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The purpose of this study is to develop an output model to extract surface microstructure characteristics of different objects, so as to predict the response of the output voltage obtained from tactile texture sensor.

The model is based on the consideration of the inverse-magnetostrictive effect, the flexure mode, the linear constitutive equations and the strain principle.

This research predicts and investigates the effect of the texture properties on the tactile texture sensor output characteristics.

The surface texture characteristic is regarded to be important information to evaluate and recognize the object.

The purpose of the study is to construct a relationship model between the consumer resistance to innovation (CRI) and innovation adoption, and the study selected the customer loyalty as the moderating variable.

Based on questionnaire survey and regression model analysis, the study analyses the psychological processes and formation mechanisms that they either resist or adopt innovation by exploring users' attitudes towards smartphone application updates.

The results showed that innovation resistance negatively affected innovation adoption, and consumers are more likely to adopt innovations simply under the influence of customer loyalty. In addition, the moderating effect of customer loyalty is different in that how the three dimensions of innovation resistance influence innovation adoption. From the perspective of affective response, when consumers become emotionally disgusted with innovative products, loyalty can hardly change their minds. When consumers' resistance to innovation comes more from cognitive evaluation or functioning, loyalty is more likely to change their resistance.

The paper tests mechanism between customer resist the new product and new product adoption and the moderate effect of customer loyalty.

The study aims to construct a model that illustrates the relationship between receiving and sharing negative electronic word-of-mouth (e-WOM), consumer resistance to innovation (CRI), and customer loyalty.

Utilizing questionnaire surveys and regression model analysis, this study examines the case of smartphones to explore the impact of customer loyalty and CRI on the spread of negative e-WOM.

The results show that when consumers receive negative e-WOM, it increases their resistance to innovation, consequently raising the probability of them sharing this negative feedback. However, strong customer loyalty mitigates this interaction. Interestingly, customer loyalty increases the likelihood of consumers sharing negative e-WOM upon receiving it. This suggests that loyal consumers tend to be more inclined to share information, regardless of its positivity or negativity.

The paper contributes by examining the mechanisms linking the receipt and dissemination of e-WOM, CRI, and customer loyalty, along with the moderating impact of customer loyalty.