Search results

This study aims to explore the impact of perceived information quality on customers' self-efficacy and knowledge and how these factors subsequently influence perceived value and intentions to participate and visit.

A video scenario was used to depict a co-creation dining experience, with participants recruited through self-selected convenience sampling. Data were collected from 472 participants who viewed a video showcasing co-creation dining in restaurants. Structural equation modeling was applied to test the proposed hypotheses.

Results indicate that perceived information quality significantly enhances customers' knowledge and confidence. Increased knowledge and self-efficacy lead to higher perceived value, which subsequently boosts customers' intentions to participate and visit. Additionally, knowledge and self-efficacy partially mediate the relationship between perceived information quality and perceived value.

This study applies framing and processing theories, highlighting how clear, engaging presentation enhances perception, comprehension and self-efficacy in the co-creation process. Practical recommendations for restaurants include developing instructional materials, staff training and tiered experiences to improve customer engagement.

This study provides new insights into the role of information quality in shaping customer perceptions and behaviors in co-creation dining experiences, highlighting the importance of knowledge and self-efficacy in enhancing perceived value and participation intentions.

This paper aims to study the impact of the interaction effects between live-streaming marketing and clothing type on consumers' intention to purchase clothing, and the mediating effect of internalization and identification on the relationship between them.

This paper conducts a scenario experiment to 486 consumers who had experience in purchasing clothing on the live-streaming platform and employs the analysis of variance, structural equation model and multivariate regression model.

Our findings reveal that professional live-streaming marketing (PLSM) can better stimulate consumers' intention to purchase formal clothing than entertainment live-streaming marketing (ELSM) does. Compared with PLSM, ELSM can better stimulate consumers' intention to purchase casual clothing. When PLSM promotes formal clothing, it triggers the internalization mechanism of consumers, so as to improve their purchase intention. When ELSM promotes casual clothing, it triggers consumers' identification mechanism, so as to improve their purchase intention.

This paper helps to identify the differences in the impact of different types of live-streaming marketing on consumers' intention to purchase different types of clothing, as well as the mediating role of internalization and identification mechanisms. This paper provides a theoretical reference for clothing firms to strategically select the appropriate type of live-streaming marketing.

Dual design for additive manufacturing (DfAM) takes into account both the opportunities and constraints of AM simultaneously, which research shows is more effective than considering them separately. Unlike existing reviews, this paper aims to map DfAM research within the engineering design process, focusing solely on studies adopting dual DfAM. Additionally, it aims to suggest future research directions by analysing prominent research themes and their inter-relationships. Special emphasis is on theme inter-relationships concerning the conceptual, embodiment and detail design phases.

The study is based on a systematic literature review of 148 publications from January 2000 to February 2024. After screening, prominent research themes were identified and systematically analysed. Theme inter-relationships were explored using quantitative analysis and chord diagrams.

The findings reveal that studies either span the entire design process, the early design phases or the later design phases. Most research focuses on the later design phases, particularly within themes of design optimisation, design evaluation and AM-specific manufacturing constraints. The most frequent theme inter-relationship occurs between design optimisation and AM-specific manufacturing constraints. Overall, the findings suggest future research directions to advance dual DfAM research, such as development of design rules and guidelines for cellular structures.

This review proposes a model by mapping prominent themes of dual DfAM research in relation to the engineering design process. Another original contribution lies in analysing theme inter-relationships and visualising them using chord diagrams – a novel approach that did not exist before.

This study aims to examine the impact of customer experience of cannabis-infused food and beverage perception (sensory experience, novelty experience, health concerns and restaurant experience) on favouring these products and subsequent customer citizenship behaviour.

Using a purposive sampling approach, an onsite survey was administered to Thai Gen Z customers in consuming cannabis-infused foods and/or beverages. Subsequently, the sample consisted of 330 respondents. Partial least squares structural equation modelling was used for the analyses.

The results indicated that sensory experience, health concerns and restaurant experience had significant positive effects on favouring cannabis-infused foods and beverages. This favourability, in turn, positively affected customer citizenship behaviour. In addition, favouring cannabis-infused foods and beverages partially mediated the relationships between customer citizenship behaviour and sensory experience, health concerns and restaurant experience.

This study provides a new contribution to the literature with a first empirical examination showing positive favouring of cannabis-infused foods and beverages among young consumers in Thailand. It provides practical insights for managers in emerging markets to leverage cannabis-infused products as part of the enhancement of the global food and beverage industry. The study also offers an example of how to move forward through an unknown territory regarding perceptions of consumer experiences.

This study empirically evaluates the effect of China’s 2016 Green Financial System (GFS) framework on corporate green development, focusing on the role of green investment in achieving sustainability.

This study uses a quasinatural experiment design to combine difference-in-difference and propensity score matching methods for analysis. It examines 799 polluting and 1,130 nonpolluting firms from 2013 to 2020, enabling a comprehensive assessment of the GFS framework’s influence.

This study affirms a statistically significant positive influence of the GFS framework on escalating green investment levels in polluting firms. Robust sensitivity analyses, encompassing parallel trend assessment, entropy balancing test, and alternative proxies, corroborate these findings. A mediation analysis identifies the implementation of an environmental management system as the potential underlying mechanism. A cross-sectional analysis identifies high financial slack, high profitability, mandatory CSR regulations, and marketization level as the influencing factors.

The study’s findings have critical implications for policymakers, regulators, and companies. Demonstrating the effectiveness of the GFS framework in driving green investment underscores the importance of aligning financial systems with sustainability goals.

This study contributes novel empirical evidence on the positive effect of China’s GFS framework on corporate green development. The quasinatural experiment design, coupled with comprehensive sensitivity analyses, strengthens the robustness of the findings.

This study examines the direct and indirect effects of shared leadership on job crafting and knowledge sharing, in turn, on employee performance, commitment and creativity via organizational support among Pakistani HEI faculty members.

Drawing on shared leadership theory, data from 311 faculty members were collected. Structural equation modeling (SEM) was employed to test the hypotheses.

The findings revealed a significant positive influence of shared leadership on job crafting and knowledge sharing among faculty members. Job crafting and knowledge sharing also significantly and positively influenced employee performance, commitment and creativity. Shared leadership includes support dynamics, so organizational support with shared leadership failed to influence job crafting and knowledge sharing.

Institutions promoting collaborative and innovative educational environments should consider strategies to nurture shared leadership practices, facilitate job crafting and bolster knowledge-sharing.

This study underscores the importance of fostering a shared leadership culture in HEIs, emphasizing the role of job crafting and knowledge sharing in employee performance, commitment and creativity.

This study aims to examine the effects of perceived product–brand fit and brand type on consumer evaluations of wearable smart masks’ technological, aesthetic and social attributes and how these affect consumers’ attitudes and intentions to use.

Through an experimental approach, a total of 240 US consumers’ evaluations of smart masks are compared according to perceived product–brand fit (high vs low) and brand type (electronics vs fashion).

The results showed that high perceived product–brand fit increases consumers’ evaluations, while brand type did not significantly affect consumers’ evaluations. Among various attributes, social acceptability had the greatest influence on consumers’ attitude and intention to use. Perceived ease of use, however, positively influenced attitude but negatively influenced intention to use.

As consumers’ interest in smart health-care wearables increases and air pollution is a serious issue across countries, research on wearable smart masks is being facilitated. Smart masks refer to the digitalized, reusable wearable masks that provide protection and health-care functions. However, their market penetration is still limited. To close this gap between smart mask technology and the market, this study examines how perceived fit and brand type can be used to enhance consumer evaluations.

A transmission tower usually experiences bolt loosening under long-term alternating cyclic load, which may lead to collapse of the tower in extreme operating conditions. The paper aims to propose a data-driven identification method for bolt looseness of complicated tower structures based on reduced-order models and numerical simulations to perceive and evaluate the health state of a tower in operation.

The equivalent stiffnesses of three types of bolt joints under various loosening scenarios are numerically determined by three-dimensional finite element (FE) simulations. The order of the FE model of a tower structure with bolt loosening is reduced by means of the component modal synthesis method, and the dynamic responses of the reducer-order model under calibration loads are simulated and used to create the dataset. An identification model for bolt looseness of the tower structure based on convolutional neural networks driven by the acceleration sensors is constructed.

An identification model for bolt looseness of the tower structure based on convolutional neural networks driven by the acceleration sensors is constructed and the applicability of the model is investigated. It is shown that the proposed method has a high identification accuracy and strong robustness to data noise and data missing. Meanwhile, the method is less dependent on the number and location of sensors and is easier to apply in real transmission lines.

This paper proposes a data-driven identification method for bolt looseness of a complicated tower structure based on reduced-order models and numerical simulations. Non-linear relationships between equivalent stiffness of bolted joints and bolt preload depicting looseness are obtained and reduced-order model of tower structure with bolt looseness is established. Finally, this paper investigates applicability of identification model for bolt looseness.

This study examines why long-term relationships between expert users and smart voice assistants (SVAs) develop. It postulates that the five dimensions of experience (i.e. sensory, affective, intellectual, behavioural and relational) generate feelings of love for SVAs. The formation of love is examined considering three components: passion, intimacy and commitment. These feelings encourage users to continue employing and to generate long-term relationships with SVAs.

Data from a survey of 403 USA expert users of SVAs provide the input for structural equation modelling.

The results show that three dimensions of experience influence users’ passion towards SVAs: affective, intellectual and behavioural. Moreover, passion can convert the effect of users’ experiences into intimacy and commitment. Finally, intimacy and commitment increase users’ intentions to continue using SVAs.

The findings obtained make three original contributions. First, this study is the first to analyse expert users of SVAs and the post-technology adoption stage. Therefore, it introduces a new case of relational marketing in smart technologies. Second, this study contributes by applying a new theoretical perspective that evaluates the importance of users’ experiences with SVAs. Third, it takes an interpersonal approach to explore user-SVA interactions, revealing that users can develop human-like love feelings for SVAs.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-10-2022-0570

This study aims to provide empirical evidence to verify the dimensional structure of artificial intelligence (AI) Chatbot quality and examine the impact of these dimensions on consumer satisfaction and brand advocacy among Gen Z in the fast food industry in Egypt.

The empirical data was obtained with an electronic self-administered survey instrument from 397 young consumers who had prior experience using AI Chatbots across multiple fast food brands in Egypt. Structural equation modeling was used to analyze the formulated hypotheses.

The results showed that AI Chatbot quality dimensions, specifically information authenticity and system compliance, significantly enhance young consumers’ satisfaction. In addition, information authenticity of AI Chatbot quality was observed to wield a significant influence on young consumers’ advocacy. In contrast, an insignificant relationship was noticed between satisfaction and advocacy. Moreover, the mediating role of consumer satisfaction was not established.

Given that Gen Z is more technology savvy and computer literate, marketers and practitioners of fast food brands should invest in AI tools to respond to young consumers’ expectations and improve their perception of their services.

This study uses stimulus-organism-response theory to understand the mediating effect of young consumers’ satisfaction in the relationship between AI Chatbot quality and consumer brand advocacy within the fast food industry. Also, it introduced two novel main constructs of AI Chatbot quality, namely, information authenticity and system compliance.