Chung Cheng Academic Achievements Information System

How should we measure the benefits of AI implementation in firms?

Nov 06, 2026

Assessing the business value of AI Does adopting artificial intelligence improve firm performance, and does moving first confer an advantage? Research by Professor Cheng-Kui Huang and his graduate student, Jheng-Siang Lin, at National Chung Cheng University finds stronger performance on selected financial indicators and higher market valuation among AI adopters. The evidence for productivity gains and first-mover advantages is less uniform. By distinguishing these outcomes, the study provides a more specific account of where the business value of AI is observed.   Linking adoption evidence with financial data The study focuses on non-IT firms in the S&P 500. It identifies AI implementation through news published between 2010 and 2017 and evaluates performance using fiscal-year 2017 data from Compustat. The final sample comprises 50 confirmed AI adopters and 250 comparison firms for which relevant AI news was not identified. Financial indicator regressions, Cobb–Douglas production functions, and a Tobin’s q-based valuation model assess financial performance, productivity, and market valuation. Additional comparisons examine adoption timing and industry groups. Figure 1 Study design   Financial and valuation benefits differ from productivity results In analyses controlling for industry differences, AI adopters show significantly stronger results for selected financial indicators, including labor productivity, profit margin, and receivables collection efficiency. Market valuation is also significantly higher. However, estimated differences in value added and output in the production-function models are not statistically significant. A favorable result on an individual financial indicator therefore should not be interpreted as evidence of improvement across every dimension of firm performance. Figure 2 Main findings   Early adoption does not guarantee an advantage Among the 50 adopters, 23 implemented AI before 2017 and 27 did so in 2017. Earlier adopters show significantly higher output, but no significant advantage in financial indicators or market valuation. Drawing on prior industry reports, the study also compares retail and finance/insurance firms with other AI adopters. This group shows higher value added without a broad financial advantage, and its market valuation is significantly lower. These findings indicate that adoption timing and industry membership alone do not guarantee benefits across all outcomes.   Implications and scope The study connects AI investment with observable firm outcomes and supports evaluating financial, operational, and market measures together. Its cross-sectional design uses a single fiscal year, and missing financial inputs substantially reduce the effective samples in the productivity models. The results describe associations in the sample, rather than establishing causal or long-term effects, and should not be treated as estimates of returns to today’s generative AI investments. Multi-year and cross-industry research can further examine how AI benefits develop over time.

A binding tie: why do customers stick to omnichannel retailers?

Sep 29, 2026

Firm-level political risk and debt choice

Sep 03, 2026

A Non-Monetary Incentive Mechanism for Mobile and Spatial Crowdsourcing Task Assignment

Oct 01, 2026

Background Crowdsourcing harnesses the collective effort of many participants and underpins today's gig economy, from ride-hailing (Uber) to food delivery (Uber Eats, foodpanda). In mobile and spatial crowdsourcing, a platform must assign location- and time-constrained tasks to suitable workers in real time (Fig. 1). This problem is NP-hard and faces three challenges: heterogeneous worker quality, long travel distances that reduce efficiency, and a lack of effective incentives that discourages participation. Most existing studies consider either spatio-temporal factors or worker reliability, but not both, and their incentives are almost entirely monetary. Method We propose STA-NIM, a suitability-based task assignment framework with a non-monetary incentive mechanism. Its system model, shown in Fig. 2, has four components: (1) Reliability evaluation: a fuzzy inference system with 27 rules infers each worker's reliability from task completion rate, task pass rate, and rating score. (2) Suitability calculation: suitability jointly considers worker reliability and task-worker distance, combining a fuzzy inference system with the entropy weight method. The framework switches between the two based on the weight ratio of the indicators: fuzzy inference keeps results stable when the weights are similar, while the entropy weight method separates candidates objectively when they differ. When a task is published, available workers are filtered by task radius and workload limit, and the task goes to the worker with the highest suitability, in O(|W|) time. (3) Monetary incentive: payment is based on reliability, travel distance, and completion time, with factor weights set by linear programming so that payment never exceeds the task budget. (4) Non-monetary incentive: in each cycle, a worker's rating and completion efficiency are quantified as a "power" value. Workers who perform well receive extra task quota, and therefore more earnings, in the next cycle. A Gini-coefficient constraint keeps tasks from concentrating on a few workers. Results Using a semi-synthetic dataset built from Foursquare, Yelp, and Kaggle data, we compared STA-NIM with STA (no non-monetary incentive), TASC-MADM, and BOPR: (1) From 2,500 to 10,000 tasks, STA-NIM's assignment rate stays above 76%, with the smallest decline (2.16%-7.97%; Fig. 3). (2) STA-NIM keeps a high assignment rate with fewer workers, doing more with less. (3) As the basic workload rises, STA-NIM's Gini coefficient falls, spreading tasks more evenly; the other methods become less even. (4) STA-NIM yields the highest average worker payment, rising 7.14%-42.9% with the budget. (5) STA-NIM achieves the highest average reliability at a moderate travel distance, with a maximum execution time under 375 ms, fast enough for real-time use. Contributions and Future Work STA-NIM balances task quality, efficiency, and fairness, and rewards high-performing workers with more opportunities and income. It can be applied to food delivery, ride-hailing, crowdsensing, and smart-city data collection. Future work will add task reassignment for worker drop-outs, handle the cold-start problem for new workers, and use game-theoretic analysis to address strategic behavior.   Providede by the Data Management Lab, Department of Computer Science and Information Engineering / Advanced Institute of Manufacturing with High-tech Innovations (AIM-HI), National Chung Cheng University  

Mitochondrial Glutathione in Cellular Redox Homeostasis and Disease Manifestation

Mar 16, 2026

Development of Hydrogen Energy and Energy Storage Technologies for Net-Zero Emissions

Nov 19, 2025

Effects of vitamin D in pregnancy on maternal and offspring health-related outcomes: An umbrella review of systematic review and meta-analyses

Jun 04, 2026

1. Background: The Importance of Vitamin D During Pregnancy Vitamin D is an essential fat-soluble vitamin that plays a critical role not only in calcium and phosphorus metabolism and bone development, but also in immune regulation, metabolic function, and fetal growth and development. Due to increased physiological demands during pregnancy, combined with insufficient sunlight exposure and inadequate dietary intake, vitamin D deficiency has become a common global health concern among pregnant women. Whether vitamin D deficiency adversely affects maternal and neonatal health, and whether vitamin D supplementation can improve these outcomes, remains an important issue in clinical medicine and public health. 2. Research Method: An Umbrella Review of Existing Evidence This study employed an umbrella review approach to comprehensively synthesize findings from published systematic reviews and meta-analyses examining the effects of maternal vitamin D status and vitamin D supplementation during pregnancy on maternal and offspring health outcomes. A systematic search was conducted in PubMed, Embase, and the Cochrane Library. Sixteen eligible systematic reviews and meta-analyses published up to October 2023 were included, representing data from more than 250,000 pregnant women. 3. Association Between Vitamin D Deficiency and Adverse Maternal and Neonatal Health Outcomes The findings indicate that vitamin D deficiency during pregnancy is significantly associated with several adverse maternal and neonatal health outcomes. Pregnant women with vitamin D deficiency are at increased risk of preterm birth, gestational diabetes mellitus, recurrent miscarriage, and bacterial vaginosis. Their infants are more likely to experience low birth weight, small-for-gestational-age (SGA) status, and other unfavorable birth outcomes. Furthermore, low maternal vitamin D levels may be associated with an increased risk of long-term neurodevelopmental disorders in offspring, including attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). 4. Benefits of Vitamin D Supplementation for Maternal and Neonatal Health The study found that appropriate vitamin D supplementation during pregnancy can increase maternal serum vitamin D concentrations and reduce the risk of pre-eclampsia, miscarriage, and vitamin D deficiency. For fetuses and newborns, vitamin D supplementation was associated with increased birth length, reduced fetal or neonatal mortality, and improved neonatal vitamin D status. 5. Additional Benefits for Women with Gestational Diabetes Mellitus The benefits of vitamin D supplementation appear to be particularly pronounced among women with gestational diabetes mellitus (GDM). Supplementation was associated with improved glycemic control and insulin sensitivity, as well as reduced risks of polyhydramnios, fetal distress, macrosomia, neonatal hyperbilirubinemia, and neonatal hospitalization. 6. Conclusions and Clinical Implications Overall, this study demonstrates that maternal vitamin D status is closely linked to both maternal and neonatal health. Maintaining adequate vitamin D levels during pregnancy may help reduce pregnancy-related complications and improve fetal growth, development, and long-term child health outcomes. The findings support routine monitoring of vitamin D levels, particularly among women at high risk of deficiency, and suggest that vitamin D supplementation during pregnancy should be considered. Current evidence indicates that supplementation with more than 400 IU/day of vitamin D may help prevent certain adverse maternal and neonatal outcomes. 7. Research Contributions and Future Perspectives The findings of this study provide valuable evidence for clinical practice, prenatal nutritional guidance, and public health policy development. By highlighting the importance of maintaining adequate vitamin D status during pregnancy, this research contributes to strategies aimed at improving the health and well-being of both mothers and their children.   (Provided by: Clinical Medical Research Center research team, Chia-Yi Christian Hospital)

Microbially Induced Carbonate Precipitation (MICP): A Promising Approach for Environmental Remediation

Mar 16, 2026

Designing Life for 100 Years: From Taiwan’s Active Aging Learning Initiatives to an Action Blueprint for a Longevity Society

Feb 28, 2025

Background: The Turning Point of an Aging Society Has Arrived   Taiwan is entering a super-aged society at an unprecedented pace. According to data from the National Development Council, by 2025, people aged 65 and over will account for more than 20% of Taiwan's total population. In the future, Taiwan’s rate of population aging is projected to surpass Japan’s starting in 2047 and, by 2070, be only slightly behind South Korea’s—ranking among the highest globally. This is no longer a future scenario—it is already happening. Many individuals are unprepared mentally, and both social systems and personal planning are struggling to keep up. While past aging policies have focused largely on care and medical support, the emergence of a decades-long elderly stage of life calls for a new paradigm. Shouldn’t we reimagine this challenge through the lens of education? How can we help people proactively plan, engage, and live meaningfully in the second half of life? Fig. 1. 臺中市樂齡學習示範中心   A Global First: Taiwan’s “Senior Learning Policy” as a Model for Educational Prevention and Proactive Aging Since 2008, my team and I have implemented a “Active Aging Learning Initiative,” which became the world’s first government-led, systemically implemented educational policy for older adults1. Unlike the international norm that prioritizes the “right to be cared for,” we advocate for a different concept: the “responsibility to design one’s later life through learning before entering old age.” Senior learning is not just about course delivery—it is a pathway to social participation and self-actualization. Over 18 years, more than 372 senior learning centers have been established across Taiwan. A community-based, intergenerational, and action-oriented model has emerged, deepening education’s role in building a longevity society2. Fig. 2. from 劉文端   The “1-2-3 Instructional Model": A New Pedagogical Paradigm for Adult Learning To overcome the passivity of traditional learning, we developed the “1-2-3 Instructional Model” tailored for older and adult learners. It emphasizes three core components3: l 1 Learning Focus: Center on a clear learning objective. l 2 Learning Activities:Combine conceptual understanding with hands-on experiences to boost motivation and contextual awareness. l 3 Applications: Transform learning into practical actions—whether personal, social, or purposeful. This model is now part of Taiwan’s Professional Training and Certification in Active Aging Education, with over 8,000 certified instructors actively teaching in Active Aging Learning Centers and community programs, becoming catalysts of educational transformation in the age of longevity. Fig. 3. 高雄市樂齡學習示範中心   The Third Life University: A New Lifelong Learning Blueprint for the 55+ Generation In 2024, commissioned by the Ministry of Education, we developed the framework and pilot for the “Third Life University” targeting adults aged 55 and above. Key features include: l Core literacy curriculum modules for a 100-year life l Ministry-accredited credit and certification systems l A hybrid learning model linking university resources with communities. l Program designs to support career transitions, meaningful engagement, and dream realization The Third Life University is not just a place for learning—it is a platform for new social roles and personal value in a long-lived society. From Anxiety to Action: Life Design Modules for a 100-Year Life Our research shows that many individuals face two tensions in later life: anxiety over identity shifts and lack of clear goals, alongside uncertainty about what they truly want. To address this, we created a “Designing Life for 100 Years” learning module, incorporating self-directed learning, narrative inquiry, and action planning to support: l Life review and future exploration l Values clarification and goal setting l Micro-practices and reflective action This module now serves as the foundation for the “Life Design for 100” Facilitator Certification, aimed at training professionals equipped to guide and inspire others45.   Beyond Academia: Social Advocacy for Designing Life After 50 As a scholar, I’ve realized that research without real-world application cannot address society’s urgent needs. Since 2012, we have translated academic insights into public initiatives and publications, including:  l Practical books such as Design Your Second Half: A Happiness Guide for Active Aging and Designing a Life That Moves You l Certified Life Design Facilitator l Public education campaigns, social innovation projects, and experimental courses for longevity living Through interdisciplinary collaboration and community co-creation, we aim to inject hope and agency into the rapidly aging society6.   A Sincere Invitation to Like-Minded Changemakers If you resonate with any of the following: l You wish to explore cutting-edge theories and practices in elder education l You hope to become a “100-Year Life” facilitator and support others in their later-life transitions l You aim to design learning programs or action plans for the 55+ generation l You want to contribute to policies or fieldwork for a longevity society We warmly invite you to join the Learning & Action Movement of Designing Life for 100 Years7. Because now is the best time to redesign the future. Fig. 5. National Chung Cheng University Aging & Education Research Center   1 Findsen, B., Wei, H.-C., & Li, A.-T. (Eds.). (2022). Taiwan's Senior Learning Movement: Perspectives from the outside in and from the inside out (Lifelong Learning Series 28). Springer. DOI: https://doi.org/10.1007/978-3-030-93567-2 2 Findsen, B., & Wei, H.-C. (2023). Senior Learning in Taiwan: Achievements and Challenges. Adult Education Discourses, 24, 103-119. DOI: https://doi.org/10.34768/dma.vi24.685 3 Wei, H.-C., & Li, A.-T. (in press). Taiwan's active aging learning practice through the 1-2-3 Instructional Model: Facilitating learning among individuals 55 years old and above. In Qiu Wang & Guofang Wan (edit.). Life-long Learning: The Education of the Aging Population (pp. xx–xx). Chinese American Educational Research and Development Association Book Series, Information Age Publishing. https://tinyurl.com/4p7427rr 4 Liao, F.-M., Chen, G.-L., Hsu, C.-T., Liu, Y.-H., Cheng, L.-L., Chan, X.-C., & Wei, H.-C.* (2023). Validation of the self-directed learning scale for middle-aged and older adults. Educational Gerontology 50(4), 304-319. DOI: https://doi.org/10.1080/03601277.2023.2270874 5 Liao, F.-M., Chen, G.-L., Hsu, C.-T., & Wei, H.-C.* (2024). Assessing the ability of self-directed learning as a prerequisite for active aging among middle-aged and older adult learners: cross-sectional study. Educational Gerontology, 51(3), 313-329. DOI: https://doi.org/10.1080/03601277.2024.2391164 6 Wei, H.-C., Lin, Y.-H., & Chang, L.-H. (2023). The Effectiveness of a Blended Learning‐Based Life Design Course: Implications of Instruction and Application of Technology. SN Computer Science, 4, Article 360. https://doi.org/10.1007/s42979-023-01730-3 7 Wei, H.-C. (2022, July). My Personal and Professional Growth in the Second Half of Life: The Impact of My Active Aging Learning Experiences. PIMA Bulletin, 43, 25-28. Special Issue on Later Life Learning, guest editors Brian Findsen and Diana Amundsen. https://vn.seameocelll.org/wpcontent/uploads/2023/12/PIMA-Bulletin-No.43-Jul-2022.pdf