{"title":"Corrigendum to “Federated learning and information sharing between competitors with different training effectiveness” [J. Econ. Technol. (2025) 1–9]","authors":"Jiajun Meng , Jing Chen , Dongfang Zhao","doi":"10.1016/j.ject.2025.02.002","DOIUrl":"10.1016/j.ject.2025.02.002","url":null,"abstract":"","PeriodicalId":100776,"journal":{"name":"Journal of Economy and Technology","volume":"3 ","pages":"Page 282"},"PeriodicalIF":0.0,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143942066","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":"The impact of customer boredom on the efficacy of a rewards","authors":"Axel Stock , Minoo Talebi Ashoori","doi":"10.1016/j.ject.2025.04.001","DOIUrl":"10.1016/j.ject.2025.04.001","url":null,"abstract":"<div><div>In this paper, we study utilizing a game theoretic model, how variety seeking triggered by customer boredom may affect a firm’s rewards program, pricing strategy and profits. Customer Boredom is conceptualized as a utility loss resulting from the purchase of a previously consumed brand. We analyze a two period model where two firms compete for a market of forward looking consumers by selling horizontally differentiated brands. When making the purchase decision in the second period, consumers trade off the utility loss from boredom with the benefits from obtaining the reward offered. In our analysis, we interestingly find that depending on consumers’ discount factor, firm profits either strictly increase or follow a u-shaped relationship with customer boredom. We also consider the case when brands differ in quality and show that under some conditions the high-quality firm’s profits decline while the low quality firm benefits when variety seeking due to boredom increases.</div></div>","PeriodicalId":100776,"journal":{"name":"Journal of Economy and Technology","volume":"3 ","pages":"Pages 299-313"},"PeriodicalIF":0.0,"publicationDate":"2025-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144069348","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":"Blockchains effects on responsiveness to recalls in the food and beverage industry","authors":"Abbas Keramati , Bethany Siau , Tyler Bellitto , Jafar Heydari , Tanya Panchal","doi":"10.1016/j.ject.2025.05.001","DOIUrl":"10.1016/j.ject.2025.05.001","url":null,"abstract":"<div><div>Blockchain technology, by revolutionizing the way businesses use data, is shifting the cost-responsiveness frontier. While the most popular application of blockchain is cryptocurrency, nowadays it is touching many other businesses including the food and beverage industry. This paper is a short survey in assessing the usefulness of blockchain technology in the food and beverage supply chain, with a narrow focus on the impact on the product recalls. While recalls are crucial in the food and beverage industry, as they deal with public health, they happen frequently and therefore an efficient and responsive recall process is essential. This paper investigates whether US companies utilizing blockchain technology experience shorter recall durations. Data from Food and Drug Administration (FDA) recall datasets, specifically targeting companies implementing blockchain technology, are analyzed using statistical analysis methods. The results reveal that companies adopting blockchain technology have significantly shorter recall times, demonstrating their usefulness in food and beverage recalls, along with its other advantages. This study highlights the potential of blockchain in improving recall management within the food and drink industry and provides applicable insights for food and beverage supply chain managers.</div></div>","PeriodicalId":100776,"journal":{"name":"Journal of Economy and Technology","volume":"3 ","pages":"Pages 283-298"},"PeriodicalIF":0.0,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144068898","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":"UCM-NetV2: An efficient and accurate deep learning model for skin lesion segmentation","authors":"Chunyu Yuan , Dongfang Zhao , Sos S. Agaian","doi":"10.1016/j.ject.2025.02.001","DOIUrl":"10.1016/j.ject.2025.02.001","url":null,"abstract":"<div><div>Accurate segmentation of skin lesions from dermoscopic images is crucial for early skin cancer detection, yet variations in lesion appearance and image artifacts present challenges. This study proposes an efficient deep learning model, UCM-NetV2, to improve accuracy and computational efficiency. UCM-NetV2 enhances the UCM-Net architecture with a novel \"cyber-structure\" com- bining Multilayer Perceptron and CNN layers, improving prediction accuracy while maintaining an ultra-lightweight design with only 0.046 million parameters. Evaluations on the ISIC2017 and ISIC2018 datasets demonstrate that UCM-NetV2 outperforms existing methods in accuracy and com- putational efficiency, achieving up to 67 times faster inference speeds than U-Net and requiring less than 0.04 GFLOPs. These advancements make skin lesion analysis more accessible, particularly in resource-limited settings, enabling proactive skin health monitoring and facilitating teledermatology. To foster further innovation in mobile health diagnostics, the source code for UCM-NetV2 is on <span><span>https://github.com/chunyuyuan/UCMV2-Net</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":100776,"journal":{"name":"Journal of Economy and Technology","volume":"3 ","pages":"Pages 251-263"},"PeriodicalIF":0.0,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143854789","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":"Remanufacturing facility installation decisions under product sourcing cost uncertainties: A real options approach","authors":"Mohammad Ahnaf Sadat, K. Jo Min","doi":"10.1016/j.ject.2025.02.003","DOIUrl":"10.1016/j.ject.2025.02.003","url":null,"abstract":"<div><div>In this paper, we investigate the strategic decision-making process of a Maintenance Repair and Overhaul (MRO) company considering the installation of a remanufacturing facility under product sourcing cost uncertainties (e.g., purchasing new products from third-party, and remanufacturing used ones). We consider the remanufacturing costs to consist of constant and variable portions. The variable portion is the acquisition cost of used products, which we consider to be correlated with the new product's purchasing costs. Assuming an indefinite lifespan for the remanufacturing facility and equivalent pricing and customer valuation for remanufactured and new products, we employ the real options approach and the quasi-analytical method for problem modeling and solution derivation. The study reveals that the decision to install a remanufacturing facility is influenced by various cost combinations rather than a single threshold. We derive and show the procedure to obtain these cost combinations. Significantly, we discover that unit-based variable subsidies, such as tax exemptions, can effectively reduce this cost threshold, making remanufacturing a more viable option. This insight is crucial for policymakers and businesses, highlighting the role of government incentives in promoting sustainable remanufacturing practices and contributing to the understanding of remanufacturing as a financially viable and sustainable strategy.</div></div>","PeriodicalId":100776,"journal":{"name":"Journal of Economy and Technology","volume":"3 ","pages":"Pages 123-142"},"PeriodicalIF":0.0,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143611380","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":"Event driven technology intelligence","authors":"Song-Kyoo Kim","doi":"10.1016/j.ject.2025.01.004","DOIUrl":"10.1016/j.ject.2025.01.004","url":null,"abstract":"<div><div>The Event Driven Technology Intelligence (EDTI) model offers a structured approach to navigating the complexities of technological innovation. This research aims to summarize the core concepts and phases of the EDTI model while also exploring its significance in various industries. By expanding on the traditional Hype-cycle model to include seven phases, EDTI guides companies from concept innovation through product execution. Crucial to this model are the Moments-of-Event which represent key breakthroughs necessary for advancing technologies. By integrating these insights, EDTI enhances decision-making, fosters innovation, and mitigates risks associated with technology obsolescence, ultimately helping organizations adapt to changing consumer demands and maintain competitiveness in dynamic markets. In the rapidly evolving landscape of technology, the EDTI model emerges as a vital tool for organizations striving to remain competitive. This model flourishes in a climate marked by global competition and the constant demand for innovation. Key to its success is the integration of critical events and technological breakthroughs, which allow businesses to effectively manage and leverage emerging technologies.</div></div>","PeriodicalId":100776,"journal":{"name":"Journal of Economy and Technology","volume":"3 ","pages":"Pages 143-150"},"PeriodicalIF":0.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143619785","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":"Federated learning and information sharing between competitors with different training effectiveness","authors":"Jiajun Meng , Jing Chen , Dongfang Zhao","doi":"10.1016/j.ject.2024.12.003","DOIUrl":"10.1016/j.ject.2024.12.003","url":null,"abstract":"<div><div>Federated Learning (FL) is an innovative technique that allows multiple firms to collaborate in training machine learning models while preserving data privacy. This is especially important in industries where data is sensitive or subject to regulations like the General Data Protection Regulation (GDPR). Despite its substantial benefits, the adoption of FL in competitive markets faces significant challenges, particularly due to concerns about training effectiveness and price competition. In practice, data from different firms may not be independently and identically distributed (non-IID) and heterogenous, which can lead to differences in model training effectiveness when aggregated through FL. This paper explores how initial product quality, data volume, and training effectiveness affect the formation of FL. We develop a theoretical model to analyze firms’ decisions between adopting machine learning (ML) independently or collaborating through FL. Our results show that when the initial product quality is high, FL can never be formed. Moreover, when the initial product quality is low, and when data volume is low and firms’ training effectiveness differences are small, FL is more likely to form. This is because the competition intensification effect is dominated by the market expansion effect of FL. However, when there is a significant difference in training effectiveness, firms are less likely to adopt FL due to concerns about competitive disadvantage (i.e., the market expansion effect is dominated by the competition intensification effect). This paper contributes to the literature on FL by addressing the strategic decisions firms face in competitive markets and providing insights into how FL designers and policymakers can encourage the formation of FL.</div></div>","PeriodicalId":100776,"journal":{"name":"Journal of Economy and Technology","volume":"3 ","pages":"Pages 1-9"},"PeriodicalIF":0.0,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143093958","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}
Martín Hernani-Merino , Jorge Tello-Gamarra , David Mayorga , Julio Zevallos
{"title":"From innovation capability to green innovation capability: Evidence from Chinese big tech firms","authors":"Martín Hernani-Merino , Jorge Tello-Gamarra , David Mayorga , Julio Zevallos","doi":"10.1016/j.ject.2025.01.003","DOIUrl":"10.1016/j.ject.2025.01.003","url":null,"abstract":"<div><div>Innovation capability as a source of competitive advantage for firms is a consolidated topic in the literature. However, there is still little evidence about the green characteristics that innovation capability incorporates. This article aims to identify the innovation capability and analyze the existence of green variables in said capability. We conducted a multiple case study comprising four Big Tech firms from the Chinese technology industry. The results show that each of the capabilities involved in the innovation capability (technological, operational, managerial, marketing, and learning) demonstrates a green variable. As a second result, we define the concept of green innovation capability as a repertoire of abilities, skills, knowledge, and routines for the firm to design, produce, and transact green products and services. Furthermore, we propose the concepts of the capabilities that form the green innovation capability.</div></div>","PeriodicalId":100776,"journal":{"name":"Journal of Economy and Technology","volume":"3 ","pages":"Pages 95-108"},"PeriodicalIF":0.0,"publicationDate":"2025-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143552834","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":"Quantitative modeling of M&A success probability: Integrating macroeconomic volatility and temporal factors through survival analysis","authors":"Dan Xu","doi":"10.1016/j.ject.2024.12.002","DOIUrl":"10.1016/j.ject.2024.12.002","url":null,"abstract":"<div><div>This paper delves into the intricate dynamics of the likelihood of merger and acquisition (M&A) completion in China and scrutinizes the influence of global and domestic economic conditions through survival analysis. By utilizing data from 3227 domestic M&A transactions from 1998 to 2024, this study employs quantitative survival analysis and the Cox proportional hazards model to evaluate how economic indicators shape M&A success rates. Notably, increases in the industrial production index (IPI) and producer price index (PPI) are positively associated with an increased likelihood of completion, reflecting how economic expansion fosters financial stability, strengthens firm capacity, and facilitates deal finalization. In contrast, rising global policy uncertainty, as captured by the global economic policy uncertainty (EPU) index, significantly reduces the likelihood of M&A completion by amplifying valuation ambiguity, negotiation frictions, and regulatory risks. Unexpectedly, the global economic growth—represented by the global real economic activity (GREA) index—correlates with a decreased likelihood of success in domestic M&A, potentially due to a shift in focus toward international opportunities and rising costs of domestic operations. Furthermore, the Kaplan<img>Meier estimator of the hazard function reveals a nonlinear curve depicting the likelihood of deal completion over time, emphasizing fluctuations in the probability of success. Our results indicate that the time elapsed from the announcement of a deal can provide crucial information on the ex-ante probability of its success or failure, highlighting the importance of considering the temporal aspect of the deal.</div></div>","PeriodicalId":100776,"journal":{"name":"Journal of Economy and Technology","volume":"3 ","pages":"Pages 202-222"},"PeriodicalIF":0.0,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143697157","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":"Innovative machine learning approaches for complexity in economic forecasting and SME growth: A comprehensive review","authors":"Mustafa I. Al-Karkhi , Grzegorz Rza̧dkowski","doi":"10.1016/j.ject.2025.01.001","DOIUrl":"10.1016/j.ject.2025.01.001","url":null,"abstract":"<div><div>Economic forecasting and small and medium-sized enterprises (SMEs) growth prediction have become essential tools for guiding policy, business strategy, and economic development in an increasingly data-driven world. This paper reviews recent advancements in economic regression and SME growth forecasts, with a focus on the application of machine learning (ML) techniques. Specifically, the findings highlight that the integration of ensemble methods and deep learning models has achieved significant improvements in prediction accuracy, while interpretability tools such as SHAP and LIME enhance transparency and user trust. It provides a structured analysis of diverse methodologies that includes ensemble methods, deep learning models, and interpretability tools to evaluate their effectiveness and limitations in addressing the complexities of economic and SME data. This review categorizes studies by regional focus to highlight unique challenges in different economic landscapes and the adaptability of various forecasting models. Key challenges—such as imbalanced data, feature selection, and the integration of real-time data—were identified as critical factors for enhancing prediction reliability and applicability. By comparing existing surveys and identifying gaps, this review presents actionable insights and proposes future research directions that emphasize the need for integrative models that combine Explainable Artificial Intelligence (XAI) with cross-regional data fusion for more accurate and adaptable economic forecasts. These integrative models have the potential to achieve greater regional generalizability by the offering of better decision-making tools for policymakers. The findings underscore the transformative role of ML and XAI in economic forecasting and offer valuable guidance for researchers and decision-makers to optimize forecasting models for business growth and economic planning.</div></div>","PeriodicalId":100776,"journal":{"name":"Journal of Economy and Technology","volume":"3 ","pages":"Pages 109-122"},"PeriodicalIF":0.0,"publicationDate":"2025-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143600456","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}