Search results

The study aims to investigate the utilisation of open research data repositories (RDRs) for storing and sharing research data in higher learning institutions (HLIs) in Tanzania.

A survey research design was employed to collect data from postgraduate students at the Nelson Mandela African Institution of Science and Technology (NM-AIST) in Arusha, Tanzania. The data were collected and analysed quantitatively and qualitatively. A census sampling technique was employed to select the sample size for this study. The quantitative data were analysed using the Statistical Package for the Social Sciences (SPSS), whilst the qualitative data were analysed thematically.

Less than half of the respondents were aware of and were using open RDRs, including Zenodo, DataVerse, Dryad, OMERO, GitHub and Mendeley data repositories. More than half of the respondents were not willing to share research data and cited a lack of ownership after storing their research data in most of the open RDRs and data security. HILs need to conduct training on using trusted repositories and motivate postgraduate students to utilise open repositories (ORs). The challenges for underutilisation of open RDRs were a lack of policies governing the storage and sharing of research data and grant constraints.

Research data storage and sharing are of great interest to researchers in HILs to inform them to implement open RDRs to support these researchers. Open RDRs increase visibility within HILs and reduce research data loss, and research works will be cited and used publicly. This paper identifies the potential for additional studies focussed on this area.

The overall goal of science is to build a valid and reliable body of knowledge about the functioning of the world and how applying that knowledge can change it. As personnel and human resources management researchers, we aim to contribute to the respective bodies of knowledge to provide both employers and employees with a workable foundation to help with those problems they are confronted with. However, what research on research has consistently demonstrated is that the scientific endeavor possesses existential issues including a substantial lack of (a) solid theory, (b) replicability, (c) reproducibility, (d) proper and generalizable samples, (e) sufficient quality control (i.e., peer review), (f) robust and trustworthy statistical results, (g) availability of research, and (h) sufficient practical implications. In this chapter, we first sing a song of sorrow regarding the current state of the social sciences in general and personnel and human resources management specifically. Then, we investigate potential grievances that might have led to it (i.e., questionable research practices, misplaced incentives), only to end with a verse of hope by outlining an avenue for betterment (i.e., open science and policy changes at multiple levels).

This study aims to investigate the factors influencing the data sharing habits of psychologists with respect to academic reciprocity.

A research model was developed based on Ostrom’s (2003) theory of collective action to map psychologists’ underlying motivations for data sharing. The model was validated by data from a survey of 427 psychologists, primarily from the psychological sciences and related disciplines.

This study found that data sharing among psychologists is driven primarily by their perceptions of community benefits, academic reciprocity and the norms of data sharing. This study also found that academic reciprocity is significantly influenced by psychologists’ perceptions of community benefits, academic reputation and the norms of data sharing. Both academic reputation and academic reciprocity are affected by psychologists’ prior experiences with data reuse. Additionally, psychologists’ perceptions of community benefits and the norms of data sharing are significantly affected by the perception of their academic reputation.

This study suggests that Ostrom’s (2003) theory of collective action can provide a new theoretical lens in understanding psychologists’ data sharing behaviours.

This study suggests several practical implications for the design and promotion of data sharing in the research community of psychology.

To the best of the authors’ knowledge, this is one of the initial studies that applied the theory of collective action to the mechanisms of reputation, community benefits, norms and reciprocity in psychologists’ data sharing behaviour. This research demonstrates that perceived community benefits, academic reputation and the norms of data sharing can all encourage academic reciprocity, and psychologists’ perceptions of community benefits, academic reciprocity and data sharing norms all facilitate their data sharing intentions.

Budget hotels are becoming an emerging industry for convenience and affordability, where consumer sentiments are of paramount importance. Tourism has become increasingly dependent on social media and online platforms to gather travel-related information, purchase travel products, food, lodging, etc., and share views and experiences. The user-generated data helps companies make informed decisions through predictive and behavioural analytics.

Design/Methodology/Approach: This study uses text mining, deep learning, and machine learning techniques for data collection and sentiment analysis based on 117,151 online reviews of the customers posted on the TripAdvisor website from May 2004 to May 2019 from 197 hotels of five prominent budget hotel groups spread across India using Feedforward Neural Network along with Keras package and Softmax activation function.

Findings: The word-of-mouth turns into electronic word-of-mouth through social networking sites, with easy access to information that enables customers to pick a budget hotel. We identified 20 widely used words that most customers use in their reviews, which can help managers optimise operational efficiency by boosting consumer acceptability, satisfaction, positive experiences, and overcoming negative consumer perceptions.

Practical Implications: The analysis of the review patterns is based on real-time data, which is helpful to understand the customer’s requirements, particularly for budget hotels.

Originality/Value: We analysed TripAdvisor reviews posted over the last 16 years, excluding the Corona period due to industry crises. The findings reverberate in consonance with the performance improvement theory, which states feed-forward a neural network enhances organisational, process, and individual-level performance in the hospitality industry based on customer reviews.

It is estimated that nearly 2 billion world population is now living in countries affected by extreme forms of violence, war, and criminal activities (World Bank, 2016). Apart from being affected by war and having higher poverty rates, millions are affected by climate-related disasters, pandemics which have destroyed livelihoods and lives. In 2011 and 2012 alone, more than 450 million individuals faced environmental crises (Blankespoor et al., 2010; Laframboise & Loko, 2012). Human rights advocates that every individual has the right to live with dignity and respect. International agencies are trying their best to ensure that everyone, and mainly the vulnerable communities, gets assistance in a manner that is consistent with human rights and includes the right to participation and non-discrimination. One such right is the right to education, a right which has been articulated in numerous conventions and documents and has been a part of policy maker’s debate. In emergency situations, whether man-made or a natural disaster, students face an acute crisis of accessing higher education, even when the country is limping back to normalcy. The book Higher Education in Emergencies: International Case Studies discusses the impact of the COVID-19 pandemic on teaching and learning practice in higher education in different countries and highlights the cultural transformation of policy and practice. In addition, the authors propose future directions on how to be prepared and address the challenges of emergencies and draw implications of their findings beyond the national context.

The Internet of Things (IoT) is perceived as an evolving trend in the tourism industry, with the potential to change its dynamics. IoT will help destinations, airlines, hotels and cruises personalise their services for tourists and guests. Moreover, it has several advantages for them, such as cost savings, increased productivity, greater efficiency and customised and differentiated services. The readers of this chapter will learn about the trends of IoT in the tourism industry, discover its benefits and learn about the most critical applications.

Scholarly interest in the business effects of organised crime (OC) has recently increased. This study aims to conduct a systematic literature review (SLR) on the conditions under which OC could pose a threat to or take control of firms within a particular context.

We use narrative synthesis and thematic analysis, with a sample of 46 theoretical and empirical studies published over the past 30 years on the relationship between OC and firms within the disciplines of Business, Management and Accounting (BMA).

SLR and thematic analysis show that scholarly interest has focused on four key domains: OC as a firm, the impact of OC on firms, firms’ efforts to counter OC’s influence and governmental interventions. Using medical metaphors, we also develop a diagram depicting the interplay between OC and firms within the BMA literature.

This study contributes to the literature shaping an agenda to steer future research towards these four key themes. The effectiveness of anti-OC tools and measures depends on a thorough understanding of local norms, behaviours and business practices. In addition to measurement and methodological challenges, several grey areas remain, including the distinction between criminal enterprises and legitimate businesses. Ambiguities also surround the circumstances under which the OC preys upon firms or employs them to establish dominance over a territory.

Settlement services in Canada have only recently started offering support and programming for emotional wellness issues faced by newcomers to Canada (immigrants who have been in Canada for less than 5 years). Funding for such services has steadily increased over the past 5 years, particularly in the wake of the COVID-19 pandemic. Greater investment in ensuring the emotional wellness of immigrants is spurring new settlement services and programming. These include a wide array of configurations and approaches across the different geographies of Canada. This is evidence that providing such services for newcomers is in the early stages of implementation, characterised by experimentation and precarity. Mental and emotional wellness programming is in contrast with more established services, such as those meant to provide language learning, where common assessment tools, measures of proficiency and progress are well established. With funding from the Immigration, Refugees and Citizenship Canada (IRCC), this chapter features data from a 2-year project that examined emotional wellness services for immigrants offered in four cities in western Canada between 2018 and 2020. The study used surveys and interviews with clients and focus groups with front-line staff to understand client needs and discern the issues and impact of emotional wellness programming. Findings include apparent limitations in staff capacity and expertise to provide help when needed, the inappropriateness of service models meant for other contexts and complex funding requirements resulting in issues of access and the overall precarity of such programming.

In the last few years, the size of Linked Open Data (LOD) describing artworks, in general or domain-specific Knowledge Graphs (KGs), is gradually increasing. This provides (art-)historians and Cultural Heritage professionals with a wealth of information to explore. Specifically, structured data about iconographical and iconological (icon) aspects, i.e. information about the subjects, concepts and meanings of artworks, are extremely valuable for the state-of-the-art of computational tools, e.g. content recognition through computer vision. Nevertheless, a data quality evaluation for art domains, fundamental for data reuse, is still missing. The purpose of this study is filling this gap with an overview of art-historical data quality in current KGs with a focus on the icon aspects.

This study’s analyses are based on established KG evaluation methodologies, adapted to the domain by addressing requirements from art historians’ theories. The authors first select several KGs according to Semantic Web principles. Then, the authors evaluate (1) their structures’ suitability to describe icon information through quantitative and qualitative assessment and (2) their content, qualitatively assessed in terms of correctness and completeness.

This study’s results reveal several issues on the current expression of icon information in KGs. The content evaluation shows that these domain-specific statements are generally correct but often not complete. The incompleteness is confirmed by the structure evaluation, which highlights the unsuitability of the KG schemas to describe icon information with the required granularity.

The main contribution of this work is an overview of the actual landscape of the icon information expressed in LOD. Therefore, it is valuable to cultural institutions by providing them a first domain-specific data quality evaluation. Since this study’s results suggest that the selected domain information is underrepresented in Semantic Web datasets, the authors highlight the need for the creation and fostering of such information to provide a more thorough art-historical dimension to LOD.

This study aimed to examine the antecedents, correlates, and consequences of burnout among higher education faculty in Saudi Arabia using the theoretical framework of the job demands-resources model.

Using a quantitative research design, a cross-sectional survey was employed to collect data from faculty members across multiple Saudi universities. The constructs were measured using validated scales, and data analysis included exploratory factor analysis, Pearson correlation analysis, factorial ANOVA, and multiple regression.

The study identified moderate levels of burnout, confirming a significant positive relationship with role conflict and a negative relationship with internal locus of control. Burnout significantly contributed to depression, insomnia, and turnover intentions. However, no significant relationship was found between burnout and workplace conflict when controlling for other variables.

The study's findings can inform policymakers and academic administrators about measures to alleviate faculty burnout, thus contributing to healthier academic work environments aligned with Saudi Arabia's Vision 2030 goals.

This research extends the job demands-resources model within the context of higher education institutions in Saudi Arabia, offering nuanced insights into burnout dynamics among university faculty in this region. Despite the model's robustness, the absence of a significant relationship between burnout and workplace conflict signals the need for a more intricate understanding of burnout's antecedents and consequences.