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This paper aims to examine the optimal promotion strategy of an e-retailer, who may advertise, or launch rebates initiative to encourage consumers' disseminating electronic word-of-mouth (eWOM) messages, with an aim to boost product sales.

This paper analyzes the decisions of the e-retailer in a two-period model, using utility function approach and backward induction method, and obtains the optimal solutions in four promotion strategies.

The study finds that rebate scheme greatly impacts the timing of advertising, and neither lower nor higher consumers' eWOM effort invariably benefits the retailer, rather, a medium level is the best choice for the retailer. When eWOM impact power is at a relatively high level, it can supplement advertising effect to attract more consumers' purchase. Otherwise, eWOM may counteract the role of advertising.

Different from the extant literature focusing on advertising or eWOM without rebates, the paper studies the issue of advertising and eWOM with rebates in two- period model which seldom addresses before the authors examine the optimal timing of advertising and eWOM with/without rebates in four promotion strategies i.e. the A-NE model the NE-A model the A-ER model and the ER-A model.

This paper aims to examine the determinants that influence acceptance towards e-wallet apps by extending the technology acceptance model (TAM) among (asnaf), a term used for charity or gift receivers from alms tax distribution institutions also known as donee.

The review of literature and structural equation modelling approach using judgemental sampling on extended TAM and determinants of e-wallet apps’ acceptance related to asnaf (donee) were conducted in a bid to contribute to the factors that are instrumental in determining acceptance of e-wallet services among asnaf.

The findings indicate that the e-wallet app’s service acceptance is determined not only by perceived usefulness, consumer maqasid index and consumer innovativeness but also by subjective norms. On the contrary, consumer maqasid index and perceived ease of use do not lend themselves to be the factor of asnafs’ e-wallet acceptance. The authors extend the TAM model to determine the factors that may be influential in predicting the e-wallet app acceptance by asnaf.

In assessing future outcomes when different sampling techniques are opted for and geographic coverage is expanded, this study should be considered in terms of the limited scope.

This study is intended to serve as a reference for making a significant contribution related to user acceptance factors related to alms tax-based e-wallet apps in asnafs’ context in Malaysia in terms of both theory and practice.

TAM is extended in the context of e-wallet app acceptance among asnafs’. A variable, namely, consumer innovativeness, is tested using the extended TAM model. To the best of the authors’ knowledge, consumer innovativeness in the context of asnafs’ acceptance of e-wallet apps is yet to be tested. Therefore, this paper will be a useful reference for policymakers, technologists, academicians and future researchers.

Blockchain’s potential is so significant that business activities across all industries can be drastically altered. Furthermore, the characteristics of blockchain appear to be well-suited to accounting requirements. However, accounting professionals’ attitude and intention toward blockchain adoption are not clear, particularly in India. Thus, this study aims to investigate and evaluate accountants’ intention to adopt blockchain technology in accounting activities.

This study examined and assessed accountants’ intention to use blockchain in accounting. To effectively measure usage intention, this study extended the unified theory of acceptance and use of technology (UTAUT) model by including context-specific constructs. To empirically test and validate the proposed model, data were collected from “369” professional accountants in India.

The findings revealed that facilitating conditions, performance expectancy and initial trust had a significant impact on adoption. Furthermore, the regulatory framework materially moderated the association between usage intention and its predictors.

These findings provide new empirical evidence about the impact of different predictors of usage intention by extending the UTAUT model. Relevant stakeholders can refer to this pioneering study to increase the adoption of blockchain as an efficient and trustworthy system among professional accountants, particularly in developing countries such as India.

This study aims to identify the factors influencing cashless transactions toward digital payment systems using the extended UTAUT model in developing countries. This model was extended with perceived usefulness, perceived ease of use, facilitating conditions, perceived security/trust and social influence for assessing consumer behavior toward cashless transactions.

Using structural equation modeling (SEM), this study conducted a cross-sectional survey to collect data, providing a snapshot of the relationship between exogenous and endogenous variables.

The results of the study indicate that perceived usefulness, facilitating conditions, perceived trust/security and social influence have a significant influence on consumer intentions toward cashless transactions. Oppositely, leaving the perceived ease of use has no significant influence on consumer intentions toward the usage of cashless transactions.

The contribution of this study is to extend the UTAUT model for adopting cashless transactions in developing countries that will help government agencies, service providers and financial institutions design effective strategies in the future.

Several waste bin sanitation initiatives have been introduced in Ghana to address the surge in indiscriminate solid waste disposal in households. What is not known are the behavior factors that determine the acceptability and use of waste bins. This study aimed to identify the determinants of waste bin acceptability and use in Ghana using the theory of planned behavior (TPB).

Data on waste bin acceptability and usage were collected from 881 households in the Volta and Oti regions of Ghana. The data were analyzed using the partial least squares-structural equation modeling technique in SmartPLS 3 software.

The coefficient of determination (R-squared value) of the original TPB and the extended model explained 39.9 and 44.7% of the variance in waste bin acceptability and use intentions, respectively. The results revealed that attitudes (ß = 0.114, t = 3.322, p < 0.001), subjective norms (ß = 0.306, t = 6.979, p < 0.001) and perceived moral obligation (ß = 0.352, t = 8.062, p < 0.001) significantly predicted household waste bin acceptability and use behavior intentions, but perceived behavioral control (ß = −0.003, t = 0.064, p < 0.949) did not influence behavior intentions significantly.

The study provides valuable insights into the behavioral factors to be prioritized by waste management service providers to improve household waste bin acceptability and usage.

This is one of Ghana's first studies investigating the behavioral determinants of waste bin acceptability and usage.

Social interaction in comment sections has become a key factor for backers' decision making in crowdfunding platforms. However, current research on the two-way social interaction in crowdfunding is insufficient, and there exist inconsistent conclusions. This study focuses on the social interaction between creators and backers and explores its influence on the successful exit of crowdfunding projects.

The extended Cox model is used for the empirical analysis of 1,988 crowdfunding projects on the Modian (www.modian.com) platform, a crowdfunding platform for cultural and creative projects in China. The two-way social interaction is reflected in comment quantity and sentiment, as well as reply rate.

Results reveal an inverted U-shaped relationship between comment quantity/sentiment and the successful exit of crowdfunding projects. This relationship is strengthened by high reply rate.

This study focuses on comment quantity and sentiment. The inverted U-shaped results reconcile previous conclusions. Replies from creators are regarded as a separate factor, and their moderating role is explained. The study research proves the importance of social interaction in crowdfunding platforms and provides suggestions for backers, creators and platform managers.

Reservation of travel and leisure services through the digital environment has gained a growing role in society, influencing the revolution of the sector. It needs to be noted that there is a considerable lack of formal approaches to the identification of factors for the positive reception and use of these digital tools. For this reason, it is necessary to establish the main factors influencing the adoption and use of digital travel and restaurant platforms (TRPs), adding to the theoretical model two new factors: trust and word-of-mouth (WOM). This paper aims to discuss the aforementioned ideas.

A theoretical model has been proposed, based on the extended unified theory of acceptance and use of technology (UTAUT2). Data collection was conducted through an online survey, in which 331 responses were compiled. Data obtained were analysed using structural equation modelling (SEM) with AMOS v27 software.

The results show that performance expectancy and WOM have a significant impact on the adoption of TRPs. However, it was found that effort expectancy, social influence, facilitating conditions, trust and price/value are not significant variables.

This research confirms that WOM communication positively influences the use of TRPs, facilitating various aspects for restaurant customers, including reducing wait times, streamlining the ordering process for allergic and intolerant customers, enhancing loyalty programs, order management and the opportunity to provide a personalised experience.

This study is the first to incorporate WOM variable into the extended UTAUT2 model applied to TRPs. Through a literature review, it has paved the way for significant future research directions that have not been adequately addressed by the scientific community, including the adoption and usage of food delivery platforms and online review platforms, as well as the behaviour of disabled customers towards these platforms.

This study aims to use the extended model of goal-directed behavior (EMGB) to examine the interaction between wine purchasing motivations and prior knowledge and their impact on consumers’ wine purchase intentions and decisions.

The survey was conducted in large discount retail stores in South Korea, and structural equation modeling analysis reveals EMGB’s strong predictive ability to understand wine buying behavior.

Notably, the findings reveal that social life and enjoyment motivations play a significant role in shaping consumers' attitudes. In addition, positive emotions, attitudes, prior knowledge, subjective norms and negative anticipated emotions all have a positive effect on desire, while desire, prior knowledge and frequency of past behavior have a significant impact on behavioral intention. Contrary to previous studies, celebration motivation has no significant effect on attitude and perceived behavioral control has no significant effect on desire and behavioral intention.

The findings provide practical insights for marketers to conduct targeted wine marketing campaigns and increase consumers' intention to purchase wine.

This study furthers the understanding of the complex mechanisms involved in shaping the intention to purchase wine using the EMGB framework.

The purpose of this work is to explore the new possibilities enabled by the recent introduction of RDF-star, an extension that allows for statements about statements within the Resource Description Framework (RDF). Alongside Named Graphs, this approach offers opportunities to leverage a meta-level for data modeling and data applications.

In this extended paper, the authors build onto three modeling use cases published in a previous paper: (1) provide provenance information, (2) maintain backwards compatibility for existing models, and (3) reduce the complexity of a data model. The authors present two scenarios where they implement the use of the meta-level to extend a data model with meta-information.

The authors present three abstract patterns for actively using the meta-level in data modeling. The authors showcase the implementation of the meta-level through two scenarios from our research project: (1) the authors introduce a workflow for triple annotation that uses the meta-level to enable users to comment on individual statements, such as for reporting errors or adding supplementary information. (2) The authors demonstrate how adding meta-information to a data model can accommodate highly specialized data while maintaining the simplicity of the underlying model.

Through the formulation of data modeling patterns with RDF-star and the demonstration of their application in two scenarios, the authors advocate for data modelers to embrace the meta-level.

With RDF-star being a very new extension to RDF, to the best of the authors’ knowledge, they are among the first to relate it to other meta-level approaches and demonstrate its application in real-world scenarios.

Promoting the adoption of digital payments by the elderly plays an important role in the development of the digital economy. The purpose of this study is to build an extended theory of planned behavior (TPB) model to predict the elderly's intention to pay for digital services under COVID-19 epidemic constraints.

Based on the extended TPB model, 320 qualified participants were recruited on the network. The structural equation model was tested using the SmartPLS3.3 tool, and the moderation effects were tested through SPSS26 and the Process macro.

The results showed that the three dimensions of TPB theory, the basic elements (perceived value and perceived risk), and the external environment (COVID-19 pandemic) were important factors that influence the elderly users' intention to adopt digital payments. Further research found that motivation factors (personal innovativeness, intergenerational support, and social support) can positively moderate these effects.

The results of the study provide a further explanation for understanding the willingness of elderly people to adopt digital payments during the COVID-19 pandemic and bring inspiration to system developers and social managers to reduce the risk of COVID-19 pandemic and increase the share of digital payments for this category.

This paper used the extended TPB theory to construct a fundamental environmental motivation (FEM) framework for understanding the main influencing factors of elderly users' intention to adopt digital payments during the COVID-19 pandemic.