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This study aimed to identify the quality consumers expect from functional food. This study investigated the quality dimensions and indicators female consumers expect in functional food.

This study used a quantitative approach. Data were collected through a survey using a self-administered questionnaire from 149 women aged 17 years and over in the Greater Jakarta area. Data analysis consists of three stages: exploratory factor analysis (EFA), confirmatory factor analysis-structural equation modeling (CFA-SEM) and consumer expectation value analysis. Statistical Package for the Social Sciences (SPSS) and Lisrel software were used to assist the analysis.

The analysis results showed that women expect functional food products to fulfill the aspects of product presentation, product assurance, convenience, health benefits and safety and sensory characteristics. These five aspects are referred to as the expected quality dimensions. Twenty-one indicators can be used to measure the quality of functional food expected by women.

Other researchers can use this study to understand functional food female consumers' behavior. Furthermore, functional food companies can utilize it to measure consumers' expectations of their products' quality and performance.

This research is believed to be the first study to identify the dimensions of functional food quality expected by female consumers. Most existing research on the perceived quality of functional food measures functional food quality based on performance and ignored the differences in expectations between men and women.

Recently, autonomous vehicles (AV) acceptance has been studied intensively. This paper aims to map and analyze the bibliometric characteristics of AV acceptance literature. Furthermore, this research aims to identify research gaps and propose future research opportunities.

The bibliometric analysis was performed. Scopus database was used as the source of the literature. This study selected and analyzed 297 AV acceptance papers. The performance and science mapping analysis were performed.

The developed countries tended to dominate the topic. The publication outlet tended to be in transportation or technology journals. There were four research themes in existing literature. Technology acceptance model (TAM) and UTAUT2 tended to be used for explaining AV acceptance. AV acceptance studies tended to use two types of psychological concepts for understanding AV acceptance, namely risk related concepts and functional utilitarian benefit related concepts. In the context of research design, quantitative approach tended to be used. Self-driving feature was the most exploited feature of AV in the existing literature. Three research gaps were mapped and future research opportunities were proposed.

This paper provided a comprehensive information that allowed scientists to develop future research on AV acceptance.

There is lack of paper that discussed the bibliometric characteristics of AV acceptance literature. This paper fulfilled the gap.

One of the organization's main goals is to maintain their customers' loyalty, as this can give them a competitive advantage. Therefore, this study is intended to look into the impact of library service quality using LibQUAL + TM dimensions (library service effect, personal control and library as a place), library image and trust on users’ loyalty with the mediating effect of perceived service value and satisfaction.

Data for hypotheses testing were gathered from Minhaj University Lahore (MUL), a private sector university's staff, administration and students, using a survey questionnaire. About 500 questionnaires were randomly distributed, and 407 were utilized as the final sample for analysis. Structural equation modelling (SEM), using SmartPLS 4 and SPSS 25, were used to analyze the empirical data.

First, research reveals that library image, users’ trust, library service effect and personal control significantly influence user satisfaction. Second, the library as a place and personal control are not a significant indicator of perceived service value. Third, perceived service value and satisfaction have a direct positive relationship with users' loyalty. Fourth, trust and library service effect is indirectly related to loyalty via perceived service value. Fifth, satisfaction does not mediate the relationship between library as a place and loyalty.

Customer satisfaction must be guaranteed by library administration if it hopes to win users’ loyalty. In light of the fact that a variety of factors can affect customer satisfaction, their perception and loyalty, library management should enhance not just the quality of library services along with other factors such as library image and users’ trust.

The study examined the independent impact of library image and users’ trust on satisfaction, perceived service value and users’ loyalty, which, within the framework of the library, has never been addressed in literature.

This bibliometric study aims to analyze the latest trends and patterns of big data applications in librarianship from 2000 to 2022. By conducting a comprehensive examination of the existing literature, this study aims to provide valuable insights into the emerging field of big data in librarianship and its potential impact on the future of libraries.

This study employed a rigorous four-stage process of identification, screening, eligibility and inclusion to filter and select the most relevant documents for analysis. The Scopus database was utilized to retrieve pertinent data related to big data applications in librarianship. The dataset comprised 430 documents, including journal articles, conference papers, book chapters, reviews and books. Through bibliometric analysis, the study examined the effectiveness of different publication types and identified the main topics and themes within the field.

The study found that the field of big data in librarianship is growing rapidly, with a significant increase in publications and citations over the past few years. China is the leading country in terms of publication output, followed by the United States of America. The most influential journals in the field are Library Hi Tech and the ACM International Conference Proceeding Series. The top authors in the field are Minami T, Wu J, Fox EA and Giles CL. The most common keywords in the literature are big data, librarianship, data mining, information retrieval, machine learning and webometrics.

This bibliometric study contributes to the existing body of literature by comprehensively analyzing the latest trends and patterns in big data applications within librarianship. It offers a systematic approach to understanding the state of the field and highlights the unique contributions made by various types of publications. The study’s findings and insights contribute to the originality of this research, providing a foundation for further exploration and advancement in the field of big data in librarianship.