Knowledge is awareness or familiarity gained by experiences of facts, data, and situations. Knowledge management includes techniques and processes to represent, store, search, integrate, and analyze knowledge that is available in digital form. Ontology is a formal explicit specification of a shared conceptualization of a domain of interest and it is a building block of the semantic web and formal description of knowledge. Ontologies capture the structure and knowledge about some domain of interest by describing the concepts in the domain and also the relationships that hold between those concepts. Even though Ethiopia has potential tourist destinations, the country is not benefited from its resources due to misperception about image of the country; lack of promoting the potential tourism resources of the country to the world; problems with sharing, searching and retrieval of tourist information. Thus, the country is forced to accept smaller number of tourists and not getting the benefits it deserves. The objective of this paper is to build ontology for Ethiopian Tourism so that it makes Ethiopian tourism destinations visible to international visitors. We use OWL language implemented in Protégé with other ontology development activities proposed in METHONTOLOGY to build Ethiopian tourism ontology. We also use OWL …

This paper will report on a research to develop Speaker Independent, Continuous Speech Recognizer for Kafi Noonoo (Afro-Asiatic language that belongs to North Omotic sub family in Ethiopia) using Hidden Markov Modeling technique. The portable and open source toolkit called Hidden Markov Model (HMM) Toolkit is used to perform the experiment. The development of HMM based Automatic Speech Recognition (ASR) requires both text and speech corpus for training and testing the HMM. In order to have a model that incorporates different features of the language, we included the different dialects of Kafi Noonoo in the corpus and then prepared the training and test corpus from the scratch, and after preprocessing we have sampled and performed feature extraction using Mel Frequency Cepstral Coefficients (MFCC) feature extraction technique.

The unquestionable demand for data generation and consumption in organizations in this century prompt an increasingly notion of data as a valuable asset, provoking the urgency for reliable analysis and reporting of complex data assets towards a critical business decision making process. Computing languages like SQL, Sequential Query Language, Data Mining and Warehouse, and data visualization tools are some examples of how information technology is being applied to the problem solving strategy related to data governance and management. The objective of this article is to provide an overall framework for effective data governance, through the examination of the hierarchy data-wisdom, that can be applied to business processes improvement and business intelligence approaches. Its purpose is to present roadmaps that will lead to superior management decisions impacting the pipeline and the relationship between leaders, staffs, stakeholders, and the corporate governance in terms of data processing and consumption. This literature review work presents the argument that effective use of information technologies, the consolidation of a learning culture, and the fostering of a technological framework that is insightful and enabler of a responsible and steward data management process have decisive impact in the business processes operations and strategies in which leadership plays a …

Wisdom is defined as “a uniquely human quality demonstrated through an ability to apply self-insight, experience, and sound judgment in conjunction with applicable data, information, and knowledge to create a course of action leading to beneficial and productive decisions for both individuals and society” (Allen et al., 2020, p. 159). Using this definition as a foundation, this research explores how veterans use wisdom to enhance the workforce through perspective, experience, and resilience.

Knowledge is the central component of knowledge management (KM); it comes into existence, is managed, and has effects through the activities performed upon it and the results of those activities. Much of the foundational KM literature identifies and classifies these activities (Baskerville, Dulipovici, 2006; Becerra-Fernandez, 2005; Evans, Ali, 2013; Evans, Dalkir, Bidian, 2014; Girard, Girard, 2015; Pee, Kankanhalli, 2009; Mohajan, 2016; Sajeva, 2010). We propose an extension of these activity classifications.

It is understood that Social Innovation (SI) is at the service of society, building a positive social value. Collaborative governance favors the government, with characteristics for a better form of applicability of its theories. Therefore, this article aims to identify how collaborative governance and social innovation collaborate for better governance in the public sector.

Emerged in the early 1990’s, governance is a construct which enables to broaden the management focus to a more comprehensive view, assessing efficiency capacity from different perspectives, such as social and political. Among its applications, Corporate Governance is the most known. In the private sector, governance has become a mandatory practice for companies aiming at increasing their market value or maintaining it high, due to the credibility earned by companies with good governance practices. In the public sector governance is a major challenge, once it concerns itself with generating value for society, in addition to the need for transparency and credibility in the management of public affairs. In this context, the objective of this article is to identify the differences and similarities between Corporate Governance in Private Companies and Public Administration.

The pandemic of the COVID-19 (coronavirus) has presented us a new world-wide reality. In a short time, huge changes had been necessary. In the sanitation it has not been different. For handle with essential services, in the majority through public concessions, the rendering of services has been strongly influenced for the chaotic economic situation, the necessity of cares with the health of the employees and for governmental decisions that restrict some activities. Thus, risk management becomes an increasingly urgent need, as the impacts of wrong decisions can lead to huge losses. Starting from the hypothesis that the better risk management within organizations, the better the decision-making process will be, this article aims to present the importance of risk management for mitigation and contingency in the face of the impacts caused by the pandemic of COVID-19.

Knowledge Management Best Practices are established through leveraged Data Science Technique based on results found on published articles of reputed literature and both advertisements and news items of newspapers. Further, the recognition showed threats to the values of Higher Education such as the quality of courses. As such, a Postgraduate study is conducted to reveal a solution to those kinds of issues in Higher Education. Consequently, based on the proposal of literature to such issues in other contexts, existences of Knowledge Management Practices are revealed in the qualitative paradigm. Meanwhile, the present study questioned whether the confirmed Practices of the Postgraduate study are Best Practices of Higher Educational Institutes. Besides, the Oxford dictionary specifies that practice becomes Best Practice if “commercial or professional procedures that are accepted or prescribed as being correct or most effective”. Accordingly, confirmed practices of Higher Educational Institutes became Best Practices due to the practices that are accepted by the industry of the Postgraduate research through a qualitative paradigm and by the other industries of researches that those reputed publications concerned into the Postgraduate study. Besides, Knowledge Management is an emerging/ emerged era. As such, present research proposes resulting practices of the Postgraduate study as Based …

Twitter is one of the major social media platforms highlighting public opinion. With over 330 million users across the globe, Twitter provides insights into global sentiments on many topics. One can estimate global sentiments towards certain events relating to COVID-19 by analyzing the most common phrases and their related sentiment scores from Twitter API data. This project has compiled the most used trigrams in tweets relating to COVID-19 to calculate sentiment scores for the period from March 22 to August 7, 2020. Another goal of the project is to optimize data collection from Twitter API. Twitter limits access to tweet contents to 900 requests per 15 minutes for unpaid API users. For student data scientists, paying for increased API usage is financially infeasible. So, to deal with the rate limit, the project has written functions using the Tweepy python library to collect Twitter API data. The Pandas library has also been used to sample 139000 tweets from over 300 million. The IEEE Dataset provided sentiment scores for the full population. So, to check the integrity of my sample, I performed a Pearson correlation test between the full dataset and sample data, and got 0.84, showing the sample is representative of …

Stakeholder-centered knowledge elicitation and acquisition for study counseling and informed decision making on the selection of study programs and study locations.

This paper aims to compile organizational innovation management indicators of papers that included some empirical step in the research and were published in the last 5 years (2015-2019). Based on PRISMA protocol, a systematic review was conducted and 356 indicators were extracted. They were categorized in 11 dimensions, following Dziallas & Blind (2019) previous literature research. The results make it possible to update the studies of innovation indicators at the organizational-level, filling an existing time gap in the research field. As for future research, we recommend the unification of similar indicators, the establishment of objective criteria for indicators categorization, and the development of an innovation indicator framework containing relevant indicators based on scholars’ and practitioners’ opinions, their description and measurement/evaluation methods.

Recent years have seen the development of quite a few measures of wisdom (e.g. Ardelt (2003); Glück (2017); Staudinger and Pasupathi (2003); Sternberg (1998); Webster (2003)). With a focus on information professionals working in the GLAM (Galleries, Libraries, Archives, and Museums) sector, this study is unique in the way it translated the quantitative measures used in previous study into a qualitative instrument that can allow wisdom aspects to be explored through interviews. Thus the purpose of this research was to investigate the key characteristics of wisdom for professionals working in the GLAM sector.

The dynamics proposed by the information and communication technologies enter economic sectors and require new behaviors. Digital Agriculture is a way to adapt to the new scenario. However, the modernization movement requires that views on agricultural industries be compensated.

This study considers Communities of Practice as a group of library and information science professionals who share their common interests and problems on a topic in order to exchange their expertise and knowledge on that topic. The study sheds lights on the ways of knowledge sharing, and assess the reasons of knowledge sharing of LIS professionals through Communities of Practice in the context of university libraries in Bangladesh.

The ever-increasing market turbulence has turned today’s corporate landscape more competitive and complex. Particularly during the last two decades, the increased utilization of ICT systems and technologies globally transformed the services sector in terms of ease of business processes and improved client service delivery. However, in the current knowledge-based era, ICT-enabled systems and tools would only be meaningful if these are appropriately utilized by the knowledgeable and skilled workforce. However, leveraging these necessitates a knowledge-enabled work culture and recognizing that people are crucial to building a robust Intellectual Capital (IC) that is central to achieving long-term market competitiveness. IC comprising of intangible assets and knowledge resources is central to value creation for the firm as evident from the growth of the knowledge-based industries. Nevertheless, the true potential of IC for deriving value advantage for diverse organizational stakeholders has not been fully utilized. Hence, by conducting 12 face2face interviews with the senior executives within Australian Professional Service Firms (PSFs), this study offers renewed approach to IC valuation by introducing ‘Triple Value Bottom-line’ perspective in PSFs. The results highlight that the IC offers enormous potential towards deriving broader value outcomes for multiple organizational stakeholders.

While explicit knowledge can be to some extent separated from human brain and stored in organizational memory, tacit knowledge cannot be detached from the individuals who possess it, therefore its management cannot rely primarily on technologies. This calls for knowledge-worker centered approach. Individuals with different cognitive styles process information differently and use a variety of reasoning patterns for decision making and building their personal knowledge bases. The paper overviews the potential applications of the construct of cognitive style to managerial practice in knowledge intensive organizations. It also presents a model that can help visualize the relationships between different cognitive styles and knowledge management processes. The model also demonstrates how such cognitive dimensions manifest themselves at different stages of KM cycle.

This study aims to understand how individuals communicated and acknowledged to COVID-19 pandemic on Twitter. It mainly focused on identifying and demonstrating the differences in the perspective of United States and Canadian residents.