There is a growing need to understand how live streaming e-commerce influences consumers’ purchasing behavior. Perceived value, engagement, and live streaming quality are crucial components that utilized structural equation modeling (SEM) to examine the factors that influence purchase intentions. This study presents a methodology for analyzing the variables that influence live streaming e-commerce purchase decisions. The study uses SEM and Machine Learning algorithms like Bayesian model, Random Forest, XGBoost, KNN and SVM to assess the prediction. This paper uses two feature transformation methods (MinMax and Zscore) and two feature selection models (InfoGain and Correlation) to improve the prediction of purchase intention. This paper gathers questionnaire responses from 500 participants who have purchased goods through E-commerce Live Broadcast in China and validates the results using a SEM. The study provides a reliability and validity analysis for the suggested model using SEM analysis. The attributes of live broadcasts can elevate the perceived value and trustworthiness, as well as consumer impulsivity, hence increasing customers’ likelihood to purchase.

The State Railway of Thailand's (SRT) rail passenger ridership has dropped from a peak of 88 million rides in 1994 to less than 23 million in 2022, with the reasons for this collapse being numerous. Therefore, the authors set out to examine how organizational image (OI), service quality (SQ), service motivation (SM), and service satisfaction (SS) affect SRT use decision (SUD) making. From August–October 2022, multiple-stage random sampling was used to select a sample of 1,250 SRT passengers from five regional rail lines and their associated 25 stations. A confirmatory factor analysis goodness-of-fit was used to confirm the model's fit. A structural equation model (SEM) using LISREL 9.10 was then used to analyze the ten hypothesized relationships. The quantitative research used a 5-level questionnaire to measure the study's five constructs and 22 observed variables. The reliability of the items ranged from 0.86 to 0.93. The data analysis included calculating various statistical measures. Results showed that the model's causal variables positively affected passenger SRT use decision, with an R² of 71%. When ranked by total effect (TE) values, service quality (SQ = 0.89) was viewed by the surveyed passengers as most important, followed by service satisfaction (SS = 0.67), organizational image (OI = 0.63), and service motivation (SM = 0.53). Additionally, all ten hypotheses were supported, with service satisfaction judged the most essential to SRT Use Decisions. The study's novelty is the ever-growing requirement for the SRT to serve as a regional hub in a more extensive East Asian rail and infrastructure strategy. The paper contributes significantly to the academic literature on factors affecting rail transportation use intent.

This study investigates the drivers of older adult loyalty (OAL) in Thailand’s rail passenger transport sector. Using structural equation modeling (SEM), data from 625 older rail passengers were analyzed to examine the direct and indirect pathways shaping loyalty. The results demonstrate that service innovation (SI) exerted the strongest overall effect on OAL, both directly and through its influence on service quality (SQ) and passenger satisfaction (PS). Interaction-oriented innovations and accessible delivery technologies emerged as particularly influential, highlighting the importance of human-centered innovation in aging societies. Perceived value (PV) also significantly predicted SQ, PS, and OAL, with price fairness, emotional reassurance, and reliability as key sub-dimensions. SQ was confirmed as a central mediator, translating SI and PV into satisfaction and loyalty outcomes, while PS, although significant, played a secondary role. The findings extend existing theories by demonstrating that innovation and value outweigh satisfaction as loyalty drivers in this context. They advance the SERVQUAL, Value–Attitude–Behavior, and Expectancy–Disconfirmation frameworks by showing that satisfaction is a necessary but insufficient condition for loyalty. The study emphasizes aligning innovation, value, and quality to build inclusive, sustainable loyalty strategies for older rail passengers.

In recent years, sustainable entrepreneurship has emerged as a dynamic field, driving innovative solutions to environmental, social, and financial issues, as evidenced by the improvement of income systems. The purpose of this study is to explore the impact of the forward-looking strategy on enterprise performance so as to ensure that enterprises can maintain the ability of sustainable development. Foresight can promote the enhancement of sustainable development. Therefore, the current research mainly determines that forward-looking strategies will ultimately affect the performance of enterprises through the impact on their own dynamic capabilities. Through the empirical investigation of 125 enterprises, the corresponding research data are obtained. The results show that the forward-looking strategy has a positive impact on enterprise performance, while enterprise dynamic capability, as an intermediary variable, has a positive impact between the forward-looking strategy and enterprise performance. This research introduces market dynamic capability as a moderating variable to explore whether forward-looking strategies can adapt to changes in the external market environment. Structural equation modeling (SEM) is used to examine the complex relationships between multiple independent and dependent variables of forward-looking strategies and dynamic capabilities, including the impact of latent variables. Under the background of digital economy, digital technology gradually infiltrates the operation of enterprises and plays a vital role in enterprise performance. Digital transformation has become a realistic need for enterprises to respond to changes in the market environment and seek development. The forward-looking strategy has brought new opportunities to solve this problem. The core of the forward-looking strategy lies in “forward thinking” and “pioneering intention”. It not only emphasizes the ability to predict and identify potential opportunity windows in uncertain environments but also pays attention to the cultivation of enterprise resilience and openness to maintaining sustainable competitive advantage. Its foresight can build dynamic capabilities and ensure the sustainable development ability of enterprises through continuous insight into market information and technology resources, such as opportunity recognition perception, knowledge absorption and transformation, resource replacement and innovation, organizational change, and reconstruction.

As sustainability becomes a strategic imperative in the manufacturing sector, firms are increasingly adopting green environmental practices to enhance their competitive advantage and long-term viability. This study investigates the influence of an Internal (IGEO) or External Green Environmental Orientation (EGEO) on the Green Competitive Advantage (GCA), Green Innovation (GI), and Sustainable Performance (SP). Specifically, this research assesses the direct impact of an IGEO and EGEO on the GCA and GI, as well as their mediating roles in achieving sustainability objectives. To empirically validate the proposed conceptual framework, this study employs structural equation modeling (SEM) using survey data collected from 468 manufacturing firms in China. The findings reveal that an IGEO and EGEO are significant drivers of a GCA and GI, both of which, in turn, positively influence Sustainable Performance. The results underscore the importance of aligning internal sustainability initiatives with external environmental expectations to achieve superior long-term sustainability outcomes. This study contributes to the literature on green management by offering empirical evidence of the mechanisms through which a green orientation fosters sustainability. The insights derived have practical implications for firms seeking to integrate their internal capabilities with external environmental demands to develop a comprehensive and effective sustainability strategy. These findings serve as a valuable resource for researchers and practitioners aiming to enhance green competitiveness and innovation in the manufacturing sector.