible through the different journal bases. In the next issue, the function of the editor will be taken by Prof. Igor Balaban. I am sure that the Journal will become much better under his leadership. I wish good luck and pleasant work on our Journal to him and his team. Alen Lovrenčić
2024-06-16
David Leong
This study examines the complex interactions in organizational structures using Bohm's ‘wholeness’ and Prigogine’s equilibrium theories. Wave analogies and quantum principles like superposition, non-locality, and entanglement explain fluctuations in these systems. Thus, this research suggests a paradigm shift in organizational methods towards a balanced, scientific approach. Organizations need flexible tactics and behave like dissipative structures to maintain internal coherence in chaos. Heightened through mindful techniques, corporate consciousness provides insights into temporal dynamics, improving decision-making, market resilience, and an expanded organizational ethos founded in present awareness. This heightened consciousness and demand for organizational alignment and coherence empowers the corporate entities to succeed in present conditions and anticipate and address future obstacles. This study introduces ‘Mindful Corporate Entity’ (‘MCE’), emphasizing mindfulness as a critical tool for organizational well-being and sustainability. This change is proposed to close management gaps.
2023-12-22
Tamara Šmaguc, Ksenija Vuković
The paper examines traditional knowledge about the role of financial and physical resources in entrepreneurship. Based on Bourdieu's theory, we search for an answer to the question of which forms of economic capital are used by Croatian entrepreneurs in the computer programming industry and what their value in the context of accessing other forms of capital is. The study is based on a qualitative methodological approach. In-depth interview technique accompanied by unstructured observations was used in data collection. In addition to primary data, research includes the use of qualitative and quantitative secondary data. Research suggests that in the computer programming industry, economic capital is just one tool in the conversion game of entrepreneurial capital. Moreover, the interviewed entrepreneurs attach the least importance to it in business, favoring the value of intangible resources such as specialized knowledge, business connections and personal acquaintances. The company's start-up phase is characterized by the entrepreneur's reliance on personal savings, which is replaced by financing based on retained earnings in the later stages of business. Other forms of growth financing, such as bank loans and recapitalization of external investors, are used by a minority of larger companies, with a good base of symbolic capital. The results on capital conversions indicate relatively easy conversion of economic capital into cultural capital and symbolic capital, and less frequent use of economic capital to create social capital. Fresh insights into the entrepreneurs' perceptions provided by the study expand existing knowledge about entrepreneurship within the computer programming industry, suggesting that it is an industry with huge potential for young talents without a personal financial base that is commonly considered a precondition for entering entrepreneurship.
2023-12-22
Amine EL HADI, Youness MADANI, Rachid EL AYACHI, Mohamed ERRITALI
Search engines are now the main source for information retrieval due to the huge expansion of data on the internet over the last ten years. Providing users with the most relevant results for their queries poses a significant challenge for search engines. Semantic search engines, which go beyond traditional keyword-based searches, have appeared as advanced information retrieval systems to address this problem. These search engines produce more precise and pertinent search results because they understand the meanings of words and their relationships. They play a pivotal role in managing the vast amount of internet data, with a primary aim of enhancing search precision and user satisfaction. However, improving search precision remains as an important goal for natural language processing researchers. The main objective of our research is to improve the search engine results. We present a novel approach for measuring the similarity between a user’s query and a list of documents within a search engine. This approach provides a new fuzzy recommendation system using a syntactic and semantic similarity. Our results indicate that our method outperforms several existing approaches from the literature, achieving a high level of accuracy.
2023-12-22
Nimas Pratiwi, Siti Fatimah, April Kukuh Susilo
Concerning the human aspect of organizational sustainability, this study aims to comprehensively examine organizational support (OS), employee attitude (EA), psychological empowerment (PE), and innovative work behavior (IWB). This study analyzes the relationship between OS, EA, and IWB in flexible manufacturing systems (FMS) and focuses on PE's role as a mediator between OS and EA. By dividing OS into perceived supervisor support (PSS) and procedural justice (PJ) and dividing EA into a sense of belonging (SB) and sense of awe (SA). A questionnaire was used to survey 341 participants from 23 teams employed in 9 large manufacturing enterprises in Indonesia. Eight Hypotheses were examined with Structural Equation Modeling (SEM). Results demonstrated that OS significantly affects EA and IWB, and PE mediates OS and EA through IWB. In this article, we seek to empirically test the entire belonging dimension of the OS as it relates to EA and IWB. These variables were chosen because they have well-documented pragmatic value for organizations. They also have reliable and valid relationships with various organizational support concepts. Future studies should include more variables for determining OS and EA to provide further context for organizational sustainability studies, particularly in FMS-transitioning industries.
2023-06-30
Behrouz Liravinia, Mahmoud Modiri, Kiamars Fathi Hafshjani
Proper risk assessment and management are considered important issues in design improvement. This tendency has been due to the continuing uncertainty of the global economy and the advancement of information technology. Despite the most important and valuable benefits, developed design topics are more vulnerable and can expose the organization to higher levels of risk. Achieving sustainability is recognized as a growing and effective strategy to meet today's global design challenges. Design in the oil, gas and petrochemical industry is important due to its characteristics and high risk in different countries, especially Iran, due to its different effects on the environmental dimension. The issue of identifying and evaluating design risks has also been neglected in recent research. Therefore, the purpose of this study is to identify and evaluate design risks in Iran’s oil, gas and petrochemical industry. The present research is descriptive-survey and is qualitative and quantitative in terms of technique and data used. Based on the literature review, 13 risk factors affecting the design were identified, in two stages, in-depth interviews were conducted with the opinions of experts, and by collecting opinions through a questionnaire, and 10 key risk factors were finally confirmed. In the first stage, the validity of the questionnaire was finally confirmed based on the opinions of 5 experts and in the second stage, using the opinions of 8 experts in this industry. Cronbach's alpha coefficient of the risk questionnaire is higher than 0.7, which indicates the reliability of the research tool. According to the research findings, two factors such as weak technology / knowledge sustainability and environmental pollution, compared to other risk factors, have a higher priority in design projects in Iran's oil, gas and petrochemical industry. It is suggested that industry owners take serious and continuous measures in the field of "improving the level of process knowledge".
2023-06-30
Alen Lovrenčić
Dear readers, Again, in this issue we are bringing thirteen scientific papers from the wide field of information and communication sciences – three preliminary communications, eight survey papers, and five original scientific papers, authors of which are from Europe, Africa, and Asia. The papers are on a wide range of topics in information, organizational, and computer sciences, so I expect the issue to be interesting for a wide range of readers. Alen Lovrenčić Editor
2023-06-30
Dunja Dobrinić, Neven Vrček
The subject of this research is to determine the level of digital technology acceptance in micro and small organizations. There is a lack of research in the existing literature that would move away from existing models and theories and explain the reasons for digital technology acceptance by micro and small organizations. It was noticed that research on the intention to accept digital technologies in micro and small organizations needs to focus on moderating factors, the influence of which has been neglected in existing research. For this reason, a model for digital technology acceptance by micro and small organizations was created, which explored the effect of moderating factors and encompassed the key characteristics of micro and small organizations. The effect of perceived financial risk, perceived security risk, perceived loss of time, perceived government pressure, and the level of knowledge of decision-makers on the intention to accept digital technologies are examined. As well the relationship between external pressure (market participants' pressure and crisis circumstances) and the level of knowledge of decision-makers in organizations was explored. The focus of the research is to explore the moderating effect of the organization's digital maturity and competitive priorities on the relationship of factors (perceived security risk, perceived loss of time, perceived government pressure) and intent to accept digital technologies. The moderating effect of the decision-makers decision-making style on the relationship between external pressure (market participants' pressure and crisis circumstances) and the level of knowledge of decision-makers are explored as well.
2023-06-30
Xhavit Islami, Naim Mustafa
The purpose of this research is to measure the mediating role of teamwork and participation (T&P) on the relationship between two human resource (HR) practices – “training and development” (T&D) and “performance appraisal” (PA) – and operational performance (OP). Employing the contingency approach, this study develops a research model that validates the assumption that appropriate internal orchestration of HR practices improves firm performance. Using AMOS, data from 157 manufacturing firms are analyzed through structural equation modeling (SEM). The results show that T&P fully mediates the relationship between T&D and OP, and partially mediates the relationship between PA and OP. This study, which provides empirical support for the importance of OP to firm effectiveness, finds that OP is positively related to financial performance (FP). The study develops a theoretical logic and empirically demonstrates that T&P is an appropriate practice for mediating the impact of T&D and PA on OP. The inclusion of T&P contributes to the theory and shows that appropriate internal orchestration of HR practices can realize effective OP and consequently greater FP of the firm.
2023-06-30
Melita Draganić
The framework for assessing the company's digital capability includes six key areas that can be individually evaluated to consider the overall maturity of a company's digital capability. According to this framework key areas are innovation capability, transformation capability and IT excellence as digital transformation enablers and customer centricity, effective knowledge worker and operational excellence as digital transformation goals. The focus of this research is the area of operational excellence. The purpose of the paper is to assess how the manufacturing company manages the digital transformation of the operational excellence. In the paper, the digital capability maturity model (DCMM) and its corresponding business transformation management methodology (BTM 2 ) are used for this assessment. The BTM2 includes nine management disciplines and each of them is individually evaluated for the case of the operational excellence. These are the following disciplines: strategy management, value management, risk management, business process management, IT management, change management, training management, project management and meta management. According to the obtained assessment results the maturity of management disciplines for the case of operational excellence within the examined company is mostly reactive (maturity level 2). In order to improve the digital transformation of the company's operational excellence, it is necessary to define digital use cases based on the new technologies and map them to the existing maturity model of operational excellence of the company. It is necessary to consider the requirements of stakeholders regarding the benefits and risks of new digital technologies to improve the operational excellence of the company. Accordingly, the company should to define a new strategic plan and align it with the new IT strategy. For this purpose, COBIT 5 framework is used in the paper. The contribution of this research is in the proposed and described three-step approach to managing the operational excellence of companies and improving the level of digital capabilities of companies.
2022-12-22
Alen Lovrenčić
Dear readers, Again, in this issue we are bringing twelve scientific papers from the wide field of information and communication sciences – four preliminary communications, three survey papers, and five original scientific papers, authors of which are from Europe, Africa, and Asia. We are trying to keep and improve the high quality of the review process, resulting in the high quality of the papers on different topics of information and communication sciences, making the Journal interesting for a wide range of scientists from the field. I hope that you will find the papers published in this issue interesting and inspiring for your own research. Editor
2022-12-22
Adrian Stepniak, Pawel Baranowski
Deep convolutional neural networks (CNNs) became an industry standard in image processing. However, in order to keep their high efficiency, a large annotated sample is required in the case of supervised learning. In this paper we apply the techniques specific for relatively small sample to a court files dataset. Specifically, we propose transfer learning and semisupervised learning to classify scanned page as having a table or not. We use four CNNs architectures established in the literature and find that transfer learning improves the classification performance, compared to the fully supervised learning. This result is especially evident in the scenarios where only a part of convolutioanl layers are transferred. The gains from semisupervised learning are ambiguous, as the results vary over CNNs architectures. Overall, our results show that office documents classification can achieve high accuracy when transferring initial convolutional layers is applied.
2022-12-22
Victor Odumuyiwa, Seun Bamidele Osuntoki, Oladipupo Sennaike
The increasing usage of the Internet and other digital platforms has brought in the era of big data with the attending increase in the quantity of unstructured data that is available for processing and storage . However, the full benefits of analyzing this large quantity of unstructured data will not be realized without proper techniques and algorithms. Topic modeling algorithms have seen a major success in this area. Different topic modeling algorithms exist and each one either employs probabilistic or linear algebra approaches. Recent reviews on topic modeling algorithms dwell majorly on probabilistic methods without giving proper treatment to the linear-algebra-based algorithms. This review explores linear-algebra-based topic models as well as probability-based topic models. An overview of how models generated by each of these algorithms represent document thematic structure is also presented.