Journal of Economy and Technology最新文献

{"title":"Women's economic empowerment and COVID-19 pandemic: A study on women entrepreneurs in Bangladesh","authors":"Nasir Uddin ,&nbsp;Proma Barua","doi":"10.1016/j.ject.2024.08.006","DOIUrl":"10.1016/j.ject.2024.08.006","url":null,"abstract":"<div><p>This paper aims to explore the impact of COVID-19 pandemic on women's economic empowerment in Bangladesh. Based on the available literature, this paper develops a holistic framework for economic empowerment and measures how COVID-19 pandemic has contributed to changes in the framework. The study adopts a quantitative research method to address the research question; of whether and to what extent women entrepreneurs were economically empowered by their businesses during COVID-19 pandemic. The empirical data was collected from 52 Bangladeshi women entrepreneurs via telephone interviews and online surveys using a structured questionnaire in February–March 2022, and respondents were chosen randomly from various online social groups and pages. The findings suggest that women entrepreneurs have contributed to family spending, resource allocation, and decision-making. However, their role has diminished significantly in asset ownership during the pandemic. In addition, women's attitudes toward violence, social stigma, and education have shifted dramatically. Furthermore, women entrepreneurs face several challenges, including a lack of government support, limited availability of credit, a lack of entrepreneurial education, and an increased responsibility in the family. Although numerous research studies have demonstrated how COVID-19 pandemic affected women during the pandemic, the impact of COVID-19 pandemic on economic empowerment through gender lenses has frequently been disregarded in Bangladesh context. This study bridges that gap, particularly in developing economies context and the framework constructed in this study is instrumental for understanding the dynamics of economic empowerment that can be applied in future research.</p></div>","PeriodicalId":100776,"journal":{"name":"Journal of Economy and Technology","volume":"2 ","pages":"Pages 258-268"},"PeriodicalIF":0.0,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949948824000386/pdfft?md5=9fbc3fcf6eac773969b5ca1926225a15&pid=1-s2.0-S2949948824000386-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142121597","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 do technological innovation and urbanization drive economic growth in Tanzania and transform societies? Exploring the potential channels","authors":"Mwoya Byaro ,&nbsp;Anicet Rwezaula","doi":"10.1016/j.ject.2024.08.001","DOIUrl":"10.1016/j.ject.2024.08.001","url":null,"abstract":"<div><p>The current era is witnessing a rapid pace of technological innovation and accelerated urbanization globally. This study examines the impact of technological innovation (trademark registrations) and urbanization on economic growth in Tanzania from the period 2002–2021 while accounting for inflation and industrialization in the regression model. Estimation is done using Kernel Regularized Least Squares (KRLS), a machine-learning technique. Results show that technological innovation has a positive impact on economic growth, with an average increase of 0.03 %. Inflation has a negative impact; reducing economic growth by 0.02 %. Urbanization and industrialization have positive impacts, increasing economic growth by 0.58 % and 0.16 %, respectively. Further, the study shows that the average increase in technological innovation (trademark registrations) leads to a 0.01 % increase in economic growth at the 50th percentile and a 0.16 % increase at the 75th percentile. However, at the 25th percentile, technological innovation reduces economic growth by 0.05 %. Conversely, the average increase in urbanization increases economic growth by 0.38 %, 0.61 %, and 0.83 % at the 25th, 50th, and 75th percentiles, respectively. Robustness tests confirm that technological innovations and urbanization promote economic growth in Tanzania. The study discusses the potential channels through which technological innovation and urbanization influence economic growth in Tanzania and transforms society, and provides practical policy implications.</p></div>","PeriodicalId":100776,"journal":{"name":"Journal of Economy and Technology","volume":"2 ","pages":"Pages 235-246"},"PeriodicalIF":0.0,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949948824000337/pdfft?md5=457a39306a7ce29206e9c50fc2eea516&pid=1-s2.0-S2949948824000337-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142048597","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":"Next generation of electronic medical record search engines to support chart reviews: A systematic user study and future research direction","authors":"Cheng Ye,&nbsp;Daniel Fabbri","doi":"10.1016/j.ject.2024.03.003","DOIUrl":"10.1016/j.ject.2024.03.003","url":null,"abstract":"<div><h3>Objective</h3><p>Little research has been done on the user-centered document ranking approach, especially in a crowdsourcing chart review environment. As the starting point of designing and implementing the next generation of Electronic Medical Record (EMR) search engines, a systematic user study is needed to better understand the users' needs, challenges, and future research directions of EMR search engines.</p></div><div><h3>Materials and methods</h3><p>One primary observation during the user study is the need for a ranking method to better support the so-called \"early stopping\" reviewing strategy (i.e., reviewing only a subset of EMRs of one patient to make the final decision) during the clinical chart reviews. The authors proposed two novel user-centered ranking metrics: \"critical documents\" and \"negative guarantee ratio,\" to better measure the power of a ranking method in supporting the “early stopping” requirements during clinical chart reviews.</p></div><div><h3>Results</h3><p>The evaluation results show that i) traditional information retrieval metrics, such as the precision-at-K, have limitations in guiding the design and development of EMR search engines to better support clinical chart reviews; ii) there is not a global optimal ranking method that fits the needs of different chart reviews and different users; iii) a learning-to-rank approach cannot guarantee a stable and optimal ranking for different chart reviews and different users; and iv) A user-centered ranking metric, such as the negative guarantee ratio (NGR) metric is able to measure the “early-stopping” performance of ranking methods.</p></div><div><h3>Conclusions</h3><p>User-centered ranking metrics can better measure the power of ranking methods in supporting clinical chart reviews. Future research should explore more user-centered ranking metrics and evaluate their impact on real-world EMR search engines.</p></div>","PeriodicalId":100776,"journal":{"name":"Journal of Economy and Technology","volume":"2 ","pages":"Pages 22-30"},"PeriodicalIF":0.0,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949948824000179/pdfft?md5=36f2dbd89d4f348572f9e914feadf69c&pid=1-s2.0-S2949948824000179-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140766510","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":"IoT-driven accessibility: A refreshable OCR-Braille solution for visually impaired and deaf-blind users through WSN","authors":"Kishor K. Reddy ,&nbsp;Rithika Badam ,&nbsp;Shadab Alam ,&nbsp;Mohammed Shuaib","doi":"10.1016/j.ject.2024.04.007","DOIUrl":"10.1016/j.ject.2024.04.007","url":null,"abstract":"<div><p>The spectacular concept of integrating OCR with the Internet of Things (IoT) and Wireless Sensor Networks (WSN), presented in this study, intends to increase the autonomy and social inclusion of people with visual impairments and deaf-blindness. This application converts text from photographs into real-time Braille representations by utilizing the capabilities of Optical Character Recognition (OCR) technology, Braille displays, and IoT. Braille is a tactile form of writing which assists the visually impaired by representing letters and numbers with raised dots. Text recognition and conversion through OCR helps people with vision issues by converting printed text into accessible formats like audio or Braille, assisting people in with recognizing things around them. Individuals with visual impairments are given autonomous access to critical information by smoothly integrating modern technologies, boosting their self-confidence and promoting active social involvement. This OCR-Braille approach's primary objective is to minimize the knowledge gap and promote social equality. Users' ease of access to labels, educational resources, and digital information about their environment fosters a sense of empowerment and independence. This ground-breaking study not only eliminates the accessibility gap but also provides the groundwork for a society that is better linked and accessible. Individuals have access to the tools they need for independently navigating their surroundings through simple IoT connectivity and WSN. This research lays the path for a future for assistive technology to catalyze equality and independence, independent of one's visual ability, by fusing assistive technology and IoT connectivity.</p></div>","PeriodicalId":100776,"journal":{"name":"Journal of Economy and Technology","volume":"2 ","pages":"Pages 128-137"},"PeriodicalIF":0.0,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949948824000246/pdfft?md5=9ab3b2ebcb91f607e5457bba705934a7&pid=1-s2.0-S2949948824000246-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140775307","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":"Factors affecting the aesthetic experiences in educational games: A qualitative investigation","authors":"Fatemeh Jafarkhani ,&nbsp;Fatemeh Barani ,&nbsp;Khaled Nawaser ,&nbsp;Hasan Rashidi ,&nbsp;Behrooz Gharleghi","doi":"10.1016/j.ject.2024.07.002","DOIUrl":"10.1016/j.ject.2024.07.002","url":null,"abstract":"<div><p>Aesthetics play a pivotal role in enriching the learning experience and are indispensable for fostering optimal educational environments. This study aims to identify the factors that shape aesthetic experiences within educational gaming contexts. Employing a qualitative methodology, data were scrutinized through inductive content analysis. A review of pertinent literature on aesthetic elements from 1994 to 2022 yielded 250 selected resources. Subsequently, based on purposive sampling, 108 sources were analyzed. These sources were systematically coded and recorded in a table as key phrases pertaining to the key components of elements of game aesthetics. In the final phase, eight faculty members with expertise in educational technology and art, specializing in educational games, evaluated the factors influencing aesthetic experiences. Their collective expertise affirmed the face and content validity of the identified factors. The findings revealed six key factors that significantly shape the aesthetic experience in educational games. These factors are instrumental in fostering player immersion, as they significantly influence attention, visualization, and emotional engagement. The findings also highlight the imperative for game designers and developers to incorporate these factors into future educational games to enhance the quality of game-based learning.</p></div>","PeriodicalId":100776,"journal":{"name":"Journal of Economy and Technology","volume":"2 ","pages":"Pages 200-207"},"PeriodicalIF":0.0,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949948824000301/pdfft?md5=930f0effc212b468d0f9f109e0d401e0&pid=1-s2.0-S2949948824000301-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141690397","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":"Predicting e-commerce CLV with neural networks: The role of NPS, ATV, and CES","authors":"Vahid Norouzi","doi":"10.1016/j.ject.2024.04.004","DOIUrl":"10.1016/j.ject.2024.04.004","url":null,"abstract":"<div><p>Accurately predicting Customer Lifetime Value (CLV) is paramount in optimizing customer relationship management. This study introduces a novel deep learning approach, employing a neural network model to forecast CLV for a leading international e-commerce retailer. This investigation delves into the interplay of key performance indicators—Net Promoter Score (NPS), Average Transaction Value (ATV), and Customer Effort Score (CES)—and their collective impact on CLV. The research utilized a dataset of 15,000 customer profiles and crafted a sequential neural network with dense layers optimized through hyperparameter tuning and regularization to thwart overfitting. The model's efficacy was assessed on a 10 % test set, revealing its adeptness at capturing intricate, nonlinear predictor-customer lifetime value (CLV) relationships. Consistency in training and test performance metrics underscored the model's generalizability, while high R-squared and explained variance scores confirmed the predictive strength of the chosen factors. This research seeks to provide a solution for building an artificial intelligence model with an artificial neural network algorithm to predict customer lifetime value. By incorporating this principle, the study aims to leverage the power of neural networks to forecast CLV, enabling retailers to make informed decisions and optimize customer relationships accurately. This study finds that Net Promoter Score (NPS) and Customer Effort Score (CES) have a powerful impact on the neural network model's ability to predict Customer Lifetime Value (CLV) accurately. On the other hand, while Average Transaction Value (ATV) exhibits the least impact, it still significantly contributes to the accuracy of Customer Lifetime Value (CLV) predictions. These results underscore the importance of incorporating customer feedback metrics like NPS and CES when building predictive models for CLV estimation. Integrating critical customer metrics into neural networks gives retailers enhanced insights, enabling precise customer segmentation, resource allocation, and strategic growth. The study paves the way for future research to refine further CLV prediction, including dataset expansion, customer profile enrichment, and prescriptive marketing optimization.</p></div>","PeriodicalId":100776,"journal":{"name":"Journal of Economy and Technology","volume":"2 ","pages":"Pages 174-189"},"PeriodicalIF":0.0,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949948824000222/pdfft?md5=e5f3c40d1d18cdc94a9190f9a8048c8d&pid=1-s2.0-S2949948824000222-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140795694","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":"Nexus between economy, technology, and ecological footprint in China","authors":"Asif Raihan","doi":"10.1016/j.ject.2023.09.003","DOIUrl":"https://doi.org/10.1016/j.ject.2023.09.003","url":null,"abstract":"<div><p>In contemporary times, nations across the globe, encompassing both developed and emerging economies, are actively pursuing the objective of achieving sustainable economic growth. China, as a prominent emerging nation, holds a significant position in the worldwide environment. However, it is imperative to acknowledge that China's ecological impact is substantial, as evidenced by its considerable contribution of almost one-third of the total global carbon emissions in the year 2021. The encouraging aspect lies in the emergence of China as a significant economic power, which may be attributed to the positive impact of technological advancements. The scientific literature suggests that the use of novel technologies has the potential to contribute significantly to mitigating environmental degradation. The objective of this study is to investigate the impact of China's economic growth and technological advancements on ecological footprint throughout the period spanning from 1985 to 2020. This study utilizes the ecological footprint concept as a means to assess environmental degradation in China. The ARDL cointegration methodology is utilized to estimate the long- and short-term impacts, and the outcomes are validated through the application of further cointegration regression techniques. Furthermore, the pairwise Granger causality analysis is employed to examine the causal links among the variables. The empirical evidence suggests that economic expansion exacerbates environmental degradation in China, whereas technological progress plays a mitigating role in addressing this issue. The results of the study also demonstrated a bidirectional causality between economic growth and technological innovation, suggesting that China's economic growth and technological progress mutually reinforce one another. The paper proposes green technical solutions that have the potential to mitigate environmental degradation while maintaining economic growth. Sustaining long-term economic prosperity necessitates the implementation of both carbon emission taxation and strategic investments in environmentally beneficial technologies.</p></div>","PeriodicalId":100776,"journal":{"name":"Journal of Economy and Technology","volume":"1 ","pages":"Pages 94-107"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949948823000069/pdfft?md5=cc5a83c6248e97867f8c3c2c74dfac1f&pid=1-s2.0-S2949948823000069-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"92045651","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":"Asynchronous distributed charging protocol for plug-in electric vehicles","authors":"Yunfan Zhang ,&nbsp;Yifan Su ,&nbsp;Yue Chen ,&nbsp;Feng Liu","doi":"10.1016/j.ject.2023.09.002","DOIUrl":"https://doi.org/10.1016/j.ject.2023.09.002","url":null,"abstract":"<div><p>The proliferation of plug-in electric vehicles (PEVs) advocates a distributed paradigm for coordinating PEV charging. Unlike existing primal-dual decomposition or consensus methods, this paper proposes a cutting-plane-based distributed algorithm considering a peer-to-peer (P2P) communication network, which enables asynchronous coordination among PEVs. First, an equivalent surrogate model is established by exploiting the duality of the original optimization problem, which masks the private information of individual users by equivalent transformation. Then, a cutting-plane based algorithm is derived to solve the surrogate problem in a distributed manner with intrinsic superiority to cope with various asynchrony. Critical implementation issues, including distributed initialization, distributed cutting-plane generation, and localized stopping criteria, are discussed in detail. Numerical tests on IEEE 37- and 123-node feeders with actual data illustrate that the proposed method is resilient to several asynchronies and admits the plug-and-play operation mode. The proposed methodology is expected to provide an alternative path toward the robust protocol for PEV charging.</p></div>","PeriodicalId":100776,"journal":{"name":"Journal of Economy and Technology","volume":"1 ","pages":"Pages 29-47"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50189037","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":"A study on ChatGPT for Industry 4.0: Background, potentials, challenges, and eventualities","authors":"Mohd Javaid ,&nbsp;Abid Haleem ,&nbsp;Ravi Pratap Singh","doi":"10.1016/j.ject.2023.08.001","DOIUrl":"10.1016/j.ject.2023.08.001","url":null,"abstract":"<div><p>ChatGPT is an Artificial Intelligence (AI)-powered Natural Language Processing (NLP) tool that comprehends and produces text in response to given commands. It can be adopted for various requirements, like answering our inquiries, assisting us with content creation, translating languages, and more. The fourth industrial revolution, called \"Industry 4.0,\" denotes a new production age focused on automation, digitalisation, and real-time connectivity of production systems. ChatGPT can help Industry 4.0 in a variety of ways. ChatGPT and AI-driven process optimisation is poised to revolutionise Industry 4.0 by enhancing productivity, quality assurance, and efficiency. For developing this paper, various articles on ChatGPT/ AI for Industry 4.0 were identified through Scopus, ScienceDirect, Google Scholar and ResearchGate. Industry 4.0 progresses due to the incorporation of cutting-edge technology like AI, Machine Learning (ML), and NLP and Manufacturing operations are changing. The ChatGPT language model is becoming well-known for daily use because of its promising applications. In the framework of Industry 4.0, it promises to revolutionise processes to assist advancement in boosting business productivity and efficiency. This paper studies the major need for ChatGPT for Industry 4.0. Various associated features, traits and versatile competencies of ChatGPT for Industry 4.0 are identified and briefed. Finally, it identifies and discusses the significant applications of ChatGPT for Industry 4.0. ChatGPT is a very flexible and efficient method for creating human-machine interfaces and automatically generating text, which provides proper knowledge and guidance to the employee. Applications for ChatGPT include chatbots, virtual assistants, automated customer care, language translation, and content production. In future, it will become an effective tool for enhancing communication and automating processes in Industry 4.0.</p></div>","PeriodicalId":100776,"journal":{"name":"Journal of Economy and Technology","volume":"1 ","pages":"Pages 127-143"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949948823000033/pdfft?md5=a29a7ee67c3e05fa7018dac392c697c3&pid=1-s2.0-S2949948823000033-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73263587","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 neural networks in supply chain management, a review","authors":"Mohsen Soori ,&nbsp;Behrooz Arezoo ,&nbsp;Roza Dastres","doi":"10.1016/j.ject.2023.11.002","DOIUrl":"https://doi.org/10.1016/j.ject.2023.11.002","url":null,"abstract":"<div><p>Artificial Neural Networks (ANNs) are a type of machine learning algorithm inspired by the structure and function of the human brain. In the context of supply chain management, ANNs can be used for demand forecasting, inventory optimization, logistics planning, and anomaly detection. ANNs help companies to optimize their inventory levels, production schedules and procurement activities in terms of productivity enhancement of part production. By considering multiple variables and constraints, ANNs can identify the most efficient routes, allocate resources effectively, and reduce costs. Furthermore, ANNs can identify anomalies as well as abnormalities in supply chain data, such as unexpected demand patterns, quality issues and disruptions in logistics operations in order to minimize their impact on the supply chain. ANNs can also analyze supplier performance data, including quality, delivery times and pricing in order to assess the reliability and effectiveness of suppliers. This information can support decision-making processes in supplier evaluation and selection processes. Moreover, ANNs can continuously monitor supplier performance, raising alerts for deviations from predefined criteria to provide safe and secure supply chain in part production processes. By analyzing various data sources, including weather conditions, and political instability, ANNs can identify and mitigate risks in terms of safety enhancement of supply chain processes. Artificial neural networks in supply chain management is studied in the research work to analyze and enhance performances of supply chain management in process of part manufacturing. New ideas and concepts of future research works are presented by reviewing and analyzing of recent achievements in applications of artificial neural networks in supply chain management. Thus, productivity of part manufacturing can be enhanced by promoting the supply chain management using the artificial neural networks.</p></div>","PeriodicalId":100776,"journal":{"name":"Journal of Economy and Technology","volume":"1 ","pages":"Pages 179-196"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949948823000112/pdfft?md5=c3a0d0ce8ab84c070736a6079499b5c5&pid=1-s2.0-S2949948823000112-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138577797","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}