International Business & Economics Studies
International Business & Economics Studies (IBES) is an international, Refereed, double-blind peer-reviewed, open-access journal published by Scholink. The journal aims to provide a high-level platform for scholars and researchers all over the world to share latest findings and views in the field of Business & Economics Studies. We would welcome scholars and researchers engaging in the related field to submit your manuscripts which are complete unpublished and original works and not under review in any other journals to IBES. Both of online submission and E-mail submission (ibes@scholink.org) are acceptable. ------------------------------------------------------------------------------ The journal includes, but is not limited to the following fields: Business Entrepreneurship Marketing Commerce Economics Financial Economics Regional Economics Economic Growth Economic Policies Economic Indicators Industrial Economics International Economics Managerial Economics Regional Development Agricultural Economics Management Finance Banking Accounting Buyer Behavior Corporate Governance Organizational Behavior Quantitative Methods and Their Applications Financial Management Decision and Risk Analysis Human Resource Management ----------------------------------------- Index/List/Archive CNKI-Scholar CrossRef WANFANGDATA LinkedIn ResearchGate ResearchBib Yahoo Google Scholar Canadiana ResearchBib Base Search CrossRef Worldcat PKP Open Archives Harvester Lockss Publons ISSN PORTAL Refereed Journal: International Business & Economics Studies is a Refereed Journal. Open access: International Business & Economics Studies is available online to the reader "without financial, legal, or technical barriers other than those inseparable from gaining access to the internet itself." Peer review: International Business & Economics Studies takes peer review policy. Peer review is the evaluation of work by one or more people of similar competence to the producers of the work (peers).
Authors who publish with this journal must agree to the following terms: Authors should promise that their works are entirely original, and all the references in their works should be appropriately cited or quoted. The works have not been published previously. The behavior of submitting the same work to other journals is unacceptable. The journal editor has the right to edit the format of works.
Social Insurance Burden and Firms’ Outward FDI: Evidence From Chinese Enterprise Data
This study examines how the social insurance burden affects firms’ decisions to invest abroad. We construct a structural investment model to show that higher domestic labor costs induced by social insurance contributions diminish the relative profitability of local operations and consequently enhance the incentive for firms’ outward foreign direct investment (OFDI). Using panel data on Chinese listed firms from 2007 to 2022, we employ a two-way fixed effects regression to test the causal relationship between firms’ social insurance burden and their decision and scale of OFDI. The results indicate that heavier social insurance burden significantly increase firms’ OFDI activities. Furthermore, this relationship is moderated by firms’ productivity and risk preference. In addition, we find that the positive effects are more pronounced among non-state-owned firms, those operating in the manufacturing sector, and firms located in the eastern regions of the country. The results demonstrate that social insurance policies play an important role in firms’ globalization strategies. Policymakers should balance social welfare financing with measures to maintain firms’ competitiveness in international markets.
Copyright (c) 2026 Gan Lin, Ruyan Tang, Zhen Wu, Yisheng Ning http://creativecommons.org/licenses/by/4.0
Board Decision-making Logic, Equity Nature, and Bank Environmental Lending
This article explores the impact of bank governance on bank environmental lending, using a manually collected sample of China’s city commercial banks from 2008 to 2018. The empirical results show that government ownership can promote bank environmental lending and a board of directors with a preference for social logic can positively moderate the relationship between them. In addition, the positive moderating effect is more pronounced in banks with state-owned shareholders as the largest shareholder and banks located in provincial capital cities. This paper is beneficial for expanding the understanding of the interaction between equity nature and board decision-making process in bank governance.
Copyright (c) 2026 Yana Zhou http://creativecommons.org/licenses/by/4.0
AI and MIST in Circular Economy and Resource Recovery: A Comparative Analysis of Ecommerce Industries
The rapid expansion of e-commerce has altered retail, but it has also exacerbated environmental issues such as packaging waste, product returns and product recovery, and resource depletion. This research evaluates the implementation of Artificial Intelligence (AI) and Modern Information Systems and Technologies (MIST) to achieve Circular Economy (CE) development and resource recovery in the context of e-commerce above the major e-commerce platforms of the United States, United Kingdom and Indian markets—Amazon, ASOS, IKEA Online, Big Basket, and Nykaa. This study used a quantitative research design and Power BI analysis to compare the extent to which these firms utilize AI and MIST to retrieve circularity, reduce carbon emissions, and improve operational efficiency. The findings revealed a clear relationship between high levels of AI and MIST relative to operations—such as predictive analytics, IoT-enabled tracking, blockchain transparency, and cloud-based logistics—and significant improvements in resource efficiency, waste reduction, and customer satisfaction. The e-commerce platforms with the greatest levels of CE performance were Amazon and IKEA Online platform, although emerging firms like Big Basket and Nykaa were beginning to adopt these models. In conclusion, both AI and MIST drive sustainable development, create customer trust, and increase competitive advantages, suggesting that their role in e-commerce is a key focus for digital transformation for sustainable e-commerce.
Copyright (c) 2026 Dr. Surjadeep Dutta, Pritam Chowdhury, Anindita Sinha, Tisha Biswas, Dr. Uma Padmini Ema http://creativecommons.org/licenses/by/4.0
Bridging Information Asymmetry through AI-driven FinTech: The Role of Digital Footprint Analytics in Financial Inclusion
Financial inclusion—broadly defined as the availability and equality of opportunities to access financial services—is widely recognized as critical for fostering economic growth, reducing poverty, and promoting equitable development (Berg, T., Burg, V., Gombović, A., & Puri, M., 2020). Nevertheless, despite global initiatives aimed at expanding financial access, a substantial number of individuals and small businesses, particularly in developing countries, remain excluded from traditional financial systems due to insufficient credit histories and inadequate financial documentation (Demirgüç-Kunt et al., 2022). Central to this issue is information asymmetry, a longstanding theoretical challenge articulated by foundational economic theories, including those of Akerlof (1970) and Stiglitz & Weiss (1981). These indicate how asymmetrical information between borrowers and lenders generates adverse selection and moral hazard, ultimately resulting in credit rationing and the systematic exclusion of otherwise creditworthy but information-poor segments of society.In recent years, the rapid development of financial technology (FinTech) powered by artificial intelligence (AI) has fundamentally reshaped the possibilities for overcoming informational barriers. Unlike traditional credit assessment methodologies that depend heavily on structured financial data such as credit bureau reports, income verification, and collateral evaluations, emerging AI-driven credit scoring systems incorporate large-scale behavioral data—often termed “digital footprints”—derived from non-traditional sources including smartphone metadata, social media interactions, e-commerce behaviors, and even geolocation patterns (Berg, T., Burg, V., Gombović, A., & Puri, M., 2020). Recent empirical studies have demonstrated that these novel data sources can outperform traditional financial data in predicting loan repayment behavior, thus substantially reducing information asymmetry and enabling lenders to extend financial services to previously underserved groups (Berg et al., 2020). Leading fintech companies such as Tala in the United States (which primarily serves Southern Africa and Southeast Asia) and Sesame Credit in China’s Ant Financial Services Group exemplify the transformative potential of AI-driven financial innovation. Tala, for instance, utilizes machine learning algorithms that analyze smartphone usage patterns to reliably estimate creditworthiness, enabling real-time unsecured loan approvals for individuals with no formal credit histories (Björkegren, D., & Grissen, D., 2019). Similarly, Zhima Credit has leveraged diverse behavioral indicators—ranging from online transaction consistency to social interaction networks—to deliver precise risk assessments, thereby broadening access not only to credit but also to various consumer services (Zhang, Q., & Li, X. 2023). These case studies highlight how digital footprint analytics can be broadly applied to help mitigate adverse selection and significantly reduce financial exclusion.Despite the transformative benefits, the integration of AI into credit assessment systems raises profound ethical and regulatory concerns. Critical issues include the opacity of algorithmic decision-making processes (“black box” models), the potential perpetuation of existing biases and inequalities embedded in historical datasets, and the privacy implications of intensive personal data use (Raghavan, M., Barocas, S., Kleinberg, J., & Levy, K. 2020). For instance, recent research has highlighted the unintended amplification of gender bias in AI-driven financial services, wherein ostensibly neutral algorithms disproportionately disadvantage women due to embedded socio-economic inequalities within training data (Arora & Gupta, 2025). Addressing these challenges requires robust governance frameworks, algorithmic transparency standards, and informed regulatory oversight, such as those advocated by recent developments in the European Union’s General Data Protection Regulation (GDPR) and emerging algorithmic fairness guidelines (Binns, 2024). Building upon these insights, this paper critically examines the role of AI in bridging information asymmetry within FinTech, with an emphasis on how digital footprints and behavioral analytics are reshaping credit access and financial inclusion. By synthesizing theoretical perspectives on asymmetric information with cutting-edge empirical evidence from recent studies and practical case analyses, this research aims to elucidate both the opportunities and limitations inherent in the AI-enabled transformation of financial decision-making. Furthermore, the paper offers actionable policy recommendations designed to balance technological innovation with ethical responsibility, alongside clearly defined directions for future interdisciplinary research in economics, data science, and regulatory policy.Building on existing theories, this study further incorporates the “Rice Theory” (Talhelm et al., 2014; Dong et al., 2024), which argues that cultural orientations influenced by agricultural practices (particularly rice farming) affect individuals’ social behaviors and cooperative tendencies. Applying this theory to financial technology (FinTech) adoption, we propose that users from collectivist cultural backgrounds—commonly associated with regions historically reliant on rice farming—may exhibit distinct patterns of interaction and acceptance toward digital financial services, thereby influencing the degree of information asymmetry and financial inclusion outcomes within FinTech ecosystems.
Copyright (c) 2026 Mingxuan Cao http://creativecommons.org/licenses/by/4.0
The Green Effects of DIF: Corporate Green Production’s Stimulation of Residents’ Low-Carbon Consumption
Against the background of full implement of China’s “dual-carbon” strategy and the rapid expansion of the digital economy, clarifying the mechanisms through which digital inclusive finance (DIF) contributes to green consumption is of both theoretical and practical importance. Using a matched panel dataset of Chinese prefecture-level cities and listed firms from 2011 to 2019, this study develops an integrated analytical framework linking DIF, corporate green production, and residents’ low-carbon consumption preferences. Two-way fixed-effects models and firm-level mediation regressions are employed to examine the green effects of DIF. The results indicate that: (1) DIF significantly enhances residents’ low-carbon consumption preferences, and this effect remains robust after controlling for socioeconomic characteristics; (2) DIF strengthens corporate green production by increasing green total factor productivity, stimulating green technological innovation, and alleviating financing constraints; (3) Corporate green production further reinforces residents’ low-carbon consumption preferences through supply-side channels such as the expansion and upgrading of green products, as well as demand-side channels including environmental improvement and green information spillovers; (4) DIF exhibits a clear chain transmission mechanism, operating through the pathway “DIF → corporate green production → residents’ low-carbon consumption preferences.” The innovation of this paper lies in: constructing a green transmission mechanism identification framework covering both the urban and enterprise dimensions, and for the first time systematically verifying the path through which DIF influences residents’ preference for low-carbon consumption by promoting green production of enterprises, and revealing the formation logic of green consumption from both the supply and demand sides. The research conclusions provide empirical evidence for the coordinated design of digital finance and green development policies.
Copyright (c) 2026 Minghan Yang http://creativecommons.org/licenses/by/4.0
Enhancing Youth Engagement with IBM SkillsBuild Platform in Singapore: A User-Centered Analysis
With the rapid development of digital economy, digital literacy and professional skills have become essential for youth employment and career development. IBM Singapore, in collaboration with RMIT, launched the SkillsBuild platform to provide free high-quality digital and professional skill training for young people. However, the platform is facing the challenge of low youth engagement. This paper aims to explore effective strategies to improve youth participation in IBM SkillsBuild. Through PESTLE analysis, this study examines external business factors influencing youth engagement; identifies and analyzes key stakeholders using Mendelow’s Power-Interest Grid; determines polytechnic students (17-21 years old) as the target user group based on potential user group analysis; constructs a user persona and empathy map through primary research (semi-structured interviews with three polytechnic students); and finally defines the core problem and proposes a “How Might We” question to guide subsequent solution development. The research findings indicate that the low engagement of youth in SkillsBuild is mainly due to insufficient platform visibility, lack of interactivity, and unclear connection between courses and career prospects. This study provides a theoretical and practical basis for IBM Singapore to optimize the SkillsBuild platform and enhance youth engagement, which also has reference significance for similar online learning platform operation.
Copyright (c) 2026 Jingxuan Ye http://creativecommons.org/licenses/by/4.0
Research on the Connotation, Dilemma and Path of Digital Transformation of Specialized, Sophisticated, Specialized and Innovative Enterprises
The digital transformation of specialized, refined, distinctive, and innovative (SRDI) enterprises has evolved from technological tool upgrades to strategic transformations that restructure core competencies and achieve high-quality sustainable development. This paper systematically defines the concept of “high-quality digital transformation” for SRDI enterprises, which focuses on enhancing total factor productivity through coordinated evolution of technological and organizational architectures, thereby digitally strengthening specialized, refined, distinctive, and innovative capabilities. The study identifies three key characteristics: strategic orientation with high-quality constraints, cross-level coupling of driving factors, and highly dynamic transformation processes. These features reveal triple advantages in operational efficiency, innovation capacity, and management decision-making. The research further analyzes four critical challenges faced by enterprises—cognitive ambiguity, fragmented applications, security vulnerabilities, and resource shortages—along with their practical manifestations of “reluctance to transform, inability to transform, fear of transformation, and inability to transform.” Optimization pathways are proposed across four dimensions: top-level design, system integration, security governance, and resource support. The integrated analytical framework established in this paper provides theoretical references for digital practices in SRDI enterprises and empirical evidence for digital policy design in small and medium-sized enterprises.
Copyright (c) 2026 Keyan Peng http://creativecommons.org/licenses/by/4.0
Research on the Composition of Kiwifruit Production Costs and Strategies for Enhancing Economic Returns
Amid the ongoing structural reform of China’s agricultural supply side and the push for rural revitalization, kiwifruit emerges as a pivotal player in the nation’s high-value fruit industry. Its development is crucial for optimizing agricultural structures and boosting farmers’ incomes. This paper employs cost-benefit analysis, industrial organization theory, and comparative advantage theory to assess the kiwifruit sector. Using panel data from 28 key kiwifruit-producing regions in China spanning 2020 to 2025, it examines production cost structures and imbalances, quantifying each cost element’s impact on economic outcomes. Additionally, by comparing international competitors and assessing current industry conditions, the study identifies sustainable paths to enhance economic returns. Findings reveal that China’s kiwifruit production is characterized by “high labor and material costs, with insufficient investment in cold chain and technology.” Core factors impacting economic benefits include labor, fertilizer, pesticide, and post-harvest processing costs. While increased industrial concentration in major areas yields scale benefits, it also heightens price volatility risks. Furthermore, inadequate technological investment, weak brand value, and poor supply chain integration hinder benefit improvements. Therefore，to support the transformation of the Chinese kiwifruit industry from “scale expansion” to “quality and efficiency” ，targeted suggestions are proposed across three dimensions: optimizing elemental configuration, leveraging technological innovation, and reconstructing the supply chain. These strategies aim to enhance the industry’s core competitiveness by offering both theoretical insights and practical guidance.
Copyright (c) 2026 YAN WANG http://creativecommons.org/licenses/by/4.0
Research on the Mechanism and Path of Balanced Regional Economic Development Driven by the Integration of Data Factors and Artificial Intelligence
This study focuses on the core issue of balanced regional economic development driven by the integration of data factors and artificial intelligence (DIAI). Aiming at the deficiency of existing studies that ignore the synergistic effects of the two elements, the study uses panel data of 30 Chinese provinces from 2012 to 2023 to construct fixed effects, mediation effect and threshold regression models. Combined with robustness tests, it systematically examines the action mechanism, boundary conditions and regional heterogeneity of DIAI. It is empirically verified that DIAI significantly narrows regional development gaps and acts as a novel synergistic driving force for balanced regional economic development. DIAI exerts its driving effect through three mechanisms, namely innovation-driven development, the upgrading of industrial structure and the optimization of resource allocation, with the contribution rates of the three mechanisms being 42.1%, 28.6% and 29.3% respectively. A single threshold effect of 12.7% is identified in the level of financial development; the marginal contribution of DIAI increases by 3.9 times after the financial development level crosses this threshold. In addition, the effect of DIAI is more pronounced in western China and national digital economy pilot zones. Theoretically, this study expands the theory of regional innovation systems. Practically, it provides a basis for local governments to formulate differentiated DIAI strategies. The study also points out its limitation in the insufficient exploration of the mechanism of microeconomic agents and clarifies the future research direction of further in-depth investigation from the micro perspective.
Copyright (c) 2026 Yaling Liu, huan Liu, Quanhong Cao http://creativecommons.org/licenses/by/4.0
Problems and Countermeasures in Rural Talent Recruitment and Development
Rural revitalization fundamentally depends on human capital development and deployment. Although China’s efforts in recruiting and developing rural talent have achieved certain progress in recent years, significant challenges persist that require urgent attention. These challenges include inefficient talent attraction channels, incomplete training mechanisms, unfavorable retention environments, and inadequate utilization platforms. Based on a systematic and comprehensive review of the current state of rural talent recruitment and development in China, this paper provides an in-depth analysis of the primary problems and their underlying causes from multiple perspectives. Furthermore, it proposes targeted policy recommendations from four interconnected dimensions: improving talent attraction mechanisms, strengthening training systems, optimizing retention environments, and building utilization platforms. This research aims to provide theoretical references and practical guidance for comprehensively promoting rural talent revitalization and supporting the broader rural revitalization strategy.
Copyright (c) 2026 Peng Du http://creativecommons.org/licenses/by/4.0
Can Regulating Major Shareholders’ Share Reductions Effectively Suppress Stock Price Volatility?—An Empirical Study Based on the 2023 New Share Reduction Rules
In order to regulate the reduction of holdings by major shareholders and ensure the sound operation of the capital market, the China Securities Regulatory Commission (CSRC) issued the document Further Regulation of Share Reduction Behavior by the CSRC on August 27, 2023. This paper focuses on this new reduction regulation and employs a fixed-effects model to empirically examine its impact on stock price volatility in the overall A-share market, as well as in the Shanghai and Shenzhen stock exchanges, during the period from January 4, 2023, to December 31, 2024. The empirical results show that: (1) The new reduction regulation has a mitigating effect on stock price volatility in both the overall market and the Shanghai and Shenzhen stock exchanges. (2) The inhibitory effect of the new reduction regulation on stock price volatility is more pronounced in companies with higher ownership concentration.
Copyright (c) 2026 Pengcheng Zhang http://creativecommons.org/licenses/by/4.0