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Most cervical cancers are caused by genital human papillomavirus (HPV). However, it can be prevented if females receive an HPV vaccine. Nevertheless, there is limited evidence of HPV vaccination and predictors of intention to obtain the vaccine among young women in Thailand. The paper aims to discuss this issue.

This cross-sectional study examined HPV vaccination and factors influencing intention to vaccinate among a convenient sample of college women in Thailand. The data collection was conducted via a self-administered “HPV and HPV vaccine-related knowledge, attitudes, and behaviors” questionnaire.

Out of 1,030 participants, 309 (30.0 percent) were aware of HPV and the HPV vaccine. Out of these, 257 participants reported that they had not obtained the vaccine and 18 participants were unsure if they had already obtained the vaccine or not. Only 34 participants confirmed that they had received the vaccine. Among those who were aware of HPV and the HPV vaccine, 56.4 percent of them did not know that most HPV-infected persons do not show any signs or symptoms, and 53.3 percent thought that the vaccine provided protection against other sexually transmitted infections as well. Most had positive attitudes toward vaccination and subjective norms. Among the participants who had not received the vaccine, the intention to obtain the vaccine was predicted by age, knowledge, attitudes toward vaccination, and subjective norms. The reasons for not being vaccinated included the cost of the vaccine, lack of knowledge, and perception of themselves being at low risk.

This study found low HPV vaccination among college women. However, those who had not received the vaccine intended to obtain the vaccine at some point in the future. An HPV vaccination campaign may be well tailored in order to increase the intention to obtain the vaccine which, in turn, may increase the HPV vaccination. Vaccination cost sharing should be discussed among Thai policy makers in order to alleviate the financial burden for women.

The purpose of this paper is to analyse and evaluate the effect of customer experience management (virtual interaction, physical interaction and service interaction) on customer loyalty in the banking industry.

The study followed an explanatory research design to sample 384 respondents. Stepwise regression analysis was used to validate the relevance of the study model.

The results indicated that there is a positive association between customer experience management and customer loyalty. The dimensions of customer experience management, namely virtual interaction, physical interaction and service interaction, were also found to be statistically significant in explaining customer loyalty behaviour.

The study practically influences the way banks and other financial institutions gain competitive advantage through managing the experiences of customers in a volatile business environment. At a time when banks are no longer the only providers of financial services, the study offers a road map to reduce portfolio purchasing and switching behaviour through enhanced experience management at all customer touch points.

The study presents an augmented model of customer experience management which is linked to consumer loyalty.

Mobile phone-based human activity recognition (HAR) consists of inferring user’s activity type from the analysis of the inertial mobile sensor data. This paper aims to mainly introduce a new classification approach called adaptive k-nearest neighbors (AKNN) for intelligent HAR using smartphone inertial sensors with a potential real-time implementation on smartphone platform.

The proposed method puts forward several modification on AKNN baseline by using kernel discriminant analysis for feature reduction and hybridizing weighted support vector machines and KNN to tackle imbalanced class data set.

Extensive experiments on a five large scale daily activity recognition data set have been performed to demonstrate the effectiveness of the method in terms of error rate, recall, precision, F1-score and computational/memory resources, with several comparison with state-of-the art methods and other hybridization modes. The results showed that the proposed method can achieve more than 50% improvement in error rate metric and up to 5.6% in F1-score. The training phase is also shown to be reduced by a factor of six compared to baseline, which provides solid assets for smartphone implementation.

This work builds a bridge to already growing work in machine learning related to learning with small data set. Besides, the availability of systems that are able to perform on flight activity recognition on smartphone will have a significant impact in the field of pervasive health care, supporting a variety of practical applications such as elderly care, ambient assisted living and remote monitoring.

The purpose of this study is to build and test an accurate offline model by using only a compact training data that can reduce the computational and memory complexity of the system. This provides grounds for developing new innovative hybridization modes in the context of daily activity recognition and smartphone-based implementation. This study demonstrates that the new AKNN is able to classify the data without any training step because it does not use any model for fitting and only uses memory resources to store the corresponding support vectors.

This research seeks to explain the mediating function of workplace happiness in enhancing employee engagement through the drivers of employee engagement among the IT sector employees of India.

Quantitative data were acquired from 104 respondents from the Indian IT industry via an online survey utilizing Google Forms, employing a stratified random sample method. The study hypotheses were tested using PLS-SEM.

Results indicated that workplace happiness positively mediates employee engagement and drivers of employee engagement.

The current study followed a cross-sectional analysis where establishing causality is difficult; however, there is a scope to do longitudinal study on the same phenomenon. Research data are produced through online surveys. Possible sources of bias may be selective memory, attribution and/or exaggeration. This study covers specific variables of workplace happiness and drivers of employee engagement other variables remain unaddressed, such as COVID-19-related impacts. The nature of the industry and sample size were limited.

This study shows that workplace happiness has a mediating effect on both drivers of employee engagement and employee engagement; as a result, organizations should consider the function of workplace happiness as a mediating factor when implementing drivers of employee engagement and employee engagement.

On the social level, this research will help organizations to understand the drivers for employee engagement and linkages between workplace happiness and employee engagement. It hopes to create more happy workplaces and have good social impact.

This is the first study to look into the function of workplace happiness as a mediator between the drivers of work engagement and work engagement.

This paper aims to explore the role of libraries and librarians in promoting appropriate cyberethical behaviour among postgraduate students in Nigeria.

Using content analysis and a review of relevant literature, this study examines the challenges that librarians face in enforcing cyberethics and highlights the strategies that libraries can adopt to promote responsible online behaviour.

This paper identifies the lack of awareness among postgraduate students regarding cybersecurity risks and the need for training and resources for librarians as key challenges in promoting cyberethics.

This study recommends that libraries provide access to training resources and develop policies and guidelines to promote cyberethics among postgraduate students. Overall, this paper argues that libraries and librarians can play a critical role in promoting responsible online behaviour and ensuring the safety and security of postgraduate students in Nigeria.

This study aims to promote the need for advanced skills acquisition within the LIS and academic libraries. This study focuses on the importance of library management systems and the need for the graduates to be equipped with analytics skills. Combined with basic data, text mining and analytics, knowledge classification and information audit skills would benefit libraries and improve resource allocation. Agile institutional libraries in this big data era success hinge on the ability to perform depth analytics of both data and text to generate useful insight for information literacy training and information governance.

This paper adopted a living-lab methodology to use existing technology to conduct system analysis and LMS audit of an academic library of one of the highly ranked universities in the world. One of the benefits of this approach is the ability to apply technological innovation and tools to carry out research that is relevant to the context of LIS or other research fields such as management, education, humanities and social sciences. The techniques allow us to gain access to publicly available information because of system audits that were performed. The level of responsiveness of the online library was accessed, and basic information audits were conducted.

This study indicated skill gaps in the LIS training and the academic libraries in response to the fourth industrial technologies. This study argued that the role of skill acquisition and how it can foster data-driven library management operations. Hence, data mining, text mining and analytics are needed to probe into such massive, big data housed in the various libraries’ repositories. This study, however, indicated that without retraining of librarians or including this analytics programming in the LIS curriculum, the libraries would not be able to reap the benefits these techniques provided.

This paper covered research within the general and academic libraries and the broader LIS fields. The same principle and concept is very important for both public and private libraries with substantial usage and patrons.

This paper indicated that librarianship training must fill the gaps within the LIS training. This can be done by including data mining, data analytics, text mining and processing in the curriculum. This skill will enable the news graduates to have skills to assist the library managers in making informed decisions based on user-generated content (UGC), LMS system audits and information audits. Thus, this paper provided practical insights and suggested solutions for academic libraries to improve the agility of information services.

The academic librarian can improve institutional and LMS management through insights that are generated from the user. This study indicated that libraries' UGC could serve as robust insights into library management.

This paper argued that the librarian expertise transcends information literacy and knowledge classification and debated the interwoven of LMS and data analytics, text mining and analysis as a solution to improve efficient resources and training.

The paper aims to address the organizational transformation of firms for value creation resulting from cloud computing (CC).

With reference to the theory of organizational fit, we modeled organizational transformation as a function of five aspects of CC practice: functionality, data management, roles and competences of information technology services, control and organizational culture. The output variable was tested against a set of input variables defined with reference to the technology–organization–environment (TOE) and technology acceptance model (TAM). Based on a sample of 487 companies in seven countries in Europe, Asia, and the United States, the authors distinguished two groups of firms: transformational and hyper transformational.

The results highlight the key factors that determine whether a firm falls into one of these two groups, and include perceived usefulness and perceived ease of use, complexity and compatibility of CC technology, and adequacy of resources. Top management support and government policy are found to only play a role for the transformational group while, surprisingly, vendor support had no impact for either group.

This research contributes to the literature on the role of digital transformation in value creation and on digitization of firms and organizational design, notably by considering the contribution of CC to the organizational dimension. To the best of the authors’ knowledge, this is the first study to make the link between TOE and TAM models and organizational fit theory, thereby going beyond the general approach to adoption found in information system research.

The prenatal distress level of the pregnant woman is influenced by many variables. Personality characteristics are one of the most important of these variables. Knowing personality characteristics of pregnant women contributes to the personalization of care. The purpose of this paper is to identify the effect of personality characteristics of pregnant women at risk on the prenatal distress level.

A total of 438 women who were hospitalized based on a medical diagnosis associated with pregnancy were included in the study. The participants were administered the Personal Information Form, Cervantes Personality Scale and Revised Prenatal Distress Questionnaire. Data were evaluated using the SPSS 22.0 software program.

Of the pregnant women, 27.4 percent found their ability to cope with stress insufficient, and one-fifth of them found their social support insufficient. The pregnant women at risk with introverted, neurotic and inconsistent personality were found to have high levels of prenatal distress.

This study was conducted on a group of Turkish pregnant women and cannot be generalized to other cultures. The data obtained from the research cannot be used to evaluate the psychological and physical disorders of the pregnant woman.

All health care professionals should evaluate women not only physically but also mentally and emotionally, beginning with the preconceptional period. They should determine the conditions that create distress and identify the personality characteristics that prevent from coping with stress. By using cognitive and behavioral techniques, pregnant women should be trained to gain skills on subjects such as risk perception and stress management, personality characteristics and coping, problem solving, psychological endurance and optimism. Caring initiatives should be personalized in line with personality characteristics of pregnant women. The care offered within this framework will contribute to the strengthening and development of the health of not only the women but also the family and society, and to the reduction of health care costs.

Researchers have determined that pregnant women at risk with introverted, neurotic and inconsistent personality characteristics have higher distress levels. They have determined that these pregnant women find their ability to cope with stress more inadequate. It is vital to cope with stress during pregnancy due to its adverse effects on maternal/fetal/neonatal health.

The prenatal distress level of the pregnant woman is influenced by many demographic (age, marital status and socioeconomic level), social (marital dissatisfaction, and lack of social support), personal (self-esteem, neuroticism and negative life experiences) and pregnancy-related (experiencing risky pregnancy, and previous pregnancy experiences) variables. Personality characteristics are one of the most important of these variables. This research is original because there are limited number of studies examining the effect of personality characteristics on prenatal distress level in the literature. And knowing the relationship between personality characteristics and distress by health professionals enables individualization of care. The care offered within this framework will contribute to the strengthening and development of the health of not only the women, but also the family and society, and to the decrease of health care costs.

The Cloud of Things (IoT) that refers to the integration of the Cloud Computing (CC) and the Internet of Things (IoT), has dramatically changed the way treatments are done in the ubiquitous computing world. This integration has become imperative because the important amount of data generated by IoT devices needs the CC as a storage and processing infrastructure. Unfortunately, security issues in CoT remain more critical since users and IoT devices continue to share computing as well as networking resources remotely. Moreover, preserving data privacy in such an environment is also a critical concern. Therefore, the CoT is continuously growing up security and privacy issues. This paper focused on security and privacy considerations by analyzing some potential challenges and risks that need to be resolved. To achieve that, the CoT architecture and existing applications have been investigated. Furthermore, a number of security as well as privacy concerns and issues as well as open challenges, are discussed in this work.