Journal of Economy and Technology最新文献

{"title":"Enhancing energy resilience in manufacturing enterprises: A systematic mapping of challenges to strategies","authors":"P. Lebepe,&nbsp;T.N.D. Mathaba","doi":"10.1016/j.ject.2025.01.002","DOIUrl":"10.1016/j.ject.2025.01.002","url":null,"abstract":"<div><div>An unreliable energy supply disrupts productivity and operational stability in manufacturing enterprises worldwide. Addressing these challenges requires achieving consensus among experts from diverse backgrounds. This study provides a preliminary understanding of mapping challenges to strategies, ensuring each challenge is paired with the most effective solution. By employing a structured and methodological approach, it ensures actionable insights, advancing academic discourse on energy resilience frameworks and their practical application in manufacturing enterprises. The study integrates Fleiss’ Kappa for expert agreement with the CRITIC (Criteria Importance Through Intercriteria Correlation) method for objective strategy weighting, ensuring rigorous evaluation of relevance and importance. Grounded in the 4As energy resilience framework; Availability, Accessibility, Affordability, and Acceptability, the approach ensures adaptability and a balanced alignment of challenges with actionable strategies. Fourteen industry experts validated the framework, prioritizing strategies such as flexible scheduling and renewable energy integration. This study addresses the limitations of traditional methods like Delphi, which require multiple rounds and delay outcomes, by achieving rapid consensus in a single round. Combining Fleiss’ Kappa and CRITIC balances qualitative insights with objective analysis, reducing biases and enhancing reliability. These contributions establish the framework as a novel, scalable, and practical tool for improving energy resilience in diverse manufacturing contexts.</div></div>","PeriodicalId":100776,"journal":{"name":"Journal of Economy and Technology","volume":"3 ","pages":"Pages 82-94"},"PeriodicalIF":0.0,"publicationDate":"2025-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143552833","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":"User activity to enhance customer lifetime value modeling in contractual streaming industry","authors":"Eudes Adiba ,&nbsp;Maurice Comlan ,&nbsp;Eugéne C. Ezin ,&nbsp;Nesta Kouzounhoue","doi":"10.1016/j.ject.2024.12.001","DOIUrl":"10.1016/j.ject.2024.12.001","url":null,"abstract":"<div><div>This article presents a model for Customer Lifetime Value (CLV) tailored to the subscription-based streaming industry, incorporating both contractual dynamics and user activity. Unlike traditional CLV models that overlook contracts, this semi-Markov model captures the time users remain in specific subscription plans and the transitions between these subscription plans. Using empirical data from the MTN TV platform for a step-by-step implementation, the study identifies key factors influencing subscription cancellations, such as expiration dates and viewing behavior. The results show that longer subscriptions yield higher CLV, with more predictable churn cycles. These findings can guide marketing strategies and resource management to maximize CLV in the streaming sector.</div></div>","PeriodicalId":100776,"journal":{"name":"Journal of Economy and Technology","volume":"3 ","pages":"Pages 69-81"},"PeriodicalIF":0.0,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143534927","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":"ChatGPT and CLT: Investigating differences in multimodal processing","authors":"Michael Cahalane,&nbsp;Samuel N. Kirshner","doi":"10.1016/j.ject.2024.11.008","DOIUrl":"10.1016/j.ject.2024.11.008","url":null,"abstract":"<div><div>Drawing on construal level theory, recent studies have demonstrated that ChatGPT interprets text inputs from an abstract perspective. However, as ChatGPT has evolved into a multimodal tool, this research examines whether ChatGPT's abstraction bias extends to image-based prompts. In a pre-registered study utilising hierarchical letters, ChatGPT predominantly associated these images with local rather than global letters, suggesting a concrete bias when analysing images. This starkly contrasts human participants who predominantly identified the same images with the global letters, indicating that humans and ChatGPT significantly diverge in image interpretations. Furthermore, while humans generally perceive ChatGPT to be more concrete in image processing, there is a notable discrepancy between this perception and the actual level of concreteness exhibited by ChatGPT in handling image-based tasks. These findings provide insights into the distinct cognitive behaviours of LLMs compared to humans, contributing to an emerging understanding of LLM cognition in the context of multimodal inputs.</div></div>","PeriodicalId":100776,"journal":{"name":"Journal of Economy and Technology","volume":"3 ","pages":"Pages 10-21"},"PeriodicalIF":0.0,"publicationDate":"2024-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143093661","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":"Research on the low-carbon transformation of energy consumption under population aging in China","authors":"Rumei Liu ,&nbsp;Lu Tang ,&nbsp;Qingrui Liu ,&nbsp;Jianing Zhang","doi":"10.1016/j.ject.2024.11.007","DOIUrl":"10.1016/j.ject.2024.11.007","url":null,"abstract":"<div><div>The low-carbon transformation of energy consumption is a key path to achieving the carbon emissions peak and carbon neutrality in China. Furthermore, technological innovation and policy regulation are necessary to promote low-carbon transformation of energy consumption, especially considering the issues associated with population aging. According to empirical facts and theoretical analysis, we demonstrate that population aging, technological innovation, and policy regulation affect the low-carbon transformation of energy consumption. Then, we build a PVAR model and conduct an empirical test using provincial panel data in China from 2003 to 2020. The results show that population aging, technological innovation, and policy regulation all contribute to the low-carbon index of energy consumption, and the interaction among the three forms a transmission mechanism to promote the low-carbon transformation of energy use in terms of both the production and consumption. The positive effect of population aging on the low-carbon index of energy consumption exhibits an inverted U-shaped curve that gradually increases at first and then gradually decreases. The positive effect of policy regulations on the low-carbon index of energy consumption follows an L-shaped curve, and the positive effect of technological innovation on the low-carbon index of energy consumption shows a constantly increasing trend. From the perspective of impact intensity, compared with population aging and policy regulation, technological innovation has a higher impact on the low-carbon index of energy consumption. With the rise in population aging, the effects of technological innovation, policy regulation, and technological innovation-policy regulation on the low-carbon index of energy consumption are ranked from low to high intensity. From the perspective of regional heterogeneity, compared with the middle and western regions, the positive effect of technological innovation and policy regulation on the low-carbon index of energy consumption under population aging in the eastern region is more significant. Our findings reveal the value of technological innovation and policy regulation in promoting low-carbon transformation of energy consumption while population aging is increasing in all countries around the world.</div></div>","PeriodicalId":100776,"journal":{"name":"Journal of Economy and Technology","volume":"3 ","pages":"Pages 151-165"},"PeriodicalIF":0.0,"publicationDate":"2024-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143619784","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":"Examining the impacts of information and communication technology (ICT) on national development and wellbeing: A global perspective","authors":"Ming-Yi Wu","doi":"10.1016/j.ject.2024.11.006","DOIUrl":"10.1016/j.ject.2024.11.006","url":null,"abstract":"<div><div>The impacts of information and communications technology (ICT) on national development and wellbeing is a current research issue. By integrating four World Bank datasets and World Happiness Report’s global wellbeing dataset, this study analyzes the impacts of ICT on national development and wellbeing in 124 economies. There are several significant findings based on multiple regression analysis. First, Internet, mobile, and broadband subscription rates are significant predictors for logged GDP per capita. Second, broadband subscription rate is a significant predictor for perceptions of corruption. Third, Internet and broadband penetration rates are significant predictors for subjective wellbeing, social support and healthy life expectancy. Finally, fixed broadband and fixed telephone subscription rates are significant predictors for freedom to make life choices. Interestingly, fixed telephone subscription rate inversely predicts freedom to make life choices. The findings of this study bring updated insights into ICT impacts on national development and wellbeing around the world.</div></div>","PeriodicalId":100776,"journal":{"name":"Journal of Economy and Technology","volume":"3 ","pages":"Pages 190-201"},"PeriodicalIF":0.0,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143642982","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 role of parental circumstances and luck in shaping socioeconomic success: A simulation-based analysis of talent","authors":"Hana Hebishima ,&nbsp;Shin-ichi Inage","doi":"10.1016/j.ject.2024.11.003","DOIUrl":"10.1016/j.ject.2024.11.003","url":null,"abstract":"<div><div>This study investigates the interplay between parental circumstances, talent, and luck in shaping long-term socioeconomic success through an agent-based simulation model. Building on prior research on the influence of socioeconomic status (SES) and parental circumstances on educational outcomes, the model simulates how parental circumstances enhance innate talent through education and examines how this talent interacts with luck throughout an individual’s life. The simulation is divided into two phases: an educational phase and a working phase. Our results reveal that while parental circumstances and education amplify talent and increase the potential for success, cumulative luck plays the most decisive role in determining savings at age 60. A strong positive correlation is observed between cumulative luck and lifetime savings, whereas the direct influence of talent, even when enhanced through education, remains limited. Additionally, favorable parental circumstances elevate baseline savings, even for individuals experiencing misfortune, underscoring the importance of early educational advantages. These findings highlight that although talent and parental support are essential for fostering success, luck ultimately dominates in shaping financial outcomes. The study offers critical policy insights, advocating for equitable access to education and strategic investments to mitigate the disproportionate impact of luck, promote social mobility, and reduce structural inequalities across generations.</div></div>","PeriodicalId":100776,"journal":{"name":"Journal of Economy and Technology","volume":"3 ","pages":"Pages 223-236"},"PeriodicalIF":0.0,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143792511","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":"Techno-economic and emissions comparison of waste-to-fuel via hydrothermal liquefaction, transesterification, and incineration","authors":"Muhammad Usman","doi":"10.1016/j.ject.2024.11.002","DOIUrl":"10.1016/j.ject.2024.11.002","url":null,"abstract":"<div><div>The global shift toward sustainable waste management and renewable energy has sparked interest in biofuel production from sewage sludge (SS). This study evaluated four waste-to-biofuel processes like Hydrothermal Liquefaction (HTL) with upgrading, Transesterification, and Incineration with and without energy recovery using ASPEN Plus V12 to assess their techno-economic, energy, and environmental performance. HTL with upgrading emerged as the most efficient, generating ∼4,000,000 MJ/year and emitting ∼700 tonnes/year of CO₂. Transesterification yielded ∼2,850,000 MJ/year, emitting ∼1200 tonnes/year due to post-lipid extraction incineration. Incineration without energy recovery was least efficient, consuming ∼5,000,000 MJ/year and emitting ∼3000 tonnes/year of CO₂, with energy recovery yielding only ∼1,250,000 MJ/year. Financially, HTL with upgrading demonstrated strong profitability with a potential Net Present Value (NPV) of 112.9 million US dollars (MUS$), while Transesterification achieved an NPV of 23.4 MUS$. Both processes were sensitive to operating costs: a 50 % increase could reduce HTL’s NPV to 62.7 MUS$, while pushing Transesterification into a loss. Capital cost reductions could further boost HTL’s profitability, highlighting its economic resilience, unlike incineration, which remained financially unviable. In summary, HTL with upgrading offered 30 % higher energy output and 70 % lower emissions than incineration, making it a scalable, sustainable approach for SS management and biofuel production. However, a complete life cycle assessment could further enhance its potential by identifying additional environmental and economic benefits.</div></div>","PeriodicalId":100776,"journal":{"name":"Journal of Economy and Technology","volume":"3 ","pages":"Pages 237-250"},"PeriodicalIF":0.0,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143834850","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":"Leveraging federated learning for privacy-preserving analysis of multi-institutional electronic health records in rare disease research","authors":"Karthik Meduri ,&nbsp;Geeta Sandeep Nadella ,&nbsp;Akhila Reddy Yadulla ,&nbsp;Vinay Kumar Kasula ,&nbsp;Mohan Harish Maturi ,&nbsp;Steven Brown ,&nbsp;Snehal Satish ,&nbsp;Hari Gonaygunta","doi":"10.1016/j.ject.2024.11.001","DOIUrl":"10.1016/j.ject.2024.11.001","url":null,"abstract":"<div><div>This research announces that the fresh federated learning structure is designed to enhance the privacy-preserving analysis of electronic health records (EHRs), and multiple institutions in this framework permit secure collaboration among institutions, allowing them to train machine-learning replicas without directly sharing patient data. We implemented and evaluated numerous machine-learning models to forecast patient treatment needs, including Logistic Regression, Decision-Tree-Classifiers, Support-Vectors-Classifiers, Random-Forests, and Stacking-Classifiers. The Random Forest classifier achieved the best performance with an accuracy of 90 % and an F1 score of 80 %, demonstrating that it handled complex and imbalanced datasets. This FL-based approach not only complies with privacy regulations such as HIPAA and GDPR but also overcomes significant challenges in data sharing, making it ideal for rare disease research. By enabling secure data aggregation across institutions, the framework significantly enhances the ability to study rare diseases and accelerates the discovery of new treatments. Future directions include extending this framework to other areas of healthcare and incorporating advanced machine-learning techniques to enhance its capabilities further. This research sets the new standard for secure and collaborative healthcare data analysis and promotes innovation and ethical practices in rare disease research.</div></div>","PeriodicalId":100776,"journal":{"name":"Journal of Economy and Technology","volume":"3 ","pages":"Pages 177-189"},"PeriodicalIF":0.0,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143636277","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":"Global adoption of generative AI: What matters most?","authors":"Hassnian Ali ,&nbsp;Atta ul Mustafa ,&nbsp;Ahmet Faruk Aysan","doi":"10.1016/j.ject.2024.10.002","DOIUrl":"10.1016/j.ject.2024.10.002","url":null,"abstract":"<div><div>This study investigates the determinants of generative AI adoption across 136 countries, leveraging cross-sectional data from 2023 and employing a negative binomial regression model to address data overdispersion. Generative AI is a transformative technology that enhances operational efficiency, drives innovation, and creates economic value across sectors. Key findings reveal that IT infrastructure, R&amp;D investments, and company investment in emerging technologies significantly foster generative AI adoption, while misaligned government policies may hinder it. The analysis identifies crucial determinants, including technological infrastructure, economic stability, regulatory environments, and workforce readiness, as pivotal to adoption rates. The study provides actionable insights for policymakers, industry leaders, and researchers, advocating for tailored policies, strategic investment in high-speed internet and cloud services, and refining government incentives to align with AI sector needs. This research uniquely contributes by offering a comprehensive, cross-country perspective on factors influencing generative AI adoption.</div></div>","PeriodicalId":100776,"journal":{"name":"Journal of Economy and Technology","volume":"3 ","pages":"Pages 166-176"},"PeriodicalIF":0.0,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143636276","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":"Deciphering algorithmic collusion: Insights from bandit algorithms and implications for antitrust enforcement","authors":"Frédéric Marty ,&nbsp;Thierry Warin","doi":"10.1016/j.ject.2024.10.001","DOIUrl":"10.1016/j.ject.2024.10.001","url":null,"abstract":"<div><div>This paper explores algorithmic collusion from both legal and economic perspectives, underscoring the increasing influence of algorithms in firms’ market decisions and their potential to facilitate anti-competitive behaviour. By employing bandit algorithms as a model—typically used in uncertain decision-making scenarios—we shed light on the mechanisms of implicit collusion that occur without explicit communication. Legally, the primary challenge lies in detecting and categorizing possible algorithmic signals, particularly when they function as unilateral communications. Economically, the task of distinguishing between rational pricing strategies and collusive patterns becomes increasingly complex in the context of algorithm-driven decisions. The paper stresses the need for competition authorities to identify atypical market behaviours. Striking a balance between algorithmic transparency and the prevention of collusion is critical. While regulatory measures could mitigate collusive risks, they might also impede the development of algorithmic technologies. As this form of collusion gains prominence in competition law and economics discussions, understanding it through models like bandit algorithms becomes essential, especially since these algorithms have the potential to converge more rapidly toward supra-competitive prices equilibria.</div></div>","PeriodicalId":100776,"journal":{"name":"Journal of Economy and Technology","volume":"3 ","pages":"Pages 34-43"},"PeriodicalIF":0.0,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387069","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}