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Article
Publication date: 23 May 2022

Caihua Yu, Tonghui Lian, Hongbao Geng and Sixin Li

This paper gathers tourism digital footprint from online travel platforms, choosing social network analysis method to learn the structure of destination networks and to probe into…

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Abstract

Purpose

This paper gathers tourism digital footprint from online travel platforms, choosing social network analysis method to learn the structure of destination networks and to probe into the features of tourist flow network structure and flow characteristics in Guilin of China.

Design/methodology/approach

The digital footprint of tourists can be applied to study the behaviors and laws of digital footprint. This research contributes to improving the understanding of demand-driven network relationships among tourist attractions in a destination.

Findings

(1) Yulong River, Yangshuo West Street, Longji Terraced Fields, Silver Rock and Four Lakes are the divergent and agglomerative centers of tourist flow, which are the top tourist attractions for transiting tourists. (2) The core-periphery structure of the network is clearly stratified. More specifically, the core nodes in the network are prominent and the core area of the network has weak interaction with the peripheral area. (3) There are eight cohesive subgroups in the network structure, which contains certain differences in the radiation effects.

Originality/value

This research aims at exploring the spatial network structure characteristics of tourism flows in Guilin by analyzing the online footprints of tourists. It takes a good try to analyze the application of network footprint with the research of tourism flow characteristics, and also provides a theoretical reference for the design of tourist routes and the cooperative marketing among various attractions.

Details

Data Technologies and Applications, vol. 57 no. 1
Type: Research Article
ISSN: 2514-9288

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Article
Publication date: 11 September 2017

Jinnan Wu, Lin Liu and Lihua Huang

Although perceived risk and usefulness have been identified as two major factors that influence consumer acceptance of an innovative mobile payment (m-payment), relatively few…

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Abstract

Purpose

Although perceived risk and usefulness have been identified as two major factors that influence consumer acceptance of an innovative mobile payment (m-payment), relatively few researchers have explored the impact of affective factors on perceived risk and usefulness, and the relationship between perceived risk and usefulness. Also, it is unclear whether there is a difference in the acceptance intention among users across different diffusion stages of this innovation. The purpose of this paper is to investigate the role of positive emotion in consumer acceptance of WeChat payment across time.

Design/methodology/approach

This study proposed and validated a framework integrating the consumer response system model and the affect heuristic. A total of 484 valid responses were collected through two online surveys at two diffusion stages of WeChat payment technology. The structural equation modeling and multigroup analysis were used to test the hypotheses.

Findings

The results show that users’ acceptance intention is relatively related to perceived risk, perceived usefulness, and positive emotion. Positive emotion has a strong negative impact on perceived risk and a positive impact on perceived usefulness. Also, perceived usefulness strongly decreases users’ perception of risk. Multigroup analyses find that both positive emotion and perceived risk have significant positive and negative impacts on acceptance intention at the stage of market introduction rather than market growth. Rather, the influence of positive usefulness on acceptance intention is significantly higher at the stage of market growth than at market introduction.

Originality/value

This study indicates that exploring the role of positive emotion and the moderating effect of diffusion stages in m-payment acceptance provides a more comprehensive understanding of how to achieve a greater acceptance rate of an innovative m-payment.

Details

Industrial Management & Data Systems, vol. 117 no. 8
Type: Research Article
ISSN: 0263-5577

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