Model Analysis Method Research Articles

Platform-based transportation company in Indonesia: Perspective brand switching behavior on Gen Z

Internet growth and the expansion of platform-based transportation companies in Indonesia are co-occurring. This study attempts to identify the factors that encourage platform-based transportation companies' customers to switch to competing platforms. This quantitative research method employed the Structure Equation Model (SEM) analysis method implemented in Warp PLS 5.0. This study's population comprises platform-based transportation users in Jakarta, the Indonesian capital. Through purposeful sampling, 200 research samples from Jakarta Generation Z were chosen. According to the results of this study, perceived price and experience dissatisfaction influence the Generation Z brand transition into platform-based transportation. In the interim, electronic service quality does not influence Generation Z brand-switching behavior in Indonesia. The relationship between perceived price and experience dissatisfaction with switching behavior is mediated by switching intention. This research contributes to transportation-based platform companies to reduce brand switching, especially among Generation Z.

Personnel training for the forestry complex of the northwestern and Arctic regions of Russia

Introduction. Forestry industry development and management in the North-West and the Arctic zone of the Russian Federation is a national priority, focused on the global competitiveness of the Russian timber industry products. The study aimed to analyze personnel training for forestry, offered by the education system of the North-West and the Arctic zone of Russia, in order to bring the qualities of the graduates of higher and secondary vocational education in line with the needs of the forestry industry in this macro-region. Materials and Methods. The research materials were statistical data from 4 forms of state federal reporting for 2021-2022: on admissions and graduations from the higher education system; graduation from the secondary vocational education system; number of employees of organizations by type of economic activity; demand of organizations by type of economic activity. The methods of descriptive statistics, mathematical modeling and comparative data analysis were used. Research Results. The study determined a list of 20 areas and disciplines of higher and secondary vocational education organizations training qualified personnel for the forestry complex, and formed a group of 19 types of economic activities related to the five main areas of forestry complex work. The scope of annual additional personnel demand of enterprises and organizations of the forestry complex of the Arctic and North-West Russia was calculated with the help of macroeconomic methodology for assessing the economy's demand for qualified personnel. The annual demand for personnel with higher education was 3.54%, for mid-level specialists it reached 4.49%, and for skilled workers and employees – 5.41% of the total number of employees with the appropriate level of education working in the forestry industry. The comparative analysis identified entities where personnel demands could be met by graduates from their region and entities needing additional sources, including graduates from other regions. Discussion and Conclusion. Pronounced lack of own personnel with higher education for enterprises and organizations of the forestry complex was identified in Leningrad Oblast, Chukotka, Nenets and YamaloNenets Autonomous Okrugs. Mid-level specialists currently graduate in sufficient numbers, with the exception of the Nenets Autonomous Okrug. In the next two to three years, a significant shortage of qualified workers and employees (more than 90%) is expected in all subjects of the macroregion. A solution to this problem may be targeted training of specialists in other regions, as well as in regions that are well-known educational centers (for example, Tomsk, Yekaterinburg, Novosibirsk).

A mathematical analytical modeling method for rotor eccentricity fault of large VSPSU

Aiming at the rotor eccentric fault modeling problem of large VSPSU (VSPSU), a mathematical analytical modeling method based on air gap magnetic field analysis is proposed. This method uses Fourier series decomposition to represent the air gap permeability of static and dynamic eccentricity faults. Then, taking a single coil as a unit, the eccentric self-inductance coefficients between each branch of the windings are derived. Furthermore, the mathematical analytical modeling of the eccentric fault is completed by combining the voltage and flux formulas of each winding branch. The model can reliably reflect the typical fault characteristics of large VSPSUs with eccentric faults, which can provide an analysis basis for subsequent relay protection research.

Coupling Dual Nonlinearity of Arch Bridge Bearing Capacity Analysis Method

In order to realistically restore the mechanical properties of the arch bridge under load and damage processes, a coupled dual nonlinear analysis method is established for the arch-bridge load–carrying capacity by considering the effects of bidirectional force transfer and adaptive section stiffness. First, based on the geometric nonlinear theoretical method of bidirectional force transfer, the macroscopic structural deformation of arch ribs under different loading conditions and load levels is preliminarily calculated, including the bending and axial deformation of each section of the arch, which is used to characterize the development of plasticity. According to deformation or strain, the fiber model analysis method is used to determine the true moment–curvature and axial force–curvature development paths of key sections, and then the elastic–plastic flexural and compressive stiffnesses of each section under different deformation states are derived. The elastic–plastic stiffness is substituted back to the geometric nonlinear equations to obtain the deformation and internal force along the arch ribs considering the cross-sectional plasticity. Finally, the above process is cycled until the equivalence condition is satisfied between the structural internal force/deformation and cross-sectional ones. In order to verify the rationality and accuracy of such a coupling method, a model test is carried out on a stiff skeletal concrete suspension chain line arch with a span of 12[Formula: see text]m, whose results match satisfactorily with that of calculated by the coupling dual nonlinearity method. Compared with the method suggested in the code JTG3362-2018, the proposed method can better predict the development of deflection of different arch rib sections, as well as the actual internal force state. The bending moment calculated as per the code is 7–16% larger than the test result at the ultimate capacity state, while the method of this paper is within 5%.

Application of 13CH4 double model online analysis method based on Fourier Transform Infrared Spectroscopy in energy exploration

In the last decades, the substantial demands for 13CH4 detection in oil, natural gas, and geological prospecting have been increasing. Among the commonly used gas detection methods, Fourier Transform Infrared Spectroscopy has the advantages of a short detection cycle and simultaneous detection of many gas components, but it has not been realized for the online analysis of 13CH4. In this paper, we propose a double model analysis method for 13CH4 concentration based on Fourier Transform Infrared Spectroscopy. This method uses a Fourier Transform Infrared Spectrometer to obtain infrared absorption spectra of gases containing 13CH4. It corrects the drift of the spectral baseline using the adaptive smoothness parameter penalized least square method. In addition, aiming to have a more fine-grained result, we categorize the volume concentration into two intervals (1 ×10−6-0.5 % and 0.5 %–100 %) for quantitative analysis, and combine a Novel Frequency control and Regression Coefficients method for characteristic variable extraction and quantitative analysis modeling to exclude the effect of other alkane gases on 13CH4 detection. We conducted a series of experiments and the results demonstrate that our proposed double model analysis method is capable of fast 13CH4 detection from mixed gas with a detection error lower than 2 % and a detection cycle shorter than 12 s for the concentration ranges from 1 × 10−6 (1ppmv) up to 100 %. Finally, we have accurately analyzed the 13CH4 content in the gas-producing formation from oilfield logging experiments.

K-POP 아이돌 그룹의 세대별 이슈 변화 분석 고찰

This study aims to identify the major issues in the news big data related to generational idols formed by the growth and development of idols amid the current global spread of K-pop, and to suggest ways to strengthen the competitiveness of the Korean music industry by identifying the major issues that are being formed through the media for each generation of K-pop idols and how they have changed. For this purpose, news big data LDA technique was used as a topic modeling analysis method for 55,660 cases, and as a result of the topic modeling analysis, common issue types of six dimensions were derived. The main issue types are activity dimension, marketing dimension, global dimension, social contribution dimension, dispute dimension, and fandom dimension, and policy, industrial, and academic implications are proposed based on the results of this study.

Optimal Allocation of Territorial Space in the Minjiang River Basin Based on a Double Optimization Simulation Model

The unequal distribution of territorial space resources stands out as a leading cause of the human–land contradictions and environmental degradation. These issues are especially pronounced in the Minjiang River Basin, which exhibits significant regional disparities. In pursuit of solutions to these pressing problems and the identification of sustainable developmental pathways, this study presents an innovative territorial space double optimization simulation model. This model integrates quantity structure optimization and distribution pattern optimization, in order to comprehensively consider the optimization of territorial space allocation and build a new territorial space pattern for the Minjiang River Basin in 2030. On this basis, we employed the Patch-generating Land Use Simulation (PLUS) model and scenario analysis method to design the double optimization scenario and natural development scenario. By comparing these two scenarios, and calculating the ecological benefits (EB), economic benefits (ECB), carbon storage (CS), and comprehensive benefits (CB) achieved in different scenarios, the validity of the double optimization model was fully verified. The results indicated that: ① the loss of sub-ecological space (PeS) under the natural development scenario was significantly larger than that under the double optimization scenario, and the loss should be mainly attributed to the large expansion of production space (PS) and living space (LS); ② the area of ecological space (ES) has reduced since 2020, but less area was lost and the retention rate was higher under the double optimization scenario; ③ the natural development scenario made the research region gain more ECB, but it also resulted in the loss of more EB and CS, whereas the Minjiang River Basin under the double optimization scenario was able to effectively balance the relationship among the three, thus achieving the best CB. The research findings provide strong scientific support for alleviating the human–land contradictions, protecting the ecological security in the basin, and promoting the sustainable development of the region.

EMPIRICAL VERIFICATION OF THE STRUCTURAL MODEL RELATING EQUILIBRIUM VALUES OF COSTS, QUALITY, AND COMFORT OF MEDICAL SERVICES WITH INDIVIDUALIZED ELASTICITIES OF DEMAND

The healthcare system in Ukraine is moving to flexible mechanisms to support the quality and comfort of medical services, in particular through the introduction of co-payments. The following necessitates the development of theoretical background and econometric models to support the process evaluation and optimization.
 Aim. The research aims at performing empirical verification of the structural model relating equilibrium values of costs, quality, and comfort of medical services with individualized elasticities of demand.
 Material and Methods. We have performed a combined (retrospective + prospective) study of the cases of uterine fibroids and/or ovarian cysts treated surgically in three city gynecological hospitals/centers in Vinnytsia, Ukraine. An econometric model of D. Dranove and M. Satterthwaite was used as the theoretical basis, the one that describes the dynamic equilibrium of cost, quality, and comfort of medical services together with demand elasticities. Importantly, the system of structural equations models joins moves of equilibrium of the price, quality, and comfort of medical services given shifts in the elasticities of demand. This is of use to analyze factors of efficiency and responsiveness to the demand of health care provision. Unfortunately, we did not find any practical use of this promising theoretical model, possibly due to the lack of empirical verification.
 Results and Disscusion. Therefore, we analyzed 150 case histories of women with uterine fibroids and/or ovarian cysts treated surgically. The data on the costs, quality, and comfort of inpatient care are studied to enable empirical verification of the model. The modern Monte Carlo Markov Chain (МСМС) methods of structural modeling and power analysis were used to estimate the required sample size.
 Conclussion. As a result of the study, the system of structural equations accompanying the theoretical model has been empirically verified for the first time and proved to be valid for ascertaining rational ways to optimize inpatient servicing of women with given gynecological pathology, in particular through the management of demand elasticities.

Multivariate SVR Demand Forecasting for Beauty Products Based on Online Reviews

Owing to changes in consumer attitudes, the beauty consumer population is growing rapidly and the demands of beauty consumers are variable. With a wide range of beauty products and exaggerated product promotions, consumers rely more on online reviews to perceive product information. In this paper, we propose a demand forecasting model that takes into account both product features and product emotional needs based on online reviews to help companies better develop production and sales plans. Firstly, a Word2vec model and sentiment analysis method based on a sentiment dictionary are used to extract product features and factors influencing product sentiment; secondly, a multivariate Support Vector Regression (SVR) demand prediction model is constructed and the model parameters are optimized using particle swarm optimization; and finally, an example analysis is conducted with beauty product Z. The results show that compared with the univariate SVR model and the multivariate SVR model with only product feature demand as the influencing factor, the multivariate SVR model with both product feature and product sentiment demand as influencing factors has a smaller prediction error, which can enable beauty retail enterprises to better grasp consumer demand dynamics, make flexible production and sales plans, and effectively reduce production costs.

The Influence of Social Media Instagram Promotion and Hedonic Shopping Motives on Purchase Decision at Shopee Clarandkei with Trust as a Moderating Variable

This study aimed to examine the effect of social media Instagram promotion on purchase decisions, hedonic shopping motives on purchase decisions, trust in moderating the effect of social media Instagram promotion on purchase decisions, and trust in moderating the effect of hedonic shopping motives on the purchase decision. The independent variables comprised Instagram promotion (x1) and hedonic purchasing motives (x2); on the other hand, purchase decision served as the dependent variable (y), and trust served as the moderating variable (m). This quantitative research used the Partial Least Square - Structural Equation Modeling (PLS-SEM) analysis method. The data was processed using SmartPLS 4 software. The sampling utilised a purposive sampling method and the instrument questionnaire using a Likert scale. Using Google Form media, the questionnaire was disseminated online. The study’s population consisted of 3.800 Instagram followers of Clarandkei. This study’s sample consisted of 180 respondents who enjoyed online clothing purchasing and had purchased clothing from Shopee Clarandkei at least once. The study’s findings indicated that social media Instagram promotion and hedonic shopping motives significantly and positively affected purchase decisions; trust moderates the effect of social media Instagram promotion on purchase decisions significantly and positively; however, the trust did not moderate the effect of hedonic shopping motives on the purchase decision.

The Effect of Halal Assurance, Product Quality and Social Media Reviews on Attitudes and Interest in Buying Food for Muslim Consumers in Yogyakarta Restaurants

This study aims to analyze and explain the influence of halal guarantees, product quality, and social media reviews on attitudes and food purchase intention for Muslim consumers at restaurants in the Yogyakarta area. This study uses primary data using convenience sampling techniques with samples obtained from 200 Muslim consumer respondents. This study uses the Structural Equation Modeling (SEM) analysis method with data processing using the SmartPLS version 3.0 program. The results of this study show that halal guarantees, product quality, and social media reviews have a positive and significant effect on Muslim consumers' purchase intention. The consumer attitudes that are influenced by halal guarantees, product quality, and social media reviews show positive and significant results. Furthermore, consumer attitudes also show a positive and significant influence on purchase intention.
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Seismic Resistance of Non-Linearly Deformable Large-Span Spatial Structures of Unique Buildings

Analytical, computer and experimental modeling methods are applied in the study of seismic resistance and changing dynamic parameters of long-term loaded non-linearly deformed large-span spatial shell structures. Physically and geometrically nonlinear deformation models and computational algorithms for solving dynamic problems are proposed for estimating the stress-strain state of smooth and ribbed spatial systems with variable stiffness caused by damage accumulation and orthotropic structure reinforced by ribs. The possibility of using the proposed method of taking into account variable dynamic stiffness in calculations for solving problems of dynamic strength and stability of spatial large-span shells of unique buildings of complex geometry is shown.

The Study of Regional Innovation Network Structure: Evidence from the Yangtze River Delta Urban Agglomeration

As a driving force for regional development, innovation holds an increasing position in regional competitiveness, and a reasonable and coordinated innovation network structure can promote high-quality regional development. Utilizing the modified gravity model and social network analysis method, an innovation network composed of 27 cities in the Yangtze River Delta urban agglomeration from 2010 to 2021 was studied. The following conclusions were founded: (1) The innovation development level in the Yangtze River Delta urban agglomeration was constantly improving, and the innovation development level generally showed a spatial pattern of high in the southeast and low in the northwest. (2) The intensity and density of innovation network correlations in urban agglomerations were increasing, and the centrality of network nodes had an obvious hierarchical characteristic. The innovation network had a significant core–periphery spatial structure, with core cities that had higher centrality, such as Shanghai, Nanjing, and Hangzhou, playing the role of “intermediaries” and “bridges”, while cities with lower centrality, such as Anhui and cities in northern Jiangsu, generally played the role of “periphery actors” in the network. (3) The spatial correlation network of innovation of the Yangtze River Delta urban agglomeration could be divided into four blocks, namely, main benefit, broker, two-way spillover, and net spillover, and the spillover effect among them had obvious gradient characteristics of hierarchy.

The Importance of Organizational Agility to Improve Performance: Evidence from the Hotel Industry in the Post-Covid-19 Era

The hospitality industry is one of the industries that has experienced the hardest hit by the COVID-19 pandemic, such as a drastic drop in visitor levels and closed businesses. Despite the importance of organizational agility in the hospitality industry during post-pandemic recovery, there has been rare research on organizational agility in the hotel industry, especially in Indonesia. The research analyzed the effect of organizational agility on organizational performance through competitive advantage and organizational culture as mediating variables in hotels in Indonesia. The research sample was 76 hotels that consist of three-to-five-star hotels in Indonesia. The analysis was conducted using the Structural Equation Modeling (SEM) analysis method through smart Partial Least Square (PLS) software to test the research hypothesis. The results indicate that organizational agility has an important role in increasing organizational performance. Organizational agility has a significant and positive impact on organizational performance in hospitality in Indonesia, with a competitive advantage and organizational culture as mediating variables. The research helps management to understand the importance of having organizational agility in a company to deal with uncertain conditions. The findings also help management not only focus on quality but also on how companies can meet customer needs, create competitiveness, take risks, innovate, and increase profitability to improve organizational performance.

Climatic limitations on grassland photosynthesis over the Tibetan Plateau shifted from temperature to water

Plant photosynthesis plays an essential role in regulating the global carbon cycle. Therefore, it is essential to understand the limitations imposed by climate on plant photosynthesis to comprehend the impacts of climate change on land carbon dynamics. In this study, taking gross primary productivity as a direct representation of photosynthesis, we employed a light use efficiency model (i.e., the revised EC-LUE) and factorial analysis method to quantify the spatiotemporal variation of temperature- and water-limitations on plant photosynthesis over the Tibetan Plateau (TP) grasslands during growing season (May to October) in 1983–2018. Results revealed a clear spatiotemporal pattern of the temperature- and water-limitations: temperature is the primary climatic limiting factor in the eastern TP, while water is the primary climatic limiting factor in the western TP; the water- and temperature-limitations prevail in summer and spring/autumn, respectively. The water- and temperature-limitations intensified and alleviated, respectively, during 1983 through 2018. There also was a widespread shift from temperature-limitation to water-limitation in the TP, particularly in midsummer (August). Our findings demonstrated the shifting relative importance of climatic limitations on plant photosynthesis under changing climate, which is crucial for predicting future terrestrial carbon cycle dynamics.

Analytical approach to piezoelectric model synthesis with the use of Cauer’s method for system design

Background: Piezoceramic materials have unique property which enables direct and bilateral conversion between mechanical and electrical energy. This ability facilitates significant miniaturisation of technology and opens many opportunities in design of new actuators and energy harvesters. Mathematical modelling of piezoelectric modules is notoriously hard due to complex constitutive equations defining mechanical and electrical energy conversion. Methods: The article presents research on a new synthesis method based on the Cauer’s method for electrical and mechanical system design. Mechanical damping is introduced with the use of Rayleigh’s approximation. A discrete electromechanical model is formed based on the Mason’s piezoelectric model. As an additional element of the research, a non-standard model analysis method using edge graphs and structural numbers is employed to investigate potential reductions in computational requirements for model analysis. Results: The electromechanical model analysis has shown an error of 5% in relation to the resonance target. The calculated peak in magnitude of displacement at the resonant frequency was well above the capability of a 3.5mm thick piezoelectric plate. The proposed non-standard method of analysis gave identical results in terms of obtained resonance frequencies. The calculated magnitude of vibrations was varying by 50 – 58%. Conclusions: The synthesis method presented in this paper allows an approximation of piezoelectric parameters of a real system based on the created mathematical model. Currently this method is subject to a considerable error in the determined vibration amplitudes of the system, but it allows a coarse approximation of the parameters while having a very limited number of input data. The additional method of analysis based on structural numbers offers a promising alternative to matrix calculations but requires a more thorough investigation of the computational power required to determine whether it can compete with existing algorithms.

The influence of women’s empowerment on tourism involvement and sustainable tourism development: the moderating role of tourism cooperatives

ABSTRACT Influenced by patriarchy, male-centered culture, and family structure, gender inequality is widespread in rural areas of China. Based on the empowerment theory and the sustainable development theory, this study assessed the perceptions of women’s empowerment in rural tourism by a multi-dimensional scale of empowerment and explored the effect of women’s empowerment on tourism involvement and sustainable tourism development. Furthermore, tourism cooperatives were introduced into the conceptual model and investigated the moderating effect of tourism cooperatives on these relationships. Using the purposive sampling and snowball sampling approaches, 778 rural women living in Langde village and Huawu village participated in the survey, and then SPSS and Structural Equation Modeling (SEM) analysis methods were utilized for data processing. The value of this study lies in tourism cooperatives as an effective way of women’s empowerment in rural areas, which contribute to tourism involvement, thereby promoting sustainable tourism development.

Intentions to Consume Sustainable Fashion Products in Indonesia: Does Religiosity Affect ?

Religiosity is expected to be a positive driving factor of consumption demand for environmentally friendly fashion products. However, few studies have been found that focus on consumer behavior in purchasing sustainable fashion, and none use religiosity as an explanatory variable. This study, therefore, is the first to analyze the effect of religiosity on the intention to consume sustainable fashion products. This study used a quantitative approach with the Structural Equation Modelling (SEM) analysis method and involved 522 respondents in Indonesia. By adopting the theory of planned behavior model, the study results show that religiosity significantly positively affects purchase intentions of sustainable fashion products through the variables' attitude towards behavior and perceived behavioral control. At the same time, the green thinking variable also has a positive impact, but altruism is irrelevant to sustainable fashion consumption. These results indicate that if the consumer is religious, this can lead to a better environmentally friendly attitude and result in a tendency to consume sustainable fashion products.JEL Classification: D12, D90, Z12

Supply Chain Finance and Industrial Efficiency: Evidence From ICT Industry

This study explores the impact of supply chain finance on industrial efficiency and the internal mechanism. The super-efficiency model and quantitative analysis method were used based on the time series data of the ICT industry in Shenzhen from 2005 to 2020. In order to better investigate the impact of supply chain finance on industrial efficiency, this study categorized industrial efficiency into operational efficiency and innovation efficiency to reflect the durability and virtuousness of the industry development. Results indicate that supply chain finance has an inverted U-shaped nonlinear effect on industrial efficiency. Even though the long-term effect on operational efficiency is positive, the effect on innovation efficiency reveals an inverted U-shape, mainly due to the mediating effect of industrial concentration. Theoretically, this study sheds light on the intricate effects of supply chain finance at the industrial level, and also provides valuable insights into the potential inhibition mechanism, which enriches and deepens the related research on the supply chain finance from the nonlinear perspective, make the research findings more consistent with the fact of industrial development and avoid the linear stereotypes of the existing theory consensus. Practically, it is conductive to an objective understanding for managers and policymakers, so that supply chain finance can facilitate both operational and innovation efficiencies and realize the effective integration of supply chain finance and industrial development.

An Innovative Strategy to Anticipate Students’ Cheating: The Development of Automatic Essay Assessment on the “MoLearn” Learning Management System

A quick and effective learning assessment is needed to evaluate the learning process. Many tools currently offer automatic assessment for subjective and objective questions; however, there is no such free tool that provides plagiarism detection among students for subjective questions in a Learning Management System (LMS). This research aims to create an automatic essay assessment in MoLearn LMS that can check students’ answers. At the same time, the LMS can also anticipate online cheating. This research employed two methods comprising (1) System Development Life Cycle (SDLC) waterfall model and (2) Latent Semantic Analysis (LSA) method. The former was used to design and create essay assessment applications, and the latter was employed to check the essay's answer and automatically detect students’ plagiarism. The result showed that MoLearn LMS was successfully working on detecting students’ plagiarism, leading to better LMS innovation. Automatic essay assessment accelerates grading time by about 8.04 times that of manual grading, which takes 5.52 seconds per question.