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The purpose of this paper is to provide an overview of the trends and challenges relating to research into the human aspects of ransomware.

A systematic mapping study was carried out to investigate the trends in studies into the human aspects of ransomware, identify challenges encountered by researchers and propose directions for future research. For each of the identified papers from this study, the authors mapped the year of publication, the type of paper, research strategy and data generation method, types of participants included, theories incorporated and lastly, the authors mapped the challenges encountered by the researchers.

Fifty-nine papers published between 2006 and 2022 are included in the study. The findings indicate that literature on the human aspects of ransomware was scarce prior to 2016. The most-used participant groups in this area are students and cybersecurity professionals, and most studies rely on a survey strategy using the questionnaire to collect data. In addition, many papers did not use theories for their research, but from those that did, game theory was used most often. Furthermore, the most reported challenge is that being hit with ransomware is a sensitive topic, which results in individuals and organisations being reluctant to share their experiences.

This mapping study reveals that the body of literature in the area of human aspects of ransomware has increased over the past couple of years. The findings highlight that being transparent about ransomware attacks, when possible, can help others. Moreover, senior management plays an important role in shaping the information security culture of an organisation, whether to have a culture of transparency or of secrecy.

This study is the first of its kind of systematic mapping studies contributing to the body of knowledge on the human aspects of ransomware.

This paper aims to curate open research knowledge graph (ORKG) with papers related to ontology learning and define an approach using ORKG as a computer-assisted tool to organize key-insights extracted from research papers.

Action research was used to explore, test and evaluate the use of the Open Research Knowledge Graph as a computer assistant tool for knowledge acquisition from scientific papers.

To extract, structure and describe research contributions, the granularity of information should be decided; to facilitate the comparison of scientific papers, one should design a common template that will be used to describe the state of the art of a domain.

This approach is currently used to document “food information engineering,” “tabular data to knowledge graph matching” and “question answering” research problems and the “neurosymbolic AI” domain. More than 200 papers are ingested in ORKG. From these papers, more than 800 contributions are documented and these contributions are used to build over 100 comparison tables. At the end of this work, we found that ORKG is a valuable tool that can reduce the working curve of state-of-the-art research.

The paper aims to provide companies with a better understanding of the needs of institutional investors to improve the disclosure of sustainability information by companies. The study investigates the changed information needs of institutional investors resulting from the Sustainable Finance Disclosure Regulation (SFDR).

This study uses an internet-based survey instrument amongst institutional investors to gain insights into their needs regarding sustainability information. The authors received 155 responses in total and use descriptive statistics and t-tests to analyse the survey data.

The results demonstrate that the implementation of the SFDR challenges institutional investors, as it affects their decision process. Additionally, the findings still indicate a lack of available corporate sustainability information, making it even more challenging for institutional investors to make appropriate investment decisions. Respondents suggest that information on climate-related risks is more important than the European Union (EU) Taxonomy metrics for meeting the SFDR requirements.

The findings are mainly restricted to the opinion of European investors. However, the evidence contributes to the existing literature by investigating institutional investors' information needs in the new regulatory landscape.

As the study provides insights into institutional investors' needs, reporting companies recognise the relevance of transparently providing sustainability information to be further considered in the investment process of institutional investors despite the regulation. The findings can help regulators develop uniform and global sustainability reporting standards.

This paper is the first to provide evidence on sustainability information requested on the institutional investors' side. The survey gathers primary data from professional investment members unavailable in databases or reports.

This study aims to compare traffic sign (TS) and obstacle detection for autonomous vehicles using different methods. The review will be performed based on the various methods, and the analysis will be done based on the metrics and datasets.

In this study, different papers were analyzed about the issues of obstacle detection (OD) and sign detection. This survey reviewed the information from different journals, along with their advantages and disadvantages and challenges. The review lays the groundwork for future researchers to gain a deeper understanding of autonomous vehicles and is obliged to accurately identify various TS.

The review of different approaches based on deep learning (DL), machine learning (ML) and other hybrid models that are utilized in the modern era. Datasets in the review are described clearly, and cited references are detailed in the tabulation. For dataset and model analysis, the information search process utilized datasets, performance measures and achievements based on reviewed papers in this survey.

Various techniques, search procedures, used databases and achievement metrics are surveyed and characterized below for traffic signal detection and obstacle avoidance.

The purpose of this study was to analyze importance of artificial intelligence (AI) in education and its emphasis on assessment and adversity quotient (AQ).

The study utilizes a systematic literature review of over 141 journal papers and psychometric tests to evaluate AQ. Thematic analysis of quantitative and qualitative studies explores domains of AI in education.

Results suggest that assessing the AQ of students with the help of AI techniques is necessary. Education is a vital tool to develop and improve natural intelligence, and this survey presents the discourse use of AI techniques and behavioral strategies in the education sector of the recent era. The study proposes a conceptual framework of AQ with the help of assessment style for higher education undergraduates.

Research on AQ evaluation in the Indian context is still emerging, presenting a potential avenue for future research. Investigating the relationship between AQ and academic performance among Indian students is a crucial area of research. This can provide insights into the role of AQ in academic motivation, persistence and success in different academic disciplines and levels of education. AQ evaluation offers valuable insights into how individuals deal with and overcome challenges. The findings of this study have implications for higher education institutions to prepare for future challenges and better equip students with necessary skills for success. The papers reviewed related to AI for education opens research opportunities in the field of psychometrics, educational assessment and the evaluation of AQ.

The purpose of this study is to examine the effects of four different sport programs on various social and subjective health outcomes among prisoners.

Four different sport programs (endurance, strength, dance-like martial arts, soccer) were provided in 2020 and 2021 in a German prison. Participants completed paper-pencil surveys before and after the sport programs (n = 134 observations), including questions about potential social health (enjoyment of physical activity, interpersonal exchange, interpersonal trust, self-efficacy) and subjective health outcomes (health status, health satisfaction, well-being). Further information such as prisoner characteristics were added to the data.

Results of regression analyses show that the endurance program had a significant positive effect on interpersonal trust, while the soccer program had a negative effect. Subjective well-being increased significantly after the strength and the soccer program. The weekly sport hours before imprisonment had a positive association with enjoyment of physical activity and interpersonal exchange while being negatively related to health status and health satisfaction. Furthermore, the number of months of imprisonment before the survey, being a young offender, the prisoners’ body mass index, educational level and migration background were significantly associated with several social and subjective health outcomes.

This study analyzed the effects of different sport programs for prisoners on various social and subjective health outcomes, revealing differences across programs and outcomes. The findings suggest that sport can be a way to enhance prisoners’ social and subjective health, ultimately facilitating their rehabilitation process.

Data used to develop the case included primary data from employees and supervisors of a commercial floorcovering manufacturing plant in Northwest Georgia. The case company is not disguised.

The survey was developed using existing instruments from the Organizational Behavior and Human Resources Literature. Instruments were listed in Exhibits 2 through 7. The survey administration had the support of the Vice President for Resources and Facilities, and employees and their supervisors were given time to complete the surveys. The data gathered was analyzed by the researcher using SPSS statistical software.

Established in 1957, J&J started as a family-owned business but had grown and diversified its product offerings by focusing on commercial flooring. It survived several economic downturns and remained competitive in a market dominated by more prominent flooring manufacturers. J&J Industries strived to empower its 800 employees with various incentive programs. Employees remained loyal to J&J; many had worked for the company for over 15 years. However, management wanted to measure the impact of empowering and initiatives on employee performance and satisfaction to determine the real power of employee incentive programs. The Resources and Facilities Vice President employed Professor Lopez, a Management Professor, to develop a survey to measure these constructs and analyze the data to guide future incentive programs. Data from the employee and supervisor survey was provided along with the statistical analysis results for interpretation and recommendations for VP Fordham.

The target audience for this case is primarily students in a research methodology course and students studying quantitative regression analysis and interpretation. The focus is predominantly on graduate-level students in Master of Business Administration or Master of Accounting programs in business. Graduate students should have completed courses in management or organizational behavior, business statistics or quantitative methods or data visualization and cleaning as background knowledge for this case. Specifically, students should understand regression analysis and know when and how the tool is used for managerial decision-making.

The purpose of this study is to explore the awareness, perception and attitude of consumers from Georgia toward smart, active and intelligent packaging of food products.

This study is based on a quantitative research method using a survey questionnaire tool to gather data from consumers in Georgia.

The scope of the sample is restricted to only one developing country. Yet, the research results are still significant in creating knowledge about innovative food packaging from different country contexts and to understanding the acceptance of intelligent active packaging by consumers.

Intelligent packaging facilitates companies with their sustainability efforts by reducing waste and environmental impact. It increases the desirability of products as responds to customer demands and leads to consumer satisfaction. Intelligent packaging can increase trust in bioproducts; for example, it is possible to track and check or monitor the origin of a product and prove that the product producer has really manufactured a bioproduct.

The study contributes to the discussion of the applicability and use of packaging with enhanced features in the food industry. In this respect, the performed pilot study fills the gap in the packaging literature by investigating consumers’ perspectives on intelligent packaging in Georgia – a non-EU, post-soviet, developing country.

This study is aimed at making an inspection of the effects of collaborative innovation network characteristics on firm innovation performance, and the intermediary roles of knowledge transfer efficiency is taken into account.

This study used a convenient sampling method to obtain population and samples. Using data obtained by publishing online and paper questionnaires, and using on-site interviews in Anhui Province in the Yangtze River Delta region of China, descriptive analysis, regression analysis and correlation analysis are utilized to study the direct influence of collaborative innovation network characteristics on knowledge transfer efficiency as well as firm innovation performance, and the intermediary roles of knowledge transfer efficiency on firm innovation performance, respectively. In this study, 3,000 questionnaires were distributed to the employees of enterprises engaged in research and development (R&D) activities, of which 2,560 were valid. With the help of SPSS24.0 software, the reliability and validity of the questionnaire was analyzed.

The results are indicative of that network centrality and relationship strength positively affect knowledge transfer efficiency and firm innovation performance. Nevertheless, network scale has no significant correlation with knowledge transfer efficiency and enterprise innovation performance. In addition, knowledge transfer efficiency is an intermediary between collaborative innovation network characteristics and enterprise innovation performance, and positively affects enterprise innovation performance, which demonstrated that managers should take advantage of collaborative innovation network characteristics to elevate knowledge transfer efficiency because well-realized transferals of knowledge can help accelerate the coordination of resources in knowledge, and finally bring about the advancement of firm's innovation abilities and performance.

There are few previous studies that fully examined the relationships among collaborative innovation network characteristics, knowledge transfer efficiency and firm innovation performance. This paper developed previous researches on the relationships between collaborative innovation network characteristics, knowledge transfer efficiency and firm innovation performance. The mediation of knowledge transfer efficiency on the relationship between collaborative innovation network characteristics and firm innovation performance is analyzed. Further, studies on collaborative innovation network characteristics using data obtained from employees engaged in R&D activities are very limited in the literature. On account of that, the findings in this study may make sense to the innovation ability of innovative enterprise and expand the literature in the field of enterprise strategic management and knowledge management.

This analysis shows that collaborative innovation network characteristics have both positive and negative effects on firm innovation performance. Therefore, business managers should pay attention to their position in the collaborative innovation network and maintain the relationship strength with other innovation subjects. Special consideration should be given to the knowledge transfer of innovative enterprises, so as to improve firm innovation performance practically.

The study may provide additional understandings for researchers, government managers, universities and enterprises with regard to strategic management from the visual angle of innovation ecosystems. It is instrumental in the exploration of the mechanisms enabling firm innovation performance.

This study aims to explore the pathway of increasing hotel booking intentions by mapping the linkage mechanism between the antecedents and components of brand equity to ultimately drive followers’ hotel booking intention. In addition, the role of over-endorsement as a moderating variable is also evaluated.

The conceptual model and research hypotheses were each assessed using covariance-based structural equation modeling. Paper-based and online surveys were used to collect data from 443 respondents who are TikTok users and follow at least one TikTok online celebrity, while that online celebrity must have reviewed at least one type of accommodation.

Except for the relationship between virtual interactivity and online celebrity brand image, the results confirmed the relationships between research concepts.

Further studies are needed to validate the results in other cultural contexts, generalize findings and broaden the range of target respondents.

This study contributes to the hotel literature by illustrating how online celebrity brand equity (OCBE) drives hotel booking intentions. The study highlights the importance of antecedent factors – follower-centered drivers (e.g. lifestyle congruence, friendship) and online celebrity-led drivers (e.g. virtual interactivity, expertise) – to achieve a hierarchical relationship between OCBE components and followers’ booking intentions.