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Consumer choices are influenced by available resources, and time is increasingly recognised as a valuable and scarce resource. This study aims to assess the effect of chronic time pressure (CTP) on the desire to stay in retail venues (DTS), considering the mediating role of utilitarian and hedonic shopping motivations and the moderating role of time management (TM); and examine the role of DTS in enhancing the shopping outcomes of satisfaction, patronage intentions and positive word-of-mouth (WOM).

Two survey-based studies were conducted, employing structural equation modelling (SEM) and Hayes’ PROCESS Model No. 1 to test the proposed model.

The findings indicate that CTP does not have a direct impact on shopping utilitarian motivations or DTS. However, it has a direct effect on hedonic motivations that mediate the path from CTP to DTS. In addition, TM positively moderates both paths from CTP and hedonic motivations to DTS. Finally, the results demonstrate that reinforcing shopper DTS leads to increased satisfaction, patronage intentions and positive WOM.

Based on the findings, theoretical contributions and actionable managerial implications regarding how to leverage CTP and TM to enhance shopper engagement and retail venue outcomes are discussed.

While prior research has often focused on situational time pressure, this study concentrates on CTP and examines the impact of perceived time constraints and feeling rushed on utilitarian and hedonic shopping motivations and DTS. Moreover, the study tests the moderating role of TM and provides evidence that DTS leads to other desirable shopping outcomes.

Generative conversational artificial intelligence (AI) demonstrates powerful conversational skills for general tasks but requires customization for specific tasks. The quality of a custom generative conversational AI highly depends on users’ guidance, which has not been studied by previous research. This study uses social exchange theory to examine how generative conversational AI’s cognitive and emotional conversational skills affect users’ guidance through different types of user engagement, and how these effects are moderated by users’ relationship norm orientation.

Based on data collected from 589 actual users using a two-wave survey, this study employed partial least squares structural equation modeling to analyze the proposed hypotheses. Additional analyses were performed to test the robustness of our research model and results.

The results reveal that cognitive conversational skills (i.e. tailored and creative responses) positively affected cognitive and emotional engagement. However, understanding emotion influenced cognitive engagement but not emotional engagement, and empathic concern influenced emotional engagement but not cognitive engagement. In addition, cognitive and emotional engagement positively affected users’ guidance. Further, relationship norm orientation moderated some of these effects such that the impact of user engagement on user guidance was stronger for communal-oriented users than for exchange-oriented users.

First, drawing on social exchange theory, this study empirically examined the drivers of users’ guidance in the context of generative conversational AI, which may enrich the user guidance literature. Second, this study revealed the moderating role of relationship norm orientation in influencing the effect of user engagement on users’ guidance. The findings will deepen our understanding of users’ guidance. Third, the findings provide practical guidelines for designing generative conversational AI from a general AI to a custom AI.

This paper aims to investigate how implying movement in food packaging imagery may affect product liking. Furthermore, the underlying mechanism is investigated by studying the effect of implied motion visuals on design appeal and naturalness perception.

Two packages of pineapple juice were designed in which the implied motion depicted in their imagery was manipulated, and a tasting experiment was conducted in which two samples of the same juice were evaluated.

The results show that the effect of packaging imagery on product liking occurs indirectly through both design appeal and the product naturalness perception. The results of a parallel multiple-mediator analysis show that (1) depicting implied motion made the package be perceived as more appealing, (2) the product corresponding to the package depicting implied motion was perceived as being more natural, and (3) both effects equally contributed to the positive effect of visuals depicting implied motion on product liking.

Overall, these findings widen our understanding of the effects of packaging design on product liking and may help both designers and manufacturers design more appropriate packaging for their products.

This study explores the profound influence of social and cultural factors on the financial conduct of indigenous tribes and groups. Anchored in Vygotsky's sociocultural theory, the analysis delves into the intricate interplay between cultural elements, such as bricolage, and the immediate availability of financial resources, illuminating their collective impact on the tribes' financial behaviour. Typically residing in proximity, these communities exhibit homogeneity by forming groups exclusive to their clans, lacking access to conventional financial services and tangible assets that dissuade banks from extending loans. Crucially, the social capital embedded within the group dynamics, often referred to as the peer mechanism, emerges as a pivotal conduit for members to secure capital and bank credit. The synergy of bricolage, representing the adept use of available social capital, facilitates access to finance and credit. Despite the existence of social capital and financial literacy programmes, a stark reality persists – a significant proportion of indigenous people remain financially excluded. This chapter endeavours to scrutinise the ramifications of these factors on tribal financial behaviour, employing the Partial Least Squares Structural Equation Modelling (PLS-SEM) method. Proposing a paradigm shift in financial attitudes, the research underscores the imperative of fostering financial inclusion within indigenous tribes and communities.

This study aims to conduct a comprehensive analysis of the current body of existing literature on chatbots and online shopping. Additionally, this study identifies and emphasize the future research agenda and emerging trends within this domain.

A thorough investigation was conducted on a set of 147 publications sourced from the Scopus database spanning the years 2016 to 2023 by using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis methodology. The analysis included bibliometric techniques through VOSviewer, including science mapping and performance analysis of the literature under investigation.

The findings of the study indicate a systematic impression of prevailing scientific research on integration of Chatbot in online shopping. A majority of publications were contributed by developing countries specifically Asian regions. There has been a notable rise in research collaborations over the course of time. Further, themes were identified through keyword co-occurrence for exploration of future trends in the domain.

This study identifies and analyzes the patterns in the existing literature on chatbot and online shopping, with the objective of enhancing e-retailers comprehension of this particular topic area. The research findings hold significance for both researchers and organizations in their efforts to enhance strategy design.

This study uses bibliometric analysis to examine the literature on chatbots and online shopping, aiming to develop a systematic comprehension of the research field. This study makes a valuable contribution to the current scholarly discourse and provides support for future scholars in their investigations.

This study aims to recognize the role of information system (IS) model on young adults’ experience of housing and real estate chatbots. This model of IS takes into account the quality of information, the quality of system and the quality of service.

This study uses a sample frame for analysis which comprises young adult population in India, i.e. between the ages of 18 and 35. A questionnaire consisting of five components was used to collect information in a structured manner. The 386 responses thus collected were analysed using the structural equation model.

It was found that there is a significant influence of the quality of information, quality of system and quality of service on young adults’ experience of housing and real estate chatbots. The findings also showed that there is moderation role of effort expectancy between the quality parameters and young adults’ user experience of housing and real estate chatbots.

This study focusses exclusively on the young adults from various parts of India. Future research can consider larger population categories across age groups and across sectors employing chatbots.

This study will enable in-depth understanding of IS model – quality dimensions’ relation with the user experience. In particular, housing and real estate organisations will profit from the expanded usage of artificial intelligence through chatbots for user correspondence and communication.

To the best of the authors’ knowledge, this study is first of its kind, as it investigates how IS model – quality dimensions affect the young adults’ experience of housing and real estate chatbots in India. This study also ventures into identifying the moderation role of effort expectancy between the quality dimensions as per IS model and young adults’ experience of housing and real estate chatbots. This study will be useful for the stakeholders of housing and real estate industry.

Healthcare organizations have been facing challenges due to high costs and low efficiency in health services. The growth of costs and losses caused by avoidable mistakes lead to the search for solutions, and Health Lean Management appears as a potential solution to help in solving service quality problems, as well as reducing risks. This study aims to analyse the state of the art in the literature centred on the Lean approach in the context of risk management in healthcare organizations, and to identify new research opportunities, highlighting possible lines of future research.

Following a systematic literature review approach, 51 papers were considered relevant for this research, and reviewed to explore the development of literature in this area.

Based on the results, five main research streams were identified: (1) risk management oriented towards patient safety; (2) risk management oriented towards employee safety; (3) importance of attitudes and behaviours in risk reduction projects; (4) Lean tools used in healthcare risk management and (5) Integration of approaches. Moreover, several shortcomings were identified in literature.

Identified shortcomings represent significant opportunities for further research development.

This study aims to prepare thymol-based deep eutectic solvents (DESs) and use them as lubricates for friction and wear tests to simulate the wear conditions of hybrid bearings.

Through the characterization and analysis of the morphology of wear scars and the elemental composition of friction films, the tribological behavior and wear mechanism of sample materials as lubricants were investigated and the anti-wear mechanism of thymol-based DESs was discussed.

The findings demonstrate that because of the formation of a fluid lubrication film and excellent kinematic viscosity, the lubrication effect of the prepared DES is improved by about 50% compared to the base lubricating oil. The prepared [Ch]Cl-thymol DES has a better anti-friction and lubrication effect than citric-thymol, EG-thymol and urea-thymol DESs, with an average friction coefficient of about 0.04.

In this work, the friction reduction properties of thymol-based DESs were studied as lubricants for the first time, and the lubrication mechanism of sample materials was investigated.

The purpose of this paper addresses the issue of inconsistent findings regarding the impact of consumers' need for touch (NFT) on webrooming behavior. It investigates the moderator of maximization by drawing on maximizing mindset theory.

Three studies were carried out to test the hypothesized relationships. The first study investigated the impact of autotelic NFT on webrooming intention. The second study examined the impact of instrumental NFT on webrooming intention. The third study tested all hypotheses by the structural equation modeling approach.

The results confirm moderation by consumers' maximizing mindset. The moderated mediation analyses show that the interaction effect of autotelic NFT and maximization influences webrooming intention indirectly via anticipated sensory pleasure. Likewise, the interaction effect of instrumental NFT and maximization influences webrooming intention indirectly via product fit uncertainty.

The study draws on maximizing mindset theory to show that consumers' autotelic NFT and instrumental NFT drive their webrooming intentions depending on the activation of their maximizing mindset. The nonsignificant relationship between autotelic NFT and webrooming intention in the context of satisficers explains the conflicting findings reported in the literature. Consumers' affective and cognitive responses were also studied to uncover the underlying mechanisms of their webrooming intention. This research contributes to the literature by enhancing the understanding of webrooming behavior.

The advancement of artificial intelligence (AI) has brought intelligent online shopping experiences to customers. AI-powered retail platforms deliver personalized shopping experiences through tailored recommendations, promotions and assistance. Given the increasing preference for online shopping, it is crucial to explore methods to optimize the adoption of AI-powered retail platforms. To address this, this study aims to examine the impact of technology readiness motivators (optimism and innovativeness) and inhibitors (discomfort and insecurity) on perceived trust, perceived usefulness and purchase intention toward AI-powered retail platforms.

Data were collected from 276 customers in Egypt, primarily from the millennial and Gen Z demographic segments. The collected data were then analyzed using the statistical package for social sciences (SPSS) and partial least squares structural equation modeling (PLS-SEM).

The findings revealed that optimism, innovativeness and discomfort significantly influence perceived trust, while optimism, insecurity and perceived trust significantly influence perceived usefulness. Both perceived trust and usefulness are significant predictors of purchase intention. Perceived trust mediates the effects of technology readiness motivators on perceived usefulness and purchase intention. Moreover, perceived usefulness mediates the effects of technology readiness motivators, insecurity and perceived trust on purchase intention.

To date, there are few investigations regarding the acceptance and adoption of AI-powered retail platforms in developing countries. Thus, this study offers valuable theoretical and practical implications in the context of smart retail technology adoption.