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Sensory-Driven Consumer Satisfaction in China’s Cigarette Market: A Structural Equation Model of Packaging, Taste, and Experience Yang, Lei; Feng, Hong Tao; Hu, Hao Ruo; Li, Chao; Zhan, Jian Bo; Fan, Duo Qing; Tao, Ying; Wang, Jin; Jiang, Meng Fei; Zhang, Tao
Indonesian Journal of Business and Entrepreneurship Vol. 11 No. 2 (2025): IJBE, Vol. 11 No. 2, May 2025
Publisher : School of Business, IPB University (SB-IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17358/ijbe.11.2.466

Abstract

Background: In recent years, the Chinese cigarette market has undergone significant changes, with tobacco companies emphasizing consumer research in their product development and marketing strategies. A noticeable shift toward analyzing and optimizing the entire consumer experience makes a consumer-centric perspective the top priority in product development. Purpose: The study aims to create a consumer-centered evaluation system focusing on sensory and emotional aspects. Exploring the connections between packaging design, the smoking experience, quality perception, internal taste, innovative design, and product naming offers insights into leveraging these elements to differentiate products and improve brand competitiveness in a declining market. Design/methodology/approach: The study was conducted in 12 cities and involved quantitative research with a sample size of 2,521 participants. Participants were selected using stratified sampling to ensure representation from China's different geographical and economic regions. The analysis included the development of a structural equation model based on the relationships among seven latent variables and 62 observed variables. Findings/Result: This study shows that the smoking experience is the most critical factor in determining satisfaction, with internal taste playing a key role. Another result is that the packaging's tactile and auditory features, such as the smoothness of the box and the sound of tearing, significantly enhance the consumer experience. Sensory attributes, including aroma and visual appeal, greatly influence quality perception and overall satisfactionConclusion: This study provides new insights and empirical evidence for cigarette companies to better serve consumers, highlighting the role of sensory and emotional factors in product development and innovation.Originality/value (State of the art): By improving these influential indicators, cigarette products can effectively enhance their performance in the consumer journey experience. This paper provides a new perspective and empirical reference for cigarette enterprises to serve consumers better. Keywords: cigarette consumption experience, consumer satisfaction, sensory elements, influencing factors, structural equation model
Comparative evaluation of left ventricle segmentation using improved pyramid scene parsing network in echocardiography Wang, Jin; Aliman, Sharifah; Ibrahim, Shafaf
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 4: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i4.pp3214-3227

Abstract

Automatic segmentation of the left ventricle is a challenging task due to the presence of artifacts and speckle noise in echocardiography. This paper studies the ability of a fully supervised network based on pyramid scene parsing network (PSPNet) to implement echocardiographic left ventricular segmentation. First, the lightweight MobileNetv2 was selected to replace ResNet to adjust the coding structure of the neural network, reduce the computational complexity, and integrate the pyramid scene analysis module to construct the PSPNet; secondly, introduce dilated convolution and feature fusion to propose an improved PSPNet model, and study the impact of pre-training and transfer learning on model segmentation performance; finally, the public data set challenge on endocardial three-dimensional ultrasound segmentation (CETUS) was used to train and test different backbone and initialized PSPNet models. The results demonstrate that the improved PSPNet model has strong segmentation advantages in terms of accuracy and running speed. Compared with the two classic algorithms VGG and Unet, the dice similarity coefficient (DSC) index is increased by an average of 7.6%, Hausdorff distance (HD) is reduced by 2.9%, and the mean intersection over union (mIoU) is improved by 8.8%. Additionally, the running time is greatly shortened, indicating good clinical application potential.