Tiago Filipe Rodrigues Ribeiro, Fernando José Mateus da Silva, Rogério Luís de Carvalho Costa
{"title":"Modelling forest fire dynamics using conditional variational autoencoders","authors":"Tiago Filipe Rodrigues Ribeiro, Fernando José Mateus da Silva, Rogério Luís de Carvalho Costa","doi":"10.1007/s10796-024-10507-9","DOIUrl":"https://doi.org/10.1007/s10796-024-10507-9","url":null,"abstract":"<p>Forest fires have far-reaching consequences, threatening human life, economic stability, and the environment. Understanding the dynamics of forest fires is crucial, especially in high-incidence regions. In this work, we apply deep networks to simulate the spatiotemporal progression of the area burnt in a forest fire. We tackle the region interpolation problem challenge by using a Conditional Variational Autoencoder (CVAE) model and generate in-between representations on the evolution of the burnt area. We also apply a CVAE model to forecast the progression of fire propagation, estimating the burnt area at distinct horizons and propagation stages. We evaluate our approach against other established techniques using real-world data. The results demonstrate that our method is competitive in geometric similarity metrics and exhibits superior temporal consistency for in-between representation generation. In the context of burnt area forecasting, our approach achieves scores of 90% for similarity and 99% for temporal consistency. These findings suggest that CVAE models may be a viable alternative for modeling the spatiotemporal evolution of 2D moving regions of forest fire evolution.</p>","PeriodicalId":13610,"journal":{"name":"Information Systems Frontiers","volume":"54 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2024-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141444896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bianca-Ştefania Munteanu, Alexandra Murariu, Mǎrioara Nichitean, Luminiţa-Gabriela Pitac, Laura Dioşan
{"title":"Value of Original and Generated Ultrasound Data Towards Training Robust Classifiers for Breast Cancer Identification","authors":"Bianca-Ştefania Munteanu, Alexandra Murariu, Mǎrioara Nichitean, Luminiţa-Gabriela Pitac, Laura Dioşan","doi":"10.1007/s10796-024-10499-6","DOIUrl":"https://doi.org/10.1007/s10796-024-10499-6","url":null,"abstract":"<p>Breast cancer represents one of the leading causes of death among women, with 1 in 39 (around 2.5%) of them losing their lives annually, at the global level. According to the American Cancer Society, it is the second most lethal type of cancer in females, preceded only by lung cancer. Early diagnosis is crucial in increasing the chances of survival. In recent years, the incidence rate has increased by 0.5% per year, with 1 in 8 women at increased risk of developing a tumor during their life. Despite technological advances, there are still difficulties in identifying, characterizing, and accurately monitoring malignant tumors. The main focus of this article is on the computerized diagnosis of breast cancer. The main objective is to solve this problem using intelligent algorithms, that are built with artificial neural networks and involve 3 important steps: augmentation, segmentation, and classification. The experiment was made using a publicly available dataset that contains medical ultrasound images, collected from approximately 600 female patients (it is considered a benchmark). The results of the experiment are close to the goal set by our team. The final accuracy obtained is 86%.</p>","PeriodicalId":13610,"journal":{"name":"Information Systems Frontiers","volume":"1 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141309086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Consumers’ Financial Distress: Prediction and Prescription Using Interpretable Machine Learning","authors":"Hendrik de Waal, Serge Nyawa, Samuel Fosso Wamba","doi":"10.1007/s10796-024-10501-1","DOIUrl":"https://doi.org/10.1007/s10796-024-10501-1","url":null,"abstract":"<p>This paper shows how transactional bank account data can be used to predict and to prevent financial distress in consumers. Machine learning methods were used to identify the most significant transactional behaviours that cause financial distress. We show that Random Forest outperforms the other machine learning models when predicting the financial distress of a consumer. We obtain that Fees and Interest paid stand out as primary contributors of financial distress, emphasizing the significance of financial charges and interest payments in gauging individuals’ financial vulnerability. Using Local Interpretable Model-agnostic Explanations, we study the marginal effect of transactional behaviours on the probability of being in financial distress and assess how different variables selected across all the data point selection sets influence each case. We also propose prescriptions that can be communicated to the client to help the individual improve their financial wellbeing. This research used data from a major South African bank.</p>","PeriodicalId":13610,"journal":{"name":"Information Systems Frontiers","volume":"53 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141304342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Mixed-Integer Formulation for the Simultaneous Input Selection and Outlier Filtering in Soft Sensor Training","authors":"Hasan Sildir, Onur Can Boy, Sahin Sarrafi","doi":"10.1007/s10796-024-10492-z","DOIUrl":"https://doi.org/10.1007/s10796-024-10492-z","url":null,"abstract":"<p>Soft sensors are used to calculate the real-time values of process variables which can be measured in the laboratory only or require expensive online measurement tools. A set of mathematical expressions are developed and trained from historical data to exploit the statistical knowledge between online and offline measurements to ensure a reliable prediction performance, for optimization and control purposes. This study focuses on the development of a mixed-integer optimization problem to perform input selection and outlier filtering simultaneously using rigorous algorithms during the training procedure, unlike traditional heuristic and sequential methods. Nonlinearities and nonconvexities in the optimization problem is further tailored for global optimality and computational advancements by reformulations and piecewise linearizations to address the complexity of the task with additional binary variables, representing the selection of a particular input or data. The proposed approach is implemented on actual data from two different industrial plants and compared to traditional approach.</p>","PeriodicalId":13610,"journal":{"name":"Information Systems Frontiers","volume":"16 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2024-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141292746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Parul Gupta, Apeksha Hooda, Anand Jeyaraj, Jonathan J.M. Seddon, Yogesh K. Dwivedi
{"title":"Trust, Risk, Privacy and Security in e-Government Use: Insights from a MASEM Analysis","authors":"Parul Gupta, Apeksha Hooda, Anand Jeyaraj, Jonathan J.M. Seddon, Yogesh K. Dwivedi","doi":"10.1007/s10796-024-10497-8","DOIUrl":"https://doi.org/10.1007/s10796-024-10497-8","url":null,"abstract":"<p>Despite considerable research on the factors influencing the use of e-government, citizens are apprehensive of e-government services due to the concerns primarily related to trust, risk, security and privacy. This study presents a meta-analytic structural equation modeling (MASEM) analysis of the findings reported by 68 prior empirical studies on e-government adoption. Specifically, the model examined the direct effects of trust in government, trust in internet, perceived risk, and perceived privacy and security on e-government trust, and its impact on users’ behavioral intention to use e-government. The findings bear significant theoretical and practical implications.</p>","PeriodicalId":13610,"journal":{"name":"Information Systems Frontiers","volume":"124 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141251597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Christina Khnaisser, Hind Hamrouni, David B. Blumenthal, Anton Dignös, Johann Gamper
{"title":"Efficiently Labeling and Retrieving Temporal Anomalies in Relational Databases","authors":"Christina Khnaisser, Hind Hamrouni, David B. Blumenthal, Anton Dignös, Johann Gamper","doi":"10.1007/s10796-024-10495-w","DOIUrl":"https://doi.org/10.1007/s10796-024-10495-w","url":null,"abstract":"<p>Time and temporal constraints are implicit in most databases. To facilitate data analysis and quality assessment, a database should provide explicit operations to identify the violation of temporal constraints. Against this background, the purpose of this paper is threefold: (1) we identify and provide a formal definition of five common anomalies in temporal databases, (2) we propose two new relational operations that allow, respectively, to label anomalous tuples in and to retrieve the anomalous tuples from a dataset, and (3) we provide three different SQL implementations of these operations for current relational database management systems. The healthcare domain is used to illustrate the usage and utility of the temporal anomalies. Finally, an experimental evaluation on real-world and synthetic data analyses the performance of the different implementations of the anomaly operators.</p>","PeriodicalId":13610,"journal":{"name":"Information Systems Frontiers","volume":"318 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141182387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Priveena Thanabalan, Ali Vafaei-Zadeh, Haniruzila Hanifah, T. Ramayah
{"title":"Big Data Analytics Adoption in Manufacturing Companies: The Contingent Role of Data-Driven Culture","authors":"Priveena Thanabalan, Ali Vafaei-Zadeh, Haniruzila Hanifah, T. Ramayah","doi":"10.1007/s10796-024-10491-0","DOIUrl":"https://doi.org/10.1007/s10796-024-10491-0","url":null,"abstract":"<p>The objective of this paper is to investigate the factors that influence the adoption of Big Data Analytics (BDA) in manufacturing companies and examine the impact of BDA adoption on performance, while also considering the moderating effect of data-driven culture. An online questionnaire survey was conducted with medium and large manufacturing companies in Malaysia, resulting in a total of 267 responses collected through non-probability purposive sampling. The results show that technology complexity, perceived relative advantage, top management support, IT infrastructure and capabilities, normative pressure, and mimetic pressure are significant determinants of BDA adoption. Moreover, the adoption of BDA has a positive impact on financial and market performance, with data-driven culture moderating the relationship between BDA adoption and financial performance. This study highlights the critical factors that contribute to BDA adoption and its outcomes, providing manufacturing companies with awareness on this topic.</p>","PeriodicalId":13610,"journal":{"name":"Information Systems Frontiers","volume":"34 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2024-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141156682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Role of E-participation, Human Capital, and Corruption-Free on Environmental Performance","authors":"Mohammad I. Merhi, Punit Ahluwalia","doi":"10.1007/s10796-024-10493-y","DOIUrl":"https://doi.org/10.1007/s10796-024-10493-y","url":null,"abstract":"<p>There are many concerns at the global level about environmental performance. The United Nations has created a framework for measuring national development goals that enable environmental sustainability. This paper examines the relationships between technological and social factors as enablers of environmental performance and draws from technological determinism and human agency paradigms. It fills an important gap in the literature by empirically examining the hypothesized relationships. The specific examined factors are online service (maturity and quality), IT infrastructure, e-participation, corruption-free, and human capital. Environmental performance is the dependent variable. These factors are relevant to ten of the seventeen goals that the United Nations set in their SDG framework. The hypotheses are tested and validated using secondary data collected by reputable global institutions and PLS-SEM analytical procedures. The results indicate that technology can enable environmental performance directly and indirectly through e-participation. We also found that e-participation influences corruption-free and human capital that positively impact environmental performance. This paper provides significant implications for research and practice.</p>","PeriodicalId":13610,"journal":{"name":"Information Systems Frontiers","volume":"17 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141069494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fabian Tingelhoff, Raphael Schultheiss, Sofia Marlena Schöbel, Jan Marco Leimeister
{"title":"Qualitative Insights into Organizational Value Creation: Decoding Characteristics of Metaverse Platforms","authors":"Fabian Tingelhoff, Raphael Schultheiss, Sofia Marlena Schöbel, Jan Marco Leimeister","doi":"10.1007/s10796-024-10494-x","DOIUrl":"https://doi.org/10.1007/s10796-024-10494-x","url":null,"abstract":"<p>The significance of metaverse platforms is growing in both research and practical applications. To utilize the chances and opportunities metaverse platforms offer, research and practice must understand how these platforms create value, which has not been adequately explored. Our research explores the characteristics of metaverse platforms that facilitate value creation for organizations in both B2B and B2C sectors. Employing a qualitative inductive approach, we conducted 15 interviews with decision-makers from international corporations active in the metaverse. We identified 26 metaverse platform characteristics, which we categorized into six dimensions based on the DeLone and McLean Information Systems success model. Subsequently, we provide examples to illustrate the application of these identified characteristics within metaverse platforms. This study contributes to the academic discourse by uncovering the characteristics that shape the competitive landscape of emerging metaverse platforms. Leveraging these characteristics may offer metaverse providers a competitive edge in attracting complementary organizations to their platforms.</p>","PeriodicalId":13610,"journal":{"name":"Information Systems Frontiers","volume":"29 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140924988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cheng-Hao Steve Chen, Gordon Liu, Gelareh Roushan, Bang Nguyen
{"title":"Exploring Information Technology Capabilities from Multiple Aspects of the Resource-Based Theory","authors":"Cheng-Hao Steve Chen, Gordon Liu, Gelareh Roushan, Bang Nguyen","doi":"10.1007/s10796-024-10490-1","DOIUrl":"https://doi.org/10.1007/s10796-024-10490-1","url":null,"abstract":"<p>This study elucidates the nature of information technology (IT) capabilities by developing an integrated framework that expounds upon the hierarchy inherent within IT capabilities. This research uses qualitative interviews with 64 IT professionals grounded in the resource-based theory to delineate three layers of IT capabilities. At the foundational level, IT capabilities reflect firms’ IT-related assets, encompassing IT infrastructure, informational, and enabled assets that are valuable, rare, and inimitable. Higher up, firms’ IT capabilities manifest through competence in organising these IT-related assets effectively. <i>Operational IT competence</i> is instrumental in mobilising and deploying each IT-related asset, while <i>dynamic IT capabilities</i> represent firms’ capacity to reconfigure and assimilate various operational IT competencies. This research contributes to the field by providing an integrative theoretical understanding of how IT capabilities are formed. The proposed model addresses fragmentation in the existing literature, facilitating the development of more cohesive, evidence-based strategies for generating business value from IT.\u0000</p>","PeriodicalId":13610,"journal":{"name":"Information Systems Frontiers","volume":"12 1","pages":""},"PeriodicalIF":5.9,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140881260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}