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A study on the relationship between Workload, Burnout to Organization Commitment and Intention to Stay - Internal Marketing as moderator variable
No full textThis study mainly wants to understand the relationship between workload, burnout, organizational commitment and willingness to stay among colleagues in the catering service industry operation site, and to regulate it across internal marketing to understand the influence and relationship between them.
The results showed that the general colleagues have a stronger sense of burnout than the current cadres; in addition, the current position of colleagues is affected by their feelings about the company, their continued employment, and even more, the support provided by the company to colleagues, benefits, working environment and other measures, current store supervisors and cadres will feel it more deeply than ordinary colleagues. In addition, in order to improve colleagues\ue2 organizational commitment and willingness to stay, the focus can be on reducing colleagues\ue2 burnout, which can achieve half the work Finally, it was found in the analysis that when the workload is low, those with higher internal marketing have lower levels of burnout than those with lower internal marketing. However, when the workload increases to a certain level, internal marketing has higher levels of burnout. Those who feel burnout are more intense
A study on the impact of different trial mechanisms on consumers' willingness to upgrade - Taking over-the-top media services as an example
No full textAccording to Taiwan's online consumer streaming insights, the overall streaming time in Taiwan is 53 billion minutes, ranking 15th in the world. As streaming platforms expand and industry competition heats up, operators must not only draw customers to their services but also convince them to subscribe and keep using them. Free trials are a frequent marketing strategy for OTT streaming platforms, however there are drawbacks, such as poor willingness to pay for subscriptions after the trial time or quick cancellation of subscriptions. At the same time, little in-depth study is done on how customer behavior during the free or trial period influences later actions. Most of the present literature uses a quantitative method to evaluate the important elements that consumers consider before upgrading. To better understand consumers, this study will make use of interviews.
This study focuses on how consumer decisions and behaviors at each of the three stages\ue2selection, trial, and subscription\ue2of using streaming video platforms affect and boost users' intentions to subscribe and renew. First, we look at the factors that influence consumers' decisions to use a streaming service; next, we examine the frequency, duration, and attitudes of users during the trial period to determine the relationship between their usage behavior during the trial period and their willingness to subscribe; and finally, we use the PPM theory to identify the key factors that influence users' willingness to upgrade to the paid version.
To examine the relationship between trial mechanisms and willingness to subscribe through various user backgrounds, the study conducted in-depth interviews with 21 users who had used the streaming platform and divided the study participants into nine combinations of limited functionality, limited time, no trial, subscription, and no subscription. According to the study's findings, customers mostly chose a platform based on its content or recommendations from others, which was not significantly different from the reasons they initially chose other products. The frequency of use and desire to subscribe both rise over the trial period. The PPM theory analysis also reveals that the incentive to upgrade generated by the pull force is significantly greater than that of the push force, and the consumers' failure to upgrade is primarily influenced by the lack of traction or pull force. In conclusion, this study offers recommendations to the market on how to select the best trial method for various services, and it offers specific customer behavior as a reference indication for businesses to measure and distinguish between the various consumer types
Evaluation of Implementing AI Carbon Footprint Tracking Software - Taking Company A as an Example
No full textSince the Industrial Revolution, the concentration of carbon dioxide in the atmosphere has increased by over 50%. As of 2022, the Earth's average temperature has risen by 1.11 degrees Celsius compared to the pre-Industrial Revolution era. In the "2023 Climate Status Report: Navigating Unknown Territory," a collaborative effort by ten climate scientists, it was stated that 20 out of 35 vital signs of life have broken records. These include record-breaking levels in greenhouse gas emissions such as carbon dioxide, methane, and nitrous oxide, as well as surface temperatures, global and North Atlantic sea surface temperatures, and the extent of sea level rise. Additionally, both the Greenland ice sheet and Antarctic sea ice have reached new lows.
As mentioned earlier, since the signing of the Kyoto Protocol by over 55 countries in 1997, and with the explicit provisions of the Paris Agreement in 2015, nations worldwide are committed to reducing their carbon emissions. The Paris Agreement sets a goal to limit global warming to below 2 degrees Celsius by the end of the 21st century, with an even more ambitious target of 1.5 degrees Celsius. In response to the international demand for carbon reduction, my country has enacted various laws, including the Energy Management Act, the Renewable Energy Development Act, the Electricity Act, and the Greenhouse Gas Reduction and Management Act.In order to enhance the effectiveness of carbon reduction efforts, many large enterprises have also actively implemented various relevant platforms.
The research aims to explore the perspectives of top-level management regarding the adoption of the system, delve into the practical aspects of the implementation process, and gather insights from individuals responsible for the system within the company. Based on these findings, the study will then provide recommendations for potential regulatory and cost-related challenges that may arise during future implementations
Social structure of Taiwanese population of Indo-Pacific humpback dolphin (Sousa chinensis)
No full textThe Taiwanese population of Indo-Pacific humpback dolphin (Sousa chinensis) only occurs in a narrow strip of coastal water in western Taiwan. This small population\ue2s habitat is an area of high anthropogenic activity, and the population is classified as Critically Endangered by the IUCN, meaning the population has a high risk of extinction in the wild. Many research studies have been conducted on this population, however, there remains much to be discovered of their ecology and life history. This study aims to update previous studies on social structure and examine in more detail the relationship between social structure and groups composition. The dataset used in this analysis was provided by Professor Lien-Siang , National Taiwan University, Taiwan, and was collected between 2016-20 from vessel-based surveys. The dataset comprised imagery and related survey data of 71 adult dolphins, catalogued using previously standardised photo-identification techniques. Of these, 39 individuals, Individuals that were observed more than the mean re-sighting rate (=23 times), were selected for social structure analyses. Half weight index (HWI) was used to calculate association indices, and a temporal analysis was conducted using standardised lagged association rate (SLAR). Analyses were performed within the software Socprog 2.9 and visualisation outputs were made in QGIS and R. The results indicate that the social structure of this population is fluid and composed of non-random associations. When groups with and without dependent young were compared, significant differences were found in association indices and social structure (HWI = 0.23 and 0.09, respectively). Groups with dependent young formed larger clusters (2 clusters identified) but maintained associations with other clusters. In contrast, groups without dependent young preferred to remain in smaller groups (9 clusters identified). An examination of associations over time indicated that associations lasted over the longer term, however, there was considerable variation between individuals. When the dependent young are present, the social pattern shifts towards a preference for specific companions, suggesting a strategy for improving nurturing or foraging efficiency through cooperation with chosen individuals. In conclusion, the population of Indo-Pacific humpback dolphins that inhabit western Taiwan waters is a fluid society, but with some structure as evidences by non-random associations. When the dolphin group has a specific function, for example, nurturing, societal structure will change to accommodate the group needs
Study on the correlation between CEMIP2 and TP53 pathway in bladder cancer cells
No full textUrothelial carcinoma (UC) stands as the most prevalent malignancy along the urinary tract globally, with bladder urothelial carcinoma (UBUC) being its most frequently occurring subtype. Previous research has revealed the pivotal role of CEMIP2 in facilitating tumor migration and invasive capabilities, yet the exact molecular mechanisms remain elusive. TP53 mutations or inactivation emerge as the primary causative factors for bladder cancer. Previous studies have found that CEMIP2 regulates MDM2, which is a major regulator of TP53, so this study focuses on the relevance analysis of CEMIP2 and the TP53 signaling pathway. This project aims to investigate the impact of the CEMIP2-TP53 pathway on the target genes CD82 and CDKN1A and investigate cellular functional studies. In this study, it was observed that upon upregulation of CEMIP2, the mRNA and protein expression levels of CD82 and CDKN1A indeed decreased. Upregulation of TP53 had the opposite effect, while coexpression of CEMIP2 and TP53 restored the expression levels of CD82 and CDKN1A, demonstrating a mutual influence between CEMIP2 and TP53. In terms of cellular functions, it was confirmed that CEMIP2 enhances non-adherent cell growth, cell migration, and invasion capabilities, while TP53 diminishes these capacities. Coexpression of CEMIP2 and TP53 elevates the low cellular functional capabilities induced by TP53. This experiment identified STAT5A as a transcription factor activating VEGFA and confirmed that CEMIP2 regulates STAT5A to activate VEGFA. The results collectively illustrate that CEMIP2 induces the carcinogenesis process by inhibiting the TP53 pathway and is a key factor in inducing cancer cell angiogenesis through STAT5A
Investigating the Factors Affecting Guitarists Adopting Digital Amplifiers
No full textThe revenue of Taiwan's music performance industry is growing year by year, live performances have become a big part of Taiwan\ue2s music industry. Guitarists have to spend a lot of time doing sound checks in order to have the perfect performance. A digital amplifier provides a certain degree of convenience, but it cannot fully meet guitarists\ue2 demands. Therefore, this research discovers the main factors which affect guitarists\ue2 adoption of digital amplifiers. This study adopts the model of unified theory of acceptance and use of technology (UTAUT) as its framework and uses performance expectancy, effort expectancy and perceived cost as constructs to investigate the behavioral intention and the actual use behavior of guitarists adopting digital amplifiers. This study targets people who play guitar and use amplifiers in Taiwan. The questionnaire is distributed online, and a total 207 respondents were surveyed. The samples used were 175 respondents and analyzed using descriptive statistics, reliability and validity analysis, Pearson correlation analysis and structural equation modeling. The results indicated that the performance expectancy, effort expectancy and perceived cost affect behavior intention positively and significantly. The effect of behavioral intention on use behavior is positive and significant
Preparation and Evaluation of Hexaarylbenzene Poly(arylene ether)s Ionomer for Fuel Cell Applications
No full textProton exchange membranes are semipermeable membranes with ion-selective properties, which have been active in industry and academia over the past decades and continue to be used and developed for this key characteristic. The perfluorosulfonic acid polymers are common products on the market and have excellent chemical stability and Proton transport properties, but their high cost and environmental pollution have encouraged continuous improvement.
In this paper, we would like to synthesize a series of partially fluorinated hexaarylbenzene poly(arylene ether)s ionomers with special three-dimensional structures and pursue better products using complex polymer technology. The hexaarylbenzene structure with steric hindrance and the trifluoromethyl group with superhydrophobic properties in the polymer effectively construct hydrophobic domains with low fluorine demand. Water uptake, dimensional stability, mechanical strength, Proton conductivity and microphase morphology were measured and investigated.
In order to investigate the morphology evolution of the hydrophobic domains in the composite membrane, a coarse-grained model dissipative particle dynamics simulation is used. Finally, a Proton exchange membrane fuel cell was used as a carrier to evaluate the feasibility of practical application of this membrane
Improve the Reliability of VANET Routing based on Navigation Information
No full textIn bustling urban landscapes, frequent vehicle movements define the dynamic environment where wireless communication plays a crucial role. These conditions pose unique challenges to the stability and effectiveness of Vehicle Ad-hoc Networks (VANETs), extending beyond traditional considerations. Tall buildings, trees, and various obstacles can obstruct the transmission of wireless signals, leading to phenomena such as reflection, refraction, or absorption during the transmission, collectively known as multipath interference. This interference introduces instability in communication, thereby affecting its reliability and consistency.
To address these challenges, this study introduces Navigation-based Reliable Routing (NAV-RR). Leveraging navigation data to anticipate future network topology, NAV-RR utilizes the Signal to Interference plus Noise Ratio (SINR) and buffer length to assess the reliability of transmission links within the network topology. Transmission links deemed less reliable are systematically eliminated from consideration. Subsequently, the transmission path with the fewest hops is selected as the packet's route, thus enhancing the packet delivery rate
Predictive Analysis for Personal Loans by Using Machine Learning
No full textThis study adopts five common machine learning algorithms for predicting consumer personal loan uptake, including Logistic Regression, Support Vector Machine, Multilayer Perceptron, Gradient Boosting Decision Trees Catboost, and Xgboost. The research utilizes data from Thera Bank available in the public database Kaggle, featuring fields like age, work experience, income, family size, average credit card expenditure, education level, home loans, securities account, deposit account, and internet banking usage. The study addresses the issue of imbalanced data using the SMOTE (Synthetic Minority Over-sampling Technique) method and compares the accuracy and stability of predictions using the five models with three different sampling rates to identify the optimal model and key factors. Empirical results show that the Gradient Boosting Catboost model and the Support Vector Machine model perform with stability and precision across different sampling ratios, making them the best models. Moreover, through the Gradient Boosting Xgboost model, the study identifies key features such as educational factors, income, family size, the existence of a deposit account, and annual credit card spending. The findings of this research can provide crucial factors for financial institutions when formulating marketing strategies for personal loans
The Effects of Job Insecurity on Work Engagement and Meaning of Work
No full textDue to the volatile ang complex work environment, job insecurity is a prevalent source of stress in today's workplaces. Many research studies have shown a connection between job insecurity and negative effects on employees, including turnover intention, burnout, and reduced job satisfaction, However, there is ongoing discussion about the relative effectiveness of quantitative and qualitative job insecurity in predicting these outcomes. Leveraging the transactional theory of stress and conservation of resource theory, this study formulated and verified a theoretical framework. It aimed to demonstrate the predictive relationship between both quantitative and qualitative job insecurity and factors like work engagement and the meaning of work. A total of 253 samples were collected from full-time workers from various industries and positions in Taiwan. The findings indicated a negative correlation between both quantitative and qualitative job insecurity and work engagement as well as the meaning of work. Furthermore, there was a stronger correlation between qualitative job insecurity and both work engagement and the meaning of work