International Journal of Information Management Data Insights最新文献

{"title":"Transformer-based model for moroccan Arabizi-to-Arabic transliteration using a semi-automatic annotated dataset","authors":"Soufiane Hajbi ,&nbsp;Omayma Amezian ,&nbsp;Mouhssine Ziyad ,&nbsp;Issame El Kaime ,&nbsp;Redouan Korchyine ,&nbsp;Younes Chihab","doi":"10.1016/j.jjimei.2025.100351","DOIUrl":"10.1016/j.jjimei.2025.100351","url":null,"abstract":"<div><div>Language models have recently achieved state-of-the-art results in tasks such as translation, sentiment analysis, and text classification for high-resource languages. However, dedicated models for low-resource languages remain scarce, largely due to a lack of annotated data and linguistic resources. Most efforts focus on fine-tuning models trained on high-resource languages using limited data, resulting in a substantial performance gap. Moroccan Darija (MD), widely spoken in Morocco, lacks language resources and dedicated models. Additionally, MD texts often employ the Arabizi writing form, which combines Latin characters and numbers with Arabic script, further complicating Natural Language Processing (NLP) tasks. This work presents the first transformer-based model designed specifically for transliterating Moroccan Arabizi to Arabic. The approach leverages a character-level modeling architecture and a semi-automatically generated dataset containing over 33k word pairs, capturing significant linguistic diversity. The model achieves a state-of-the-art word transliteration accuracy (WTA) of 93 % and a character error rate (CER) of 4.73 % on unseen Moroccan Arabizi data, highlighting the potential of transformer models to improve transliteration accuracy for low-resource languages, particularly MD.</div></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"5 2","pages":"Article 100351"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144313205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Achieving operational excellence through artificial intelligence: The case of Ghanaian banks","authors":"Acheampong Owusu","doi":"10.1016/j.jjimei.2025.100377","DOIUrl":"10.1016/j.jjimei.2025.100377","url":null,"abstract":"<div><div>Using the resource-based theory as the lens, this research proposes a conceptual model to explore the determinants of AI in the Ghanaian banking sector and also examine its impact on the OpEx of the banks. The study adopted a quantitative research approach with a survey method to collect data from 331 CIOs/IS/IT Managers/Data Scientists/Business Analysts and other knowledgeable managers in the Ghanaian banks who were sampled via stratified and purposive sampling techniques. The data analysis was done via partial least squares structural equation modelling (PLS-SEM). The findings revealed the determinants of AI adoption in the Ghanaian banks are Absorptive Capacity, Agility and Capabilities of the banks. Also, it was established from the empirical results that the adoption of AI enhances OpEX of the banks. The determinants obtained in this study would lay a foundation for future research which could be incorporated into a new theoretical model of AI adoption.</div></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"5 2","pages":"Article 100377"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145323989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning and probabilistic analysis strategies for defect reduction in windshield manufacturing","authors":"Carlos Guachamín-Chicaiza ,&nbsp;Freddy Hernán Villota-González ,&nbsp;Virgilio Zúñiga-Grajeda","doi":"10.1016/j.jjimei.2025.100383","DOIUrl":"10.1016/j.jjimei.2025.100383","url":null,"abstract":"&lt;div&gt;&lt;div&gt;Defects in automotive windshields (e.g., breakages, bubbles, cracks) compromise safety, increase production costs, and reduce product quality. This study integrates machine learning techniques and probabilistic modeling to optimize defect classification and derive prescriptive strategies for windshield manufacturing. A dataset of 1151 samples was analyzed through: (i) descriptive and correlational analysis of categorical (Thickness, Paint, Color, Tone, Sanding) and continuous (Weight, Area) variables; (ii) clustering and t-SNE for group identification; (iii) a stacking ensemble (MLP, Gradient Boosting, Random Forest, SVM, CatBoost) for classification; and (iv) probabilistic modeling with Shannon entropy for uncertainty assessment. Descriptive analysis revealed several important patterns. Area showed a bimodal distribution (IQR = 1.27–12.76 m², maximum = 39.89 m²), with Breaks more frequent in smaller surfaces and Cracked defects in larger ones (&lt;em&gt;H&lt;/em&gt; = 111.86, &lt;em&gt;p&lt;/em&gt; &lt; 0.001, η² = 0.024). Thickness &lt;5 mm was linked to higher Breaks (&lt;em&gt;H&lt;/em&gt; = 19.16, &lt;em&gt;padj&lt;/em&gt; = 1.8 × 10⁻⁴, η² = 0.022). Correlational analysis identified a moderate association between Tone and Color (Cramér’s &lt;em&gt;V&lt;/em&gt; = 0.50), while Sanding was largely independent (&lt;em&gt;V&lt;/em&gt; ≤ 0.20). Kruskal–Wallis tests confirmed that Thickness (&lt;em&gt;H&lt;/em&gt; = 240.10, &lt;em&gt;p&lt;/em&gt; &lt; 0.001) and Tone (&lt;em&gt;H&lt;/em&gt; = 136.18, &lt;em&gt;p&lt;/em&gt; &lt; 0.001) were significantly associated with Weight and Area. Clustering (&lt;em&gt;k&lt;/em&gt; = 3, silhouette = 0.27) differentiated groups characterized by low weights/small areas with Breaks, larger areas with Cracked, and heavier compact units with Bubbles. The ensemble achieved a weighted F1-score of 0.83 on the hold-out test, with AUC = 0.96 (Breaks), 0.98 (Bubbles), 0.91 (Cracked). Its performance followed the same tendencies suggested by the exploratory phase, where nonlinear relationships between Thickness, Weight, and Area were already apparent. Building on this, probabilistic modeling refined the insights by detecting critical sensitivity thresholds: Breaks &gt;60 % below 20 kg, with a high-risk zone at 11.3–17.2 kg (η² = 0.028), and Bubbles slightly increasing in heavy windshields &gt;60–70 kg (≤15 %). Together, these results show a coherent narrative: exploratory analyses highlighted patterns, the model aligned with those trends, and probabilistic methods quantified the operational limits where defects become most likely. Based on this integrated analysis, three interventions were proposed: (i) structural reinforcement of thin glass (&lt;5 mm), (ii) implementation of automated handling for large-area windshields, and (iii) ergonomic protocols to minimize operator-related defects. Overall, the complementarity between exploratory, modeling, and probabilistic approaches not only validated defect mechanisms but also provided prescriptive strategies for quality control. Nevertheless, limitations include the reliance on data from a single","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"5 2","pages":"Article 100383"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145570936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Blockchain technology to improve traceability in the coffee supply chain: A systematic literature review","authors":"Christian Gómez,&nbsp;Benoit Garbinato","doi":"10.1016/j.jjimei.2025.100359","DOIUrl":"10.1016/j.jjimei.2025.100359","url":null,"abstract":"<div><div>Coffee is consumed worldwide, with its supply chain starting with coffee growers, who benefit least from it. Across its production, distribution, and commercialization processes, there are risks and issues that could damage the safety and authenticity of this product. Therefore, the coffee industry is looking for innovative technologies that allow traceability in the coffee supply chain. In this context, blockchain technology offers a promising solution as it supports traceability via a decentralized system that allows immutable records and transparent access; it also promotes collaborative work and removes intermediaries by generating trust between participants. This systematic literature review describes the state-of-the-art in research and development about the use of blockchain technology to improve traceability in the coffee supply chain. We also outline the open challenges that remain to be addressed in this field. We use the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) methodology to achieve this goal. Our findings suggest that the developments are mainly conceptual designs and prototypes, focusing on tracing products and verifying their authenticity using the Ethereum or Hyperledger blockchains. Also, our results show various challenges on the technology side, like efficiency improvements, integration with other technologies, infrastructure, and a lack of standards. There are also challenges at the management level, like the necessity of agreements for traceability processes, data governance, willingness to invest and pay, education, and support to deploy the technology on farms. After overcoming these open challenges, blockchain technology can improve traceability and increase value for stakeholders in the coffee supply chain.</div></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"5 2","pages":"Article 100359"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144695251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mitigating uncertainty in travel agency selection in Jordan: A signaling theory approach","authors":"Fadi Herzallah ,&nbsp;Bashar Alhaj Mohammad ,&nbsp;Mahmoud Alhayek ,&nbsp;Syed Md. Faisal Ali Khan","doi":"10.1016/j.jjimei.2025.100362","DOIUrl":"10.1016/j.jjimei.2025.100362","url":null,"abstract":"<div><div>Uncertainty plays a critical role in tourism purchase decisions, particularly in developing markets. This study investigates how Jordanian tourists reduce uncertainty when buying package tours by applying signaling theory. A questionnaire was distributed to 450 tourists with prior travel agency experience, yielding 376 valid responses analyzed using PLS-SEM and IPMA. Results show that information quality, popularity, positive comments, and reputation significantly reduce uncertainty about travel agencies, while return policy has no significant effect. Moreover, uncertainty negatively influences purchase decisions. IPMA findings highlight that reputation is the most important factor in reducing uncertainty, followed by popularity and positive comments. Although return policy scores highest in performance, it has the least impact on uncertainty. This study contributes to tourism literature by identifying specific customer-seller signals that influence perceived uncertainty and by clarifying the link between uncertainty reduction and purchase behavior in the context of travel agencies in developing countries.</div></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"5 2","pages":"Article 100362"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144764043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding sustainable technologies use: The role of empowerment and cultural dimensions","authors":"Catarina Neves ,&nbsp;Tiago Oliveira ,&nbsp;Stylianos Karatzas","doi":"10.1016/j.jjimei.2025.100375","DOIUrl":"10.1016/j.jjimei.2025.100375","url":null,"abstract":"<div><div>Given today’s paradigm of environmental crises, studies on the role of technology for sustainable purposes are now more relevant than ever. Therefore, this work analyses sustainable technology use behaviours from a social perspective, evaluating the impact of empowerment and culture-specific dimensions: context and time perception. For that, a research model is created and tested with a sample of 400 responses using structural equation modelling. This study reveals a strong positive impact of empowerment on deep structure use and cognitive absorption. Additionally, time perception is found to be a positive moderator between empowerment and user behaviors. These findings are relevant for theory - exploring the explanatory power of empowerment in a sustainable context, as well as the importance of cultural dimensions in understanding user behaviors – and practice – better understanding strategies to increase sustainable technologies use.</div></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"5 2","pages":"Article 100375"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145218939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analyzing the evolution of environmental policy themes and governance stakeholder networks: A computational approach","authors":"Yong Zhu,&nbsp;Gang Li","doi":"10.1016/j.jjimei.2025.100382","DOIUrl":"10.1016/j.jjimei.2025.100382","url":null,"abstract":"<div><div>Environmental policy is a critical tool for countries to establish principles and guidelines for effective environmental governance. This paper explores the evolution of environmental policy themes and stakeholder networks in China’s governance framework over a decade. Based on a dataset of 1,153 policy documents from 31 provinces, this study applies natural language processing for tokenization and utilizes unsupervised and supervised machine learning techniques — Dynamic Topic Modeling for topic detection and Named Entity Recognition for stakeholder extraction. Through spatio-temporal analysis and network analysis, this innovative approach provides new insights into governance dynamics and establishing a novel research paradigm for the academic community. Findings indicate a significant transition from a government-centric approach to a collaborative multi-stakeholder governance model that enhances data-driven decision-making and offers practical recommendations for policymakers.</div></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"5 2","pages":"Article 100382"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145519050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Robot resistance in the land of smiles: Unraveling the behavior of Thai consumers toward restaurant service robots","authors":"Noptanit Chotisarn ,&nbsp;Nontouch Srisuksa ,&nbsp;Rachanon Taweephol ,&nbsp;Panuschagone Simakhajornboon ,&nbsp;Thadathibesra Phuthong","doi":"10.1016/j.jjimei.2025.100379","DOIUrl":"10.1016/j.jjimei.2025.100379","url":null,"abstract":"<div><div>This study examined resistance to service robots among younger, educated Thai consumers in chain restaurants and addressed the research gaps to better understand technology adoption in non-Western markets. Data were analyzed from 325 Thai consumers using structural equation modeling. Five significant resistance factors were identified as interaction discomfort (β = 0.361), service robot personality (β = 0.217), warmth competence (β = 0.170), perceived service failure (β = 0.169), and inflexibility (β = -0.166). The counterintuitive negative effect of inflexibility suggested that predictable, standardized robot behavior may reduce resistance in Thailand, challenging Western assumptions about customization. Our model demonstrated strong explanatory power (R² = 0.586), extending innovation resistance theory (IRT) to service robotics by identifying culturally specific barriers in an emerging market. The findings suggested that prioritizing improved robot-customer interactions while leveraging predictability would be a service advantage in Thai cultural contexts.</div></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"5 2","pages":"Article 100379"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145323990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"BAR-analytics: A web-based platform for analyzing information spreading barriers in news: Comparative analysis across multiple barriers and events","authors":"Abdul Sittar,&nbsp;Dunja Mladenić,&nbsp;Alenka Guček,&nbsp;Marko Grobelnik","doi":"10.1016/j.jjimei.2025.100368","DOIUrl":"10.1016/j.jjimei.2025.100368","url":null,"abstract":"<div><div>This paper presents BAR-Analytics, a web-based, open-source platform designed to analyze news dissemination across geographical, economic, political, and cultural boundaries. Using the Russian–Ukrainian and Israeli–Palestinian conflicts as case studies, the platform integrates four analytical methods: propagation analysis, trend analysis, sentiment analysis, and temporal topic modeling. Over 350,000 articles were collected and analyzed, with a focus on economic disparities and geographical influences using metadata enrichment. We evaluate the case studies using coherence, sentiment polarity, topic frequency, and trend shifts as key metrics. Our results show distinct patterns in news coverage: the Israeli–Palestinian conflict tends to have more negative sentiment with a focus on human rights, while the Russia–Ukraine conflict is more positive, emphasizing election interference. These findings highlight the influence of political, economic, and regional factors in shaping media narratives across different conflicts.</div></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"5 2","pages":"Article 100368"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144925140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Retrieving and discovering new knowledge from documents' abstracts in scientific databases: Proposing a query-based abstractive summarization model","authors":"Neda Abbasi Dashtaki ,&nbsp;Mehrdad CheshmehSohrabi ,&nbsp;Mitra Pashootanizadeh ,&nbsp;Hamidreza Baradaran Kashani","doi":"10.1016/j.jjimei.2025.100366","DOIUrl":"10.1016/j.jjimei.2025.100366","url":null,"abstract":"<div><div>Current search engines for Knowledge Retrieval (KR) and Knowledge Discovery (KD) do not effectively utilize scientifically validated documents, especially those indexed in scientific databases. Scientific databases e.g., Scopus primarily consist of document-based content and provide documents' abstract. Their Information Retrieval (IR) system only perform document searches and lack the capability to extract and discover new knowledge from documents' abstract in these databases and responding to users’ queries. The aim is to introduce a model that can efficiently perform these tasks. The statistical population for this study encompasses all scientific databases, with a particular emphasis on Scopus. To clarify the process of KR and KD as we define it, we employed a systematic review and meta-analysis framework using 33 queries. We conducted the identification, screening, eligibility, and inclusion steps following the PRISMA protocol. Next, we performed extraction, labeling, grouping, analysis, and inference. The outcome of these processes provided us with novel insights, which contribute to our exploratory knowledge. To automate these processes, we have proposed a conceptual model from query-based indirect abstractive summarization approach. The outcomes of this research offer fresh insights to database designers, administrators, and researchers, enabling the development of tools for KR and KD within these invaluable knowledge repositories. The integration of such tools into scientific databases will enhance user access to scientific knowledge to meet their informational and research needs.</div></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"5 2","pages":"Article 100366"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144931756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}