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This study aims to analyze the motivations underlying information usefulness, attitude and acceptance of health information related to coronavirus disease 2019 (COVID-19) avoidance based on the information acceptance model (IAM) and the elaboration likelihood model (ELM).

This study conducted a quantitative approach using survey that generated 364 valid responses. Structural equation modeling was applied to analyze the data and evaluate the hypotheses.

The results of this study showed that the determinants of information usefulness are argument quality (comprising accuracy and timeliness) and peripheral route (comprising credibility and relevance), whereas no significant relationship was found between completeness and information quantity and information usefulness. Further analysis indicated that attitude and information usefulness significantly affect health information acceptance to COVID-19 avoidance.

Using ELM and IAM, an explanation of health information acceptance in the salient pandemic context was given. This study contributed to the current literature by offering insights into attitude and information usefulness for information acceptance. The validation of the model was strengthened by identifying the effects of argument quality and peripheral route attributes on information usefulness, which is stated to make contributions to the earlier literature.

Practitioners should strive to understand the facilitators regarding argument quality and peripheral routes to broaden information usefulness. The findings of this study are helpful for practitioners to implement communication campaigns that foster attitude and health information acceptance in the COVID-19 pandemic as well as in similar disease situations.

This study provides individuals and organizations with necessary information about the importance of mobile applications (m-applications) in distributing online information and about reliable guidelines for the implementation of disease avoidance to improve their health status.

Existing studies investigated users’ health information acceptance in some contexts related to general disease, but less is known about this behavior among young individuals via m-applications at the moment of COVID-19 and in emerging economies. This study identifies the efforts made by the relationship between information and technological diffusion to help individuals surmount difficulties in times of crisis.

Smart card-based E-payment systems are receiving increasing attention as the number of implementations is witnessed on the rise globally. Understanding of user adoption behavior of E-payment systems that employ smart card technology becomes a research area that is of particular value and interest to both IS researchers and professionals. However, research interest focuses mostly on why a smart card-based E-payment system results in a failure or how the system could have grown into a success. This signals the fact that researchers have not had much opportunity to critically review a smart card-based E-payment system that has gained wide support and overcome the hurdle of critical mass adoption. The Octopus in Hong Kong has provided a rare opportunity for investigating smart card-based E-payment system because of its unprecedented success. This research seeks to thoroughly analyze the Octopus from technology adoption behavior perspectives.

Cultural impacts on adoption behavior are one of the key areas that this research posits to investigate. Since the present research is conducted in Hong Kong where a majority of population is Chinese ethnicity and yet is westernized in a number of aspects, assuming that users in Hong Kong are characterized by eastern or western culture is less useful. Explicit cultural characteristics at individual level are tapped into here instead of applying generalization of cultural beliefs to users to more accurately reflect cultural bias. In this vein, the technology acceptance model (TAM) is adapted, extended, and tested for its applicability cross-culturally in Hong Kong on the Octopus. Four cultural dimensions developed by Hofstede are included in this study, namely uncertainty avoidance, masculinity, individualism, and Confucian Dynamism (long-term orientation), to explore their influence on usage behavior through the mediation of perceived usefulness.

TAM is also integrated with the innovation diffusion theory (IDT) to borrow two constructs in relation to innovative characteristics, namely relative advantage and compatibility, in order to enhance the explanatory power of the proposed research model. Besides, the normative accountability of the research model is strengthened by embracing two social influences, namely subjective norm and image. As the last antecedent to perceived usefulness, prior experience serves to bring in the time variation factor to allow level of prior experience to exert both direct and moderating effects on perceived usefulness.

The resulting research model is analyzed by partial least squares (PLS)-based Structural Equation Modeling (SEM) approach. The research findings reveal that all cultural dimensions demonstrate direct effect on perceived usefulness though the influence of uncertainty avoidance is found marginally significant. Other constructs on innovative characteristics and social influences are validated to be significant as hypothesized. Prior experience does indeed significantly moderate the two influences that perceived usefulness receives from relative advantage and compatibility, respectively. The research model has demonstrated convincing explanatory power and so may be employed for further studies in other contexts. In particular, cultural effects play a key role in contributing to the uniqueness of the model, enabling it to be an effective tool to help critically understand increasingly internationalized IS system development and implementation efforts. This research also suggests several practical implications in view of the findings that could better inform managerial decisions for designing, implementing, or promoting smart card-based E-payment system.

Deepfake information poses more ethical risks than traditional disinformation in terms of fraud, slander, rumors and other malicious uses. However, owing to its high entertainment value, deepfake information with ethical risks has become popular. This study aims to understand the role of ethics and entertainment in the acceptance and regulation of deepfake information.

Mixed methods were used to qualitatively identify ethical concerns and quantitatively evaluate the influence of ethical concerns and perceived enjoyment on the ethical acceptability and social acceptance of deepfake information.

The authors confirmed that informed consent, privacy protection, traceability and non-deception had a significantly positive impact on ethical acceptability and indirectly influenced social acceptance, with privacy protection being the most sensitive. Perceived enjoyment impacts the social acceptance of deepfake information and significantly weakens the effect of ethical acceptability on social acceptance.

The ethical concerns affecting acceptance behavior identified in this study provide an entry point for the ethical regulation of deepfake information. The weakening effect of perceived enjoyment on ethics serves as a wake-up call for regulators to guard against pan-entertainment deepfake information.

The present study addresses acceptance of in vitro meat (IVM) among a predominantly student sample in Germany. It is investigated to which extent food technology neophobia, the currently followed diet and information treatments impact acceptance of IVM measured via the construct willingness to buy (WTB).

A quantitative online-survey was conducted in August 2020 using a between-subject design with three different information treatments and one control group. Moreover, the Food Technology Neophobia (FTN) scale was employed, For the statistical analysis, the χ² and Kruskal–Wallis test were used. Additionally, a binary logit model was specified and estimated in order to investigate the determinants of willingness to buy IVM accounting for the effects of gender, age, vegetarianism/veganism, FTN, prior knowledge, information treatments and potential interaction effects.

Participants following a vegan or vegetarian diet exhibit a lower likelihood of IVM acceptance in comparison to participants following an omnivore diet. However, a considerable share of vegan and vegetarian participants expressed a positive WTB. Moreover, an increasing FTN score (i.e. an increase in food technology neophobia) goes along with a reduced likelihood of acceptance, while all three information treatments increase acceptance in comparison to the control group. The largest effect on acceptance could be found for the environmental benefit treatment.

The findings show that especially among a young and highly educated sample the stressing of environmental benefits of IVM has a substantial impact on acceptance. This might be taken up in information and marketing campaigns once the product becomes available on the European market.

So far the empirical evidence on German consumers' acceptance of IVM is scarce. The present study addressed this research gap by focusing on a young sample with a high percentage of vegetarians and vegans and analyzing the role of food technology neophobia and different information treatments in a between-subject design.

This study applied eye-tracking techniques and questionnaires within the framework of the Stimulus-Organism-Response Model (SOR) and Technology Acceptance Model (TAM), to investigate the influencing factors of the public acceptance of 5G base stations.

This study used a combination of eye-tracking experiments and questionnaires. The data were analyzed using partial least squares structural equation modeling (PLS-SEM).

(1) The Technology Acceptance Model (TAM) could be used to explain the effects on public acceptance of 5G base stations in the context of the COVID-19 pandemic. The public's perceived usefulness and ease of use of 5G base stations positively affects public acceptance of 5G base stations. (2) The public's perceived risk of 5G base stations has a negative influence on the public acceptance of 5G base stations. (3) The public's visual attention to the different valence information about 5G base stations positively impacts the perceived ease of use while having negative impacts on perceived risk. (4) Visual attention to various valence information of 5G base stations can indirectly influence public acceptance through the perceived risk.

Applying the SOR and TAM to data obtained from eye-tracking experiments and questionnaires, this study analyzed the factors and mechanisms influencing public acceptance of 5G base stations in the context of the COVID-19 pandemic.

In light of a growing trend towards mobile information management and a UK governmental drive for police forces to implement mobile technologies and realise significant benefits, it is important to examine the factors affecting officer acceptance. There appears to be little understanding of the key factors, yet this is critical to the success of the initiative. The purpose of this paper is to investigate the main factors that influence the usage of mobile technologies amongst police officers.

A qualitative, partially ethnographic design was followed to allow an in‐depth exploration of this issue. The study was based on a mixed‐methods longitudinal evaluation study of the implementation of mobile technologies within a UK police force over a nine‐month period. The technology acceptance model (TAM) and the subsequent TAM2 and TAM3, were then reengineered to provide a suitable theoretical model for a mobile policing context.

In total, four main categories of officer acceptance factors were identified: officer performance, security/reliability, management style and cognitive acceptance. Evidence from the study showed a key shortfall in all three versions of the TAM in that they focus on the user perspective and did not confirm the broader organisational factors within the implementation and social contexts of mobile policing.

Consequently, an adapted mobile‐TAM (m‐TAM) was produced that incorporated these factors into the existing TAM elements. The high‐level nature of the adapted model for mobile policing means it could be applied by other police forces and potentially other organisations, regardless of the type of mobile device implemented, to address the barriers to acceptance. The m‐TAM addresses the need for a more relevant and robust model to the mobile policing paradigm, which goes beyond the static technology environment in which the TAM2 and TAM3 were built.

Advances in electronic banking technology have created novel ways of handling daily banking affairs, especially via the online banking channel. The acceptance of online banking services has been rapid in many parts of the world, and in the leading e‐banking countries the number of e‐banking contracts has exceeded 50 percent. Investigates online banking acceptance in the light of the traditional technology acceptance model (TAM), which is leveraged into the online environment. On the basis of a focus group interview with banking professionals, TAM literature and e‐banking studies, we develop a model indicating online‐banking acceptance among private banking customers in Finland. The model was tested with a survey sample (n=268). The findings of the study indicate that perceived usefulness and information on online banking on the Web site were the main factors influencing online‐banking acceptance.

This paper seeks to explore factors that can help generate a bigger ripple for diffusive Word‐of‐Mouth (WOM) in an online environment. Specifically, the paper aims to demonstrate how the characteristics of WOM information influence the ripple effect.

The paper used a survey based on real posts in online discussion forums to collect the data. Structural Equation Modelling (SEM) was utilized for analysis.

WOM as diffusive communication could generate a ripple effect. All of the WOM characteristics, which were investigated (quality, authority, authenticity and interestingness), have a positive effect on resenders' acceptance toward WOM, which, in turn, have a significant positive impact on resenders' resending intention. Furthermore, the positive impacts of WOM characteristics on resenders' acceptance exist, regardless of whether the valence of WOM information is positive or negative.

This study provides insights into the role of WOM information in facilitating the WOM ripple effect. However, the specific characteristics of WOM information that influence consumers' perceptions of WOM are not explored in the present research.

The results of the study may help practitioners manipulate and use online WOM information in order to make marketing communications more efficient and influential.

The concept and practice of e-services has become essential in business transactions. Yet there are still many organizations that have not developed e-services optimally. This is especially relevant in the context of Indonesian Airline companies. Therefore, many airline customers in Indonesia are still in doubt about it, or even do not use it. To fill this gap, this study attempts to develop a model for e-services adoption and empirically examines the factors influencing the airlines customers in Indonesia in using e-services offered by the Indonesian airline companies. Taking six Indonesian airline companies as a case example, the study investigated the antecedents of e-services usage of Indonesian airlines. This study further examined the impacts of motivation on customers in using e-services in the Indonesian context. Another important aim of this study was to investigate how ages, experiences and geographical areas moderate effects of e-services usage.

The study adopts a positivist research paradigm with a two-phase sequential mixed method design involving qualitative and quantitative approaches. An initial research model was first developed based on an extensive literature review, by combining acceptance and use of information technology theories, expectancy theory and the inter-organizational system motivation models. A qualitative field study via semi-structured interviews was then conducted to explore the present state among 15 respondents. The results of the interviews were analysed using content analysis yielding the final model of e-services usage. Eighteen antecedent factors hypotheses and three moderating factors hypotheses and 52-item questionnaire were developed. A focus group discussion of five respondents and a pilot study of 59 respondents resulted in final version of the questionnaire.

In the second phase, the main survey was conducted nationally to collect the research data among Indonesian airline customers who had already used Indonesian airline e-services. A total of 819 valid questionnaires were obtained. The data was then analysed using a partial least square (PLS) based structural equation modelling (SEM) technique to produce the contributions of links in the e-services model (22% of all the variances in e-services usage, 37.8% in intention to use, 46.6% in motivation, 39.2% in outcome expectancy, and 37.7% in effort expectancy). Meanwhile, path coefficients and t-values demonstrated various different influences of antecedent factors towards e-services usage. Additionally, a multi-group analysis based on PLS is employed with mixed results. In the final findings, 14 hypotheses were supported and 7 hypotheses were not supported.

The major findings of this study have confirmed that motivation has the strongest contribution in e-services usage. In addition, motivation affects e-services usage both directly and indirectly through intention-to-use. This study provides contributions to the existing knowledge of e-services models, and practical applications of IT usage. Most importantly, an understanding of antecedents of e-services adoption will provide guidelines for stakeholders in developing better e-services and strategies in order to promote and encourage more customers to use e-services. Finally, the accomplishment of this study can be expanded through possible adaptations in other industries and other geographical contexts.

Online ride-hailing platforms match drivers with passengers by receiving ride requests from passengers and forwarding them to the nearest driver. In this context, the low acceptance rate of offers by drivers leads to friction in the process of driver and passenger matching. What policies by the platform may increase the acceptance rate and by how much? What factors influence drivers' decisions to accept or reject offers and how much? Are drivers more likely to turn down a ride offer because they know that by rejecting it, they can quickly receive another offer, or do they reject offers due to the availability of outside options? This paper aims to answer such questions using a novel dataset from Tapsi, a ride-hailing platform located in Iran.

The authors specify a structural discrete dynamic programming model to evaluate how drivers decide whether to accept or reject a ride offer. Using this model, the authors quantitatively measure the effect of different policies that increase the acceptance rate. In this model, drivers compare the value of each ride offer with the value of outside options and the value of waiting for better offers before making a decision. The authors use the simulated method of moments (SMM) method to match the dynamic model with the data from Tapsi and estimate the model's parameters.

The authors find that the low driver acceptance rate is mainly due to the availability of a variety of outside options. Therefore, even hiding information from or imposing fines on drivers who reject ride offers cannot motivate drivers to accept more offers and does not affect drivers' welfare by a large amount. The results show that by hiding the information, the average acceptance rate increases by about 1.81 percentage point; while, it is 4.5 percentage points if there were no outside options. Moreover, results show that the imposition of a 10-min delay penalty increases acceptance rate by only 0.07 percentage points.

To answer the questions of the paper, the authors use a novel and new dataset from a ride-hailing company, Tapsi, located in a Middle East country, Iran and specify a structural discrete dynamic programming model to evaluate how drivers decide whether to accept or reject a ride offer. Using this model, the authors quantitatively measure the effect of different policies that could potentially increase the acceptance rate.