An empirical investigation of patients’ acceptance and resistance toward the health cloud: The dual factor perspective

Hsieh, Pi-Jung

doi:10.1016/j.chb.2016.06.029

Cited by 81 publications

(51 citation statements)

References 47 publications

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“…Una teoría empleada para explicar la forma en la que el uso de un sistema de información (SI) impacta las percepciones e intenciones vinculadas a uno nuevo es la tendencia al statu quo (SQB), que analiza el impacto que supone mantener la situación actual traducida en percepciones inhibidoras del uso de un nuevo SI (Hsieh, 2016;Kahneman et al, 1991). La SQB se apoya en argumentaciones teóricas, dependientes del contexto, relativas a los motivos por los que los individuos toman decisiones que los llevan a mantener un determinado curso de acción, más que cambiar a un nuevo, aunque pueda llegar a ser potencialmente superior (Polites y Karahanna, 2012;Wang et al, 2013).…”

Section: La Administración Pública Comportamental La Tendencia Al Stunclassified

“…El hábito se constituye en una fuente inconsciente de inercia (Ng y Kwahk, 2010;Polites y Karahanna, 2012), afirmándose que los consumidores continúan haciendo algo debido a la inercia resultante del hábito (Khedhaouria et al, 2016). La resistencia viene determinada por el compromiso psicológico, por la toma de decisión racional y por la ausencia de percepción cognitiva, entre cuyos componentes se encuentra la inercia, considerándose que la inercia tiene un efecto positivo en la resistencia (Hsieh, 2016;Hsieh y Lin, 2017). Es por lo expuesto que planteamos las siguientes hipótesis:…”

Section: Modelo De Investigación E Hipótesisunclassified

“…Entre los determinantes de la intención de continuación de un SI se han identificado el hábito, la inercia y la resistencia (Khedhaouria et al, 2016;Kim y Gupta, 2012;Hsieh, 2016;Hsieh y Lin, 2017). Los individuos guiados por la inercia evitan la búsqueda de la variedad, pudiendo convertirse en una aversión a la innovación, incluso ante mejores alternativas.…”

Section: Modelo De Investigación E Hipótesisunclassified

“…La inercia es un determinante inconsciente de la intención de continuar, una manifestación de la tendencia al statu quo (Khedhaouria et al, 2016;Kim y Gupta, 2012). No obstante, en ocasiones se indica que la relación entre inercia e intención de uso es inversa (Hsieh, 2016;Hsieh y Lin, 2017). La resistencia puede presentar diversos resultados, entre ellos una mayor búsqueda de información, posponer el uso o bien oponerse a la innovación (Patsiotis et al, 2013).…”

Section: Modelo De Investigación E Hipótesisunclassified

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Sesgos cognitivos y uso del e-gobierno. Una perspectiva conductual

Molina

Moreno

González

et al. 2018

GAPP

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El e-gobierno se presenta como una herramienta al servicio de la mejora de la eficacia y eficiencia en la prestación de los servicios públicos. Pero, pese a los esfuerzos por lograr una adopción generalizada del e-gobierno, éste presenta unas tasas de uso inferiores a las anheladas. Si bien dicho fenómeno ha sido estudiado desde diferentes perspectivas, en el presente trabajo se presenta la perspectiva conductual como enfoque que responda a tal reto. Para ello, se analiza la relación entre diferentes sesgos cognitivos vinculados a la tendencia del statu quo (hábito, inercia y resistencia) con la intención (de uso para los usuarios y de continuación para los usuarios). Los datos fueron captados tras un trabajo cualitativo (dos sesiones de grupo) y un trabajo cuantitativo (923 cuestionarios), dirigido a dos muestras diferentes de ciudadanos (no-usuarios y usuarios del e-gobierno). Los resultados constatan la presencia de la tendencia al statu quo en el uso del e-gobierno. Mientras en el caso de los no-usuarios del e-gobierno se encuentran presentes los sesgos cognitivos analizados, llevando a dilatar su uso, entre los usuarios del e-gobierno carece de relevancia el hábito, por lo que se mantienen en su uso como canal de acceso a los servicios públicos.

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Section: La Administración Pública Comportamental La Tendencia Al Stunclassified

Section: Modelo De Investigación E Hipótesisunclassified

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Sesgos cognitivos y uso del e-gobierno. Una perspectiva conductual

Molina

Moreno

González

et al. 2018

GAPP

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“…Perceived usefulness measures the performance of specific technology in prompting people to act, whereas perceived ease of use indicates the degree of difficulty in using specific technology. Scholars have subsequently verified the effectiveness of this model [56], and the influence of perceived usefulness and perceived ease of use on the adoption of mobile health care have been demonstrated in numerous studies [38,57]. Therefore, the technological dimension of this study involves usefulness and ease of use.…”

Section: Analysis Of the Characteristics And Adoption Of Mobile Healtmentioning

confidence: 99%

Key Influence Factors of Consumers� Intentions Towards Mobile Health Care Promotion: An Empirical Study Based on the DDANPMV Model

Liu¹,

Yang²,

Liu³

et al. 2017

Preprint

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IntroductionMobile health care is an important aspect of electronic medicine that involves using mobile devices (e.g., mobile phones, tablet computers, and personal digital assistants) to provide medical services and health information to patients [1]. Health care faces numerous problems, including high medical costs, restricted coverage, complex medical procedures, and uneven distribution of resources [2]. Mobile health care can help to reduce medical costs and waiting times and improve the efficiency of medical resources use [3]. Mobile health care involves the following categories [4]: (1) Mobile phone applications such as Chun Yu Yi Sheng, which acts as an information exchange platform linking doctors and patients, and comprehensive mobile health care platforms that hospital service providers can apply for appointment registrations, payments, and medical alerts. (2) The collection of users' medical data through wearable devices or mobile intelligent terminals for health monitoring. For example, Kangkang launched a portable intelligent sphygmomanometer that can dynamically monitor blood pressure over a 24-hour period and automatically send data to a corresponding server. Users can view their 24-hour blood pressure analysis report through WeChat. (3) Diagnosis systems that connect with the Internet of Things (IoT). For example, an integrated diagnosis system developed by German researchers can transmit medical data to smart phones through Bluetooth technology. Smartphones applications can then process these data for reference and diagnosis.With the development of mobile networks, many countries have entered the 4G era and benefit from continuously improving mobile communication networks and innovation in software and hardware technology. Abstract: Identifying the key influence factors of mobile health care adoption is a key issue. We established an evaluation index system for consumer adoption and verified the effectiveness of our model by using a DDANPMV model. This model comprises three parts: (1) the decision making trial and evaluation laboratory (DEMATEL) technique, which is used to establish an influence network relationship map at both the "dimensions" and "criteria" levels; (2) a DEMATEL-based analytic network process (ANP; DANP), which determines the interrelationships and influential weights among the criteria; and (3) a modified VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, which applies the influence weights obtained through DANP to performance gaps regarding consumer perception. VIKOR thereby evaluates and improves performance gaps with the aims of satisfying consumer needs, achieving continuous improvement, and enabling sustainable product development. The main innovation of this method is the construction of the DDANPMV model, which integrates the DEMATEL, DANP, and modified VIKOR approaches to examine consumers' adoption of mobile health care. This method was developed to not only help decision-makers evaluate alternative mobile health care and determine the best option b...

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The paradox of technology: Negativity bias in consumer adoption of innovative technologies

Frank

Chrysochou

Mitkidis

2022

Psychology and Marketing

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Innovative technologies often feature inherently conflicting properties. This poses a challenge for marketers because negative properties not only weigh heavily on consumers' technology adoption decisions but potentially do more so than positive ones. To shed light on the paradox of technology and its underlying processes, the present research develops a conceptual model drawing on technology adoption and valence perception theories about the prevalence of negativity bias in consumers' technology adoption decisions with its unique effect through the serial chain of consumers' perceptions of risk and trust regarding the technology. Results of three studies (N = 1309) demonstrate that the effect of negative valence consistently outperforms that of positive valence in consumers' technology adoption intentions (Studies 1–2) and decisions (Study 3). Furthermore, results show that the disproportionate effect of negative (vs. positive) valence can be explained by the proposed serial causal chain through consumers' perception of risk of the technology and trust in the technology (Studies 2–3) while ruling out company trust and consumer knowledge as alternative drivers of the effects (Study 3). These findings contribute to the pertinent literature on consumer psychology in decisions to adopt novel technologies in that they quantify and explain the potential outcome stemming from the ambiguous properties of novel technology. Moreover, this study finds negativity bias to be an often overlooked consumer bias with implications for marketing practice and useful for understanding and lowering resistance towards artificial intelligence technology.

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An empirical investigation of patients’ acceptance and resistance toward the health cloud: The dual factor perspective

Cited by 81 publications

References 47 publications

Sesgos cognitivos y uso del e-gobierno. Una perspectiva conductual

Sesgos cognitivos y uso del e-gobierno. Una perspectiva conductual

Key Influence Factors of Consumers� Intentions Towards Mobile Health Care Promotion: An Empirical Study Based on the DDANPMV Model

The paradox of technology: Negativity bias in consumer adoption of innovative technologies

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