International Journal of Information Management Data Insights最新文献

{"title":"Forecasting cryptocurrency returns using classical statistical and deep learning techniques","authors":"Nehal N. AlMadany ,&nbsp;Omar Hujran ,&nbsp;Ghazi Al Naymat ,&nbsp;Aktham Maghyereh","doi":"10.1016/j.jjimei.2024.100251","DOIUrl":"https://doi.org/10.1016/j.jjimei.2024.100251","url":null,"abstract":"<div><p>The emergence of cryptocurrencies has generated enthusiasm and concern in the modern global economy. However, their high volatility, erratic price fluctuations, and tendency to exhibit price bubbles have made investors cautious about investing in them. Consequently, it is essential to develop methods and models to forecast cryptocurrency returns to benefit investors, traders, and the scientific community. Despite the considerable volume of research on Bitcoin price forecasting, other cryptocurrencies have received little attention in academic literature. Additionally, the current body of literature on predicting cryptocurrency prices or returns emphasizes the use of in-sample methodologies. However, this method is susceptible to overfitting. To address these gaps in the literature, this study employs autoregressive moving average (ARMA), generalized autoregressive conditional heteroskedasticity (GARCH), exponential generalized autoregressive conditional heteroskedasticity (EGARCH), and long short-term memory (LSTM) deep learning neural networks to forecast returns for the ten most actively traded digital currencies: Bitcoin, Ethereum, Ripple, Chainlink, Litecoin, Cardano, Ethereum Classic, Bitcoin Cash, Tether, and Binance Coin. To assess the accuracy of the two models, this study utilizes an out-of-sample method with data gathered sequentially from November 9, 2017, to September 18, 2022. The results indicate that all models exhibit high accuracy, as evidenced by their low root mean square error (RMSE), mean absolute error (MAE), and mean squared error (MSE) values. Meanwhile, the hybrid EGARCH-LSTM or GARCH-LSTM models demonstrate slightly better accuracy compared with the other models. The findings are valuable for investors, traders, and researchers involved in cryptocurrency forecasting.</p></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"4 2","pages":"Article 100251"},"PeriodicalIF":0.0,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667096824000405/pdfft?md5=0f01b5aca6e5ef34121a507ba9a98cd9&pid=1-s2.0-S2667096824000405-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141083767","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":"Does service quality matter in FinTech payment services? An integrated SERVQUAL and TAM approach","authors":"Vikas Sharma ,&nbsp;Kshitiz Jangir ,&nbsp;Munish Gupta ,&nbsp;Ramona Rupeika-Apoga","doi":"10.1016/j.jjimei.2024.100252","DOIUrl":"https://doi.org/10.1016/j.jjimei.2024.100252","url":null,"abstract":"<div><p>As the number of FinTech start-ups continues to rise globally, the utilization of these services by users becomes increasingly crucial, especially considering potential risks. Various factors affect users' utilization of financial technology, with the quality of services offered by FinTech providers standing out as a significant consideration. The aim of this study is to investigate the relationship between the quality of services offered by FinTech payment platforms and the utilization of FinTech services. We develop a novel conceptual model integrating elements from SERVQUAL and TAM (the Technology Acceptance Model) to investigate these dynamics. To gain a comprehensive understanding, we employed a mixed methods research approach. This approach included a quantitative survey analyzed using a partial least squares structural equation model (PLS-SEM) to examine the proposed framework and the relationships between its constructs. Following the survey, a follow-up focus group discussion with industry experts and academics was conducted to delve deeper into the findings and explore the \"why\" behind the statistical relationships. The findings reveal a significant impact of the quality of services offered by FinTech payment service providers on the utilization of such services. It demonstrates that in the FinTech sector, perceived usefulness does not always dominate perceived ease of use. Moreover, it confirms the profound influence of perceived usefulness in shaping attitudes and subsequent behaviour related to technology use. These insights contribute to an enhanced understanding of the factors driving the utilization of FinTech services.</p></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"4 2","pages":"Article 100252"},"PeriodicalIF":0.0,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667096824000417/pdfft?md5=ee3c88fe482fc94dfd68ebbc6a19e91d&pid=1-s2.0-S2667096824000417-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141078186","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":"From self-descriptions (SD) to self-recommendations (SR): Evolving Gaia-X for the future European economy","authors":"Vincent Geilenberg ,&nbsp;Wolfgang H. Schulz ,&nbsp;Jonathan Mize ,&nbsp;Henrik Kleis","doi":"10.1016/j.jjimei.2024.100249","DOIUrl":"https://doi.org/10.1016/j.jjimei.2024.100249","url":null,"abstract":"<div><p>The European decentralized-organized data-infrastructure ecosystem Gaia-X faces the challenge of initiating, maintaining, and intensifying data exchange between data providers and data consumers in all its Gaia-X data exchange domains to contribute significantly to the future viability of the European economy. The overall success of Gaia-X would enhance the innovative power and competitiveness of European companies and reduce their dependence on American and Chinese platform companies. This paper analyzes how the Big Data era affects the design of centralized-organized and decentralized-organized platforms and applies the findings to Gaia-X. It proposes to extend the Self-Descriptions (SD) already firmly embedded in Gaia-X with so-called Self-Recommendations (SR) because, in this way, the decentralized-organized data-infrastructure ecosystem Gaia-X can better express its advantages over centralized-organized platform companies.</p></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"4 2","pages":"Article 100249"},"PeriodicalIF":0.0,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667096824000387/pdfft?md5=93a626e5a29d4fdfc128d6be09324706&pid=1-s2.0-S2667096824000387-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140951330","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":"Artificial intelligence technology readiness for social sustainability and business ethics: Evidence from MSMEs in developing nations","authors":"Apoorva Vikrant Kulkarni ,&nbsp;Shaji Joseph ,&nbsp;Kanchan Pranay Patil","doi":"10.1016/j.jjimei.2024.100250","DOIUrl":"https://doi.org/10.1016/j.jjimei.2024.100250","url":null,"abstract":"<div><p>Social, economic, and environmental development together contributes to sustainable development. Social sustainability (SS) is essential to create just and inclusive societies where people's basic needs are satisfied, human rights are protected, and social cohesion and fairness exist. To achieve holistic, sustainable development, policymakers and management must consider SS and environmental and economic considerations. Employees' social and behavioral interactions impact SS and business ethics. Micro, small, and medium enterprises (MSMEs) can learn from artificial intelligence (AI) for better decision-making, operational optimization, increased employability, and employee empowerment. Therefore, this research aims to assess how artificial intelligence technology affects SS and business ethics in the MSMEs. We studied the artificial intelligence (AI) readiness among MSME companies in developing nations. We analyzed AI readiness using the theory of technology-organization-environment (TOE). Further, we also studied AI readiness and its influence on business ethics and SS, which we measured through skill development, work conditions, environment, and safety among MSMEs. We collected the data from 236 MSME employees. We used Structural Equation Modeling using SmartPLS software for data analysis. The research findings indicated that AI readiness directly impacts SS. We also found that the findings directly impact employees' social and ethical behavior. We also observed that business ethics significantly affects SS, indicating partial mediation. This study has substantial theoretical and managerial implications as policymakers and MSME leadership need to consider SS an essential component of sustainable development.</p></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"4 2","pages":"Article 100250"},"PeriodicalIF":0.0,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667096824000399/pdfft?md5=d8f0f5b1aebabeeedcc5dbaf8fecc2f8&pid=1-s2.0-S2667096824000399-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140951329","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":"Textual similarity for legal precedents discovery: Assessing the performance of machine learning techniques in an administrative court","authors":"Hugo Mentzingen ,&nbsp;Nuno António ,&nbsp;Fernando Bacao ,&nbsp;Marcio Cunha","doi":"10.1016/j.jjimei.2024.100247","DOIUrl":"https://doi.org/10.1016/j.jjimei.2024.100247","url":null,"abstract":"<div><p>The importance of legal precedents in ensuring consistent jurisprudence is undisputed. Particularly in jurisdictions following the Common law, but even in Civil law systems, uniformity in case law requires adherence to precedents. However, with the growing volume of cases, manual identification becomes a bottleneck, prompting the need for automation. Leveraging the capabilities of natural language processing (NLP) and machine learning (ML), our study delves into the potential of automation in identifying similar cases indicative of precedents. Drawing from a unique, substantial dataset of legal cases from an administrative court in Brazil, we extensively evaluated over one hundred combinations of document representations and text vectorizations. Contrary to earlier studies that relied on minimal validation samples, ours employed a statistically significant sample vetted by legal experts. Our findings reveal that models focusing on granular text representations perform optimally, especially when extracting concepts and relations. Notably, while intricate models may not always guarantee superior outcomes, the importance of refining textual features cannot be understated. These findings pave the way for creating efficient decision support systems in judicial contexts and set a direction for future research aiming to integrate technology in legal decision-making.</p></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"4 2","pages":"Article 100247"},"PeriodicalIF":0.0,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667096824000363/pdfft?md5=27abd719154af3d76e4033b1afbe7e3d&pid=1-s2.0-S2667096824000363-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140946871","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":"An empirical evidence on the impact of social customer relationship management on the small and medium enterprises performance","authors":"Fathey Mohammed ,&nbsp;Rahayu Binti Ahmad ,&nbsp;Syahida Binti Hassan ,&nbsp;Yousef Fazea ,&nbsp;Ahmed Ibrahim Alzahrani","doi":"10.1016/j.jjimei.2024.100248","DOIUrl":"https://doi.org/10.1016/j.jjimei.2024.100248","url":null,"abstract":"<div><p>Social media has swiftly established itself as a primary source of products’ information for customers. Nowadays, Small and Medium-size Enterprises (SMEs) can use social media to develop Customer Relationship Management platforms (social CRM). Firms, particularly SMEs in developing countries need to understand the factors affecting their performance by implementing social CRM. However, there is a dearth of awareness on the impact of social CRM on the performance of SMEs. This study proposes an integrated model that aims to investigate the effects of social CRM on SMEs’ performance. The model is constructed by incorporating three dominant theoretical frameworks: the Fit-Viability Model (FVM), Network Externalities, and the Resource-Based View (RBV). A cross-sectional survey was used to gather data from 149 SMEs managerial staff. Findings revealed that almost 50% of the variability in the performance of SMEs is explained by the fitness and viability of social CRM. In addition, network externalities of social media significantly impact the social CRM fitness in the context of SMEs with path coefficient 0.617. Furthermore, the internal financial resources factor makes sCRM viable for SMEs as the results show significant relationship between the internal financial resources and the sCRM viability with 0.536 path coefficient. Manager innovativeness, IT knowledge, top management support, and government assistance, on the other hand, do not contribute significantly to the viability of social CRM for SMEs. The model aids SMEs in making well-informed decisions regarding the adoption of social CRM by evaluating both the suitability of social media for CRM tasks and the enterprise preparedness to implement social CRM, leading to enhanced performance.</p></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"4 2","pages":"Article 100248"},"PeriodicalIF":0.0,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667096824000375/pdfft?md5=eee9061522d353839a0fdc0a4b7c1383&pid=1-s2.0-S2667096824000375-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140905587","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":"Stage-wise green supply chain management and environmental performance: Impact of blockchain technology","authors":"Sahil Singh Jasrotia ,&nbsp;Siddharth Shankar Rai ,&nbsp;Shivam Rai ,&nbsp;Sunil Giri","doi":"10.1016/j.jjimei.2024.100241","DOIUrl":"https://doi.org/10.1016/j.jjimei.2024.100241","url":null,"abstract":"<div><p>In the era of globalisation, the use of technology and concerns for sustainability is eminent in the supply chain management practices. The current study focuses on sustainable and green supply practices in different stages of supply chain management and how they can be facilitated by blockchain technology (BT). The study has addressed the existing gaps in the area namely, the lack of research assessing stage-wise green supply chain for environmental performance focusing on BT. The current study aims to assess the impact of BT on different stages of the green supply chain and a firm's environmental performance. The study also focuses on analyzing the impact of green supply chain stages on environmental performance. The study uses PLS-based structural equation modelling approach to investigate the hypothesised relationships between BT adoption and stage-wise green supply chain practices. The data was collected from individuals from medium-sized enterprises from the manufacturing industry in India. The findings reveal a positive association between blockchain adoption and green supply chain management practices leading to enhancement in environmental performance. Furthermore, the study indicates a positive relationship between blockchain integration and different stages of the green supply chain, underscoring its multi-faceted impact on environmental performance. The findings imply that the BT adoption can facilitate the realization of sustainable supply chain practices and performance improvement.</p></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"4 2","pages":"Article 100241"},"PeriodicalIF":0.0,"publicationDate":"2024-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667096824000302/pdfft?md5=7cdef9f1ea9c6d06e51182d0fbfdd38e&pid=1-s2.0-S2667096824000302-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140823134","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":"Analyzing the interplay between social media analytics and nudges in pandemic control","authors":"Anup Kumar ,&nbsp;Abhijeet Tewary ,&nbsp;Parijat Upadhyay","doi":"10.1016/j.jjimei.2024.100246","DOIUrl":"https://doi.org/10.1016/j.jjimei.2024.100246","url":null,"abstract":"<div><p>This study employs a data-driven approach to examine the government's use of data insights and nudges to promote social distancing during the pandemic. Drawing from well-established technology adoption theories, a nationwide online survey was conducted among professionals and postgraduate students adapting to remote work and learning. The study unveils that access to suitable information and communication technology (ICT) significantly influences people's willingness to adhere to social distancing and work from home (WFH). Moreover, respondents' expectations of WFH's impact on job performance emerged as a critical driver for sustained social distancing, with individuals' habits playing a pivotal role in enhancing WFH performance expectancy. Notably, the study pioneers in exploring the psychological effects of government nudges during a pandemic, shedding light on an uncharted aspect of pandemic control strategies.</p></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"4 2","pages":"Article 100246"},"PeriodicalIF":0.0,"publicationDate":"2024-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667096824000351/pdfft?md5=d84d60a965bb05849fd6aa7c86ce692b&pid=1-s2.0-S2667096824000351-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140823135","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":"Adoption and continued usage of mobile learning of virtual platforms in Iraqi higher education an unstable environment","authors":"Al-Rikabi Ahmed Ghazi Hameed,&nbsp;Putra Bin Sumari","doi":"10.1016/j.jjimei.2024.100242","DOIUrl":"https://doi.org/10.1016/j.jjimei.2024.100242","url":null,"abstract":"<div><p>This study investigates the implementation and continued utilization of mobile learning (M-learning) in Iraqi universities, considering the challenging circumstances of an unstable environment. The research expands upon the UTAUT2 and ECM models. The main objective is to tackle the difficulties and possibilities in Iraq's higher education institutions (HEIs) caused by geopolitical instability and comprehend their influence on student acceptance, satisfaction, and ongoing M-learning usage. The study expands on the increasing significance of mobile learning, particularly in higher education institutions (HEIs). It acknowledges the distinct difficulties encountered by institutions in Iraq due to the region's instability. The study identifies deficiencies in current models and suggests expansions by introducing the variable \"Civil Conflicts\" to consider the unstable environment. The study seeks to enhance comprehension of M-learning acceptance in conflict-affected regions and offer insights for enhancing M-learning initiatives in Iraqi higher education institutions. To accomplish its goals, this study utilizes a quantitative survey to gather data from 399 students in five universities in Iraq. PLS-SEM is employed to analyze quantitative data and assess the extended UTAUT2 and ECM models. The study's results are anticipated to enhance the understanding of M-learning adoption and ongoing usage in conflict-affected regions, specifically in the context of Iraqi higher education institutions. The study's results can guide improving the efficiency of M-learning programs in Iraqi higher education institutions and provide valuable knowledge on supporting education in regions marked by instability. Researchers' findings can assist educators and policymakers in making well-informed choices to promote the continuity and excellence of education, especially in regions affected by conflict. Researchers can expand upon this study by conducting further investigations into the implementation and utilization of M-learning in volatile environments and assessing the efficacy of the suggested model enhancements.</p></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"4 2","pages":"Article 100242"},"PeriodicalIF":0.0,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667096824000314/pdfft?md5=f36660aab6aa71f4f35fc363ff8b4ce8&pid=1-s2.0-S2667096824000314-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140823133","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":"Cryptocurrency trading: A systematic mapping study","authors":"Duy Thien An Nguyen,&nbsp;Ka Ching Chan","doi":"10.1016/j.jjimei.2024.100240","DOIUrl":"https://doi.org/10.1016/j.jjimei.2024.100240","url":null,"abstract":"<div><p>Cryptocurrency's unique features – decentralisation, anonymity, and diversification – have propelled it into the spotlight, attracting both investors and researchers despite its relative youth compared to traditional markets. This study utilizes a systematic mapping approach to examine the current state of cryptocurrency trading research. We are particularly interested in influential variables and technologies involved in cryptocurrency trading systems. By summarizing key findings on data, technology compatibility, and future research directions, this study serves as a starting point for new research activities in the field of cryptocurrency trading.</p></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"4 2","pages":"Article 100240"},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667096824000296/pdfft?md5=81497202624e361cacda5f99dfb85173&pid=1-s2.0-S2667096824000296-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140816437","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}