Toward Business Process Innovation in the Big Data Era: A Mediating Role of Big Data Knowledge Management

Authors: Saide Saide, Margaret L Sheng


 

Abstract:

While recent debate recognizes the importance of big data (BD) and knowledge management (KM) in firm performance, there has been a paucity of literature regarding big data analytics technological (BDAT) and knowledge exploration–exploitation capabilities (KEEC) in the context of business process innovation (BPI). This study aims to identify whether BD and KM can be established in these emerging issues. We used a survey questionnaire to collect data from various firms and industries. We used structural equation modeling (SmartPLS and SPSS) to validate the research model with a sample of 155 companies in a developing country such as Indonesia. The result demonstrates a positive relationship between KEEC and BPI, followed by several significant findings such as BDAT with KEEC; KEEC on big data knowledge management (BDKM); BDKM and BPI; and BDAT on BDKM. In contrast, BDAT is nonsignificant for direct relationship on BPI, and interestingly, it becomes a significant result after mediated by BDKM. Similarly, BDKM has successfully mediated the relationship between KEEC and BPI. The management level ideally develops and increases such a knowledge creation/acquisition practices and BDAT in an organization to gain more meaningful benefits from these two capabilities. BDAT, KEEC, and BDKM simultaneously are a clear antecedent approach, which ultimately results in flexibility, effectiveness, and effectivity of BPI. The cases of this research are profit firms in a developing country such as Indonesia. A future study could be considered in different settings such as type of industries or more specific company's type, the economy level of countries (comparing between developed and developing countries), and environmental dynamical. A novel field of study is the inclusion of knowledge exploration-exploitation and BDAT that drives BPI.

Full article: https://pubmed.ncbi.nlm.nih.gov/33216653/


Saide Saide received the bachelor’s degree with the Department of Information System, Faculty of Science and Technology, Universitas Islam Negeri Sultan Syarif Kasim Riau-UIN SUSKA Riau, Indonesia, in 2013, the master’s degree from the Department of Information Management, National Taiwan University of Science and Technology, Taipei, Taiwan, in 2016, and the master’s degree from the Departmentof Information System, Sepuluh Nopember Instituteof Technology (ITS Surabaya), Surabaya, Indonesia, in 2016, all in information systems and knowledge management. He is currently a Lecturer with the Department of Information System, Facultyof Science and Technology, Universitas Islam Negeri Sultan Syarif Kasim Riau - UIN SUSKA Riau. He was a Visiting Scholar and Research Collaboration withTampere University, Finland, a Researcher with the Department of Information Management, National Taiwan University of Science and Technology, a Project Management with EnReach - Energy Research Center, UIN SUSKA Riau, Indonesia. He has authored numerous articles published in SSCI/SCI journals such as Big Data, Technology Analysis & Strategic Management, IEEE Transactions on Engineering Management, and Journal of Enterprise Information Management, International Journal of Innovation Management, Journal of Science and Technology Policy Management, and International Journal of Business and Society. His research interests include knowledge management, information system, and IT-business strategy.

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Knowledge exploration–exploitation and information technology: crisis management of teaching–learning scenario in the COVID-19 outbreak

Authors: Saide Saide, Margaret L Sheng


 

Abstract: 

Education institution closure is considered as an effective way to prevent coronavirus (COVID-19) pandemic. However, there are several challenges concerning teaching and learning activities (knowledge transfer) in crisis times such a COVID-19. This study aims to provide a holistic view of knowledge transfer and information technology scenario in the education sector during COVID-19 or another uncertain environment. A systematic literature review was conducted by several search techniques such as study selection, synthesis of papers, and reporting the results. A total of 290 peer-reviewed research studies were carried out. These articles were filtered, and 51 relevant articles were selected. The study mainly contributes by illustrating the schema or scenario of effective knowledge transfer of the teaching–learning process in the context of coronavirus crisis through maximising the information technology (IT) tools and knowledge management (KM) approach. Several factors namely IT tools of remote and online learning, knowledge exploration–exploitation, education’s knowledge types (tacit-explicit knowledge), and internal–external knowledge in education were identified. The study further provides the new paradigm for future study. Additionally, several concepts and theories were merged, namely SECI theory and ambidexterity view (knowledge exploration and knowledge exploitation). Future studies may extend the research area to different types of organisations and extend this model into empirical tests.

Full article: https://www.tandfonline.com/doi/full/10.1080/09537325.2020.1854714


Saide Saide received the bachelor’s degree with the Department of Information System, Faculty of Science and Technology, Universitas Islam Negeri Sultan Syarif Kasim Riau-UIN SUSKA Riau, Indonesia, in 2013, the master’s degree from the Department of Information Management, National Taiwan University of Science and Technology, Taipei, Taiwan, in 2016, and the master’s degree from the Departmentof Information System, Sepuluh Nopember Instituteof Technology (ITS Surabaya), Surabaya, Indonesia, in 2016, all in information systems and knowledge management. He is currently a Lecturer with the Department of Information System, Facultyof Science and Technology, Universitas Islam Negeri Sultan Syarif Kasim Riau - UIN SUSKA Riau. He was a Visiting Scholar and Research Collaboration withTampere University, Finland, a Researcher with the Department of Information Management, National Taiwan University of Science and Technology, a Project Management with EnReach - Energy Research Center, UIN SUSKA Riau, Indonesia. He has authored numerous articles published in SSCI/SCI journals such as Big Data, Technology Analysis & Strategic Management, IEEE Transactions on Engineering Management, and Journal of Enterprise Information Management, International Journal of Innovation Management, Journal of Science and Technology Policy Management, and International Journal of Business and Society. His research interests include knowledge management, information system, and IT-business strategy.

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INTANGIBLE RESOURCES AND INSTITUTION PERFORMANCE: THE CONCERN OF INTELLECTUAL CAPITAL, EMPLOYEE PERFORMANCE, JOB SATISFACTION, AND ITS IMPACT ON ORGANIZATION PERFORMANCE

Authors: SAIDE SAIDE, DIDI MUWARDI, RICHARDUS EKO INDRAJIT 



Abstract:

Purpose: The aim of this research paper is to examine the relationships between intangible assets, employee’s performance, and job satisfaction (JS) with structural model. The research explores both the practical and theoretical basis of these paradigms on organisation performance. This research also aims to identify whether a relation can be established between these aspects in the context of non-profit organisation performance in Indonesia. Design/methodology/approach: Reviewing the literature explores a theoretical existence of related context preceding the organisational performance. The authors used structural equation modelling to check the research prototype with a sample of 121 respondents. The respondents were heads of departments and general employees. In addition, SPSS was used to measure demographic, non-response bias, and generate descriptive statistics. Findings: Overall, the results demonstrate that organisation with a higher level of intellectual capital (IC), employee performance (EP), and job performance (JP) are important predictors of organisational performance in this sample. Similarly, JS and IC predicted EP. It is acknowledged that emotional intelligence such as satisfaction and dissatisfaction are important incentives to necessitate action tendencies. Research limitations/implications: This research is focused on organisations. Further research may extend the focus to different types of organisations and countries. Practical implications: The findings of this study may help institutions and HR departments to initiate new strategies such as integrating the traditional company performance measurement systems based on various indicators of this study. These factors succeed in providing an effective representation of a set of intangible assets that are developed by the company and that contribute to the improvement of company’s performance. Additionally, to maximise IC assets, the company can implement knowledge sharing practices among employees and experts as well. Original value/knowledge contribution: This research is useful for organisations and academics as a reference of the comparative and intersecting explanation of enhancing organisational performance. Moreover, various main concepts/theories are combined, namely, IC, JS, and employee’s performance to solve the obstacles of organisation performance.

Full article: https://www.worldscientific.com/doi/abs/10.1142/S1363919621500092

 

Saide Saide received the bachelor’s degree with the Department of Information System, Faculty of Science and Technology, Universitas Islam Negeri Sultan Syarif Kasim Riau-UIN SUSKA Riau, Indonesia, in 2013, the master’s degree from the Department of Information Management, National Taiwan University of Science and Technology, Taipei, Taiwan, in 2016, and the master’s degree from the Departmentof Information System, Sepuluh Nopember Instituteof Technology (ITS Surabaya), Surabaya, Indonesia, in 2016, all in information systems and knowledge management. He is currently a Lecturer with the Department of Information System, Facultyof Science and Technology, Universitas Islam Negeri Sultan Syarif Kasim Riau - UIN SUSKA Riau. He was a Visiting Scholar and Research Collaboration withTampere University, Finland, a Researcher with the Department of Information Management, National Taiwan University of Science and Technology, a Project Management with EnReach - Energy Research Center, UIN SUSKA Riau, Indonesia. He has authored numerous articles published in SSCI/SCI journals such as Big Data, Technology Analysis & Strategic Management, IEEE Transactions on Engineering Management, and Journal of Enterprise Information Management, International Journal of Innovation Management, Journal of Science and Technology Policy Management, and International Journal of Business and Society. His research interests include knowledge management, information system, and IT-business strategy.

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Knowledge Data Discovery (Frequent Pattern Growth): The Association Rules for Evergreen Activities on Computer Monitoring

Authors: Fauzan Asrin, Saide Saide


 

Abstract: 

The aim of this research paper is to construct a set of guidelines that can improve the quality and efficiency of knowledge data discovery process by utilizing various types of knowledge domains. In addition, this paper offered the way of how the knowledge domain could be adopted for helping the system developer. The methodologies contain various scenarios of data exploring and the authors used data mining approach. The paper shows evidence of important to adopt data mining methods in the industry sector as well as the advantages and disadvantages. Evergreen human machine interface (HMI) at PT. Chevron Pacific Indonesia (CPI) is kind of activities to maintenance computer equipment. Nowadays, the errors were frequently happened in the accuracy of computer maintenance which has a profound effect on production results. Therefore, this study focuses on the rules of association using the frequent pattern growth algorithm (FP-growth) which is producing knowledge with trust value of 100% and a support value is 95%. The value results of support and confidence are the new approach and knowledge for the management level to decide decisions in the evergreen activities process.

Full article: https://link.springer.com/chapter/10.1007/978-3-030-51156-2_93


Saide Saide received the bachelor’s degree with the Department of Information System, Faculty of Science and Technology, Universitas Islam Negeri Sultan Syarif Kasim Riau-UIN SUSKA Riau, Indonesia, in 2013, the master’s degree from the Department of Information Management, National Taiwan University of Science and Technology, Taipei, Taiwan, in 2016, and the master’s degree from the Departmentof Information System, Sepuluh Nopember Instituteof Technology (ITS Surabaya), Surabaya, Indonesia, in 2016, all in information systems and knowledge management. He is currently a Lecturer with the Department of Information System, Facultyof Science and Technology, Universitas Islam Negeri Sultan Syarif Kasim Riau - UIN SUSKA Riau. He was a Visiting Scholar and Research Collaboration withTampere University, Finland, a Researcher with the Department of Information Management, National Taiwan University of Science and Technology, a Project Management with EnReach - Energy Research Center, UIN SUSKA Riau, Indonesia. He has authored numerous articles published in SSCI/SCI journals such as Big Data, Technology Analysis & Strategic Management, IEEE Transactions on Engineering Management, and Journal of Enterprise Information Management, International Journal of Innovation Management, Journal of Science and Technology Policy Management, and International Journal of Business and Society. His research interests include knowledge management, information system, and IT-business strategy.

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Mapping Analysis of Student`s Core-Competencies in University (Case: Department of Information System, State Islamic University of Sulthan Syarif Kasim Riau, Indonesia)

Authors: Nesdi Evrilyan Rozanda, Saide Saide, Zulrahmadi Zulrahmadi


 

Abstract:

Core-competence is allowing university to be creative and adaptable on their student's capabilities by mapping their student's research focus. In order to be successful of core-competences goals, department strategy, student, and lecturer are crucial role in that process. However, previous study offered more general contexts and cases of competence mapping approach while less or misplaced discussed more technical process in higher education environment. Therefore, to fill out the research gap, this research examines whether and why competence mapping can help university to prepare their graduations candidate. We evaluated two core-competences which are information system management and information system engineering by checking several main construct such as information technology quality management, knowledge management, and information technology risk management. The data collected from students in department of information system, state islamic university of sulthan syarif kasim Riau, Indonesia. The results from our analysis support that students who focused on information system management (ISM) focus were 37.8%, and in information system engineering (ISE) were 2.7%, and students who taken both ISM and ISE were 59.5 %. Regarding the result, the authors concluded that students more prefer to take more or combining two fields (ISM and ISE). More theoretical and practical implications are discussed.

Full article: https://ieeexplore.ieee.org/abstract/document/9066410


Saide Saide received the bachelor’s degree with the Department of Information System, Faculty of Science and Technology, Universitas Islam Negeri Sultan Syarif Kasim Riau-UIN SUSKA Riau, Indonesia, in 2013, the master’s degree from the Department of Information Management, National Taiwan University of Science and Technology, Taipei, Taiwan, in 2016, and the master’s degree from the Departmentof Information System, Sepuluh Nopember Instituteof Technology (ITS Surabaya), Surabaya, Indonesia, in 2016, all in information systems and knowledge management. He is currently a Lecturer with the Department of Information System, Facultyof Science and Technology, Universitas Islam Negeri Sultan Syarif Kasim Riau - UIN SUSKA Riau. He was a Visiting Scholar and Research Collaboration withTampere University, Finland, a Researcher with the Department of Information Management, National Taiwan University of Science and Technology, a Project Management with EnReach - Energy Research Center, UIN SUSKA Riau, Indonesia. He has authored numerous articles published in SSCI/SCI journals such as Big Data, Technology Analysis & Strategic Management, IEEE Transactions on Engineering Management, and Journal of Enterprise Information Management, International Journal of Innovation Management, Journal of Science and Technology Policy Management, and International Journal of Business and Society. His research interests include knowledge management, information system, and IT-business strategy.

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What we give, we get back: Investigating the dimensions that influence knowledge sharing on profit enterprise in Indonesia

Authors: Saide Saide, Astuti Endang Siti, Indrajit Richardus Eko, Trialih Rahmat, Diniaty Amirah, Dewi Fitriyana, Herzavina Herzavina


 

Abstract: 

Purpose

As prior study offered further general context of knowledge management approach while misplaced more personal behavior development in the context of knowledge sharing practices, this study examined whether and why personal factors predict knowledge sharing practices. This study aims to integrate and analyze indicators such as altruism, grant, interaction ability and knowledge sharing participation to develop a comprehensive behavioral model.

Design/methodology/approach

Structural equation modeling was used to check the research hypotheses framework with 268 samples of eight profit companies in Indonesia, divided into broadcasting, banking and services company.

Findings

The results showed that altruism and interaction ability factors are significantly correlated with knowledge sharing participation. The findings may help companies and workers to initiate knowledge sharing implementation and encourage knowledge sharing in the internal company.

Research limitations/implications

The research focused on profit company in a single province in Indonesia. Further research may extend the study with a focus on non-profit organizations (e.g. academic institutions) and different geographical areas.

Practical implications

Managerial ideally creates standardization or regulation that to encourage participation of workers for transfer their knowledge. In this aspect, the company needs to organize, such as formal/informal training and meeting to make their workers more confident to communicate with each other.

Originality/value

Prior studies explored knowledge sharing behavior in a general sense; this paper examined the phenomenon specifically within the context of broadcasting, banking and services company in Indonesia, then analyzed the potential for a company to enhance their knowledge sharing strategy.

Full article: https://www.emerald.com/insight/content/doi/10.1108/JSTPM-06-2018-0056/full/html


Saide Saide received the bachelor’s degree with the Department of Information System, Faculty of Science and Technology, Universitas Islam Negeri Sultan Syarif Kasim Riau-UIN SUSKA Riau, Indonesia, in 2013, the master’s degree from the Department of Information Management, National Taiwan University of Science and Technology, Taipei, Taiwan, in 2016, and the master’s degree from the Departmentof Information System, Sepuluh Nopember Instituteof Technology (ITS Surabaya), Surabaya, Indonesia, in 2016, all in information systems and knowledge management. He is currently a Lecturer with the Department of Information System, Facultyof Science and Technology, Universitas Islam Negeri Sultan Syarif Kasim Riau - UIN SUSKA Riau. He was a Visiting Scholar and Research Collaboration withTampere University, Finland, a Researcher with the Department of Information Management, National Taiwan University of Science and Technology, a Project Management with EnReach - Energy Research Center, UIN SUSKA Riau, Indonesia. He has authored numerous articles published in SSCI/SCI journals such as Big Data, Technology Analysis & Strategic Management, IEEE Transactions on Engineering Management, and Journal of Enterprise Information Management, International Journal of Innovation Management, Journal of Science and Technology Policy Management, and International Journal of Business and Society. His research interests include knowledge management, information system, and IT-business strategy.

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A theoretical and empirical validation of information technology and path-goal leadership on knowledge creation in university: Leaders support and social media trend

Authors: Saide Saide, Eko Indrajit Richardus, Trialih Rahmat, Najamuddin Najamuddin


 

Abstract: 

Purpose

This paper aims to assess the importance of maximizing resources in an institution to promote knowledge management (KM) practices, namely, leadership, information technology (IT) and KM. The relationship among them was analyzed. Previous studies’ relating aspects of KM were concerned about the industry; however, the academic institution has not received much attention. Therefore, to address this in an academic setting, the authors developed research model by focusing on an academic institution.

Design/methodology/approach

The authors used structural equation modeling to check the research prototype with a sample of 160 respondents. The respondents were heads of departments, lecturers and general employees. In addition, the authors used SPSS to measure demographic, non-response bias and generate descriptive statistics.

Findings

The findings of this research show that the leadership style with path goal theory and IT are elements that support KM program in university setting. The results of hypothesis are displayed in Figure 2, including examining factors that influence of path goal theory, technology and KM program. In other hand, path goal theory had a positive influence on KM program (c = 0.13, p < 0.05), and IT had a positive influence on KM program (c = 0.20, p < 0.05).

Research limitations/implications

Finally, the authors are not to claim that this will be suitable in many academic institutions and organization types. In this study, the authors tested or checked existing leadership style in university, then suggest/explain to University what style of leadership currently they have and suggest to them how this style may support knowledge sharing practice in University. While the strength of this study provides an opportunity to explore the KM program of an academic institution, limitations do exist above. Therefore, this statement needs to be investigated and validated further.

Practical implications

The findings of this research may help companies and workers to initiate sharing knowledge or to encourage knowledge sharing in University. In addition, managerial staffs/officers are supposed to make standardization or regulation to encourage workers’ participation for transferring their knowledge. In this aspect, company needs create such as training or formal/informal meeting to make their workers more confidence to communicate each other.

Originality/value

The authors have combined various aspects, namely, KM, leadership style and social media tools, to solve the obstacle of knowledge sharing practices.

Full article: https://www.emerald.com/insight/content/doi/10.1108/JSTPM-06-2018-0067/full/html 


Saide Saide received the bachelor’s degree with the Department of Information System, Faculty of Science and Technology, Universitas Islam Negeri Sultan Syarif Kasim Riau-UIN SUSKA Riau, Indonesia, in 2013, the master’s degree from the Department of Information Management, National Taiwan University of Science and Technology, Taipei, Taiwan, in 2016, and the master’s degree from the Departmentof Information System, Sepuluh Nopember Instituteof Technology (ITS Surabaya), Surabaya, Indonesia, in 2016, all in information systems and knowledge management. He is currently a Lecturer with the Department of Information System, Facultyof Science and Technology, Universitas Islam Negeri Sultan Syarif Kasim Riau - UIN SUSKA Riau. He was a Visiting Scholar and Research Collaboration withTampere University, Finland, a Researcher with the Department of Information Management, National Taiwan University of Science and Technology, a Project Management with EnReach - Energy Research Center, UIN SUSKA Riau, Indonesia. He has authored numerous articles published in SSCI/SCI journals such as Big Data, Technology Analysis & Strategic Management, IEEE Transactions on Engineering Management, and Journal of Enterprise Information Management, International Journal of Innovation Management, Journal of Science and Technology Policy Management, and International Journal of Business and Society. His research interests include knowledge management, information system, and IT-business strategy.

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An adoption of acceptance model for the multi-purpose system in university library

Authors: Saide Saide, Zhaohan Ding, Endang Siti Astuti, Didi Muwardi, Najamuddin Najamuddin, Mutiara Jannati, Herzavina Herzavina


 

Abstract: 

Since previous study offered a more general context of the IT acceptance model, here we place specific emphasis on the library context. Our study examines whether and why the Technology Acceptance Model (T.A.M.) can be used in a multi-purpose system (M.P.S.) in a university. The M.P.S. is a system for users to borrow, return and renew books on loan. The variables in this study were modified, such as Perceived Usefulness (P.U.) and Perceived Ease of Use (P.E.O.U.) as independent variables and acceptance of IT as a dependent variable. The sampling technique used was proportionate stratified random, using 98 students of the Faculty of Teacher Training and Education who have implemented the M.P.S. system. Data processing techniques used multiple linear regression analysis with the SPSS data processing tool. The results showed that usefulness and ease of use have significantly positive effect on the M.P.S. acceptance model. The research focused on a university context in single province in Indonesia. Further research may extend the study with a focus on profit or non-profit organisations and different geographical areas.

Full article: https://www.tandfonline.com/doi/abs/10.1080/1331677X.2019.1635898

 

Saide Saide received the bachelor’s degree with the Department of Information System, Faculty of Science and Technology, Universitas Islam Negeri Sultan Syarif Kasim Riau-UIN SUSKA Riau, Indonesia, in 2013, the master’s degree from the Department of Information Management, National Taiwan University of Science and Technology, Taipei, Taiwan, in 2016, and the master’s degree from the Departmentof Information System, Sepuluh Nopember Instituteof Technology (ITS Surabaya), Surabaya, Indonesia, in 2016, all in information systems and knowledge management. He is currently a Lecturer with the Department of Information System, Facultyof Science and Technology, Universitas Islam Negeri Sultan Syarif Kasim Riau - UIN SUSKA Riau. He was a Visiting Scholar and Research Collaboration withTampere University, Finland, a Researcher with the Department of Information Management, National Taiwan University of Science and Technology, a Project Management with EnReach - Energy Research Center, UIN SUSKA Riau, Indonesia. He has authored numerous articles published in SSCI/SCI journals such as Big Data, Technology Analysis & Strategic Management, IEEE Transactions on Engineering Management, and Journal of Enterprise Information Management, International Journal of Innovation Management, Journal of Science and Technology Policy Management, and International Journal of Business and Society. His research interests include knowledge management, information system, and IT-business strategy.

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Check Journal Indexes, Journal and Conference Call for Paper

Check Journal Indexes, Journal and Conference Call for Paper (SSCI, SCI, SCIE, ESCI, ISI, etc)


Search for SCI journals ( full list of SCI journals here)

Search for SCIE journals ( full list of SCIE journals here)

Search for SSCI journals ( full list of SSCI journals here)

Search for ISI journals

List of conferences/journals

- Conferences by due date (cfplist) (wikicfp)
- Conferences by date (conferencealerts)
- Conferences for the field of data mining by due date (link1) (link2)
- List of call for papers of special issues in computer science/electronics for impact factor journals (guide2research)
- List of call for papers of top conferences in computer science/electronics (guide2research)


EI compendex website
( Note: to download the list of EI journals and proceedings in Excel format, (1) click on this link and then (2) click on "Compendex source list" )


Check the JCR (Journal Citation Report) ranking of a journal and its impact factor  (requires a subscription) :https://jcr.incites.thomsonreuters.com/

Check SCImago Journal Ranking (SJR) in terms of quartile Q1, Q2, Q3, Q4, note: this ranking is different from the Chinese Academy of Science ranking below, and different from the JCR ranking above) http://www.scimagojr.com/

Check Chinese Academy of Science journal ranking using LetPub (中科院分区 ) in terms of quartile Q1, Q2, Q3, Q4 note: this ranking is different from the SCImago and JCR rankings, above).

Check the Chinese Computer Federation (CCF) ranking of artificial intelligence and data mining/database journals and conferences.

Search for citations in the ISI Web of Science (also called Web of Knowledge): http://apps.webofknowledge.com/

Search for papers

- Search on Google scholar (or use the GlGoo mirror in China)
- Search or Google Books

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Bibliometric Software

Tools and Software

General network and graph analysis and visualization  

  • You might find this Wikipedia list of social network analysis software useful. 
  • AGNA. free Java-based software for SNA, sociometry and sequential analysis. Its name stands for Applied Graph and Network Analysis.
  • CFinder. A is a free software for finding and visualizing overlapping dense groups of nodes in networks, based on the Clique Percolation Method (CPM). 
  • Cytoscape. A free Java-based open-source software that although originally designed for bioinformatics research, now it is a general platform for complex network analysis and visualization. Cytoscape core distribution provides a basic set of features for data integration and visualization. Additional features are available as plugins.
  • GeoVIZ. A free toolkit for systematic analysis of spatial, temporal, and attribute data sets. It allows analysts to discover previously hidden patterns in data, moving from spatial patterns to statistical patterns and back again by mixing and matching data visualization components to quickly construct custom analysis tools. It provides a large selection of mapping and statistical graphing components for depicting univariate and multivariate data in dynamically linked views.
  • Gephi. A free open-source interactive visualization and exploration platform for all kinds of networks and complex systems, dynamic and hierarchical graphs.
  • Graphviz. A free open-source graph visualization software. Its main applications are networking, bioinformatics,  software engineering, database and web design, machine learning, and in visual interfaces for other technical domains. It takes descriptions of graphs in a simple text language, and make diagrams in useful formats, such as images and SVG for web pages, PDF or Postscript for inclusion in other documents; or display in an interactive graph browser.
  • GUESS. An free exploratory data analysis and visualization tool for graphs and networks. It can import standard formats (Pajek, GML) and export a wide variety of image types (GIF, PNG, EPS, PDF, JPG, SVG...). Because it is Jython/Java-based, users can also construct your own applications and applets without much coding.
  • igraph. A free software package for creating and manipulating undirected and directed graphs. It includes implementations for classic graph theory and also implements algorithms for some recent network analysis methods, like community structure search.
  • KeyPlayer. A free software  for identifying an optimal set of nodes in a network for one of two basic purposes: (a) crippling the network by removing key nodes, and (b) selecting which nodes to either keep under surveillance or to try to influence via some kind of intervention. Written by Steve Borgatti.
  • InFlow. commercial software for Social Network Analysis & Organizational Network Analysis.
  • MapEquation. Free algorithm and software for detecting communities in large networks.
  • Multinet. A free data analysis package that can be used for ordinary data (in which you have a file that has one line of data for each case) and for network data (in which there are two files -- the "node" file describes the individuals and the "link" file describes the connections between individuals). [It hasn't been updated for a long time].
  • NetDraw. A free program written by Steve Borgatti for visualizing both 1-mode and 2-mode social network data. It can read UCINET system files, UCINET DL files, Pajek files, and its own VNA format. It exports networks as a metafile, jpg, gif and bitmap formats.
  • NetMiner. A commercial software tool for exploratory analysis and visualization of Network Data. It has 73 kinds of SNA modules and 23 kinds of visualization modules.
  • NetworkX. A  free Python-based open-source software for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. 
  • NodeXL. A free, open-source template for MS Excel to draw graphs and networks. Networks can be imported from and exported to a variety of file formats (e.g. GraphML, UCINet, Pajek, and matrix), and built-in connections for getting networks from Twitter, Flickr, YouTube, and your local email are provided. You can learn how to use it by reading the book by Hansen et al. (2010).
  • Pajek. A free Python-based open-source software for large networks analysis of visualization. It is probably the most popular network analysis software and largely used by experts in scientometrics. You can learn how to use it by reading the book by de Nooy et al. (2011).
  • prefuse. A free Java-based set of software tools for creating rich interactive data visualizations. Some of its features are Table, Graph, and Tree data structures supporting arbitrary data attributes, data indexing, and selection queries, and animation support.
  • Smart Local Moving (SLM) algorithm: A free Java-based open-source algorithm (implemented in Modularity Optimizer) for community detection (or clustering) in large networks. It maximizes a so-called modularity function and it has been successfully applied to networks with tens of millions of nodes and hundreds of millions of edges. You can read its paper here.
  • SNA package for R. A free range of tools for social network analysis with R, including node and graph-level indices, structural distance and covariance methods, structural equivalence detection, network regression, random graph generation, and 2D/3D network visualization.
  • SoNIA. or Social Network Image Animator is a free open-source Java-based package for visualizing dynamic or longitudinal network data.
  • StOCNET. free open-source software for advanced statistical analysis (based on probability model) of social networks.
  • Tulip. A free information visualization framework written by C++ dedicated to the analysis and visualization of relational data.
  • UCINet. A commercial social network analysis program developed by Steve Borgatti and colleagues and distributed by Analytic Technologies. UCINET works in tandem with freeware program called NetDraw for visualizing networks. NetDraw is installed automatically with UCINet.
  • Visone. free software for analysis and visualization of social network data.

 Scientometric and bibliometric analysis 

  • You might also find this Wikipedia comparison of research networking tools and research profiling systems useful.  
  • Bibexcel. Free software designed by Olle Persson to assist a user in analyzing bibliographic data, or any data of a textual nature formatted in a similar manner. The idea is to generate data files that can be imported to Excel or any program that takes tabbed data records, for further processing. It can be used for co-citation, bibliographic coupling, mapping and clustering analysis.
  • Bibliometrix R package. A free tool that provides various routines for importing bibliographic data from SCOPUS and Clarivate Analytics' Web of Science databases, performing bibliometric analysis and building data matrices for co-citation, coupling, scientific collaboration analysis and co-word analysis.
  • BiblioTool. It is a set of python scripts (open source) written by Sebastian Grauwin. They can read ISI data in CSV format and do some analyses including co-occurrence map and bibliographic coupling.
  • CiteSpace. A free Java-based software for visualizing and analyzing trends and patterns in the scientific literature. It is designed as a tool for progressive knowledge domain visualization. Its primary source of input data is ISI WoS. But it also provides some simple interfaces for obtaining data from PubMed, arXiv, ADS, and NSF Award Abstracts. It can be used to generate geographic map overlays viewable in Google Earth based on the locations of authors.
  • CitNetExplorer. A free Java-based software tool developed by Uni of Leiden for visualizing and analyzing citation networks of scientific publications. It allows citation networks to be imported directly from the Web of Science database. Citation networks can be explored interactively, for instance by drilling down into a network and by identifying clusters of closely related publications. 
  • CopalRed. (obsoleted) A free program written by Xavier Polanco for the analysis of scholarly publications and scientometric purposes for example for analysing and visualizing the network structure of a scientific field.
  • CRExplorer. Or Cited Reference Explorer is a free Java-based program that was primarily developed to identify those publications in a field, a topic or by a researcher which have been frequently cited. It is especially suitable to study the historical roots of this field, topic or researcher.
  • InCite Retrieve: a set of Python codes for retrieving journal impact factor values from InCite API.
  • InterDisciplinary Research (IDR). It's a free tool to measure and map interdisciplinary research. It creates overlay maps of science, as a method to explore the degree of interdisciplinarity of a set of publications. 
  • IN-SPIRE. A commercial software for exploring and visualizing textual data, including Boolean and “topical” queries, term gisting, and time/trend analysis tools. It can be used to explore technical and patent literature, marketing and business documents, web data, accident and safety reports, newswire feeds and message traffic, and more.
  • Headstart. A free open-source software to visualize readership data from Mendeley. It presents users with the main areas in the field and lets them zoom into the most important publications within each area. It is intended to give researchers that are new to a field a head start on their literature review (hence the name). It has been developed by P. Kraker.
  • HistCite(obsoleted) free software developed by E. Garfield to aid researchers in visualizing the results of literature searches in the Web of Science. It lets you analyze and organize the results of a search to obtain various views of the topic's structure, history, and relationships. It visualizes the citation network in a historical manner.
  • Loet Leydesdorff. A set of free DOS-based pieces of software to parse, transform and analyse bibliometrics data obtained from sources such as Scopus, ISI, and Google Scholar for analyses such as coauthorship, international, institutional, inter-city collaboration networks, co-word, co-citation and bibliographic analysis and so on. Although they do not include visualization tools, they prepare the data for the creation of relational databases and visualization by other tools such as Pajek. ISI.exe reads ISI data in txt format and generates files suitable for creating a relational database.
  • Network Workbench. A free Java-based large-scale network analysis, modelling and visualization toolkit for biomedical, social science and physics research. It includes specific features for bibliometric studies.
  • Publish or Perish. A free software program that retrieves and analyzes academic citations Google Scholar and calculates No of papers, citations, average No. of citations per paper and per author and per year as well as h-index, g-index, and some more metrics.
  • SAINT: (obsoleted) (Science Assessment Integrated Network Toolkit). It is open-source software for scientometrics analysis and one of the few packages that can be used to convert ISI data into a relational database (dbm or accdb or sql files). There is a forum to discuss the issues related to SAINT. The software is not available on its original website anymore.
  • ScientoPY, a free open source scientometric software. You can read about it in this paper
  • SciMAT. SciMAT (Science Mapping Anaylsis Tool) is a java-based open source (GPLv3) free software tool developed to perform a science mapping analysis under a longitudinal framework. SciMAT reads bibliographic data in different formats and creates a relational database in Sqlite 3 format and allows you to do different analyses. The advantage is that you can amend the data in the knowledgebase as you wish.
  • Sci2 Tool. A free Java-based modular toolset specifically designed for the study of science. It supports the temporal, geospatial, topical, and network analysis and visualization of scholarly datasets at the micro (individual), meso (local), and macro (global) levels. It has several visualization features.
  • Scientometric Project. A set of open-source Python scripts for some scientometric data analyses written by Theresa Velden.
  • Scopus API R code: This is some R code to query Scopus API and parse the results into a data frame. For instance, if you have a list of DOI and want to get citation data for them from Scopus.
  • Pybliometrics: Python-based API-Wrapper to access Scopus: A free Python library to cache and extract data from the Scopus, developed by M. E. Rose and J. R. Kitchin. You can read about it in this paper
  • Sitkis: (obsoleted) Sitkis is a free Java-based software tool developed exclusively for bibliometric analysis. Sitkis provides tools for extremely streamlined analysis of bibliometric networks. Read more about it here.
  • VOSviewer. A free Java-based program, primarily intended to be used for analyzing and visualizing bibliometric networks. It can create maps of publications, authors, or journals based on a co-citation network or to construct maps of keywords based on a co-occurrence network.
  • Web of Science API: a set of Python code to retrieve the times cited counts for DOIs and/or PMIDs.
  • Webometric Analyst: a free Windows-based program for altmetrics, citation analysis, social web analysis and webometrics, including link analysis, developed by Prof. Mike Thelwall.
For a list of some of the tools used in scientometrics studies see Borner et al (2010) and for comparison of some of these software packages see Cobo et al. (2011). 

Science Mapping Resources

  • Places & Spaces: Mapping Science. It is a collection of science maps and visualizations. It is exhibited in different places and they can be ordered.
  • Atlas of Science. This is a book by Katy Börner published by MIT press. It includes 500 colour illustrations of different science maps.
  • Excellence Mapping. This web application visualizes the scientific performance of institutions (universities or research-focused institutions) within specific subject areas (e.g. Chemical Engineering) as ranking lists and on maps.

Science Analysis Companies and Services

  • Academic Analytics. It is a provider of high-quality, custom business intelligence data and solutions for research universities in the United States and the United Kingdom. It helps universities identify their strengths and areas where improvements can be made.
  • Clarivate. It publishes Web of Knowledge and Web of Science and it also produces a few science analysis databases such as Journal Citation Reports, Science Watch, and Essential Science Indicators. WoS includes some analysis tools.
  • Elsevier. It is the publisher of Scopus database as well as SciVal which Is a suite of research tools that helps you evaluate, establish and execute your research strategies more effectively. SciVal Spotlight is a unique web-based strategic analysis tool that enables academic executives to make informed strategic decisions by measuring and evaluating an institution's research performance. It evaluates your institution's research output in a single interface. SciVal Funding is a web-based solution that gives research administrators and researchers in the pre-award stage access to current research funding opportunities and award information. It allows you to find the right funding opportunities and analyze the funding environment.
  • SCImago. Is a portal that includes the journals and country scientific indicators developed from the information contained in the Scopus. These indicators can be used to assess and analyze scientific domains.
  • Science Metrix. (now owned by Elsevier) It provides customized services in performance measurement and program evaluation using advanced bibliometric indicators and recognized quantitative and qualitative research methods. In 2010 it published a '30 Years in Science' report.
  • SciTech Strategies Inc. It mainly creates maps of science.

Journals related to Scientometrics


Books on Scientometrics

  1. Anderes, A. (2009). Measuring Academic Research: How to undertake a bibliometric study. Oxford: Chandos.
  2. Biagioli, M., & Lippman, A. (editors) (2020). Gaming the Metrics: Misconduct and Manipulation in Academic Research, Cambridge: MIT Press. 
  3. Borgman, C.L. (1990). Scholarly communication and bibliometrics: Sage Publications.
  4. Borner, K. (2010). Atlas of Science: Visualizing What We Know: MIT Press.
  5. Braam, R.R. (1991). Mapping of science: foci of intellectual interest in scientific literature: DSWO Press, University of Leiden.
  6. Braun, T. (Ed.). (2006). Evaluations of Individual Scientists and Research Institutions. Part I. Scientometrics Guidebooks Series: Akademiai Kiado Zrt.
  7. Braun, T. (Ed.). (2006). Evaluations of Individual Scientists and Research Institutions. Part II. Scientometrics Guidebooks Series: Akademiai Kiado Zrt.
  8. Braun, T. (2007). The Impact Factor of Scientific and Scholarly Journals: Its Use and Misuse in Research Evaluation: Akadémiai Kiadó.
  9. Braun, T. (2008). The Hirsch-index for evaluating science and scientists. Its uses and misuses: Akadémiai Kiadó.
  10. Braun, T., Bujdosó, E., & Schubert, A. (1987). Literature of analytical chemistry: a scientometric evaluation: CRC Press.
  11. Braun, T., Glänzel, W., & Schubert, A. (1985). Scientometric indicators: a 32 country comparative evaluation of publishing performance and citation impact: World Scientific.
  12. Cantú-Ortiz, F. J. (2017). Research Analytics: Boosting University Productivity and Competitiveness through Scientometrics. Auerbach Publications.
  13. Chiesa, V., & Frattini, F. (2009). Evaluation and performance measurement of research and development: techniques and perspectives for multi-level analysis: Edward Elgar.
  14. Cronin, B. (1984). The citation process: the role and significance of citations in scientific communication: Taylor Graham.
  15. Cronin, B., & Atkins, H.B. (Eds.). (2000). The Web of Knowledge: A Festschrift in Honor of Eugene Garfield: Information Today Inc.
  16. Cronin, B. & Sugimoto, C. (Eds). (2014) Beyond Bibliometrics : Harnessing Multidimensional Indicators of Scholarly Impact. Massaschussets, MIT Press.
  17. Cronin, B. & Sugimoto, C.R., (Eds.) (2015). Scholarly metrics under the microscope. Medford, NJ: Information Today.
  18. De Bellis, N. (2009). Bibliometrics and Citation Analysis: From the Science Citation Index to Cybermetrics. Lanham: Scarecrow Press.
  19. Devarajan, G. (1997). Bibliometric studies: Ess Ess Publications.
  20. Diodato, V.P. (1994). Dictionary of bibliometrics: Haworth Press.
  21. Egghe, L. (2005). Power Laws in the Information Production Process: Lotkaian Informetrics: Emerald Group Publishing Limited.
  22. Egghe, L., & Rousseau, R. (1990). Introduction to informetrics: quantitative methods in library, documentation and information science: Elsevier Science Publishers.
  23. Eom, S. (2009). Author cocitation Analysis: Quantitative Methods for Mapping the Intellectual Structure of an Academic Discipline. Hershey: Information Science Reference.
  24. Érdi, P. (2019). Ranking - The Unwritten Rules of the Social Game We All Play. New York: Oxford University Press. 
  25. Evered, D., & Harnett, S. (1989). The Evaluation of Scientific Research: Wiley.
  26. Gingras, Y. (2016). Bibliometrics and Research Evaluation: Uses and Abuses, Cambridge, MA: MIT Press.
  27. Geisler, E. (2000). The metrics of science and technology: Quorum Books.
  28. Harzing, A.W. (2010). The Publish Or Perish Book: Your Guide to Effective and Responsible Citation Analysis: Tarma Software Research.
  29. Hasan, N. (2010). Mapping the dynamics of world agricultural research output: A scientometric study LAP LAMBERT Academic Publishing.
  30. Hjerppe, R. (1980). An outline of bibliometrics and citation analysis, Royal Institute of Technology Library.
  31. Holden, G., Rosenberg, G., & Barker, K. (2006). Bibliometrics in social work: Haworth Social Work Practice Press.
  32. International Survey of Research University Faculty: Use of Bibliometric Ratings, Identifiers & Indicators (2017). Primary Resource Group.
  33. Leydesdorff, L. (2001). The Challenge of Scientometrics: The Development, Measurement, and Self-Organization of Scientific Communications: Universal-Publishers.
  34. Moed, H.F. (2017). Applied evaluative informetrics, Springer.
  35. Moed, H.F. (1989). The use of bibliometric indicators for the assessment of research performance in the natural and life sciences: aspects of data collection, reliability, validity, and applicability: DSWO Press.
  36. Moed, H.F., Glänzel, W., & Schmoch, U. (2004). Handbook of quantitative science and technology research: the use of publication and patent statistics in studies of S & T systems: Kluwer Academic Publishers.
  37. Nicholas, D., & Ritchie, M. (1978). Literature and bibliometrics: C. Bingley.
  38. Okubo, Y. (1997). Bibliometric indicators and analysis of research systems: methods and examples: OECD.
  39. PÇŽces, V., Pivec, L., & Teich, A.H. (1999). Science evaluation and its management: IOS Press.
  40. Raan, A.F.J. (1988). Handbook of quantitative studies of science and technology: North-Holland.
  41. Raan, A.F.J., Nederhof, A.J., & Moed, H.F. (1989). Science and technology indicators: their use in science policy and their role in science studies: select proceedings of the First International Workshop on Science and Technology Indicators, Leiden, The Netherlands, 14-16 November 1988: DSWO Press, University of Leiden.
  42. Rana, M.S. (2010). Scientometric Study of Wild Mammal Research in India: Authorship, Distribution and Research Trend: LAP Lambert Academic Publishing
  43. Rao, I.K.R. (2010). Growth of Literature and Measures of Scientific Productivity: Scientometric Models, Ess Ess Publications.
  44. Roemer, R. C. & Borchardt, R. (2015). Meaningful Metrics: A 21st Century Librarian's Guide to Bibliometrics, Altmetrics, and Research Impact, ACRL. 
  45. Santo, A.E. (1978). A measure of the dimensions of interdisciplinarity of two applied sciences: a scientometric model: University of Wisconsin.
  46. Sinha, S. C. & Zhiman, A. K. (2001). Citation Analysis of Research Field and Information Technology Development. ESS ESS Publications. 
  47. Sugimoto, C.R., & Larivière, V. (2017). Measuring research: what everyone needs to know. Oxford: Oxford University Press. 
  48. Tattersall, A. (editor) (2015). Altmetrics: A practical guide for librarians, researchers and academics, Facet Publishing.
  49. Thelwall, M. (2016). Web indicators for research evaluation: A practical guide. Synthesis Lectures on Information Concepts, Retrieval, and Services. San Rafael, CA: Morgan & Claypool Publishers.
  50. Tijssen, R.J.W. (1992). Cartography of science: scientometric mapping with multidimensional scaling methods: DSWO Press, Leiden University.
  51. Tijssen, R.J.W., Leeuwen, T.N., & Raan, A.F.J. (2002). Mapping the scientific performance of German medical research: an international comparative bibliometric study: Schattauer.
  52. Todeschini, R., & Baccini, A. (2016). Handbook of bibliometric indicators: quantitative tools for studying and evaluating research. Wiley-VCH..
  53. Vinkler, P. (2010). The Evaluation of Research by Scientometric Indicators. Oxford: Chandos.
  54. Whitley, R., & Gläser, J. (2007). The changing governance of the sciences: the advent of research evaluation systems: Springer.
  55. Zhao, D. & Strotmann, A.(2015). Analysis and Visualization of Citation Networks, Morgan & Claypool Publishers.
source: https://sites.google.com/site/hjamali/scientometric-portal

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How mobile banking service quality influence customer satisfaction of generation x and y?

Authors: Rahmat Trialih, Endang Siti Astuti, Devi Farah Azizah, Yusi Tyroni Mursityo, Miftakhul Dwi Saputro, Saide Saide, Yudha Alief Aprilian, Afian Syafaadi Rizki



Abstract: 

This study addresses satisfaction of generation X and Y as customer to mobile banking service quality of bank ABC in Indonesia. This research purposes to find out how mobile banking service quality influences the customer satisfaction especially in generation X and Y. While most studies relating to bank customers of generation X and Y have not received much attention even though these two generations are the customer majority that Indonesian bank owned currently. This research uses quantitative approach with descriptive research type. The sample number of this research is 100 respondents. We conclude that the mobile banking service quality has positive influence to customer satisfaction. Finally, recommendations and implications are discussed to help improving their mobile service to make the company remain competitive and keep the customers satisfied.

Full article: https://ieeexplore.ieee.org/abstract/document/8539720 


Saide Saide received the bachelor’s degree with the Department of Information System, Faculty of Science and Technology, Universitas Islam Negeri Sultan Syarif Kasim Riau-UIN SUSKA Riau, Indonesia, in 2013, the master’s degree from the Department of Information Management, National Taiwan University of Science and Technology, Taipei, Taiwan, in 2016, and the master’s degree from the Departmentof Information System, Sepuluh Nopember Instituteof Technology (ITS Surabaya), Surabaya, Indonesia, in 2016, all in information systems and knowledge management. He is currently a Lecturer with the Department of Information System, Facultyof Science and Technology, Universitas Islam Negeri Sultan Syarif Kasim Riau - UIN SUSKA Riau. He was a Visiting Scholar and Research Collaboration withTampere University, Finland, a Researcher with the Department of Information Management, National Taiwan University of Science and Technology, a Project Management with EnReach - Energy Research Center, UIN SUSKA Riau, Indonesia. He has authored numerous articles published in SSCI/SCI journals such as Big Data, Technology Analysis & Strategic Management, IEEE Transactions on Engineering Management, and Journal of Enterprise Information Management, International Journal of Innovation Management, Journal of Science and Technology Policy Management, and International Journal of Business and Society. His research interests include knowledge management, information system, and IT-business strategy.

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A Brief Review: The Roles in Triggering Knowledge Management Scheme Adoption to Increase Enterprise Performance

Authors: Richardus Eko Indrajit, Saide Saide, Rahmat Trialih, Herzavina Herzavina



Abstract:

Knowledge management (KM) is considered as an important instrument for gaining enterprise competitive advantage. However, a major obstacle from the perspective of integration still exists. Several studies show that the support of Top Management (TM) and Information Technology (IT) become two core issues faced by the enterprise. This study aims to review a determine factor related to those components for the purpose of creating a conceptual model related to KM adoption. The authors used a series of methodological activities, which are: literature review, problems identification, selection process, synthesizing, ideas formulation, and conclusions generation. Finally, the output of this research is a conceptual model that consists of four variables namely Knowledge Management, Information Technology, Top Management and Enterprise Performance.

Full Article: https://ieeexplore.ieee.org/abstract/document/8539520 


Saide Saide received the bachelor’s degree with the Department of Information System, Faculty of Science and Technology, Universitas Islam Negeri Sultan Syarif Kasim Riau-UIN SUSKA Riau, Indonesia, in 2013, the master’s degree from the Department of Information Management, National Taiwan University of Science and Technology, Taipei, Taiwan, in 2016, and the master’s degree from the Departmentof Information System, Sepuluh Nopember Instituteof Technology (ITS Surabaya), Surabaya, Indonesia, in 2016, all in information systems and knowledge management. He is currently a Lecturer with the Department of Information System, Facultyof Science and Technology, Universitas Islam Negeri Sultan Syarif Kasim Riau - UIN SUSKA Riau. He was a Visiting Scholar and Research Collaboration withTampere University, Finland, a Researcher with the Department of Information Management, National Taiwan University of Science and Technology, a Project Management with EnReach - Energy Research Center, UIN SUSKA Riau, Indonesia. He has authored numerous articles published in SSCI/SCI journals such as Big Data, Technology Analysis & Strategic Management, IEEE Transactions on Engineering Management, and Journal of Enterprise Information Management, International Journal of Innovation Management, Journal of Science and Technology Policy Management, and International Journal of Business and Society. His research interests include knowledge management, information system, and IT-business strategy.

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Investigating The Adoption of Knowledge Management in a Non-Govermental Organization in Malaysia

Authors: Khairul Shafee Kalid and Saide Saide


 

Abstract:

Non-governmental organizations use knowledge extensively in humanitarian efforts, engagements with organizations concerning the welfare of the people and other activities. The knowledge in nongovernmental organizations are mostly tacit. Nevertheless, little is known about knowledge management practices in non-governmental organizations.The aim of this study is to investigate the adoption of knowledge management in a nongovernmental organization.This study adopts a case study research design. Data was collected through a survey sent to a non-governmental organization.The questionnaire was based on the four pillars of knowledge management namely management and organization, people and culture, content and processes and infrastructure. A total of 31 respondents from one NGO participated in the survey.The data was analyzed using descriptive analyses.The findings indicate that knowledge is widely acknowledge as important in non-governmental organizations.To a certain extent, knowledge management principles have been practiced in the organization.However, non-governmental organizations have yet to establish an organization wide knowledge management strategy.The study provides an understanding of how knowledge management is perceived by the non-governmental organizations and provide valuable insights to the practice of knowledge management in nongovernmental organizations.

 

Full article: http://repo.uum.edu.my/25190/ 


Saide Saide received the bachelor’s degree with the Department of Information System, Faculty of Science and Technology, Universitas Islam Negeri Sultan Syarif Kasim Riau-UIN SUSKA Riau, Indonesia, in 2013, the master’s degree from the Department of Information Management, National Taiwan University of Science and Technology, Taipei, Taiwan, in 2016, and the master’s degree from the Departmentof Information System, Sepuluh Nopember Instituteof Technology (ITS Surabaya), Surabaya, Indonesia, in 2016, all in information systems and knowledge management. He is currently a Lecturer with the Department of Information System, Facultyof Science and Technology, Universitas Islam Negeri Sultan Syarif Kasim Riau - UIN SUSKA Riau. He was a Visiting Scholar and Research Collaboration withTampere University, Finland, a Researcher with the Department of Information Management, National Taiwan University of Science and Technology, a Project Management with EnReach - Energy Research Center, UIN SUSKA Riau, Indonesia. He has authored numerous articles published in SSCI/SCI journals such as Big Data, Technology Analysis & Strategic Management, IEEE Transactions on Engineering Management, and Journal of Enterprise Information Management, International Journal of Innovation Management, Journal of Science and Technology Policy Management, and International Journal of Business and Society. His research interests include knowledge management, information system, and IT-business strategy.

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