What Drives Volunteers to Accept a Digital Platform That Supports NGO Projects?

Antecedents of physicians' intentions to engage in digital volunteering work: an extended technology acceptance model (TAM) approach

Purpose

The digitalization has changed the volunteer paradigm, making young volunteers use technology in their volunteering activities. The current study sets out to identify and model the antecedents that determine intention to engage in digital health volunteering among Algerian physicians to give insights promoting the development of digital volunteering in different countries of the world.

Design/methodology/approach

To this end, the authors used a survey design to extend the technology acceptance model (TAM) with two construct (self-efficacy and perceived risk of COVID-19 infection). A convenience sample of 163 physicians; working in the private and public sectors in six provinces of Algeria was selected. The data were analyzed through a multiple linear regression.

Findings

The findings show that the perceived usefulness, ease of use, attitudes toward digital volunteering, level of self-efficacy and perceived risk of COVID-19 infection have a significant positive effect on physicians' intentions to engage in digital volunteering work in the context of health crises.

Practical implications

This study reveals that engaging in digital volunteering can be promoted during health crises as an effective strategy to provide support and assist public health institutions and emergency management.

Originality/value

To the best of the authors' knowledge, this is the first study from Africa that explores digital volunteer work, and the first study that extends the TAM to investigate digital volunteer intention among physicians.

Community-Based Response to the COVID-19 Pandemic: Case Study of a Home Isolation centre using Flexible Surge Capacity

Objectives

Coronavirus disease 2019 (COVID-19) has consumed many available resources within contingency plans, necessitating new capacity surges and novel approaches. This study aimed to explore the possibility of implementing the concept of flexible surge capacity to reduce the burden on hospitals by focussing on community resources to develop home isolation centres in Bangkok, Thailand.

Study design

A qualitative study consisted of observational and semi-structured interview data.

Methods

The development and activities of home isolation centres were observed, and interviews were conducted with leaders and operational workforces. Data were deductively analysed and categorised based on the practical elements necessary in disaster and emergency management.

Results

Data were categorised into the seven collaborative elements of the major incident medical management and support model. The command-and-control category demonstrated four subcategories: (1) coordination and collaboration; (2) staff engagement; (3) responsibility clarification; and (4) sustainability. Safety presented two subcategories: (1) patients' information privacy and treatment; and (2) personnel safety and privacy. Communication showed internal and external communications subcategories. Assessment, triage, treatment and transport followed the processes of the COVID-19 treatment protocols according to the World Health Organisation (WHO) guidelines and hospital operations. Several supply- and patient-related challenges were identified and managed during centre development.

Conclusions

The use of community resources, based on the flexible surge capacity concept, is feasible under restricted circumstances and reduced the burden on hospitals during the COVID-19 pandemic. Continuous education among multidisciplinary volunteer teams facilitated their full participation and engagement. The concept of flexible surge capacity may promote an alternative community-based care opportunity, irrespective of emergencies' aetiology.

Examining the Prediction of COVID-19 Contact-Tracing App Adoption Using an Integrated Model and Hybrid Approach Analysis

COVID-19 contact-tracing applications (CTAs) offer enormous potential to mitigate the surge of positive coronavirus cases, thus helping stakeholders to monitor high-risk areas. The Kingdom of Saudi Arabia (KSA) is among the countries that have developed a CTA known as the Tawakkalna application, to manage the spread of COVID-19. Thus, this study aimed to examine and predict the factors affecting the adoption of Tawakkalna CTA. An integrated model which comprises the technology acceptance model (TAM), privacy calculus theory (PCT), and task-technology fit (TTF) model was hypothesized. The model is used to understand better behavioral intention toward using the Tawakkalna mobile CTA. This study performed structural equation modeling (SEM) analysis as well as artificial neural network (ANN) analysis to validate the model, using survey data from 309 users of CTAs in the Kingdom of Saudi Arabia. The findings revealed that perceived ease of use and usefulness has positively and significantly impacted the behavioral intention of Tawakkalna mobile CTA. Similarly, task features and mobility positively and significantly influence task-technology fit, and significantly affect the behavioral intention of the CTA. However, the privacy risk, social concerns, and perceived benefits of social interaction are not significant factors. The findings provide adequate knowledge of the relative impact of key predictors of the behavioral intention of the Tawakkalna contact-tracing app.

Improving the Sustainable Usage Intention of Mobile Payments: Extended Unified Theory of Acceptance and Use of Technology Model Combined With the Information System Success Model and Initial Trust Model

Under the background of global cross-border mobile commerce (m-commerce) integration, the importance of cross-border payment research is becoming increasingly prominent and urgent. The important value of this study is to empirically research the influence power of key elements in using two different mobile payment (m-payment) platforms in Korea. The extended unified theory of acceptance and use of technology (UTAUT2) has been widely applied in various studies because of its strong interpretive power. In Korea, there are a few empirical studies on Chinese users. Based on a survey of 908 Chinese participants (486 WeChat Pay's Chinese users and 465 Kakao Pay's Korean users) in Korea, this study is one application extending UTAUT2 by incorporating multi-group and multi-model constructs: UTAUT2, information system success (ISS) model, and an initial trust model (ITM), considering a multi-group analysis with some mediating variables (payment difference). By comparing the two different payment platforms' characters, this manuscript provides a set of targeted measures to ensure Chinese WeChat Payment platform decision-makers create effective long-term strategic policies for cross-border m-payments in Korea, and eventually, benefit cross-border m-commerce and economic cooperation in Southeast Asia.

Judgments in the Sharing Economy: The Effect of User-Generated Trust and Reputation Information on Decision-Making Accuracy and Bias

The growing ecosystem of peer-to-peer enterprise - the Sharing Economy (SE) - has brought with it a substantial change in how we access and provide goods and services. Within the SE, individuals make decisions based mainly on user-generated trust and reputation information (TRI). Recent research indicates that the use of such information tends to produce a positivity bias in the perceived trustworthiness of fellow users. Across two experimental studies performed on an artificial SE accommodation platform, we test whether users' judgments can be accurate when presented with diagnostic information relating to the quality of the profiles they see or if these overly positive perceptions persist. In study 1, we find that users are quite accurate overall (70%) at determining the quality of a profile, both when presented with full profiles or with profiles where they selected three TRI elements they considered useful for their decision-making. However, users tended to exhibit an "upward quality bias" when making errors. In study 2, we leveraged patterns of frequently vs. infrequently selected TRI elements to understand whether users have insights into which are more diagnostic and find that presenting frequently selected TRI elements improved users' accuracy. Overall, our studies demonstrate that - positivity bias notwithstanding - users can be remarkably accurate in their online SE judgments.

An Exploratory Approach to the Adoption Process of Bitcoin by Business Executives

The purpose of this research study is to analyze the exploratory study of the adoption of Bitcoin cryptocurrency based on blockchain technology and its use as a means of payment in companies. This research is exploratory in nature. As such, an adoption model was investigated using the technology acceptance model (TAM) which was extended with new variables. The sample was made up of business executives from companies and commercial establishments (n = 248). Partial least squares structural equation modeling (PLS-SEM) was chosen as the analysis and evaluation technique for the model. The authors demonstrated that privacy has an important influence on perceived utility, and that trust has a very significant influence on privacy and perceived ease of use, thus indirectly affecting the intention to use cryptocurrencies.

Researching COVID-19 tracing app acceptance: incorporating theory from the technological acceptance model

BACKGROUND

The expansion of the coronavirus pandemic and the extraordinary confinement measures imposed by governments have caused an unprecedented intense and rapid contraction of the global economy. In order to revive the economy, people must be able to move safely, which means that governments must be able to quickly detect positive cases and track their potential contacts. Different alternatives have been suggested for carrying out this tracking process, one of which uses a mobile APP which has already been shown to be an effective method in some countries.

OBJECTIVE

Use an extended Technology Acceptance Model (TAM) model to investigate whether citizens would be willing to accept and adopt a mobile application that indicates if they have been in contact with people infected with COVID-19. Research Methodology: A survey method was used and the information from 482 of these questionnaires was analyzed using Partial Least Squares-Structural Equation Modelling.

RESULTS

The results show that the Intention to Use this app would be determined by the Perceived Utility of the app and that any user apprehension about possible loss of privacy would not be a significant handicap. When having to choose between health and privacy, users choose health.

CONCLUSIONS

This study shows that the extended TAM model which was used has a high explanatory power. Users believe that the APP is useful (especially users who studied in higher education), that it is easy to use, and that it is not a cause of concern for privacy. The highest acceptance of the app is found in over 35 years old's, which is the group that is most aware of the possibility of being affected by COVID-19. The information is unbelievably valuable for developers and governments as users would be willing to use the APP.

Exploring the Novel Input Attributes Affecting eWOM

Electronic word of mouth (eWOM) has become significantly important in online communities, which are influential sources of instant information on the internet. This study examines the eWOM input attributes linked to consumers’ information adoption behavior in the context of information-related interaction. This study uses a structural equation modeling approach by choosing participants from Fujian and Guangdong provinces of China. The results reveal that eWOM input attributes studied positively influence information-related interactions. An individual’s perception of value enhances the performance of products or services, which is an essential predictor of information adoption. Furthermore, information usefulness and related interactions are key eWOM message characteristics affecting information adoption on the internet. This study contributes to the eWOM input attributes and message characteristics literature by exploring information-related interaction as a new mediator to consumers’ online information adoption. The authors provide suggestions for marketers and firms to dynamically develop strategies in response to consumers’ concerns while making a purchase online.