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1 – 5 of 5Yabin Yang, Xitong Guo, Tianshi Wu and Doug Vogel
Social media facilitates the communication and the relationship between healthcare professionals and patients. However, limited research has examined the role of social media in a…
Abstract
Purpose
Social media facilitates the communication and the relationship between healthcare professionals and patients. However, limited research has examined the role of social media in a physicians' online return. This study, therefore, investigates physicians' online economic and social capital return in relation to physicians' use of social media and consumer engagement.
Design/methodology/approach
Using ordinary least squares (OLS) regression with fixed effects (FE) and panel data collected from Sina Weibo and Sina Health, this study analyzes the impact of physicians' social media use and consumer engagement on physicians' online return and the moderation effect of professional seniority.
Findings
The results reveal that physicians' use of social media and consumer sharing behavior positively affect physicians' online economic return. In contrast, consumer engagement positively impacts physicians' online social capital return. While professional seniority enhances the effect of physicians' social media use on online economic return, professional seniority only enhances the relationship between consumers' sharing behavior to the posts and physicians' online social capital return when professional seniority comes to consumer engagement.
Originality/value
This study reveals the different roles of social media use and consumer engagement in physicians' online return. The results also extend and examine the social media affordances theory in online healthcare communities and social media platforms.
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Shuqing Chen, Xitong Guo, Tianshi Wu and Xiaofeng Ju
With the advent of the Digital 2.0 era, online doctor–patient (D–P) interaction has become increasingly popular. However, due to the fact that doctors use their fragmented time to…
Abstract
Purpose
With the advent of the Digital 2.0 era, online doctor–patient (D–P) interaction has become increasingly popular. However, due to the fact that doctors use their fragmented time to serve patients, online D–P interaction inevitably has some problems, such as the lack of pertinence in the reply content and doctors' relative unfamiliarity with their individual patients. Therefore, the purpose of this study is to excavate whether potential D–P social ties and D–P knowledge ties accentuate or attenuate the influence of patient selection (online and offline selection).
Design/methodology/approach
The authors used the methods of text mining and empirical analysis on the structured and unstructured data of an online consultation platform in China to examine the research hypotheses.
Findings
The findings illustrate that the potential D–P social ties increase the influence on patient selection, as do the potential D–P knowledge ties. Specifically, the effect of social ties on patient selection is positively moderated by patient health literacy. Conversely, health literacy weakens the link between knowledge ties and patient selection. In addition, the doctor's title weakens the influence of social ties on patient selection, in contrast to knowledge ties (partially).
Originality/value
This study provides guidance for doctors and patients on how to communicate effectively and alleviate tension within D–P relationships. The study’s findings have both theoretical and practical implications for both doctors' and online platforms' decision-making.
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Xuening Fei, Yuanyuan Li, Shuai Li, Lingyun Cao, Dajie Xing, Bingyang Cheng, Meitong Li and Hongbin Zhao
This study aims to realize the multipurpose use of inorganic materials in adsorption treatment of pigment wastewater and preparation of core-modified Color Index Pigment Red 57:1…
Abstract
Purpose
This study aims to realize the multipurpose use of inorganic materials in adsorption treatment of pigment wastewater and preparation of core-modified Color Index Pigment Red 57:1 (C.I. Pigment Red 57:1, PR 57:1).
Design/methodology/approach
In this paper, the inorganic materials (sepiolite and SiO2·nH2O) were used in both PR 57:1 production wastewater treatment and its core-modification. The inorganic material firstly adsorbed 3-hydroxy-2-naphthoic acid (bon acid) in the pigment wastewater to reduce chemical oxygen demand. Then, the inorganic material adsorbed with bon acid was reused to prepare core-modified PR 57:1.
Findings
In the pigment wastewater adsorption experiment, it was found that under pH = 3, the adsorption percentage of bon acid by inorganic material can reached up to 46.00%. The pigment characterization results showed that the core-modified PR 57:1 had a core-shell structure. Under UV light irradiation for 1 h, the core-modified PR 57:1 prepared with sepiolite and SiO2·nH2O showed total color difference ΔE value of 1.43 and 2.05, respectively, which was lower than that of unmodified PR 57:1 (ΔE = 2.89). In addition, the transmittance of pigment water suspension test results showed that the core-modified PR 57:1 showed better water dispersibility.
Originality/value
This paper attempts to develop a synergistic strategy based on the multipurpose use of inorganic materials in adsorption treatment of pigment wastewater and preparation of core-modified PR 57:1.
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Fengjun Tian, Yang Yang, Zhenxing Mao and Wenyue Tang
This paper aims to compare the forecasting performance of different models with and without big data predictors from search engines and social media.
Abstract
Purpose
This paper aims to compare the forecasting performance of different models with and without big data predictors from search engines and social media.
Design/methodology/approach
Using daily tourist arrival data to Mount Longhu, China in 2018 and 2019, the authors estimated ARMA, ARMAX, Markov-switching auto-regression (MSAR), lasso model, elastic net model and post-lasso and post-elastic net models to conduct one- to seven-days-ahead forecasting. Search engine data and social media data from WeChat, Douyin and Weibo were incorporated to improve forecasting accuracy.
Findings
Results show that search engine data can substantially reduce forecasting error, whereas social media data has very limited value. Compared to the ARMAX/MSAR model without big data predictors, the corresponding post-lasso model reduced forecasting error by 39.29% based on mean square percentage error, 33.95% based on root mean square percentage error, 46.96% based on root mean squared error and 45.67% based on mean absolute scaled error.
Practical implications
Results highlight the importance of incorporating big data predictors into daily demand forecasting for tourism attractions.
Originality/value
This study represents a pioneering attempt to apply the regularized regression (e.g. lasso model and elastic net) in tourism forecasting and to explore various daily big data indicators across platforms as predictors.
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The purpose of this paper is to demonstrate that the sustainable development thought is one good reason why Chinese civilization is continuously developing, and it can be used as…
Abstract
Purpose
The purpose of this paper is to demonstrate that the sustainable development thought is one good reason why Chinese civilization is continuously developing, and it can be used as a reference for the development of Chinese agriculture today.
Design/methodology/approach
The paper employs a historical analysis approach to examine the sustainable thoughts concerning Chinese traditional agriculture, including view of sancai, farming season, fertility, the nature of matters, recycling, and economization.
Findings
The results reveal that the nature of Chinese traditional agriculture is akin to ecological agriculture, which is precious heritage for China and the whole world.
Originality/value
The originality of this paper is that it confirms the fundamental reason of the continuous development of Chinese civilization which, based on organization of sustainable development thought, lies in traditional agriculture.
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