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This study investigates how artificial intelligence (AI) chatbots persuade customers to accept their recommendations in the online shopping context.

Drawing on the elaboration likelihood model, this study establishes a research model to reveal the antecedents and internal mechanisms of customers' adoption of AI chatbot recommendations. The authors tested the model with survey data from 530 AI chatbot users.

The results show that in the AI chatbot recommendation adoption process, central and peripheral cues significantly affected a customer's intention to adopt an AI chatbot's recommendation, and a customer's cognitive and emotional trust in the AI chatbot mediated the relationships. Moreover, a customer's mind perception of the AI chatbot, including perceived agency and perceived experience, moderated the central and peripheral paths, respectively.

This study has theoretical and practical implications for AI chatbot designers and provides management insights for practitioners to enhance a customer's intention to adopt an AI chatbot's recommendation.

1. The study investigates customers' adoption of AI chatbots' recommendation.

2. The authors develop research model based on ELM theory to reveal central and peripheral cues and paths.

3. The central and peripheral cues are generalized according to cooperative principle theory.

4. Central cues include recommendation reliability and accuracy, and peripheral cues include human-like empathy and recommendation choice.

5. Central and peripheral cues affect customers' adoption to recommendation through trust in AI.

6. Customers' mind perception positively moderates the central and peripheral paths.

The study investigates customers' adoption of AI chatbots' recommendation.

The authors develop research model based on ELM theory to reveal central and peripheral cues and paths.

The central and peripheral cues are generalized according to cooperative principle theory.

Central cues include recommendation reliability and accuracy, and peripheral cues include human-like empathy and recommendation choice.

Central and peripheral cues affect customers' adoption to recommendation through trust in AI.

Customers' mind perception positively moderates the central and peripheral paths.

With the advancement of technology, microlearning has emerged as a promising method to improve the efficacy of teaching and learning. This study aims to investigate the document types, volume, growth trajectory, geographic contribution, coauthor relationships, prominent authors, research groups, influential documents and publication outlets in the microlearning literature.

We adapt the PRISMA guidelines to assess the eligibility of 297 Scopus-indexed documents from 2002 to 2021. Each was manually labeled by educational level. Descriptive statistics and science mapping were conducted to highlight relevant objects and their patterns in the knowledge base.

This study confirms the increasing trend of microlearning publications over the last two decades, with conference papers dominating the microlearning literature (178 documents, 59.86%). Despite global contributions, a concentrated effort from scholars in 15 countries (22.39%) yielded 68.8% of all documents, while the remaining papers were dispersed across 52 other nations (77.61%). Another significant finding is that most documents pertain to three educational level categories: lifelong learning, higher education and all educational levels. In addition, this research highlights six key themes in the microlearning domain, encompassing (1) Design and evaluation of mobile learning, (2) Microlearning adaptation in MOOCs, (3) Language teaching and learning, (4) Workflow of a microlearning system, (5) Microlearning content design, (6) Health competence and health behaviors. Other aspects analyzed in this study include the most prominent authors, research groups, documents and references.

The finding represents all topics at various educational levels to offer a comprehensive view of the knowledge base.

Despite significant advances in previous work, there are still gaps in the research on customers' acceptance of virtual fitting rooms (VFRs). This research aims to highlight the effects of the characteristics of VFRs on the intention to use.

Fashionable clothing shoppers in Harmony Shopping Plaza and Ginza Shopping Plaza in Jinan, China, were chosen as the main sample. A total of 304 valid questionnaires were collected using a questionnaire QR code, which was scanned to access the questionnaire. Structural equation modeling was used to test the relevant hypotheses.

The results showed that customers' usage intention (UI) was positively associated with perceived efficiency, design and perceived security. Furthermore, the mediating effects of perceived ease of use and perceived usefulness were significant between design, vividness and UI.

In contrast to existing research, which focuses primarily on the posterior effects of psychological perception and behavior, this paper focuses on the antecedents of customer psychological perceptions. This study also examines the moderating effect of fashion consciousness, which also provides reference value for future research. The findings of this paper provide practical guidance for the promotion of VFRs.

This paper aims to investigate the impact of online identity orientation and online friendship homophily on online socializing, online information search and ethnic guests’ hospitality experiences.

The study uses structural equation modeling to test a conceptual model developed after reviewing hospitality literature. Data is collected from a sample of 514 Turkish-Dutch ethnic guests living in the Netherlands using a self-administered questionnaire.

The results show that online identity orientations aligned with minority and majority cultures impact online friendship homophily and online socializing, which subsequently impact online information search and hospitality experiences of ethnic guests.

On the whole, ethnic communities have considerable spending power. The findings point to heritage and mainstream cultural socialization accounting for travel and hospitality experiences within an ethnic minority group. The findings supply relevant information for hospitality sectors on services to endorse or promote to guests from ethnic communities.

The study examines the simultaneous effects of online identity orientations and online friendship homophily on online socialization and hospitality experiences of ethnic guests. It highlights the role of culture in explaining the use of social networking sites and its potential impact on hospitality-related behaviors and experiences of ethnic guest consumers.

For successful management of construction projects, a precise analysis of the balance between time and cost is imperative to attain the most effective results. The aim of this study is to present an innovative approach tailored to tackle the challenges posed by time-cost trade-off (TCTO) problems. This objective is achieved through the integration of the multi-verse optimizer (MVO) with opposition-based learning (OBL), thereby introducing a groundbreaking methodology in the field.

The paper aims to develop a new hybrid meta-heuristic algorithm. This is achieved by integrating the MVO with OBL, thereby forming the iMVO algorithm. The integration enhances the optimization capabilities of the algorithm, notably in terms of exploration and exploitation. Consequently, this results in expedited convergence and yields more accurate solutions. The efficacy of the iMVO algorithm will be evaluated through its application to four different TCTO problems. These problems vary in scale – small, medium and large – and include real-life case studies that possess complex relationships.

The efficacy of the proposed methodology is evaluated by examining TCTO problems, encompassing 18, 29, 69 and 290 activities, respectively. Results indicate that the iMVO provides competitive solutions for TCTO problems in construction projects. It is observed that the algorithm surpasses previous algorithms in terms of both mean deviation percentage (MD) and average running time (ART).

This research represents a significant advancement in the field of meta-heuristic algorithms, particularly in their application to managing TCTO in construction projects. It is noteworthy for being among the few studies that integrate the MVO with OBL for the management of TCTO in construction projects characterized by complex relationships.

The Scottish economy was experiencing steady growth prior the hit of the COVID-19, with the pandemic causing the government to announce extreme lockdown measures with unprecedented impact on small and medium-sized enterprises (SMEs). Whilst some of the industry sectors in Scotland took a lighter hit, a large part of the organizations had to either adapt or completely disrupt their business. An essential aspect of their survival, risk management (RM) was among the areas requiring the most significant acceleration. This study compared the RM practices implemented by Scottish SMEs prior and after the outbreak as well as examined the attitudes of key decision-makers in the SMEs in relation to risk, including their perceived readiness for another crisis of similar significance.

An online survey based on ISO 31000 RM guidelines was distributed to 232 Scottish SMEs. Based on the official government reports and existing knowledge on how SMEs around the world have handled crisis events within the past 20 years, the authors developed the hypothesis that crisis events significantly accelerate SMEs' RM implementation. Around 13 items were tested in relation to the hypothesis and responses were tested via two-tailed T-test to establish significant statistical difference.

The research provides insight into the current state of risk management practices implemented by Scottish SMEs. As expected, SMEs showed significant difference in their RM implementation prior and after the COVID-19 outbreak. Whilst this has been viewed as a positive, motivations, priorities and approaches in managing risk demonstrated by the SMEs is questionable with views to their sustainable long-term recovery. The study highlights the lack of confidence instilled within the SMEs that they can handle another crisis of similar significance and provides directions for further investigation and improvements with the aim of helping the SMEs prepare better to mitigate the consequences of future crisis events.

In academic sense, the study offers a tested universal framework and a detailed questionnaire for assessment of RM strategy, applicable to organisations of various type, size and geography. Several implications with regards to managerial practices have been highlighted, including the neglect of the SMEs’ own internal environments and its significance in their risk strategies, the predominantly reactive approach to RM displayed by most Scottish SMEs as well as the neglect of compliance risk leading to potential quality and customer satisfaction issues preventing SMEs from full post-crisis recovery.

The current research aims to investigate the relationship between supply chain (SC) processes maturity and SC performance in the context of an emerging market (i.e. Morocco). Based on the SCOR model, the authors propose and test a thorough conceptual framework in which information systems moderates the relationship between SC processes maturity and performance. The effects of firm age and size are also taken into account.

Based on data collected from 175 top and middle managers using self-administered questionnaires, the authors empirically assessed the conceptual model using a partial least squares (PLS) estimation.

The study's findings demonstrate that SC processes maturity has a significant effect on SC performance. Second, information systems act as a moderator in the relationship between SC maturity and performance, e.g. the impact of supply chain processes maturity on supply chain performance measures is stronger in the presence of information systems support. Ultimately, firm size and age were found to have no significant impact on supply chain performance.

The study's findings help SC managers to better understand how SC maturity contributes to SC performance. A firm effectively executing maturity factors in its SC processes is more likely to achieve a better SC performance. The authors also established the key role of information systems in strengthening the impact of SC maturity on performance. SC managers should capitalize on the use of information systems to achieve superior SC performance.

The present research bridges a gap pertaining to the impact of supply chain maturity on SC performance, particularly in emerging markets. It is the first of its kind to investigate the influence of SC maturity on SC performance the context of emerging markets.

The paper’s main goal is to examine the relationship between the video marketing of financial technologies (Fintechs) and their vulnerable website customers’ brand engagement in the ongoing coronavirus disease 2019 (COVID-19) crisis.

To extract the required outcomes, the authors gathered data from the five biggest Fintech websites and YouTube channels, performed multiple linear regression models and developed a hybrid (agent-based and dynamic) model to assess the performance connection between their video marketing analytics and vulnerable website customers’ brand engagement.

It has been found that video marketing analytics of Fintechs’ YouTube channels are a decisive factor in impacting their vulnerable website customers’ brand engagement and awareness.

By enhancing video marketing analytics of their YouTube channels, Fintechs can achieve greater levels of vulnerable website customers’ engagement and awareness. Higher levels of vulnerable customers’ brand engagement and awareness tend to decrease their vulnerability by enhancing their financial knowledge and confidence.

Fintechs should aim to increase the number of total videos on their YouTube channels and provide videos that promote their customers’ knowledge of their services to increase their brand engagement and awareness, thus reducing their vulnerability. Moreover, Fintechs should be aware not to over-post videos because they will be in an unfavorable position against their competitors.

This research offers valuable insights regarding the importance of video marketing strategies for Fintechs in promoting their vulnerable website customers’ brand awareness during crisis periods.

This bibliometric mapping study aimed to provide comprehensive insights into the global research landscape of cybernetics. Utilizing the biblioshiny function in R Studio, we conducted an analysis spanning 1958 to 2023, sourcing data from Scopus. This research focuses on key terms such as cybernetics, cybernetics systems, complex adaptive systems, viable system models (VSM), agent-based modeling, feedback loops and complexity systems.

The analysis leveraged R Studio’s biblioshiny function to perform bibliometric mapping. Keyword searches were conducted within titles, abstracts and keywords, targeting terms central to cybernetics. The timespan, 1958–2023, provides a comprehensive overview of the evolution of cybernetics-related literature. The data were extracted from Scopus to ensure a robust and widely recognized source.

The results revealed a rich and interconnected global research network in cybernetics. The word cloud analysis highlights prominent terms such as “agent-based modeling,” “complex adaptive systems,” “feedback loop,” “viable system model” and “cybernetics.” Notably, the journal Kybernetes has emerged as a focal point, with significant citations, solidifying its position as a key source within the cybernetics research domain. The bibliometric map provides visual clarity regarding the relationships between various concepts and their evolution over time.

This study contributes original insights by employing advanced bibliometric techniques in R Studio to map the cybernetics research landscape. The comprehensive analysis sheds light on the evolution of key concepts and the global collaborative networks shaping cybernetics research. The identification of influential sources, such as Kybernetes, adds value to researchers seeking to navigate and contribute to the dynamic field of cybernetics. Furthermore, this study highlights that cybernetics not only provides a useful framework for understanding and managing major economic shocks but also offers perspectives for understanding phenomena in various fields such as economics, medicine, environmental sciences and climate change.

This research aimed to visualize and analyze the co-word network and thematic clusters of the intellectual structure in the field of linked data during 1900–2021.

This applied research employed a descriptive and analytical method, scientometric indicators, co-word techniques, and social network analysis. VOSviewer, SPSS, Python programming, and UCINet software were used for data analysis and network structure visualization.

The top ranks of the Web of Science (WOS) subject categorization belonged to various fields of computer science. Besides, the USA was the most prolific country. The keyword ontology had the highest frequency of co-occurrence. Ontology and semantic were the most frequent co-word pairs. In terms of the network structure, nine major topic clusters were identified based on co-occurrence, and 29 thematic clusters were identified based on hierarchical clustering. Comparisons between the two clustering techniques indicated that three clusters, namely semantic bioinformatics, knowledge representation, and semantic tools were in common. The most mature and mainstream thematic clusters were natural language processing techniques to boost modeling and visualization, context-aware knowledge discovery, probabilistic latent semantic analysis (PLSA), semantic tools, latent semantic indexing, web ontology language (OWL) syntax, and ontology-based deep learning.

This study adopted various techniques such as co-word analysis, social network analysis network structure visualization, and hierarchical clustering to represent a suitable, visual, methodical, and comprehensive perspective into linked data.