Effects of technology readiness on behavioral intention toward technology-based self-service: comparison of superiority of construct and measurement model for technology readiness

2019 ◽  
Vol 81 ◽  
pp. 275-289
Author(s):  
Hyeyoung Moon ◽  
Hye-Sun Moon
Keyword(s):  
Behavioral Intention ◽  
Measurement Model ◽  
Technology Readiness ◽  
Self Service

Measuring Self-Service Technology Latent Difficulties: Insurance Decisions on Utilitarian and Hedonic Influences

2015 ◽  
Vol 9 (1) ◽  
pp. 1-33 ◽  
Author(s):  
Ann Shawing Yang
Keyword(s):  
Measurement Model ◽  
Rasch Measurement ◽  
High Income ◽  
Middle Aged ◽  
Rasch Measurement Model ◽  
Expectation Disconfirmation ◽  
Self Service ◽  
Self Service Technology ◽  
Insurance Decisions

AbstractThis study investigates the difficulties encountered by consumers in forming insurance decisions when using self-service technology (SST) channels, such as electronic insurance. Rasch measurement model is applied. This model employs the expectation disconfirmation theory to categorize and rank the order of importance of latent utilitarian and hedonic insurance purchase motives. Consumers find that electronic insurance has high risks and high premiums with respect to utilitarian motives but lacks information and performs unsatisfactorily in terms of hedonic motives. Nevertheless, electronic insurance is preferred for the convenience brought by SST channels, and because it provides greater discounts and offers product–channel matching through self-consultation in the absence of agents. Being middle-aged and having a high income are factors that significantly influence electronic insurance purchases.

scholarly journals Technology Readiness and Likelihood to Use Self-Checkout Services Using Smartphone in Retail Grocery Stores: Empirical Evidences from Hyderabad, India

2018 ◽  
Vol 7 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Hory Sankar Mukerjee ◽  
G. K. Deshmukh ◽  
U. Devi Prasad
Keyword(s):  
Mobile App ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Technology Readiness ◽  
Grocery Stores ◽  
Perceived Ease Of Use ◽  
Self Service ◽  
Positive Correlations ◽  
Self Service Technology ◽  
Retail Grocery

Present study is an attempt to measure technology readiness of Indian customers towards self checkout service (SCS) through mobile app at retail stores at Hyderabad, India. Self-checkout services (SCS), a key offering of self service technology (SST), ‘is the technological enablement of customers to make payments and complete a checkout, after shopping, with little or no interaction with a service employee.’ Researchers also studied correlations between technology readiness, perceived usefulness, perceived ease of use, and likelihood to use SCS. For the purpose of the study TRI 2.0 developed by Parasuraman and Colby (2015) was used along with items of perceived usefulness and perceived ease of use, adapted from Davis (1989) , and items of ‘likelihood to use’ adapted from Bitner, Ostrom and Meuter (2002) . The findings of the study reveal that respondents’ technology readiness was moderate with respect to mobile based SCS. Significant positive correlations were found between: technology readiness and perceived ease of use, perceived ease of use and perceived usefulness, perceived ease of use and likelihood to use, perceived usefulness and likelihood to use. Further the respondents were categorised in to five technology segments as sceptics, explorers, pioneers, avoiders and hesitators.

User Behavioral Intention toward Using Mobile Healthcare System

2015 ◽  
pp. 128-143 ◽  
Author(s):  
Pantea Keikhosrokiani ◽  
Norlia Mustaffa ◽  
Nasriah Zakaria ◽  
Ahmad Suhaimi Baharudin
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Healthcare System ◽  
Behavioral Intention ◽  
Measurement Model ◽  
Healthcare Systems ◽  
Intention To Use ◽  
Mobile Healthcare ◽  
Effort Expectancy ◽  
Behavioral Intention To Use

This chapter introduces Mobile Healthcare Systems (MHS) and employs some theories to explore the behavioral intention of Smartphone users in Penang, Malaysia to use MHS. A survey was conducted in the form of questionnaire to Smartphone users in Penang, Malaysia for the duration of three weeks starting in September 2013. A total number of 123 valid surveys out of 150 were returned, which is equivalent to a response rate of 82%. The authors use Partial Least Squares (PLS) for analyzing the proposed measurement model. The factors that are tested are self-efficacy, anxiety, effort expectancy, performance expectancy, attitude, and behavioral intention to use. The results indicate which factors have a significant effect on Smartphone users' behavioral intention and which factors are not significant. The results assist in assessing whether MHS is highly demanded by users or not, and will assist in development of the system in the future.

scholarly journals Social Image Impacting Attitudes of Middle-Aged and Elderly People toward the Usage of Walking Aids: An Empirical Investigation in Taiwan

Healthcare ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 543
Author(s):  
Shao-Wei Huang ◽  
Tsen-Yao Chang
Keyword(s):  
Elderly People ◽  
Behavioral Intention ◽  
Structural Equation ◽  
Positive Impact ◽  
Measurement Model ◽  
Subjective Norms ◽  
Model Verification ◽  
Middle Aged ◽  
Social Image ◽  
Walking Aids

The elderly need the assistance of walking aids due to deterioration of their physical functions. However, they are often less willing to use these aids because of their worries about how others may think of them. Not using professional walking aids often makes elderly people fall easily when walking. This study explores the behavioral intention factors of middle-aged people (45–64 years old) and elderly people (65 years and older) that affect the use of walking aids. Based on the Theory of Reasoned Action (TRA), subjective norms, attitude toward usage, behavior intention, safety, and usefulness were combined with social image to establish the research framework. This study used questionnaire surveys both in paper form assisted by volunteers and in online electronic form. A total of 457 questionnaires were collected. Data analysis was carried out in three stages: descriptive analysis, measurement model verification, and structural equation model analysis. The results showed that social image had a significant impact on the attitude toward using walking aids. Factors such as attitude toward usage, subjective norms, and safety of walking aids also had a significant positive impact on behavioral intention. Finally, through the research results, some suggestions are proposed for stakeholders to improve the elderly’s concerns about the social image of using walking aids.

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