Search results

1 – 3 of 3
Content available
Article
Publication date: 1 December 2003

228

Abstract

Details

Microelectronics International, vol. 20 no. 3
Type: Research Article
ISSN: 1356-5362

Open Access
Article
Publication date: 10 April 2023

Xiaohua Fu, Thanawan Sittithai and Thitinan Chankoson

The primary purpose of this study is to investigate the influence of tourists' perceived value, satisfaction and behavioral intention on the development of Lipu Yi costume culture…

1212

Abstract

Purpose

The primary purpose of this study is to investigate the influence of tourists' perceived value, satisfaction and behavioral intention on the development of Lipu Yi costume culture to promote the development of intangible cultural tourism and better construct a model of the influencing factors of Lipu Yi costumes in the development of intangible cultural heritage tourism.

Design/methodology/approach

The study site is the intangible cultural district of Panzhihua, Sichuan Province, China. This study examines the interrelationships between tourists' perceived value of experience, behavioral intention and satisfaction as the tourists relate to Lipu Yi costume and intangible cultural heritage tourism. A sample of 225 tourists who had visited Panzhihua at least once was selected for the study.

Findings

All seven of the survey's hypotheses were supported. Therefore, this study concludes that tourists' perceived value, satisfaction and behavioral intention directly affect the development of intangible cultural tourism and significantly positively impact the growth of Lipu Yi costumes culture. Descriptive analysis, confirmatory factor analysis (CFA) and structural equation modeling (SEM) investigation methods were used.

Originality/value

This paper analyzes tourists' perceived value of Lipu costume culture and tourists' satisfaction and behavioral intention during the tourism process. This study provides a more in-depth understanding of the relationship between Lipu Yi costume and non-heritage tourism factors. Practical methods and approaches are sought to further develop Lipu Yi costume non-heritage tourism.

Details

Journal of Cultural Heritage Management and Sustainable Development, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2044-1266

Keywords

Open Access
Article
Publication date: 14 August 2020

Paramita Ray and Amlan Chakrabarti

Social networks have changed the communication patterns significantly. Information available from different social networking sites can be well utilized for the analysis of users…

6253

Abstract

Social networks have changed the communication patterns significantly. Information available from different social networking sites can be well utilized for the analysis of users opinion. Hence, the organizations would benefit through the development of a platform, which can analyze public sentiments in the social media about their products and services to provide a value addition in their business process. Over the last few years, deep learning is very popular in the areas of image classification, speech recognition, etc. However, research on the use of deep learning method in sentiment analysis is limited. It has been observed that in some cases the existing machine learning methods for sentiment analysis fail to extract some implicit aspects and might not be very useful. Therefore, we propose a deep learning approach for aspect extraction from text and analysis of users sentiment corresponding to the aspect. A seven layer deep convolutional neural network (CNN) is used to tag each aspect in the opinionated sentences. We have combined deep learning approach with a set of rule-based approach to improve the performance of aspect extraction method as well as sentiment scoring method. We have also tried to improve the existing rule-based approach of aspect extraction by aspect categorization with a predefined set of aspect categories using clustering method and compared our proposed method with some of the state-of-the-art methods. It has been observed that the overall accuracy of our proposed method is 0.87 while that of the other state-of-the-art methods like modified rule-based method and CNN are 0.75 and 0.80 respectively. The overall accuracy of our proposed method shows an increment of 7–12% from that of the state-of-the-art methods.

Details

Applied Computing and Informatics, vol. 18 no. 1/2
Type: Research Article
ISSN: 2634-1964

Keywords

Access

Only content I have access to

Year

Content type

1 – 3 of 3