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Artificial intelligence (AI) is experiencing growth and prosperity worldwide because of its convenience and other benefits. However, AI faces challenges related to consumer resistance. Thus, drawing on the user resistance theory, this study explores factors that influence consumers’ resistance to AI and suggests ways to mitigate this negative influence.

This study tested four hypotheses across four studies by conducting lab experiments. Study 1 used a questionnaire to verify the hypothesis that AI’s “substitute” image leads to consumer resistance to AI; Study 2 focused on the role of perceived threat as an underlying driver of resistance to AI. Studies 3–4 provided process evidence by the way of a measured moderator, testing whether AI with servant communication style and literal language style is resisted less.

This study showed that AI’s “substitute” image increased users' resistance to AI. This occurs because the substitute image increases consumers’ perceived threat. The study also found that using servant communication and literal language styles in the interaction between AI and consumers can mitigate the negative effects of AI-substituted images.

This study reveals the mechanism of action between AI image and consumers’ resistance and sheds light on how to choose appropriate image and expression styles for AI products, which is important for lowering consumer resistance to AI.

Virtual reality (VR) offers unprecedented immersion and interactivity in education, and working and learning from home have become the norm during the COVID-19 pandemic. This study empirically investigated the factors affecting the use of a VR online learning system (VROLS).

To explore factors affecting users’ continuance behavioral intentions toward using VROLSs, a research framework was formed comprising factors that constitute benefits (i.e. pull factors) and costs (i.e. push factors); these factors included perceived value, flow and social influence. The data for this study were collected via online survey questionnaires. A total of 307 valid responses were used to examine the hypotheses in the research model, employing structural equation modeling (SEM) techniques.

Perceived value, flow experience and the number of peers using VR primarily affect the decision to adopt a VROLS. The pull factors of spatial presence, entertainment and service compatibility, along with the push factors of complexity and visual fatigue, affect perceived value. Therefore, we conclude that perceived value is a primary factor positively influencing both flow experience and the decision to adopt the service.

This study contributes to a theoretical understanding of factors that explain users’ intention to use VROLSs.

Although extant studies have investigated the antecedents of negative electronic word of mouth (eWOM), they treated it as a unidimensional concept without classification. To bridge this knowledge gap, this paper distinguishes rational negative eWOM (RNW) from emotional negative eWOM (ENW) and leverages the consumer value framework to investigate their drivers in the context of peer-to-peer accommodation platforms (PPAPs).

This study collected data through an online survey of 437 PPAP users. Partial least squares (PLS) were used to validate the proposed hypotheses. Further, the path coefficients comparison method was adopted to distinguish the different impacts of consumer values on RNW and ENW.

This research showed that self-presentation exerted a positive impact on RNW, but its relationship with ENW was insignificant. Anger and regret were, respectively, positively related to ENW and RNW. Besides, altruism exerted a positive effect on RNW, whereas it had a negative effect on ENW.

First, this paper makes a fresh attempt to categorize negative eWOM into RNW and ENW. Second, this paper draws upon the consumer value framework to dissect varied motivations for posting RNW versus ENW on PPAPs. Third, this paper empirically verifies the differential influences that consumer values exert on RNW and ENW.

To assess which partnerships were most critical during the recovery planning process following Hurricanes Maria and Irma. We discuss the roles and impact of different types of partners, barriers and facilitators to partnerships and lessons in collaboration during the development of the economic and disaster recovery plan for Puerto Rico.

The Homeland Security Operational Analysis Center (HSOAC) was tasked with assisting the Puerto Rican government with an assessment of damages from Hurricanes Maria and Irma and the development of the Recovery Plan. During the process, a small team compiled and coded a database of meetings with non-HSOAC partners. The team was divided into sector teams that mirrored FEMA’s Recovery Support Functions. Each sector completed two surveys identifying high impact partners and their roles and contributions, as well as barriers and facilitators to partnerships.

A total of 1,382 engagements were recorded across all sectors over seven months. The most frequently identified high impact partners were federal and Puerto Rican governmental organizations partners. NGOs and nonprofits were noted as key partners in obtaining community perspective. Sector teams cited a lack of trust and difficulty identifying partners as barriers to partner engagement. Given the expedited nature of disaster response, establishing partnerships before disasters occur may help facilitate community input. Early networking, increased transparency and defining roles and responsibilities may increase trust and effectiveness among partnerships.

To our knowledge, this is one of the few studies that quantifies and illustrates the partnerships formed and their contributions during recovery planning, and lessons learned.

This study aims to investigate the effect of social influence and value-driven mobile marketing activities on consumers’ acceptance of mobile marketing offers.

The method used is survey questionnaire. A proposed model was tested by using structural model analysis and data gathered from 356 Mexico consumers and 346 US consumers.

The study shows the number of peers and providing information are the main predictor variables of consumer acceptance of mobile marketing offers in both countries. These results suggest that social value factors are important variables for explaining consumers’ responses to mobile marketing offers across two countries characterized by dissimilar macro-environmental conditions.

The study’s overall implication about standardization vs adaptation is that social value messages can be standardized across countries. However, the marketing tools and touch points required to communicate any message appeal must be adapted across countries. One limitation in this study is the use of a convenience sample of undergraduate college students. This study did not control for different types of mobile phones and the screen sizes of mobile phones.

The overall implication of standardization vs adaptation from the study results is that social value messages can be standardized across countries. However, the marketing tools and touch points required to communicate any message appeal must be adapted across countries.

Unlike previous studies where the emphasis is to explicate the effect of value-oriented mobile activity, this study examines the combined effect of social influence and value-driven mobile activities on acceptance of mobile marketing.

This paper explores the Adoption of Technological Innovation (ATI) in the healthcare industry. It investigates how the literature has evolved, and what are the emerging innovation dimensions in the healthcare industry adoption studies.

We followed a mixed-method approach combining bibliometric methods and topic modeling, with 57 papers being deeply analyzed.

Our results identify three latent topics. The first one is related to the digitalization in healthcare with a specific focus on the COVID-19 pandemic. The second one groups up the word combinations dealing with the research models and their constructs. The third one refers to the healthcare systems/professionals and their resistance to ATI.

The study’s sample selection focused on scientific journals included in the Academic Journal Guide and in the FT Research Rank. However, the paper identifies trends that offer managerial insights for stakeholders in the healthcare industry.

ATI has the potential to revolutionize the health service delivery system and to decentralize services traditionally provided in hospitals or medical centers. All this would contribute to a reduction in waiting lists and the provision of proximity services.

The originality of the paper lies in the combination of two methods: bibliometric analysis and topic modeling. This approach allowed us to understand the ATI evolutions in the healthcare industry.

This study investigates the motivation among customers to be more loyal to online food delivery applications (OFDA) services even after the COVID-19 epidemic by using perceived service quality aspects in Sri Lanka. The data were gathered by physically distributing a self-administrated questionnaire to clients in Sri Lanka who continue to use OFDA services on platform to customer (P2C) service delivery platforms to buy food despite the COVID-19 outbreak. Multiple regression is employed to analyse 287 effective observations, and the data revealed the significant positive effect of interaction, environment, outcome, and food qualities on customer loyalty to OFDA services. In fact, there is no impact from the delivery quality on customer loyalty to OFDA services due to outsourced food delivery. The findings suggest regular improvements in attributes such as interaction, environment, outcome, and food qualities in this hyper-competitive business environment. Further, this study sets substantial facts for the interested parties to establish an exemplary delivery system and other technological advancements to have a sustainable competitive advantage and solid customer base in the long run.

As net-zero pledges gain momentum globally, more and more accommodation businesses seek to quantify their carbon emissions. Building on Chan (2021), this study aims to explore what drives Australian accommodation providers to measure the carbon footprint of their businesses and what barriers hinder them from doing so.

Empirical data were collected by conducting ten semi-structured interviews with owners, senior executives, consultants, certification bodies and hotel management companies. The set of interviews represented different segments of the hotel industry and various accommodation types. Data were analysed with thematic analysis.

The major drivers for adopting carbon footprint analysis are as follows: the analysis being perceived as an important contribution to a company's corporate responsibility, the owner or manager's environmental concern, the assessment being a requirement for obtaining an eco-certification and the business benefits associated with implementing the initiative. The major barriers hindering adoption include the following: difficulties with data gathering, the lack of a standard methodology, a lengthy decision-making process and a lack of resources.

Based on the empirical findings and three theories on ecological responsiveness, this study develops a conceptual framework for implementing carbon footprint analysis in the accommodation context and recommends strategies to increase the adoption of carbon footprint analysis.

This study responds to Chan and Hsu's (2016) call for further research on carbon footprint in the hotel context and represents the first attempt to explore the drivers and barriers specifically associated with implementing carbon footprint analysis in the accommodation sector.

This study aims to assess the alignment of South Korea’s government-certified social enterprises (GCSEs) with prevailing social enterprise (SE) models, notably the entrepreneurial nonprofit, social cooperative and social business models delineated in the “Emergence of Social Enterprises in Europe” (Defourny and Nyssens, 2012, 2017a, 2017b) and the “principle of interest” frameworks (Defourny et al., 2021). Thereby, it seeks to situate these enterprises within recognized frameworks and elucidate their hybrid identities.

Analyzing panel data from 2016 to 2020 for 259 GCSEs, this study uses tslearn for k-means clustering with dynamic time warping to assess their developmental trajectories and alignment with established SE models, which echoes the approach of Defourny et al. (2021). We probe the “fluid” identities of semi-public sector SEs, integrating Gordon’s (2013) notion that they tend to blend various SE traditions as opposed to existing in isolation.

Results indicate that GCSEs do align with prevalent SE frameworks. Furthermore, they represent a spectrum of SE models, suggesting the versatility of the public sector in fostering diverse types of SEs.

The concept of a semi-public sector SE model has been relatively uncharted, even though it holds significance for research on SE typologies and public sector entrepreneurship literature. This study bridges this gap by presenting empirical evidence of semi-public SEs and delineating the potential paths these enterprises might take as they amalgamate various SE traditions.

The Chinese housing market has witnessed rapid growth during the past decade and the significance of housing price forecasting has undoubtedly elevated, becoming an important issue to investors and policymakers. This study aims to examine neural networks (NNs) for office property price index forecasting from 10 major Chinese cities for July 2005–April 2021.

The authors aim at building simple and accurate NNs to contribute to pure technical forecasts of the Chinese office property market. To facilitate the analysis, the authors explore different model settings over algorithms, delays, hidden neurons and data-spitting ratios.

The authors reach a simple NN with three delays and three hidden neurons, which leads to stable performance of about 1.45% average relative root mean square error across the 10 cities for the training, validation and testing phases.

The results could be used on a standalone basis or combined with fundamental forecasts to form perspectives of office property price trends and conduct policy analysis.