Data Science and Management最新文献

{"title":"Analysis of digital twin and its physical object: Exploring the efficiency and accuracy of datasets for real-world application","authors":"H. C. Ukwuoma, Gilles Dusserre, G. Coatrieux, Johanne Vincent","doi":"10.1016/j.dsm.2024.04.002","DOIUrl":"https://doi.org/10.1016/j.dsm.2024.04.002","url":null,"abstract":"","PeriodicalId":100353,"journal":{"name":"Data Science and Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140794710","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":"Bibliometric analysis of the art market: from art price to market efficiency","authors":"Mingjun Guo, Xuerong Li, Yunjie Wei","doi":"10.1016/j.dsm.2024.03.006","DOIUrl":"https://doi.org/10.1016/j.dsm.2024.03.006","url":null,"abstract":"","PeriodicalId":100353,"journal":{"name":"Data Science and Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140780736","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":"Application of user preference mining algorithms based on data mining and social behavior in brand building","authors":"","doi":"10.1016/j.dsm.2024.03.007","DOIUrl":"10.1016/j.dsm.2024.03.007","url":null,"abstract":"<div><div>Small and medium-sized enterprises currently suffer from a lack of branding. Therefore, to further promote their active branding, this study proposes a user preference mining algorithm based on data mining and social behavior. Employing this algorithm to study the degree of users’ brand preference can provide data support for enterprises’ brand building. The experimental results showed that the proposed algorithm outperforms previous algorithms in terms of performance, convergence, and accuracy. The area under the curve reached 0.953, indicating highly authentic output results with extremely high realism. In actual simulation experiments, its prediction results for the user’s brand preference index are accurate, with an error of only 0.11, and the algorithm has extremely high ratings among industry insiders. In conclusion, the user-preference mining algorithm based on data mining and social behaviors suggested in this study plays a better role in promoting an enterprise’s brand building. It can help the enterprise know the level of consumer preference for its brand; accordingly, it can determine the shortcomings in, provide effective and accurate data support for, and thereby promote its brand building.</div></div>","PeriodicalId":100353,"journal":{"name":"Data Science and Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140404802","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 dynamics of multidimensional educational poverty","authors":"","doi":"10.1016/j.dsm.2024.03.004","DOIUrl":"10.1016/j.dsm.2024.03.004","url":null,"abstract":"<div><div>Education is a cornerstone in promoting the overall welfare of individuals and plays a pivotal role in shaping their lives. As the developing world grapples with the multifaceted challenges of poverty, there is a growing emphasis on evaluating poverty from a multidimensional perspective. Therefore, this study estimates the educational poverty index (EPI). To construct the EPI, Alkire and Foster’s methodology was used with data from the Pakistan Panel Household Survey. We also estimated the dynamics of educational poverty using logistic regression. The results show that the EPI declined from 0.24 in 2001 to 0.21 in 2010. Similarly, the intensity decreased from 0.42 to 0.30. However, the incidence of educational poverty increased from 0.58 to 0.69. At the provincial level, there was a reduction in educational poverty and intensity across all provinces. However, the rate of decline in the EPI and intensity was comparatively higher in Baluchistan than in other provinces. Most of the population belonged to the transitory poor category (0.47). Other dynamic factors such as the household head’s age, education, family size, disability, and land acres also play vital roles in moving into or out of poverty. Our study reveals numerous dimensions that can increase household educational poverty. The government should be vigilant while preparing the policy and must consider the multiple dimensions of a household to eradicate educational poverty.</div></div>","PeriodicalId":100353,"journal":{"name":"Data Science and Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140274631","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":"Quality of life issues in rural settlements: Assessment by social media users","authors":"","doi":"10.1016/j.dsm.2024.03.005","DOIUrl":"10.1016/j.dsm.2024.03.005","url":null,"abstract":"<div><div>Disparity in the quality of life of people living in rural and urban areas is among the major problems, often leading to greater depression among the rural population compared to those in urban areas who have access to a high standard of living. The goal of this study was to identify the issues of the quality of life that are fundamental from the point of view of rural settlements and typical for the rural population in various regions of the Russian Federation with diverse geographical, socioeconomic, and demographic characteristics. The practical relevance of our study is based on the identification of the scope of typical problems related to the quality of life in rural areas. The fundamental value of this study is the significance of digital tracks, which can serve as a source of information. The data sources included messages and posts discussing various quality of life aspects of the rural population published by VKontakte. For this study, we used messages and posts with negative implications from communities in rural settlements in ten Russian regions. These issues include housing infrastructure and utilities, transportation, the environment, telecommunications, banking, healthcare, and education.</div></div>","PeriodicalId":100353,"journal":{"name":"Data Science and Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140282987","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":"When cryptography stops data science: Strategies for resolving the conflicts between data scientists and cryptographers","authors":"","doi":"10.1016/j.dsm.2024.03.001","DOIUrl":"10.1016/j.dsm.2024.03.001","url":null,"abstract":"<div><p>The advent of the digital era and computer-based remote communications has significantly enhanced the applicability of various sciences over the past two decades, notably data science (DS) and cryptography (CG). Data science involves clustering and categorizing unstructured data, while cryptography ensures security and privacy aspects. Despite certain CG laws and requirements mandating fully randomized or pseudonoise outputs from CG primitives and schemes, it appears that CG policies might impede data scientists from working on ciphers or analyzing information systems supporting security and privacy services. However, this study posits that CG does not entirely preclude data scientists from operating in the presence of ciphers, as there are several examples of successful collaborations, including homomorphic encryption schemes, searchable encryption algorithms, secret-sharing protocols, and protocols offering conditional privacy. These instances, along with others, indicate numerous potential solutions for fostering collaboration between DS and CG. Therefore, this study classifies the challenges faced by DS and CG into three distinct groups: challenging problems (which can be conditionally solved and are currently available to use; e.g., using secret sharing protocols, zero-knowledge proofs, partial homomorphic encryption algorithms, etc.), open problems (where proofs to solve exist but remain unsolved and is now considered as open problems; e.g., proposing efficient functional encryption algorithm, fully homomorphic encryption scheme, etc.), and hard problems (infeasible to solve with current knowledge and tools). Ultimately, the paper will address specific solutions and outline future directions to tackle the challenges arising at the intersection of DS and CG, such as providing specific access for DS experts in secret-sharing algorithms, assigning data index dimensions to DS experts in ultra-dimension encryption algorithms, defining some functional keys in functional encryption schemes for DS experts, and giving limited shares of data to them for analytics.</p></div>","PeriodicalId":100353,"journal":{"name":"Data Science and Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666764924000134/pdfft?md5=74cffc92910a646ae465235dd70aec61&pid=1-s2.0-S2666764924000134-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140269093","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":"Survival strategies for family-run homestays: Analyzing user reviews through text mining","authors":"Jay Krishnan ,&nbsp;Biplab Bhattacharjee ,&nbsp;Maheshwar Pratap ,&nbsp;Janardan Krishna Yadav ,&nbsp;Moinak Maiti","doi":"10.1016/j.dsm.2024.03.003","DOIUrl":"10.1016/j.dsm.2024.03.003","url":null,"abstract":"<div><p>Online booking of homestays through e-travel portals is based on the virtual brand and perception, which are largely affected by user-generated electronic word-of-mouth (eWOM). With the objective of mining actionable insights from eWOM, this study conducted opinion mining for homestays located in four thematic areas of Kerala. Accordingly, various techniques have been deployed, such as sentiment and emotional analyses, topic modeling, and clustering methods. Key themes revealed from topic modeling were breakfast, facilities provided, ambience, bathroom, cleanliness, hospitality exhibited, and satisfaction with the host. A lasso logistic regression-based predictive binary text classification model (with 97.6% accuracy) for homestay recommendations was developed. Our findings and predictive model have implications for managers and homestay owners in devising appropriate marketing strategies and improving their overall guest experience.</p></div>","PeriodicalId":100353,"journal":{"name":"Data Science and Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666764924000158/pdfft?md5=89c56a3dcbb307fb2011d2afb14b790b&pid=1-s2.0-S2666764924000158-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141990805","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":"Development of a machine learning model for predicting abnormalities of commercial airplanes","authors":"","doi":"10.1016/j.dsm.2024.03.002","DOIUrl":"10.1016/j.dsm.2024.03.002","url":null,"abstract":"<div><p>Airplanes are a social necessity for movement of humans, goods, and other. They are generally safe modes of transportation; however, incidents and accidents occasionally occur. To prevent aviation accidents, it is necessary to develop a machine-learning model to detect and predict commercial flights using automatic dependent surveillance–broadcast data. This study combined data-quality detection, anomaly detection, and abnormality-classification-model development. The research methodology involved the following stages: problem statement, data selection and labeling, prediction-model development, deployment, and testing. The data labeling process was based on the rules framed by the international civil aviation organization for commercial, jet-engine flights and validated by expert commercial pilots. The results showed that the best prediction model, the quadratic-discriminant-analysis, was 93% accurate, indicating a “good fit”. Moreover, the model’s area-under-the-curve results for abnormal and normal detection were 0.97 and 0.96, respectively, thus confirming its “good fit”.</p></div>","PeriodicalId":100353,"journal":{"name":"Data Science and Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666764924000146/pdfft?md5=72d22c62c77d91a47de3980ce379bce3&pid=1-s2.0-S2666764924000146-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140270485","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":"Machine acceleration time series prediction for dimensional accuracy of 3D printed parts","authors":"","doi":"10.1016/j.dsm.2024.02.002","DOIUrl":"10.1016/j.dsm.2024.02.002","url":null,"abstract":"<div><p>This study explores the influence of infill patterns on machine acceleration prediction in the realm of three-dimensional (3D) printing, particularly focusing on extrusion technology. Our primary objective was to develop a long short-term memory (LSTM) network capable of assessing this impact. We conducted an extensive analysis involving 12 distinct infill patterns, collecting time-series data to examine their effects on the acceleration of the printer’s bed. The LSTM network was trained using acceleration data from the adaptive cubic infill pattern, while the Archimedean chords infill pattern provided data for evaluating the network’s prediction accuracy. This involved utilizing offline time-series acceleration data as the training and testing datasets for the LSTM model. Specifically, the LSTM model was devised to predict the acceleration of a fused deposition modeling (FDM) printer using data from the adaptive cubic infill pattern. Rigorous testing yielded a root mean square error (RMSE) of 0.007144, reflecting the model’s precision. Further refinement and testing of the LSTM model were conducted using acceleration data from the Archimedean chords infill pattern, resulting in an RMSE of 0.007328. Notably, the developed LSTM model demonstrated superior performance compared to an optimized recurrent neural network (RNN) in predicting machine acceleration data. The empirical findings highlight that the adaptive cubic infill pattern considerably influences the dimensional accuracy of parts printed using FDM technology.</p></div>","PeriodicalId":100353,"journal":{"name":"Data Science and Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666764924000122/pdfft?md5=5279d6a024ea6a759468bdafb34bcc56&pid=1-s2.0-S2666764924000122-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140463746","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":"Determinants of continuous usage intention of branded apps in omni-channel retail environment: Comparison between experience-oriented and transaction-oriented apps","authors":"Lixia Jiang,&nbsp;Shenglan Yang,&nbsp;Qing Tang,&nbsp;Zhengjie Zhang","doi":"10.1016/j.dsm.2024.01.004","DOIUrl":"10.1016/j.dsm.2024.01.004","url":null,"abstract":"<div><p>Branded applications (apps) have become core touchpoints for improving consumer shopping experiences in omni-channel retailing, and many firms have developed different types of branded apps to provide additional value. Moreover, continuous usage intention is the key to improving enterprises’ gain efficiency and consumers’ brand loyalty. This study aims to reveal how branded apps achieve continuance intention from the perspective of consumer perceptions by combining the technology acceptance model and investigating the impact of differences in channel features on usage behavior between the two types of branded apps. An experiment was designed comparing transaction- and experience-oriented branded apps. A structural equation modeling technique was employed to validate the model based on the survey data of respondents from the experimental groups. The results show that the supportive role of omni-channel has a unique experience mechanism that promotes continuous usage intention. However, there are two discrepant results regarding the effect of perceived complementarity on perceived usefulness in transaction- and experience-oriented branded apps. The mediating role of perceived usefulness between perceived consistency, complementarity, ease of use and consumer satisfaction was supported in the experience-oriented apps but rejected in the transaction-oriented apps.</p></div>","PeriodicalId":100353,"journal":{"name":"Data Science and Management","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666764924000092/pdfft?md5=a7bb4247cfcf6752ca93c863b7a071ac&pid=1-s2.0-S2666764924000092-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139966302","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}