Research in Economics and Management (REM) is the official open access journalof Scholink. In order to give all researchers equal opportunity to share their ideas, REM adopts double-blind peer-review. REM focuses on scholarly research and practical experience of a wide range of research areas within the general field of economics and management, which covers, but is not limited to the following areas: Banking Marketing Accounting Economic Growth Economic Policies Economic Indicators Industrial Economics International Economics Managerial Economics Financial Management Knowledge Management Decision and Risk Analysis Human resource management Management research methods Project and Quality Management Purchasing and Supply Management Information technology management Innovation Management We welcome scholars and researchers engaged in the related fields to submit their manuscripts to REM. Both of online submission and E-mail submission (rem@scholink.org) are acceptable. ----------------------------------------------------------------------------- Index/List/Archive CNKI Scholar CrossRef LinkedIn OALib Research Bib Refseek academic search engine Yahoo Academia.edu Library and Archives Canada Lockss PKP Open Archives Harvester Google Scholar Canadiana Standard Periodical Directory Academic Journal Articles AMICUS Bielefeld Academic Search Engine (BASE) CrossCheck Cosmos Impact Factor Directory of Research Journals Indexing (DRJI) Electronic Journals Library (EZB) Global Impact Factor (GIF) Journalseek JournalTOCs NewJour Scientific Indexing Service (SIS) Universal Impact Factor Open J-Gate Base Search Worldcat ------------------------------------------------------------------------ Open access: Research in Economics and Management 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: Research in Economics and Management 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: Copyrights for articles published in our are retained by the authors. 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.
Research on Technology Embedding and Industrial Chain Synergy in Digital Transformation of Specialized, Refined, Unique and New Enterprises
Specialized, refined, distinctive, and innovative enterprises are the key players in the modernization of China’s industrial chain. The technological embedding in their digital transformation and industrial chain collaboration constitute two core propositions that mutually empower each other. Based on clarifying the theoretical connotations and logical connections of these two aspects, this paper analyzes the empowering effects of technological embedding on industrial chain collaboration through data integration, process reengineering, and decision optimization. The study reveals that current challenges include low levels of technological embedding, prominent system silos, incomplete collaborative mechanisms, significant resource constraints, and relatively high data security risks. Accordingly, the paper proposes a four-dimensional optimization path: deepening technological embedding, improving collaborative mechanisms, enhancing endogenous capabilities, and strengthening risk prevention and control. This provides theoretical references and practical insights for the digital capability enhancement of specialized, refined, distinctive, and innovative enterprises and the collaborative governance of industrial chains.
Copyright (c) 2026 Keyan Peng http://creativecommons.org/licenses/by/4.0
Can Institutional Analysts Identify Non-financial Information Manipulation? Evidence from China
Based on the data of Chinese listed companies from 2009 to 2023, this paper examines analysts’ ability to discriminate distorted information by examining the sensitivity of analysts’ earnings forecast correction behavior to textual readability. The empirical study found that China’s securities analysts have a certain screening ability for the non-financial information disclosed by listed companies based on the motivation of interest encroachment. Through robustness analysis, the above conclusion is still significant. The conclusion of this paper provides theoretical reference and policy enlightenment for improving China’s non-financial information disclosure system and alleviating the distortion of information disclosure.
Copyright (c) 2026 Shuxin Hao http://creativecommons.org/licenses/by/4.0
Assessment of Eye Care Knowledge among Patients Attending the Outpatient Department of Selected Eye Hospitals in Dhaka City
A descriptive type cross sectional study was designed to study knowledge on eye care among the patients attending outpatient department of selected eye hospital of Dhaka city with a sample size of 182. The study showed that 44%, 29.1% and 19.8% of the respondent were in the age group 30-39 years, 40-49 years and 20-29 years, respectively with the mean age of 36.18 ±8.129. The Study findings showed that 34.6% of the respondents were in service, 32.4% were in business, 22% of the respondents were day laborer & 11% were housewife. Study reveals that 56.6% of the respondents did not think vitamin deficiency cause’s eye problem and rest of them (43.4%) were think vitamin deficiency causes eye problem. Study shows that 67% of the respondents were think aging cause’s cataract and rest of them (33%) did not think aging causes cataract. Study explores that majority (83.5%) of the respondents were think ocular pressure causes glaucoma and rest of them (33%) did not think ocular pressure causes glaucoma. In study found that explore that majority (72.5%) said surgery was the treatment for the blindness. On the other hand, 16.5% answered that medication was the treatment for Cataract and lastly 11.0% didn’t know anything about it. It reveals that 63.2% of the respondents had eye diseases on relatives, 23.1 % of the respondents were don’t know about eye diseases on relatives & only 13.7% of the respondents had no eye diseases on their relatives. Eyes are one of the most important organ in the human body and vision is one of the most wonderful gift. But often many people neglect the importance of eye care and do not pay proper attention towards eye care. The prevalence is higher in community too along with urban areas and is increasing day by day. To address the issue proper policies and community-based awareness should be taken. Training & awareness program in the community can minimize it.
Copyright (c) 2026 Most. Jaki Sultana Liza http://creativecommons.org/licenses/by/4.0
Evaluating the Use of Artificial Intelligence in Recruitment and Selection: A Four-Dimensional Framework
Artificial intelligence is increasingly used across recruitment and selection. Existing research has mainly examined its applications at different stages of recruitment and the trade-off between efficiency and fairness. However, a framework for assessing the appropriate boundaries of AI use across the recruitment process remains undeveloped. This paper develops a four-dimensional framework based on standardization, future-oriented judgment, opportunity visibility, and explainability. It applies the framework to the early, middle, and late stages of recruitment and selection. The analysis shows that AI should play different roles across stages. In the early stage, it can support job definition and attraction strategies. In the middle stage, AI may support sourcing and initial screening, but it also raises concerns about opportunity visibility and screening fairness, which require close attention. In the later stage, AI should not be used as a black-box tool to infer personality, potential, or future performance, nor should it make independent hiring decisions. The key issue in AI recruitment is therefore not efficiency alone, but its implications for candidate opportunity, procedural fairness, and accountability.
Copyright (c) 2026 Huitong Sun http://creativecommons.org/licenses/by/4.0
Empirical Academic Platform: Building an Intelligent Infrastructure for Empirical Research in China
Current empirical research faces structural difficulties, and data silos exist in many fields. Also, researchers spend much time on repetitive labor in low level, and scientific resources are wasted because of this. These issues can limit the efficiency of academic innovation and they make achievement transformation difficult in current system. We propose to build an empirical academic platform which has the core function of data integration and automatic standardization of empirical results, with dynamic update, and we use big data and artificial intelligence, plus econometric modeling so that the entire process of empirical research can be automated. Then we describe the theoretical framework, core architecture, technological path, and application scenarios of this platform, and we design a Chinese pilot program which is government led, with university co-construction, and enterprises also participate. We also analyze the challenges and response strategies that the platform faces. It is worth noting that research suggests empirical academic platforms can promote the return of empirical research from method driven to problem driven. They can reshape academic research paradigms. Also, technical support can be provided for the construction of Chinese philosophy and social science system and it has significant theoretical value and practical significance.
Copyright (c) 2026 Huilin Zhao http://creativecommons.org/licenses/by/4.0
Key Associated Characteristics and Industry Heterogeneity of Corporate Data Asset Potential in China-Evidence from Generative Models and Explainable Machine Learning
This study takes A-share listed firms that recognized data resources as assets in their 2024 annual reports as the initial sample. To address the issue of limited sample size, a generative model is adopted for data augmentation. Based on the augmented data, an interpretable machine learning framework is developed to explore the main firm characteristics associated with data asset potential, as well as the nonlinear patterns underlying these associations. The results show that innovation investment and firm size are the two most relevant characteristics. Their marginal contributions to data asset potential exhibit clear nonlinear threshold effects. In contrast, conventional profitability metrics have weak explanatory power, and their influence is contingent on the level of innovation input. A subsequent analysis covering the entire market reveals that the information technology sector and the scientific research and technical services sector tend to have substantially higher data asset potential. This study not only offers new empirical evidence on the correlates of data asset potential but also provides practical insights for the design of data factor market institutions, asset valuation practices, investment decisions, and corporate strategic planning.
Copyright (c) 2026 Junhong Luo, Huijuan Zheng, Junxi Huang http://creativecommons.org/licenses/by/4.0
Research on the Impact of Fintech on the Profitability of Commercial Banks
The external competition brought about by the rapid rise of financial technology companies has prompted the banking industry to develop fintech businesses, and the development of fintech businesses will have a certain impact on bank performance. Based on the financial data of 20 listed commercial banks in China from 2014 to 2023, this paper researches the impact of fintech development on bank performance. Preliminary analysis through panel regression shows that the development of fintech business has reduced the operating performance of the banking industry. By constructing period dummy variables, this paper analyzes the changes in the impact of fintech development on bank performance in different periods. Fintech is an emerging thing and has its imperfect side. The banking industry should accelerate the pace of financial innovation, build its own fintech business, and cooperate with fintech enterprises to achieve mutual benefit and win-win results, so as to enhance the overall competitiveness of China’s banking industry with the development of fintech.
Copyright (c) 2026 Siyu Chen http://creativecommons.org/licenses/by/4.0
Big Data Construction and Shadow Banking of Private Non-Financial Enterprises——Based on the National-level Big Data Comprehensive Pilot Zone Policy
In recent years, more private non-financial enterprises engage in shadow banking activities, causing serious negative effects on corporate operations and the financial system. Meanwhile, to promote big data innovation and development, the Party and government established national comprehensive big data pilot zones to enhance data circulation as a key production factor. From the perspective of big data development, this study takes private non-financial enterprises in national-level big data comprehensive pilot zones at the prefectural level (2012–2022) as samples and employs the PSM-DID method to examine whether big data development affects the shadow banking behavior of non-financial enterprises and explore its underlying mechanisms. The results show that big data development effectively curbs shadow banking activities among private non-financial enterprises, and this finding remains robust across multiple tests. Further analysis reveals that big data construction suppresses such activities by alleviating information asymmetry and enhancing social trust. Heterogeneity analysis indicates that the inhibitory effect is more pronounced in regions with higher economic development levels and among high-tech private non-financial enterprises. This study offers a new research solution for mitigating shadow banking in private non-financial enterprises, effectively reduces financial risks, and holds significant implications for promoting the growth of these enterprises.
Copyright (c) 2026 Man Sun, Tao Jiang, Zhisu Wang, Wen Zhou, Qianqiang Li, Jianing Tong http://creativecommons.org/licenses/by/4.0
Algorithmic Control, Economic Dependence, and Institutional Mismatch: A Mixed-Methods Study of Food-Delivery Riders in Beijing
The growth of digital platforms has rapidly expanded the food-delivery sector while intensifying concerns about riders’ employment status, social protection, algorithmic management, and access to dispute resolution. This study adopts a multi-source mixed-methods design, drawing on 976 judicial decisions involving food-delivery riders across China, including 52 from Beijing, a survey of 482 riders in Beijing, and semi-structured interviews with 20 riders, five platform managers, and five legal practitioners. Only 7.7% of surveyed riders had formal employment contracts. Only 23% had coverage for work-related injuries or occupational injury protection. Moreover, 63.9% regarded platform algorithmic rules as unreasonable. Across the three data sources, riders mainly face difficulties in identifying employment status classification, insufficient social security, algorithmic management disputes, and poor access to legal remedies. Algorithmic control, economic dependence and institutional mismatch constitute important mechanisms to understand the above labor protection gaps. The paper argues for improving employment-status determination standards based on actual control, expanding the coverage of occupational injury protection, and strengthening algorithmic transparency, appeal review, and coordination among multiple responsible actors.
Copyright (c) 2026 Longfei Li, Yuxuan Wang, Wenjue Li, Yiting Zhao http://creativecommons.org/licenses/by/4.0
Structural Optimization and Mechanical Performance Analysis of Combined Permanent–Temporary Construction Access Roads under Heavy Loads
Construction access roads constructed for highway projects are frequently subjected to traffic loads that exceed those considered in conventional pavement design. To evaluate the applicability of the permanent–temporary integration concept, a highway project in Shaanxi Province was selected as a case study. Three representative pavement structures were established in ABAQUS and analysed under concrete transport vehicle loading conditions. The simulation results indicate that both the stiffness and thickness of the supporting layer have a significant influence on pavement behaviour. An increase in subgrade stiffness reduces slab stress and promotes load diffusion, whereas a thicker supporting layer is more effective in controlling pavement deflection. Compared with the surface layer modulus, changes in subgrade properties produce a more pronounced effect on the overall structural response. Considering mechanical performance together with construction cost, a single-layer pavement consisting of 30 cm C40 concrete was identified as the most suitable alternative for the investigated project. The findings may provide useful references for the design and optimization of construction access roads subjected to heavy traffic loading.
Copyright (c) 2026 Hansong 2024 Li, Shiqiang Cheng, Yucheng Hu, Dan Song, Lei Liu http://creativecommons.org/licenses/by/4.0