A Study on the Influencing Factors of Mobile Digital Music Selection in Subhealthy People Based on Perceived Value Theory

Abstract

Background. The mode of combining mobile terminals and mobile digital music has gradually entered a bottleneck period while promoting the development of the mobile terminal industry. Proposing personalized solutions for specific groups of people including subhealthy people has become the current direction for the further long-term development of this mode. Understanding the influencing factors that affect subhealthy people’s selection of mobile digital music is an urgent problem that needs to be solved in the development of personalized solutions. Objective. This article analyzes the influencing factors of the purchase intent to buy mobile digital music for subhealthy people and provides suggestions for mobile terminal vendors on how to design personalized solutions for this group of people. Methods. In order to achieve the above goals, this article constructs an influencing factor model based on the theory of perceived value, collects data by means of questionnaires, and uses the method of structural equations to verify the proposed model. Results. The results show that perceived quality, perceived price, social value, and emotional value all have a significant effect on users’ purchase intention. Meanwhile, the conditional value and epistemic value have a negative moderating effect on the relationship between the social value and subhealthy people’s digital music purchase intention but strengthen the positive relationship between the emotional value and subhealthy people’s digital music purchase intention. Conclusions. The analysis shows that mobile terminal vendors should have their own unique attitudes and feelings when designing personalized mobile digital music solutions for subhealthy people, clarify their position, find strategies to improve the experience of subhealthy people, and win the reputation of subhealthy people. Let subhealthy people have a sense of belongingness.

Interrelation of Zakat Literacy, Social Behavior and Perceived Value on Intention of paying Zakat

“…But in this study, zakat literacy does not affect the perceived value or the value that can be felt from the results of this study. In line with research (Jiang et al, 2021) It is believed that the social environment has a great influence on our intention or motivation to pay Zakat. This motivation arises from the individual's response to the dominant behaviour in an environment.…”

[Retracted] Automatic Classification Method of Music Genres Based on Deep Belief Network and Sparse Representation

“…In formula (5), δ is the number of training set data. e essence of RBM is to map the original data to different feature spaces to retain the key feature information of the data and obtain a better low-dimensional representation.…”

“…e essence of RBM is to map the original data to different feature spaces to retain the key feature information of the data and obtain a better low-dimensional representation. According to this idea, an idea of optimizing RBM training in this paper is to replace the objective function formula (5) of RBM equally. If the output of each RBM is converted according to formula (6), the output of its hidden layer can be inversely converted and then compared with the original data.…”

“…Rock music, jazz, classical music, and other music genres are examples of diverse style tracks comprised of unique beats, timbres, and other aspects exhibited in music works. With the fast development of network and multimedia technologies, people's primary method of listening to music has shifted to digital music, which has fueled people's need for music appreciation to some level [4][5][6]. Most online music websites' major categorization and retrieval elements are now based on the music genre.…”

Nexus Among Online Banking Services, Perceived Value and Consumer’s Post-Adoption Behaviour

“…PV has been broadly utilized in relevant research in the domain of Consumer's purchase/buying intention and PV. Abundant research revealed that PV is a better predictor as compared to quality or satisfaction for predicting the buying/purchase intentions of the consumer (Jiang et al, 2021).…”