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During the past decades, several researchers have introduced devices that use sonar systems to detect and/or to determine the object location or to measure the distance to an object using reflected sound waves. The purpose of this paper is to use sonar sensor with textile structure and to test it for detection of objects.

In this study, a sonar system based on intelligent textiles approach for detection of objects has been developed. In order to do this, ultrasonic sensor has been integrated to textile structures by using conductive yarns. Furthermore, an electronic circuit has been designed; PIC 16F877 microcontroller unit has been used to convert the measured signal to meaningful data and to assess the data. The algorithm enabling the objects detection has also been developed. Finally, smart textile structure integrated with ultrasonic sensor has been tested for detection of objects.

Beam shape is presented related to identified object and compared with the actual one given in sensor's datasheet in order to test the efficiency of the proposed method of detection. The achieved results showed that the determined beam pattern matches with the actual one given in its datasheet. Therefore, it can be concluded that the integration of sensor was successful.

This is the first time in the literature that a sonar sensor was integrated into textile structure and tested for detection of objects.

Purpose/Objective: This study aims to investigate the inferences of technological innovations introduced by companies, emphasised by firm investments in innovative products, the use of information technologies (ITs), and the number of innovative products in achieving economic and environmental sustainability.

Design/Methodology/Approach: Simple regression models with Driscoll–Kraay standard errors processed through the Pooled OLS method, and cluster analysis performed through the Ward method inset on hierarchical clustering. A newly compiled dataset with information extracted from the European Innovation Scoreboard (EIS) 2023 was employed in the analysis, covering the time lapse from 2016 to 2023 and integrating 28 European countries.

Findings: A statistically significant relationship between firm investments, technological innovations, and companies’ environmental and sustainability credentials. Clusters associated with the impact of innovative technologies on environmental and economic sustainability were identified. The results showed four different clusters, including countries that present similarities among the variables or distinctive tendencies from the countries belonging to other clusters.

Significance/Implications/Conclusions: New insights for firms, managers, entrepreneurs, and local or foreign investors and emphasise the need for innovation and technological investments within companies to improve their business activities and support more effective and sustainable development.

Limitations: The reduced availability of data and regarding the sample of representative indicators.

Future Research: Future research avenues might explore the importance of collaboration among technologists, financiers, policymakers, and environmentalists to harness technology’s full potential and navigate the complexities of integrating it with sustainable practices.

This study explores the effects of virtual streamer characteristics, virtual scene characteristics and streamer image-scene fit on users’ watching intention from the perspective of flow experience.

The survey data for this study were collected from the QQ fan group of virtual streamers between November 26th 2022 and December 5th 2022. The authors survey 274 viewers who have experience of watching virtual streaming and employ the partial least squares structural equation model to test the research hypotheses.

Among the characteristics of virtual streamers, interactivity significantly influences users’ perceived enjoyment and concentration, while vividness only affects perceived enjoyment. In addition, the novelty of the virtual scene has a notable impact on users’ perceived enjoyment and concentration, whereas aesthetic appeal serves as an important indicator solely for concentration. Furthermore, the virtual streamer image-scene fit also affects users’ perceived enjoyment and concentration. Finally, perceived enjoyment and concentration equally contribute to users' watching intention.

This study explores the impact of virtual streamer characteristics, virtual scene characteristics and streamer image-scene fit on users’ watching intention, which enriches the research on user behavioral intention in virtual streaming. Additionally, this study attempts to combine the stimulus-organism-response (S-O-R) model and flow theory in the field of virtual streaming, expanding the research areas. Finally, this study also provides valuable insights for virtual streamers and virtual streaming platforms. By enhancing their virtual personas and optimizing their streaming strategies, virtual streamers can more effectively retain users and maintain audience engagement. Meanwhile, virtual streaming platforms can gain a deeper understanding of user preferences, enabling them to launch high-quality events that sustain user popularity. These efforts collectively contribute to the advancement of the virtual streaming industry.