Interdisciplinary Journal of Information, Knowledge, and Management 

About: Interdisciplinary Journal of Information, Knowledge, and Management is an academic journal published by Informing Science Institute. The journal publishes majorly in the area(s): Information system & Business. It has an ISSN identifier of 1555-1229. It is also open access. Over the lifetime, 268 publications have been published receiving 4899 citations. The journal is also known as: IJIKM.

Towards a Typology of Virtual Communities of Practice

Abstract: The literature is packed with “one-size-fits-all” advice on how to develop intentionally formed virtual communities of practice (VCoPs). However, a closer look at the literature shows that VCoPs often have unique “personalities.” Based on an extensive review of the literature and a study of 18 VCoPs, we built a typology containing 21 structuring characteristics. We then used this typology and three of the studied VCoPs to show how different their basic natures are. Researchers and practitioners alike must not only recognize the diversity of VCoPs, but also identify challenges, strategies and practices that are contingent upon their specific characteristics.

A New Typology Design of Performance Metrics to Measure Errors in Machine Learning Regression Algorithms

Abstract: Aim/Purpose: The aim of this study was to analyze various performance metrics and approaches to their classification. The main goal of the study was to develop a new typology that will help to advance knowledge of metrics and facilitate their use in machine learning regression algorithms Background: Performance metrics (error measures) are vital components of the evaluation frameworks in various fields. A performance metric can be defined as a logical and mathematical construct designed to measure how close are the actual results from what has been expected or predicted. A vast variety of performance metrics have been described in academic literature. The most commonly mentioned metrics in research studies are Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), etc. Knowledge about metrics properties needs to be systematized to simplify the design and use of the metrics. Methodology: A qualitative study was conducted to achieve the objectives of identifying related peer-reviewed research studies, literature reviews, critical thinking and inductive reasoning. Contribution: The main contribution of this paper is in ordering knowledge of performance metrics and enhancing understanding of their structure and properties by proposing a new typology, generic primary metrics mathematical formula and a visualization chart Findings: Based on the analysis of the structure of numerous performance metrics, we proposed a framework of metrics which includes four (4) categories: primary metrics, extended metrics, composite metrics, and hybrid sets of metrics. The paper identified three (3) key components (dimensions) that determine the structure and properties of primary metrics: method of determining point distance, method of normalization, method of aggregation of point distances over a data set. For each component, implementation options have been identified. The suggested new typology has been shown to cover a total of over 40 commonly used primary metrics Recommendations for Practitioners: Presented findings can be used to facilitate teaching performance metrics to university students and expedite metrics selection and implementation processes for practitioners Recommendation for Researchers: By using the proposed typology, researchers can streamline development of new metrics with predetermined properties Impact on Society: The outcomes of this study could be used for improving evaluation results in machine learning regression, forecasting and prognostics with direct or indirect positive impacts on innovation and productivity in a societal sense Future Research: Future research is needed to examine the properties of the extended metrics, composite metrics, and hybrid sets of metrics. Empirical study of the metrics is needed using R Studio or Azure Machine Learning Studio, to find associations between the properties of primary metrics and their “numerical” behavior in a wide spectrum of data characteristics and business or research requirements

Critical Success Factors for Implementing Business Intelligence Systems in Small and Medium Enterprises on the Example of Upper Silesia, Poland

Abstract: The main objective of this article is to identify the critical success factors (CSFs) for Business Intelligence (BI) systems implementation in small and medium enterprises (SMEs).The structure of the article is subordinated to this objective. The paper identifies the term Business Intelligence, characteristics of Business Intelligence systems, and various perspectives of their development. Then, the existing CSFs of IT projects and BI projects proposed by various authors in literature are reviewed. Next, on the basis of statistical data and literature, the role of SMEs in the economy and the barriers to their development are assessed. The obtained results allowed us to determine that one of the barriers to the SMEs development is the implementation and use of IT. Subsequently, using in-depth interviews with SMEs, the SMEs need for BI systems as well as the determinants and barriers to their implementation are recognized. Based on the findings, using critical thinking and inductive reasoning, the authors of the article along with the researched enterprises have defined CSFs that are crucial for implementing BI systems in SMEs. The results obtained may be useful for managers, policy makers, business analysts, and IT specialists in dealing with planning and implementation of BI systems in SMEs.

Approach to Building and Implementing Business Intelligence Systems

Abstract: The article aims at describing processes of building Business Intelligence (BI) systems. Taking the BI systems specifics into consideration, the authors present a suggested methodology of the systems creation and implementation in organisations. The considerations are focused on objectives and functional areas of the BI in organisations. Hence, in this context the approach to be used while building and implementing the BI involves two major stages that are of interactive nature, i.e. BI creation and BI "consumption". A large part of the article is devoted to presenting objectives and tasks that are realised while building and implementing BI.

User Acceptance of the E-Government Services in Malaysia: Structural Equation Modelling Approach

Abstract: This paper identifies the factors that determine users’ acceptance of e-Government services and its causal relationships using a theoretical model based on the Technology Acceptance Model. Data relating to the constructs were collected from 200 respondents in Malaysia and subjected to Structural Equation Modeling analysis. The proposed model fits the data well. Results indicate that the important determinants of user acceptance of the e-Government services are perceived usefulness, ease of use, compatibility, interpersonal influence, external influence, self efficacy, facilitating conditions, attitude, subjective norms, perceived behavioral control, and intention to use e-Government services/system. Finally, implications and recommendations of these finding are discussed.