Search results

The purpose of this paper is to ascertain if practising healthy lifestyles improves the technical efficiency of farms in Kwara state, Nigeria. In theory, all deviations from the optimum level of output are due to random effects and inefficiency of producers in which their health plays a key part and is dependent on the kind of lifestyle practiced whether healthy or unhealthy.

Cross-sectional data were employed through a three-staged sampling technique to pick 320 arable crop farmers across the state using a well-defined questionnaire. Data analysis was carried out using descriptive statistics, healthy lifestyles index (HLI), stochastic production frontier (SPF) and propensity score matching (PSM).

First, the analysis showed that about one-third of the sampled arable crop farmers practised healthy lifestyles. Second, the average technical efficiency of arable crop production for farmers who practised a healthy lifestyle was 0.893, and the level of technical inefficiency of the farms was determined by health-related lifestyle status, number of day's illness and educational level. Third, technical efficiency was improved by 0.00431067 for farms whose farmers practised a healthy lifestyle.

Rather than seeing that technical efficiencies of farms are attributed to farm characteristics, inputs used and socioeconomic characteristics alone, the findings suggest that technical inefficiencies of arable crop farmers were also due to the kind of lifestyle practised, which was evidenced in the increased efficiency for farmers who practised healthy lifestyle.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0353

Home is a place/system/product that becomes increasingly occupied with various tasks used to be performed in workplaces. However, the knowledge of the relationship between residential physical environments and occupant experience is limited, especially when considering the effect of indoor plants (IPs) and climate zones. To address the gap, this study conducted a questionnaire survey in three cities across different regions in China.

Based on User Experience and Customer Satisfaction Index theory, following the research paradigm, a total of 627 valid samples were collected and analyzed in a stepwise statistical analysis, including descriptive statistics, reliability and validity test, correlation test and region comparison, then the model of PROCESS was adopted to examine the hypotheses that are given based on the former studies.

The results showed that residential physical environments have a significant effect on occupant satisfaction (OS) in all regions, as well as OS on occupant performance. However, regional differences were found that OS is a complete mediator in the Middle region, while a partial mediator in the North and South. A slight moderating effect of IPs was also found in the region of South. Nevertheless, both the number of plants and plant types have a significant moderating effect on the mechanism.

Besides combining two theories and confirming the mechanism in the residential physical environment, it is also the first study to consider the moderating effects of IPs and climate zones, providing potential empirical support for not only design and management stages but also facing global challenges of working at home and climate changes.

With gaining popularity, online communities are increasing. It is leading to the data and information overflow. So, there are some challenges like cyber frauds, cyberbullying, etc. while engaging with online communities. Not only this, anonymity of the participants, stress and racism are also big challenges in online communities' interaction. Online harassers' attack tactics have changed over time. In addition, there are challenges like quality of discussion, inequality in participation of the users, etc. may scale online communities towards incitement and activism. Therefore, this study will try to analyse these challenges for overall benefit of the society.

The underlying fuzzy set theory is employed to handle the fuzziness of users' perceptions since the attributes are expressed in linguistic preferences. Through exhaustive literature review, the authors have identified 15 challenges. These challenges are further categorised as cause and effect by using DEMATEL (Decision-Making Trial and Evaluation Laboratory) approach.

Lack of strategic planning and uninspired discussions between users has emerged as a major challenge in cause category. This study further demonstrates how individual challenge can be managed and developed to navigate the online communities to maintain a healthy environment in society.

Results are based on limited dataset. Therefore, findings cannot be generalised for all online communities.

The research findings offer a suitable direction to policymakers to formulate and design policies, laws and regulations to increase user engagement in the online community. The study is beneficial to firms and researchers in understanding the factors influencing effective management of online communities.

This study aims to examine Big Data and the management of libraries in the era of the Fourth Industrial Revolution and its implications for policymakers in Nigeria.

A qualitative methodology was used, involving the administration of open-ended questionnaires to librarians from six selected federal universities located in Southwest Nigeria.

The findings of this research highlight that a significant proportion of librarians are well-acquainted with the relevance of big data and its potential to positively revolutionize library services. Librarians generally express favorable opinions concerning the relevance of big data, acknowledging its capacity to enhance decision-making, optimize services and deliver personalized user experiences.

This study exclusively focuses on the Nigerian context, overlooking insights from other African countries. As a result, it may not be possible to generalize the study’s findings to the broader African library community.

To the best of the authors’ knowledge, this study is unique because the paper reported that librarians generally express favorable opinions concerning the relevance of big data, acknowledging its capacity to enhance decision-making, optimize services and deliver personalized user experiences.

The primary objective of this research is to identify and analyze the influence of digital marketing practises on performance of business of manufacturing enterprises in Delhi-NCR. A quantitative and descriptive research design was implemented in this study. 368 participants from various enterprises were chosen. Questionnaires were used to collect data on the benefits and challenges which are perceived of digital marketing, as well as usage and business performance of these enterprises. SPSS v24.0 is utilized to carry out statistical analysis on the collected data. The study discovered that advantages and problems of digital marketing practices influenced the usage of digital marketing. Furthermore, the execution of digital marketing had a prominent influence on sales and total number of customers of these enterprises, and this relationship was moderated by type and size of businesses. It was discovered that using digital marketing strategies increased business profits by raising digital marketing awareness among consumers and various industries. It made digital marketing easier to implement in various businesses. However, research should be conducted for appropriate generalization in a larger scale.

This study aims to propose a force control algorithm based on neural networks, which enables a robot to follow a changing reference force trajectory when in contact with human skin while maintaining a stable tracking force.

Aiming at the challenge of robots having difficulty tracking changing force trajectories in skin contact scenarios, a single neuron algorithm adaptive proportional – integral – derivative online compensation is used based on traditional impedance control. At the same time, to better adapt to changes in the skin contact environment, a gated recurrent unit (GRU) network is used to model and predict skin elasticity coefficients, thus adjusting to the uncertainty of skin environments.

In two robot–skin interaction experiments, compared with the traditional impedance control and robot force control algorithm based on the radial basis function model and iterative algorithm, the maximum absolute force error, the average absolute force error and the standard deviation of the force error are all decreased.

As the training process of the GRU network is currently conducted offline, the focus in the subsequent phase is to refine the network to facilitate real-time computation of the algorithm.

This algorithm can be applied to robot massage, robot B-ultrasound and other robot-assisted treatment scenarios.

As the proposed approach obtains effective force tracking during robot–skin contact and is verified by the experiment, this approach can be used in robot–skin contact scenarios to enhance the accuracy of force application by a robot.

This study explores cybersecurity behavior in the metaverse, focusing on the opportunities, challenges and future trends for libraries. This study aims to assess the evolving threats in virtual environments and the role libraries play in addressing cybersecurity in these immersive digital spaces.

This research uses a narrative review approach, synthesizing existing literature on cybersecurity threats in the metaverse, vulnerabilities of metaverse platforms and user behavior risks. It also examines how libraries can mitigate these risks while leveraging metaverse technologies.

This study identifies significant cybersecurity risks in the metaverse, including data breaches, identity theft and virtual property theft. It also highlights the vulnerabilities of metaverse platforms, such as weak user authentication and system integration challenges. Moreover, user behavior – like weak passwords and susceptibility to social engineering – amplifies these risks. Libraries have an opportunity to enhance digital literacy and cybersecurity education but face technological and skill-based barriers.

This study provides a novel exploration of how libraries can address cybersecurity concerns in the metaverse. It highlights the importance of proactive measures and evolving technologies in ensuring a safe virtual experience.

This study aims to identify the librarians’ readiness to leverage artificial intelligence for sustainable competence development and smart library services.

This study used a quantitative research design for addressing the objectives. The population consisted of librarians from the public and private sector universities of Pakistan. The data were analyzed by using Smart PLS software.

The analysis consisted of two major parts: first the assessment of measurement model and second the structural equation modeling analysis. A significant positive impact of AI adoption was found on the implementation smart library services. Findings revealed that behavioral intention motivated librarians to adopt AI tools in university libraries for the delivery of smart library services.

We applied quantitative method to carry out the study while future authors may conduct a systematic literature review on the same topic for offering a broader outlook.

It has provided practical contributions by providing a baseline for management bodies to construct policies for the successful adoption of AI in libraries for sustainable competence development of practicing librarians and implementation of smart library services.

The study has social implications too as AI integrated library services prove fruitful for society and digitally skilled librarians play a vital role for the promotion of reading and research culture in society.

To the best of the authors’ knowledge, this is the first study on librarians’ readiness to leverage artificial intelligence for the enhancement of digital literacy skills, sustainable competence development and smart library services in the context of Pakistan.

Quality of life is dependent on a healthy lifestyle and the self-care behavior of individuals. The study's purpose is to find out the determinants of individuals' self-care behavior. As such, self-care behavior is influenced by several factors that include individual knowledge, available information sources and their use, information-seeking related skills and cognitive state.

A quantitative research design followed using a questionnaire-based survey method. A total of 384 responses from the Pakistani public were collected using the convenience sampling technique. Structural equation modeling (SEM) was performed for examining the possible link between the variables.

Health literacy, Internet and social media use, and health information-seeking behavior had a direct/indirect positive impact on self-care behavior, but health anxiety had a negative impact. Health literacy and health information-seeking behavior positively mediated the relationship among Internet and social media use health anxiety and self-care.

Improving health literacy appears to be key to supporting better self-care, but it is an exploratory study, more research is required to confirm these findings. Policymakers, health professionals and information professionals should work together to improve health literacy and support informed self-care among the population.

Thus far, no previous study has examined the collective role of social media exposure, health anxiety, health literacy and health information-seeking behavior as predictors of self-care behavior. Although self-care behavior among the general population might be different compared to chronic patients, only few studies have examined the former as a unit of analysis.

This study aims to identify the effects of artificial intelligence (AI) on university libraries and to reveal challenges associated with the adoption of AI-powered applications in libraries.

A systematic literature review (SLR) was applied to address the study’s objectives. The 25 most relevant seminal studies published in Scopus- and Web of Science-indexed journals were selected to conduct the study.

Findings revealed that AI has strong positive effects on university libraries. These effects included efficiency and promotion of library products, innovative library services, alignment of library services with the fourth industrial revolution (4IR), collection management and user services and transformation of library systems. Results also manifested that skills and knowledge barriers, financial and resource constraints and resistance to change created challenges to adopt AI-based services in university libraries.

This study has added valuable literature to the existing body of knowledge by conducting SLR on the basis of 25 most relevant research articles published in cite score and impact factor journals. It has provided practical implications by offering recommendations to adopt AI in university libraries. The study is a benchmark for policymakers, AI applications developers, higher education bodies, government representatives, university administration and library leadership to devise effective strategies and methods for the efficient adoption of AI in libraries. The study has also provided a framework to adopt AI applications in library settings.