Exploring the switching intention of patients to e-health consultations platforms: blending inertia with push–pull–mooring framework

背景(考古学) 独创性 业务 营销 医疗保健 结构方程建模 服务(商务) 心理学 现状 公共关系 护理部 医学 社会心理学 经济 计算机科学 政治学 生物 机器学习 经济增长 古生物学 市场经济 创造力
作者
Nikita Dogra,Shuchita Bakshi,Anil Gupta
出处
期刊:Journal of Asia Business Studies [Emerald Publishing Limited]
卷期号:17 (1): 15-37 被引量:15
标识
DOI:10.1108/jabs-02-2021-0066
摘要

Purpose Technology has revolutionized the delivery of health-care services, with e-consultations becoming popular mode of service delivery, especially during the pandemic. Extant research has examined the adoption of e-health consultation services, with little attention paid to examine the switching behavior. This study aims to identify factors affecting patients’ intentions to switch from conventional mode i.e. visiting hospitals/clinics to e-health consultations. Design/methodology/approach To understand this we use the push–pull–mooring (PPM) framework and integrate variables from status quo bias framework to the model. A cross-section research design was used, which rendered 413 valid responses which were obtained from the patients visiting a traditional hospital setup. The data was analyzed using partial least square – structural equation modeling using SmartPLS 3.0. Findings Findings suggest that push effects (inconvenience and perceived risk), pull effects (opportunity for alternatives and ubiquitous care), mooring effects (trust) and inertia significantly influence patients’ switching intentions from visiting hospitals/clinics to e-health consultations. Further, habit and switching cost positively influence inertia. Practical implications This study shall enable online health-care service providers and practitioners to understand patients’ intentions to switch to online health platforms and accordingly develop related marketing strategies, services and policies to encourage them to switch to the new offerings. Originality/value The current study enriches the previous research on e-health services by applying and extending PPM framework as the base model and showing its efficiency in predicting individuals switching intentions in the context of emerging economies. This study bridges the gap by focusing on switching behavior in context of health services.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
maomaozi发布了新的文献求助10
刚刚
欢乐佩奇完成签到,获得积分10
1秒前
1秒前
科研通AI5应助ting采纳,获得30
3秒前
悦耳妙旋应助拉总采纳,获得10
3秒前
瘦瘦的铅笔完成签到 ,获得积分10
3秒前
CyberHamster完成签到,获得积分10
3秒前
SY发布了新的文献求助200
3秒前
4秒前
CipherSage应助花开四海采纳,获得10
6秒前
JamesPei应助maomaozi采纳,获得30
6秒前
inter完成签到,获得积分10
7秒前
YOGA完成签到,获得积分10
7秒前
7秒前
上官若男应助怪味痘采纳,获得10
7秒前
8秒前
CA完成签到,获得积分10
9秒前
LinYX完成签到,获得积分10
10秒前
10秒前
盛夏完成签到,获得积分10
10秒前
zyy完成签到,获得积分10
12秒前
ccc发布了新的文献求助20
13秒前
ahsisalah完成签到,获得积分10
13秒前
希望天下0贩的0应助熊二采纳,获得10
13秒前
14秒前
墨与笙完成签到,获得积分10
15秒前
Jasper应助A宇采纳,获得10
16秒前
maomaozi完成签到,获得积分20
17秒前
19秒前
guoguo发布了新的文献求助10
19秒前
sunidea完成签到,获得积分10
19秒前
桐桐应助lbc采纳,获得10
20秒前
20秒前
21秒前
申燕婷完成签到,获得积分10
21秒前
陈晓迪1992发布了新的文献求助10
22秒前
22222完成签到,获得积分10
23秒前
CIOOICO1发布了新的文献求助10
23秒前
23秒前
23秒前
高分求助中
Applied Survey Data Analysis (第三版, 2025) 800
Assessing and Diagnosing Young Children with Neurodevelopmental Disorders (2nd Edition) 700
Images that translate 500
Algorithmic Mathematics in Machine Learning 500
Handbook of Innovations in Political Psychology 400
Mapping the Stars: Celebrity, Metonymy, and the Networked Politics of Identity 400
Nucleophilic substitution in azasydnone-modified dinitroanisoles 300
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3842227
求助须知:如何正确求助?哪些是违规求助? 3384315
关于积分的说明 10534047
捐赠科研通 3104710
什么是DOI,文献DOI怎么找? 1709789
邀请新用户注册赠送积分活动 823323
科研通“疑难数据库(出版商)”最低求助积分说明 774034