Customer retention through service quality and satisfaction: using hybrid SEM-neural network analysis approach

Trust in AI-augmented design: Applying structural equation modeling to AI-augmented design acceptance

With the emergence of Artificial Intelligence (AI) 2.0, computers are now equipped with new creative capabilities and are playing an increasingly significant role in design. The use of AI augmentation has the potential to enhance design performance, however, there is limited research on the acceptance of AI-augmented design. The research gap under consideration in this study is addressed by presenting an acceptance model designed for AI-augmented design. This model integrates a range of variables including perceived privacy risk, enjoyment, perceived value, perceived usefulness, perceived ease of use, perceived behavioral control, social influence, and behavioral intention. The proposed model was validated through a questionnaire survey of 249 designers in China. The results reveal that enjoyment, perceived value, perceived ease of use, perceived behavioral control, and social influence have a significant positive impact on users' intention to use AI-augmented design, while perceived privacy risk has a significant negative impact. Perceived value was found to mediate the relationship between enjoyment and behavioral intention, while perceived behavioral control play a mediation role in the relationship between social influence and behavioral intention. In conclusion, this study highlights the variables that influence the acceptance of AI-augmented design and provides valuable insights into the potential benefits and drawbacks of integrating AI technologies in design. The proposed acceptance model serves as a framework for future research in this area and can guide the development of more user-friendly and effective AI-augmented design tools and technologies.

The Impact Mechanism of Consumer's Initial Visit to an Automobile 4S Store on Test Drive Intention: Product Aesthetics, Space Image, Service Quality, and Brand Image

[Purpose/Significance] Under the influence of various factors such as the pandemic, oil prices, and economic conditions, the global automotive industry has entered a period of downturn. Therefore, how to activate market potential and increase consumers' willingness to purchase cars has become an important research topic. Unlike many other products, test drives play a significant role in the car-buying process. [Method/Procedure] This study employs a questionnaire survey to explore how consumer perceptions of product aesthetics, space quality, and service quality during their initial visit to an automobile 4S store influence their test drive intention through two dimensions of brand image: symbolic and experiential. A structural equation model is used to establish a test drive intention impact model incorporating these dimensions. [Results/Conclusions] The study found that brand image, both symbolic and experiential, plays a significant mediating role in enhancing potential consumers' test drive intentions. Space image had the most significant impact on brand image. Although product aesthetics did not directly affect brand image experientially, they remained an important factor in enhancing brand image symbolically. [Contribution/Value] The results of this study can provide insights for automotive brand managers, automobile 4S store designers, and others aiming to promote the sustainable development of automotive consumption.

Determinants of cloud computing integration and its impact on sustainable performance in SMEs: An empirical investigation using the SEM-ANN approach

Although extant literature has thoroughly investigated the incorporation of cloud computing services, examining their influence on sustainable performance, particularly at the organizational level, is insufficient. Consequently, the present research aims to assess the factors that impact the integration of cloud computing within small and medium-sized enterprises (SMEs) and its subsequent effects on environmental, financial, and social performance. The data were collected from 415 SMEs and were analyzed using a hybrid SEM-ANN approach. PLS-SEM results indicate that relative advantage, complexity, compatibility, top management support, cost reduction, and government support significantly affect cloud computing integration. This study also empirically demonstrated that SMEs could improve their financial, environmental, and social performance by integrating cloud computing services. ANN results show that complexity, with a normalized importance (NI) of 89.14%, is ranked the first among other factors affecting cloud computing integration in SMEs. This is followed by cost reduction (NI = 82.67%), government support (NI = 73.37%), compatibility (NI = 70.02%), top management support (NI = 52.43%), and relative advantage (NI = 48.72%). Theoretically, this study goes beyond examining the determinants affecting cloud computing integration by examining their impact on SMEs' environmental, financial, and social performance in a comprehensive manner. The study also provides several practical implications for policymakers, SME managers, and cloud computing service providers.

Factors affecting adoption and use of M-commerce services among the customers in Saudi Arabia

M-commerce has the potential to change consumers' shopping habits and establish itself as a significant commerce channel. People rely on digital devices more than ever before, and the growth in M-commerce predicts that mobile will become the preferred channel for online shopping soon. This study is aimed at examining the effect of personal factors, economic factors, ease of doing factors, and safety-related factors due to Covid-19 on the adoption and use of M-commerce services among customers in Saudi Arabia. The study is empirical and is based on survey responses from 340, M-commerce customers in Saudi Arabia. The questionnaire method was used to collect the data. ANOVA and bivariate regression analysis were used to evaluate the collected data. The results showed that four independent variables, namely, personal, economic, ease of doing, and safety factors during the Covid-19 pandemic, are significant predictors of the dependent variable, adoption and use of M-commerce services by the customers. These factors influence customers' purchasing decisions when they use M-commerce services. The study also concluded that the frequency of using M-commerce has increased during the Covid-19 pandemic because of health, safety, and social distancing guidelines. One of the main limitation of the study is the few selective constructs for the research. The finding of the study will be beneficial to the customers to understand the significance of M-commerce services, especially during pandemic situations.