International Journal of Information Management Data Insights最新文献

{"title":"Deciphering the evolution of metaverse - A techno-functional perspective in digital marketing","authors":"Mohammad Wasiq ,&nbsp;Abu Bashar ,&nbsp;Brighton Nyagadza ,&nbsp;Amar Johri","doi":"10.1016/j.jjimei.2024.100296","DOIUrl":"10.1016/j.jjimei.2024.100296","url":null,"abstract":"<div><div>The metaverse has disrupted the traditional marketing practices and it has potential to transform entire world of marketing activities with thrilling immersive experiences. This study provides an analysis of evolving field of metaverse marketing in the context of information systems using state of the art bibliometric and scientometric tools coupled with machine learning algorithms. Utilizing 257 documents from Scopus database that published between 1996 and 2024, this research maps and unveils the development of metaverse marketing from its inception and the role of information systems in its evolution. The analysis of literature resulted in five main emerging themes of the role of information systems in metaverse marketing research as User Experience, Customer engagement, Convergence of metaverse Technology, Design of virtual goods &amp; experience and Global Social Interaction. The major sub-themes of the study are User Behaviors and Preferences, Branding on virtual environment, Virtual reality, Virtual wearables and Virtual Socialization. This study also reveals the emerging trends and gaps in literature that pave the ways for future research expansion in the information systems and metaverse marketing. Few of the important future research areas identified are understanding user experience, design of immersive customer engagement strategies, customer virtual presence and Security &amp; privacy concerns of the users on metaverse platform.</div></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"4 2","pages":"Article 100296"},"PeriodicalIF":0.0,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142418307","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 applications for information management in sustainable supply chain management: A systematic review and future research agenda","authors":"Alok Yadav,&nbsp;Rajiv Kumar Garg,&nbsp;Anish Sachdeva","doi":"10.1016/j.jjimei.2024.100292","DOIUrl":"10.1016/j.jjimei.2024.100292","url":null,"abstract":"<div><div>In a Sustainable Supply Chain (SSC) context, information management offers a unique perspective on the digital economy and information management. Artificial intelligence (AI) is developing into a more robust digital field to facilitate quick information access and intelligent decisions in expanding commercial contexts. These days, Supply Chains (SC) would crumble without robust information systems. Applying AI and information management is crucial in determining the direction of sustainable supply chain management (SSCM). A systematic literature review (SLR) of the use of AI in SSCM is conducted in this research. The authors can identify crucial factors of the present literature using bibliometric and network analysis. AI is essential to the SSC to address sustainability challenges and manage the large volumes of data produced by numerous industrial processes. In the corpus of research that is already accessible, there is currently no comprehensive and bibliometric analysis of the potential for AI techniques for information management in SSC. Scientific publications were analysed from an objective point of view. Based on our results, we have drafted a proposal for an AI supply chain framework. Researchers, policymakers, and SCM practitioners may all benefit from the approach. This study is the first to analyse AI applications for information management in SSCM. In consideration of this, organizations are now exploring AI capabilities to improve operational efficiency and innovate their processes. This will assist industry people in understanding how AI methods support SC processes in their optimization to attain sustainability in SC practices.</div></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"4 2","pages":"Article 100292"},"PeriodicalIF":0.0,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142358555","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":"How can we predict transportation stock prices using artificial intelligence? Findings from experiments with Long Short-Term Memory based algorithms","authors":"Dinar Ajeng Kristiyanti,&nbsp;Willibrordus Bayu Nova Pramudya,&nbsp;Samuel Ady Sanjaya","doi":"10.1016/j.jjimei.2024.100293","DOIUrl":"10.1016/j.jjimei.2024.100293","url":null,"abstract":"<div><div>Inflation growth in Indonesia and other countries impacts the currency value and investors' purchasing power, particularly in the transportation sector. This research explores the impact of inflation growth in Indonesia and comparable nations on currency valuation and the purchasing power of investors, with a focus on the transportation sector. Data collection was carried out from April to October 2023 by scraping stock data from several transportation stocks such as: AKSI.JK, CMPP.JK, SAFE.JK, SMDR.JK, TMAS.JK, and WEHA. The research primarily aims to forecast stock prices in Indonesia's transportation sector, utilizing data mining techniques within the Cross Industry Standard Process for Data Mining (CRISP-DM) framework, which includes stages such as business understanding, data preparation, modeling, evaluation, and deployment. It employs the Long Short-Term Memory (LSTM) algorithm, assessing different hyperparameter activation functions (linear, ReLU, sigmoid, tanh) and optimizers (ADAM, ADAGRAD, NADAM, RMSPROP, ADADELTA, SGD, ADAMAX) to refine prediction accuracy. Findings demonstrate the ReLU activation function and ADAM optimizer's effectiveness, highlighted by evaluation metrics such as Mean Absolute Error (MAE) of 0.0092918, Mean Absolute Percentage Error (MAPE) of 0.06422, and R-Squared of 96 %. The study notably identifies significant growth in Temas (TMAS.JK) stock from April to October 2023, surpassing other sector stocks. Additionally, a web-based application for predicting transportation stock prices has been developed, facilitating user inputs like ticker, activation-optimizer choice, and date range.</div></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"4 2","pages":"Article 100293"},"PeriodicalIF":0.0,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142358554","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":"SAFERIDES: Application of decentralized control edge-computing to ridesharing monitoring services","authors":"Samaa Elnagar ,&nbsp;Kweku Muata Osei Bryson ,&nbsp;Manoj Thomas","doi":"10.1016/j.jjimei.2024.100282","DOIUrl":"10.1016/j.jjimei.2024.100282","url":null,"abstract":"<div><div>Edge computing changed the face of many industries and services. Common edge computing models offload computing which is prone to security risks and privacy breach. However, advances in deep learning enabled Internet of Things (IoTs) to onload tasks and run cognitive tasks locally. This research introduces a decentralized-control edge model where computation and decision-making are moved to the IoT level. The model aims at decreasing <em>communication and computation dependance</em> on the edge which affect <em>efficiency</em> and <em>latency</em>. The model also limits data transfer to the edge to avoid <em>security</em> and <em>privacy</em> risks. Decentralized control is a key to many business applications that prioritizes <em>safety, real-time response, and privacy</em> such as ridesharing monitoring and industrial operations. To examine the model, we developed <em>SAFERIDES,</em> a scene-aware ridesharing monitoring system where smart phones are detecting violations at the runtime. Current monitoring systems require costly infrastructure and continuous network connectivity. However, <em>SAFRIDES</em> uses optimized deep learning models that run locally on IoTs to detect and record violations in ridesharing. The system achieved the lowest latency among current solution, while minimizing data sharing and maintaining <em>privacy</em>. Moreover, decentralized edge computing empowers IoTs and upgrades their functionality from sensing to independent decision-making.</div></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"4 2","pages":"Article 100282"},"PeriodicalIF":0.0,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142328244","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: An opportunity to improve supply chains in the wake of digitalization","authors":"Liliana Rivera ,&nbsp;Valérie Gauthier-Umaña ,&nbsp;Chetna Chauhan","doi":"10.1016/j.jjimei.2024.100290","DOIUrl":"10.1016/j.jjimei.2024.100290","url":null,"abstract":"<div><div>Industry 4.0 technologies have created the opportunity to overcome inefficiencies along the supply chain by offering data transparency, tracing, and security. In this regard, the role of blockchain technology has garnered a lot of attention among practitioners as well as academia. Blockchain's decentralized and immutable nature ensures trustworthy data sharing, real-time tracking, and enhanced cybersecurity. However, adoption in emerging markets has not been as fast as in developed countries. There has been little clarity as to what the drivers and barriers to its adoption are, and what role governments and academia should play in the process. The present study addresses these issues using a qualitative study that utilizes data obtained from semi-structured interviews conducted with blockchain companies and supply chain companies in Latin America. Results show that the main barriers are 1) low knowledge about blockchain, 2) insufficient information, connectivity, and financial infrastructure, 3) lack of clear regulation, 4) a scarce presence of a local market for entrepreneurs to produce blockchain applications. It is also interesting to find that in contrast to lack of skilled manpower in many emerging economies globally, Latin America has skilled human capital for blockchain adoption. Thus, emerging markets need to foster collaborative work between companies, government, and academia to overcome these barriers and be able to enjoy blockchain benefits while increasing competitiveness in supply chains.</div></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"4 2","pages":"Article 100290"},"PeriodicalIF":0.0,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142358553","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":"Extending the theory of information poverty to deepfake technology","authors":"Walter Matli","doi":"10.1016/j.jjimei.2024.100286","DOIUrl":"10.1016/j.jjimei.2024.100286","url":null,"abstract":"<div><div>The advent of deepfake technology has introduced complex challenges to the information technology landscape, simultaneously presenting benefits and novel risks and ethical considerations. This paper delves into the evolution of deepfakes through the prism of information poverty theory, scrutinising how deepfakes may contribute to a growing information access/use inequality. The research focuses on the risks of misinformation and the ensuing expansion of digital divides, particularly when manipulative media could delude individuals lacking access to legitimate information sources. The study outlines the potential exacerbation of information asymmetries and examines the societal implications across various demographics. By integrating an analytical discussion on the risks associated with deepfakes, the study aligns the observed trends with the theoretical underpinnings of information poverty. As part of its contribution, the paper offers actionable policy-making recommendations and educational strategies to combat the proliferation of harmful deepfake content. The article aims to ensure a more equitable distribution of authentic information and foster media literacy. Through a multifaceted approach, this study endeavours to provide a foundational understanding for stakeholders to navigate the ethical minefield posed by deepfakes and to instil a framework for information equity in the digital era. The article provides critical insights into the discourse on deepfake technology and its relation to information poverty, underscoring the urgent need for equitable access to informed digital spaces. As deepfake technology evolves and more data emerges, a societal demand exists for comprehensive knowledge about deepfakes to promote discernment, decision-making and awareness. Policymakers are tasked with recognising the significance of widening access to sophisticated information technologies whilst addressing their negative repercussions. Their efforts will be particularly crucial for disseminating knowledge about deepfakes to those with limited or non-existent information and communication awareness and infrastructures. Learning from past successes and failures becomes pivotal in shaping effective strategies to address the challenges posed by deepfakes and fostering accessible, informed digital communities.</div></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"4 2","pages":"Article 100286"},"PeriodicalIF":0.0,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667096824000752/pdfft?md5=03c4539aa8be2df8356c77492752997c&pid=1-s2.0-S2667096824000752-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142314784","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":"Location factors and ecosystem embedding of sustainability-engaged blockchain companies in the US. A web-based analysis","authors":"Jan Kinne ,&nbsp;Robert Dehghan ,&nbsp;Sebastian Schmidt ,&nbsp;David Lenz ,&nbsp;Hanna Hottenrott","doi":"10.1016/j.jjimei.2024.100287","DOIUrl":"10.1016/j.jjimei.2024.100287","url":null,"abstract":"<div><p>While many digital technologies provide opportunities for creating business models that impact sustainability, some technologies, especially blockchain applications, are often criticized for harming the environment, e.g. due to high energy demand. In our study, we present a novel approach to identifying sustainability-focused blockchain companies and relate their level of engagement to location factors and entrepreneurial ecosystem embeddedness. For this, we use a large-scale web scraping approach to analyze the textual content and hyperlink networks of all US companies from their websites. Our results show that blockchain remains a niche technology, with its use communicated by about 0.6% of US companies. However, the proportion of blockchain companies that are committed to sustainability is significantly higher than in the overall firm population. Additionally, we find that such sustainability-engaged blockchain companies have, at least quantitatively, a more intensive embedding in entrepreneurial ecosystems, while infrastructural and socio-economic location factors hardly play a role.</p></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"4 2","pages":"Article 100287"},"PeriodicalIF":0.0,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667096824000764/pdfft?md5=4f962436143461d36d43a227994573c0&pid=1-s2.0-S2667096824000764-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142274834","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":"The adoption of mobile health applications by physicians during the COVID-19 pandemic in developing countries: The case of Saudi Arabia","authors":"Sultan Alsahli ,&nbsp;Su-yin Hor","doi":"10.1016/j.jjimei.2024.100289","DOIUrl":"10.1016/j.jjimei.2024.100289","url":null,"abstract":"<div><p>The rapid evolution of mobile health applications (mHealth apps) has become increasingly important in enhancing healthcare delivery, especially during the COVID-19 pandemic. Despite the critical role of such technologies, however, acceptance and adoption rates among physicians in developing countries, particularly Saudi Arabia, have been relatively low. This highlights the need to explore the determinants of acceptance. In response to this call, this study aimed to identify the factors that influence Saudi physicians’ acceptance and adoption of mHealth apps during the COVID-19 pandemic using the unified theory of acceptance and use of technology. Data were collected using an online survey, after which the responses were analyzed via structural equation modeling. The analysis assessed the influence of four primary constructs, namely, performance expectancy, effort expectancy, social influence, and facilitating conditions, on the physicians’ behavioral intention to adopt these technologies. The results indicated that while all factors significantly affected the intention to adopt the apps, facilitating conditions were the most influential. These findings punctuate the necessity of investing in infrastructure and implementing training programs focused on integrating mHealth technology into medical practice. By drawing attention to influencing factors, this research provides critical insights for policymakers and healthcare managers to enhance the adoption of mHealth apps. This enhancement, in turn, can help improve healthcare delivery and patient outcomes during and beyond health crises. Finally, this study not only sheds light on the adoption dynamics prevalent in a developing context but also serves as a valuable guide for implementing similar technologies in other global regions.</p></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"4 2","pages":"Article 100289"},"PeriodicalIF":0.0,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667096824000788/pdfft?md5=29e48c7923786a555f795eb9342d4c82&pid=1-s2.0-S2667096824000788-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142274835","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":"Analysis of the potential of artificial intelligence for professional development and talent management: A systematic literature review","authors":"Natalia Tusquellas ,&nbsp;Ramon Palau ,&nbsp;Raúl Santiago","doi":"10.1016/j.jjimei.2024.100288","DOIUrl":"10.1016/j.jjimei.2024.100288","url":null,"abstract":"<div><p>The aim of this paper was to analyse the current applications of Artificial Intelligence in professional development and talent management within the corporate world with a focus on corporate training. By means of a Systematic Literature Review based on the PRISMA 2020 reporting criteria this paper highlights the current applications of AI along with the main benefits and drawbacks associated with its implementation. The findings show that AI is being used to enhance recruitment processes, to identify individual training and development skills and needs, to develop personalised training paths, to retain talent and predict attrition, and to detect future workforce skills development needs. It has been outlined that there is a need for automated talent management processes within companies and that talent intelligence should be implemented along with facing the challenges this will entail, such as minimising the risk of bias and hiring high-skilled qualified personnel.</p></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"4 2","pages":"Article 100288"},"PeriodicalIF":0.0,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667096824000776/pdfft?md5=0b96fd4ba774d8d51880f8fff37b90e0&pid=1-s2.0-S2667096824000776-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142232453","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":"Classification of suicidal ideation severity from Twitter messages using machine learning","authors":"Pantaporn Benjachairat ,&nbsp;Twittie Senivongse ,&nbsp;Nattasuda Taephant ,&nbsp;Jiratchaya Puvapaisankit ,&nbsp;Chonlakorn Maturosjamnan ,&nbsp;Thanakorn Kultananawat","doi":"10.1016/j.jjimei.2024.100280","DOIUrl":"10.1016/j.jjimei.2024.100280","url":null,"abstract":"<div><p>Depression has become a major mental health problem in Thailand and can lead to suicidal ideation. As suicidal ideation may vary in intensity and lead to suicide attempts, early detection of suicidal ideation severity should be implemented. This research presents text classification models for the prediction of suicidal ideation severity. A dataset of Twitter messages in Thai was used to develop several classification models. A web application prototype was also developed to predict suicidal ideation severity and introduce self-therapy based on Cognitive Behavioral Therapy to its users for managing negative automatic thoughts. The application prototype received satisfactory feedback during the user experience assessment. The results of this research highlight the importance and need for socio-technical systems to help with early suicidal ideation detection and early therapy in the social environment where mental health support is inadequate.</p></div>","PeriodicalId":100699,"journal":{"name":"International Journal of Information Management Data Insights","volume":"4 2","pages":"Article 100280"},"PeriodicalIF":0.0,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667096824000697/pdfft?md5=7d239a55544ebdb5f4c9115aa83fb27e&pid=1-s2.0-S2667096824000697-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142230114","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}