Search Results (27)

With the advent of disruptive technologies, blockchain is considered to be the most prominent technology that has the potential to have a significant influence on the knowledge management field, particularly knowledge sharing, knowledge transfer and knowledge spillover. This paper outlines the development and validation of the Knowledge Spillover through Tourism Blockchain Questionnaire, the TBlockQ. The purpose of this questionnaire is to acknowledge the key factors aligned with the level of knowledge spillover generated within a blockchain network. The TBlockQ was a synthesis of 29 5-point Likert scaled questions. A total of 422 correspondents participated in this study. The results of this study outline the reliability and validation of this questionnaire. The reliability statistics of all the items are high. Three factors, revealed from the factor analysis, identifying the knowledge spillover from a blockchain network in the tourism industry were: (a) networking expansion, improvement and spillover intention, (b) entrepreneurial and future prospects and (c) trust and security. Full article

This study aimed to identify the tacit or practical knowledge of an online community of practice (CoP) based on a content management system (CMS) technology. The E-Learning Industry site is one of the most prominent news outlets that provides instructional design and technology (IDT) practitioners with insights into the field. Natural language processing (NLP) techniques were implemented to extract practical knowledge of publicly available and not password-protected text sources in seven news categories. First, the findings suggest emphasizing the production of online articles related to the production of e-learning materials in technology-enabled environments. Second, the results indicate the alternative uses of learning management systems to manage different aspects of the production of e-learning materials. Third, the findings show that the CoP’s main priority was to reference existing materials in the community and external resources. The results of this study have implications and provide recommendations for researchers, community leaders, and practitioners toward improving knowledge discovery mechanisms, increasing transparency and integrity in communities, and increasing practitioners’ ability to self-assess existing practical knowledge against competencies in the field. The present study takes an inventory of the organizational knowledge capital and functions embedded in a CoP using a CMS platform as a delivery mechanism for creating and sharing knowledge. Full article

The amount of available information in the digital world contains massive amounts of data, far more than people can consume. Beekeeper AG provides a GDPR-compliant platform for frontline employees, who typically do not have permanent access to digital information. Finding relevant information to perform their job requires efficient filtering principles to reduce the time spent on searching, thus saving work hours. However, with GDPR, it is not always possible to observe user identification and content. Therefore, this paper proposes link prediction in a graph structure as an alternative to presenting the information based on GDPR data. In this study, the research of user interaction data in a graph database was compared with graph machine learning algorithms for extracting and predicting network patterns among the users. The results showed that although the accuracy of the models was below expectations, the know-how developed during the process could generate valuable technical and business insights for Beekeeper AG. Full article

Reducing the environmental impact of a device arising from unexpected failures should be an environmental goal. However, this problem can be difficult to tackle, especially due to the limitations of the traditional eco-design methods, which are more used to reduce the baseline impacts. This study proposes a novel method to overcome this limitation, working at the intersection of conceptual design, robust design, and eco-assessment. Based on the inquiry-based approach, the method consists of 52 questions, systematically organised on 4 hierarchical levels dedicated to the formulation of the initial environmental problem, the definition of the design goal, and the strategy and the selection of the methods, tools, and solutions to be applied. The method was applied in two real case studies about an adsorption air dryer and a medium-voltage circuit breaker by providing different solutions, where the most promising one was able to avoid the environmental impact variations up to 2% of the total impacts of the device. The method could be a starting point to build a design theory that is dedicated to this sector, still largely unexplored, while this vocation towards conceptual design is an appeal for a contamination of the more routine fields of robust and eco-design on the educational, application, and research levels. Full article

The subject of the proposed study is a method implementable for a search engine able to provide supply chain information, gaining the company’s knowledge base. The method is based on the construction of specific supply chain ontologies to enrich Machine Learning (ML) algorithm results able to filter and refine the searching process. The search engine is structured into two main search levels. The first one provides a preliminary filter of supply chain attributes based on the hierarchical clustering approach. The second one improves and refines the research by means of an ML classification and web scraping. The goal of the searching method is to identify a georeferenced supply chain district, finalized to optimize production and planning production strategies. Different technologies are proposed as candidates for the implementation of each part of the search engine. A preliminary prototype with limited functions is realized by means of Graphical User Interfaces (GUIs). Finally, a case study of the ice cream supply chain is discussed to explain how the proposed method can be applied to construct a basic ontology model. The results are performed within the framework of the project “Smart District 4.0”. Full article

Social media platforms can be used as a tool to expand awareness and the consideration of cultural heritage organizations and their activities in the digital world. These platforms produce daily behavioral analytical data that could be exploited by the administrators of libraries, archives and museums (LAMs) to improve users’ engagement with the provided published content. There are multiple papers regarding social media utilization for improving LAMs’ visibility of their activities on the Web. Nevertheless, there are no prior efforts to support social media analytics to improve users’ engagement with the content that LAMs post to social network platforms. In this paper, we propose a data-driven methodology that is capable of (a) providing a reliable assessment schema regarding LAMs Facebook performance page that involves several variables, (b) examining a more extended set of LAMs social media pages compared to other prior investigations with limited samples as case studies, and (c) understanding which are the administrators’ actions that increase the engagement of users. The results of this study constitute a solid stepping-stone both for practitioners and researchers, as the proposed methods rely on data-driven approaches for expanding the visibility of LAMs services on the Social Web. Full article

It appears that open access (OA) academic publishing is better for science because it provides frictionless access to make significant advancements in knowledge. OA also benefits individual researchers by providing the widest possible audience and concomitant increased citation rates. OA publishing rates are growing fast as increasing numbers of funders demand it and is currently dominated by gold OA (authors pay article processing charges (APCs)). Academics with limited financial resources perceive they must choose between publishing behind pay walls or using research funds for OA publishing. Worse, many new OA journals with low APCs did not have impact factors, which reduces OA selection for tenure track professors. Such unpleasant choices may be dissolving. This article provides analysis with a free and open source python script to collate all journals with impact factors with the now more than 12,000 OA journals that are truly platinum OA (neither the author nor the readers pay for the peer-reviewed work). The results found platinum OA is growing faster than both academic publishing and OA publishing. There are now over 350 platinum OA journals with impact factors over a wide variety of academic disciplines, giving most academics options for OA with no APCs. Full article

Significant research has been conducted into the preferences of college students for what their course instructors wear while teaching face-to-face university classes. This article focuses on a specific focus within that research: students within a teacher education department of a midsized midwestern state university. The study used a survey to examine student preferences into this topic. Data were gathered using an online survey of 92 teacher education department students in one midwestern state university. The survey asked students to respond to images of men and women in various levels of formal dress: very informal attire, casual attire, business casual attire, and more formal attire. Students were asked to respond on a Likert-type scale about the impact of instructor dress on their own learning, on their perception of the instructor’s competence, and on their attitudes toward the professor’s apparent approachability or friendliness. Data were analyzed using descriptive statistics. This study suggests that students prefer their instructors to wear business casual attire while teaching. This finding was true for both male and female professors, and the survey results further indicate that business casual dress is best for student learning, for student perception of the instructor’s competence, and for the perceived approachability of the professor by students. The results of this study provide direction for college-level instructors seeking to enhance their overall effectiveness. Full article

The use of artificial intelligence in paediatrics has vastly increased in the last few years. Interestingly, no historical bibliometric study analysing the knowledge development in this specific paediatric field has been performed yet, thus our study aimed to close this gap. References Publication Years Spectrography (RPYS), more precisely Cited Reference Explorer (CRE) software tool was employed to achieve this aim. We identified 28 influential papers and domain experts validation showed that both, the RPYS method and CRE tool performed adequately in the identification process. Full article

The world is suffering from a myriad of challenges. These are not only a direct result of the COVID-19 pandemic but also the evidence of a series of structural problems that existing socio-economic structures have. Inspired by real examples of social innovations and based on a selective literature review, this article debates six domains of opportunities for social innovation. These domains refer to well-being, finance and banking, work, technology, learning and education, and leadership and governance. The article ends with crucial implications for implementing change and a sustainable transition. Full article

Due to the non-played matches on the grounds of COVID-19 pandemics, the usual evaluation of the results of tournaments is biased. Matches won by default may cause unrealistic results. In this paper, an expedient method, the generalization of Thurstone method for more than two options, is applied. It is able to evaluate the results of the played matches without requiring equal matches’ numbers. This method takes the strength of the opposer into consideration as well. We apply the method for evaluating Handball Champions’ League’s results. We illustrate that it efficiently predicts the results in the future. Full article

The building-and-construction industry has been researched extensively over its life cycle regarding green and sustainable processes and techniques due to its major contributions towards energy consumption and its environmental impacts. Over the past decade, the construction stage of a building is often criticized for overlooking or approximating the environmental impacts as compared to other life-cycle stages of a building. This is evident through strong research findings regarding other building life-cycle stages in building-emission-assessment studies. With the drive towards digitization, the construction industry is receiving significant research attention in order to minimize environmental impacts at the construction stage. Despite these research initiatives, only a handful of recent review studies have systematically furnished current advances, gaps and future directions in environmentally sustainable building-construction techniques. The current study represents a systematic literature review of the environmental impacts at the building-construction stage with the objective of identifying the current findings, gaps and future research scopes. A bibliometric assessment revealed key author contributions, key research areas and collaboration aspects of research works related to environmental impacts of construction in building projects. Four major barriers and knowledge gaps in conducting a comprehensive assessment at the construction stage of a building were identified, including the lack of definition of a generic system boundary, difficulties in data collection, complex modeling issues and complications in the classification and analysis of emissions. The findings would provide key knowledge for passionate construction-industry stakeholders who are keen to benchmark green and sustainable construction practices in the building industry. Full article

In the realm of information, conversational search is a relatively new trend. In this study, we have developed, implemented, and evaluated a multiview conversational image search system to investigate user search behaviour. We have also explored the potential for reinforcement learning to learn from user search behaviour and support the user in the complex information seeking process. A conversational image search system may mimic a natural language discussion with a user via text or speech, and then assist the user in locating the required picture via a dialogue-based search. We modified and improved a dual-view search interface that displays discussions on one side and photos on the other. Based on the states, incentives, and dialogues in the initial run, we developed a reinforcement learning model and a customized search algorithm in the back end that predicts which reply and images would be provided to the user among a restricted set of fixed responses. Usability of the system was validated using methodologies such as Chatbot Usability Questionnaire, System Usability Scale, and User Experience Questionnaire, and the values were tabulated. The result of this usability experiment proved that most of the users found the system to be very usable and helpful for their image search. Full article

This article uses a qualitative research method to identify eighty elementary pre-service teachers’ conceptual representations concerning static electricity. We carry out this analysis using a paper and pencil questionnaire. This study shows that pre-service teachers have an erroneous understanding compared to those commonly accepted by the scientific community. The inaccurate representations identified are relevant for developing teaching strategies focused on conceptual conflict. Full article

This study shows a methodological approach to improve geospatial interpolation carried out with the Inverse Distance Weighted algorithm using distances and other parameters to which we attribute relative weights such as elevation. We also provide reliable information about better data output by elaborating a more realistic confidence interval with various percentages of reliability. We tested the methodology to monthly accumulated rainfall and temperatures recorded by multiple monitoring stations in the Puglia region in South Italy. The whole procedure has been called Augmented Inverse Distance Weighted and is tested with the ultimate goal of predicting missing values at a regional scale based on cross-validation techniques applied to a dataset consisting of ten years of precipitation data and five years of temperature data. The efficacy of this approach is evaluated using statistical scores regularly employed in the model’s evaluation studies. Results show that the improvements over the classical approach are remarkable and that the “augmented” method provides more accurate measurements of environmental variables. The main application of this algorithm is the possibility to provide the spatialisation of values of precipitation and temperature, or any other based on its own needs, at every point of the territory, playing a very important role in agricultural decision support systems and letting us identify frosts, drought events, climatic trends, accidental events, cyclicality and seasonality. Full article