International Journal of Information Management Data Insights最新文献

{"title":"Exploring the drivers of digital technology adoption for enhancing domestic tax mobilization in Ghana","authors":"Alexander Asmah,&nbsp;Kingsley Ofosu Ampong,&nbsp;Dzifa Bibi,&nbsp;Wihlemina Ofori","doi":"10.1016/j.jjimei.2025.100327","DOIUrl":"10.1016/j.jjimei.2025.100327","url":null,"abstract":"<div><h3>Purpose</h3><div>This study investigates the determinants of tax compliance through the lens of performance expectancy, effort expectancy, social influence, facilitating conditions and hedonic motivation.</div></div><div><h3>Design/methodology/approach</h3><div>The study adopted both quantitative and qualitative research methods to gather data on the adoption of tax technologies. Based on the five determinants, a conceptual framework was developed consisting of seven proposed hypotheses tested through a structural equation model. Interviews were conducted to gain further insight into the drivers of the taxpayers’ portal in Ghana.</div></div><div><h3>Findings</h3><div>The study finds that performance expectancy and effort expectancy are the most significant factors predicting tax compliance intentions, indicating that taxpayers consider the portal as a useful tool in managing their taxes and very easy to use. It reduces their exposure to corrupt government officials and lessens their cost of paying taxes. It is also very convenient and serves as a useful way to avoid the long queues they experience at the tax offices. The study recommends that the Ghana Revenue Authority (GRA) and the Ministry of Finance (MoF) should promote more revenue collection technologies and create more awareness among taxpayers to utilise the portal.</div></div><div><h3>Originality/value</h3><div>The taxpayers’ portal in Ghana was recently introduced to enhance revenue mobilisation. No empirical research has been conducted to identify the adoption factors which will aid its smooth implementation. This paper thus provides significant value to both literature and practice.</div></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"5 1","pages":"Article 100327"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143095585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Blockchain-based conceptual model for enhanced transparency in government records: a design science research approach","authors":"Eid M Alotaibi ,&nbsp;Hussein Issa ,&nbsp;Mauricio Codesso","doi":"10.1016/j.jjimei.2024.100304","DOIUrl":"10.1016/j.jjimei.2024.100304","url":null,"abstract":"<div><div>In recent years, there have been massive changes to the government reporting requirements, which reflect the government's recognition of the need for a more open evidence-based practice. As a response, the U.S. government ordered to apply open government in all government agencies. The open government's objective is to have open government systems that include open access to their records, procedures, and data for public review and engagement. Currently, government agencies control and filter shared data with the public, limiting the ability to efficiently and effectively promote public oversight. This paper proposes a conceptual model, named GovBlockchain, that has the potential to achieve open government data objectives. The GovBlockchain is illustrated using the procurement cycle, and the results are subsequently compared with current open government practice. The results indicate that GovBlockchain provides stakeholders with a higher level of transparency.</div></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"5 1","pages":"Article 100304"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142664167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"User-driven technology in NGOs—A computationally intensive theory approach","authors":"Marie-E. Zubler (née Godefroid) ,&nbsp;Julian Koch ,&nbsp;Ralf Plattfaut","doi":"10.1016/j.jjimei.2024.100307","DOIUrl":"10.1016/j.jjimei.2024.100307","url":null,"abstract":"<div><div>Non-governmental organizations (NGOs) typically have restrained information and communication technology (ICT) budgets and resources. At the same time, they face high pressure to reduce administrative costs. A possible solution to the resulting conundrum could be user-driven technology. This term describes a selection of technologies, including intelligent process automation, low-code platforms, and business intelligence tools that push innovation and user-centricity by letting operational employees directly deploy comparably cheap solutions without the need for central ICT support. Practitioner literature indicates, however, that user-driven technologies are lagging in the social sector despite evidence from some individual success stories published by researchers. Thus, a systematic assessment of user-driven technologies within NGOs and of potential challenges in their introduction is necessary. To close this research gap, we employ the method of computationally intensive theory construction, combining data mining with qualitative interviews. Results indicate that user-driven technologies are indeed lagging and that forming a problem-mindset and creating adequate governance structures are the main challenges to their introduction within NGOs.</div></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"5 1","pages":"Article 100307"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142664169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sentiment works in small-cap stocks: Japanese stock’s sentiment with language models","authors":"Masahiro Suzuki ,&nbsp;Yasushi Ishikawa ,&nbsp;Masayuki Teraguchi ,&nbsp;Hiroki Sakaji","doi":"10.1016/j.jjimei.2024.100318","DOIUrl":"10.1016/j.jjimei.2024.100318","url":null,"abstract":"<div><div>We calculate sentiment from the Japanese Company Handbook, which contains a compact overview of Japanese companies’ business situation and financial data, using multiple methods, including large language models. Language models such as BERT and ChatGPT are advancing the application of natural language processing (NLP) to financial fields. We construct multiple sentiment calculation methods using sentiment dictionaries, models trained on existing sentiment datasets, ChatGPT, and GPT-4. Our analysis shows that stocks with higher sentiment scores tend to have higher excess returns, while those with lower scores tend to have lower excess returns. This feature is enhanced particularly in small-cap stocks. Comparisons between the models showed higher returns at high sentiment for the model trained with the existing sentiment dataset and lower returns at low sentiment for ChatGPT. The DeBERTaV2 model trained on Economy Watchers Survey data performed best in terms of returns at the highest sentiment quantile.</div></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"5 1","pages":"Article 100318"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143096272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Wearable IoT (w-IoT) artificial intelligence (AI) solution for sustainable smart-healthcare","authors":"Gurdeep Singh","doi":"10.1016/j.jjimei.2024.100291","DOIUrl":"10.1016/j.jjimei.2024.100291","url":null,"abstract":"<div><div>Smart technologies, specifically wearables are cutting edge innovation of design science with an emerging Artificial Intelligence (AI) capability for sustainable healthcare. Wearable IoT (w-IoT) applications, solutions and systems can promote early warning measures for physiological parameter monitoring and other vital health observation while addressing, streamlining and enhancing emergency response procedures in the provision and deliverance of healthcare services. These solutions exhibit real-time responses with underlying machine-learning (ML) methodologies alongside ubiquitous, context-aware, pervasive and advance software features. AI frameworks, for the development and implementation of solutions are well covered in this study adopting design science (DS) principles for new product development (NPD), comprising various healthcare scenarios for distributed numbers and environments. Physiological or health activity-related data produced by embedded optical smartwatch sensors can instigate sustainable and economical health-oriented solutions for continuous monitoring, semantic predictions for constrained, intractable and autonomous environments to address cardiac disorders. This paper addresses, the practical implementation of the w-IoT health technology solution prototype for real-time applicability, covering problem identification and utilizing design science guidelines, evaluation and contribution by emphasizing on the experimental stage in general and with specificity. It covers performance results rendering research science communication on machine learning models for time series analysis, regression and classification to implement defined and adaptive thresholds, adopting standard deviation and moving average, computing mean square error (MSE), root mean square error (RSME) and mean absolute error (MAE) values, utilizing exponential moving average results on multiple features, prominently targeting resting heartrate data. Machine Learning algorithms for classification with higher F-score or performance metrics adopted are Decision Trees (DT), K-Nearest Neighbours (KNN), XGboost, One-class SVM and Logistic Regression. In Binary classification, KNN achieved F-score of 91 %, followed by DT at 81 % which seems an effective algorithm with flexibility on overfitting with high accuracy result. This study will cover all stages of design science methodology, guidelines for w-IoT healthcare solution development, by presenting experimental prototype towards pipeline implementation to address healthcare needs, alleviating previously prevalent Body Area Networks (BANs) solutions precision with advancing w-IoT smart technologies or Wireless Body Sensor Networks (WBSNs).</div></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"5 1","pages":"Article 100291"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143095580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A robust scheme for securing relational data incremental watermarking","authors":"Maikel Lázaro Pérez Gort,&nbsp;Agostino Cortesi","doi":"10.1016/j.jjimei.2025.100320","DOIUrl":"10.1016/j.jjimei.2025.100320","url":null,"abstract":"<div><div>Watermarking techniques aim to protect relational databases by embedding on them a copyright signal known as the watermark without imposing additional restrictions. However, unlike other digital assets, such as multimedia data, relational data are often subject to frequent updates that may dramatically compromise the quality of the embedded watermark. Hence, it is relevant to implement incremental watermarking for this type of data. Although incremental watermarking is defined in theory as the requirement of generating and inserting a mark whenever data is inserted or updated in a watermarked database (if the new value requires marking), its practical deployment is often ignored in the validation of proposed techniques, possibly due to how its deployment affects other requirements, such as the public system and security. In this work, we present different architectural approaches that, rather than conflicting with security and the public system, are built upon and contribute to them. The experimental results validate their applicability in terms of deployment, portability, scalability, and performance. As an architectural proposal, our work can be applied to different watermarking techniques, regardless of their particularities and the protected databases, making the preservation and enhancement of the watermark possible. Thus, we face the silent threats to security posed by opportunistic malicious operations in the absence of incremental watermarking.</div></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"5 1","pages":"Article 100320"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143095584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Digital transformation in the real estate industry: A systematic literature review of current technologies, benefits, and challenges","authors":"Basheer Al-haimi ,&nbsp;Haliyana Khalid ,&nbsp;Nor Hidayati Zakaria ,&nbsp;Tuti Haryati Jasimin","doi":"10.1016/j.jjimei.2025.100340","DOIUrl":"10.1016/j.jjimei.2025.100340","url":null,"abstract":"<div><div>The digital transformation of the real estate sector constitutes a pivotal and dynamic field of inquiry as emergent technologies incessantly alter conventional methodologies. This systematic literature review evaluates the integration, utilization, and ramifications of significant digital transformation technologies within the real estate sector, with a particular focus on artificial intelligence (AI), the Internet of Things (IoT), blockchain technology, augmented reality (AR), virtual reality (VR), and digital twins. Employing the PRISMA methodology, an exhaustive search across four principal academic databases yielded 36 studies that provide a solid foundation for comprehensive analysis. This review elucidates how these technologies fundamentally restructure real estate operations, encompassing property management, investment evaluation, consumer interaction, and operational frameworks. The findings demonstrate that digital transformation yields substantial advantages for stakeholders, including property managers, investors, purchasers, and tenants. Principal benefits comprise enhanced operational efficiency, improved data-driven decision-making, and augmented user engagement. Nevertheless, the review underscores significant obstacles, such as elevated implementation costs, apprehensions regarding data security, resistance to technological advancement, and integration challenges that may obstruct seamless assimilation. By furnishing precise analyses regarding these advantages and obstacles, this review presents pragmatic methodologies for industry practitioners to maneuver through digital transformation effectively. It advocates for implementing modular technology to optimize financial expenditures and emphasizes the necessity of resilient cybersecurity protocols to mitigate data-related apprehensions. Subsequent investigations ought to concentrate on the enduring implications of these technologies on market dynamics and the fulfillment of stakeholders.</div></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"5 1","pages":"Article 100340"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143937119","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":"Financial textual sentiment connectedness: Evidence from alternative data","authors":"Yudhvir Seetharam,&nbsp;Kingstone Nyakurukwa","doi":"10.1016/j.jjimei.2025.100337","DOIUrl":"10.1016/j.jjimei.2025.100337","url":null,"abstract":"<div><div>This study investigates the connectedness of various firm-level investor sentiment proxies—news, social media, ESG positive (ESGpos), and ESG negative (ESGneg) sentiment using aggregate connectedness measures and a sample of DJIA stocks between 2015 and 2024. Our findings reveal that each sentiment proxy maintains strong internal consistency, predominantly shaped by its own sources. Specifically, news and social media exhibit high self-connection scores, indicating that these proxies are primarily influenced by their respective content. ESG sentiment proxies show minimal cross-influence from news and social media, indicating their distinct and independent nature. Network analysis further highlights that news and social media transmit sentiment shocks, while ESG-based proxies are predominantly receivers. The most significant flow of sentiment shocks is from social media to ESG negative sentiment. This reflects the central role of social media in shaping sentiment within the system, in contrast to the more isolated influence of news. During significant global event periods, ESGpos and ESGneg shift roles, with ESGpos becoming a transmitter and ESGneg a receiver of sentiment shocks. Sector-specific analysis shows that the Financials (Technology) sector is a net transmitter (receiver) of sentiment shocks. The practical implications of the findings are discussed. The paper contributes to the literature, which has treated different sentiment proxies as distinct phenomena despite their interconnectedness. Additionally, we find that the aggregate connectedness measures used in this study exhibit stronger connectedness compared to the traditional Diebold-Yilmaz framework.</div></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"5 1","pages":"Article 100337"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143791105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial: Artificial intelligence, digitization, sustainable development goals & global disruptions","authors":"Sonali Bhattacharya ,&nbsp;Manish Sinha ,&nbsp;Vincent Dutot ,&nbsp;Shahriar Akter ,&nbsp;V G Venkatesh","doi":"10.1016/j.jjimei.2025.100334","DOIUrl":"10.1016/j.jjimei.2025.100334","url":null,"abstract":"<div><div>This editorial summarizes the content of the special issue. It begins with the motivations behind the initiation of the special issue proposal and is followed by summarization of existing literature on the topic through a bibliometric analysis from a SCOPUS database. Finally, it shortly presents the special issue articles on the topical areas such as artificial intelligence, digitization, sustainable goals, and global disruptions. The deliberations will help both academics and professionals to expand their knowledge boundaries of these domains.</div></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"5 1","pages":"Article 100334"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144231612","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":"Harnessing the potential of generative AI in digital marketing using the Behavioral Reasoning Theory approach","authors":"Sujata Joshi ,&nbsp;Sonali Bhattacharya ,&nbsp;Pankaj Pathak ,&nbsp;N.A. Natraj ,&nbsp;Juhi Saini ,&nbsp;Soumya Goswami","doi":"10.1016/j.jjimei.2024.100317","DOIUrl":"10.1016/j.jjimei.2024.100317","url":null,"abstract":"<div><div>Generative AI (GAI) is an upcoming field and its impact on marketing is indisputable. Very little evidence in academic literature is present regarding the factors affecting the usage of GAI in Digital Marketing (DM). This study addresses this gap by exploring the key drivers and barriers associated with using GAI in DM. Leveraging Behavioral Reasoning Theory (BRT), the research validates prior findings and introduces a conceptual model outlining factors that shape attitudes toward adopting GAI in DM to enhance customer experiences.</div><div>A qualitative inductive approach was undertaken by conducting expert interviews to investigate the “reasons for” and ‘reasons against’ using GAI in DM and its impact on customer experience. The transcripts generated were manually coded and a deductive thematic analysis was done using the BRT as the theoretical framework.</div><div>The findings indicate four significant themes for adopting GAI in digital marketing viz: innovation, creative communication and content creation, speed, efficiency and timesaving, enhanced customization and personalization; predictive analytics and simulation. It also indicates five significant themes related to the key barriers were also identified viz: ethics and infringement of Intellectual Property; security and deepfake; learning ecosystem for the adoption of new technology; quality of data; reduced manpower requirement. The study further highlights how GAI influences customer experience in DM.</div><div>This study contributes to the field by (a) proposing a conceptual framework for applying GAI in DM to improve customer experiences, (b) examining the drivers and challenges of GAI adoption in DM, and (c) presenting a research agenda to guide future studies. These insights offer value to researchers, marketing practitioners, and academics navigating the dynamic intersection of GAI and Digital Marketing</div></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"5 1","pages":"Article 100317"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143096268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}