Christian Ploder

Knowledge Management Toolkit for SMEs

The discipline of knowledge management is no longer emerging in large organizations, but also small and medium-sized enterprises (SMEs) are focusing on finding the right process that will allow them to make advantages of their intellectual capital. Using survey data from 219 small and medium-sized enterprises in Austria and Switzerland, this article illustrates the four key knowledge processes (1) knowledge identification, (2) knowledge acquisition, (3) knowledge distribution, and (4) knowledge preservation for SMEs and also reports the findings of the empirical study designed to allocate cost-efficient software products to each of the four knowledge processes. As a result a knowledge toolkit for SMEs that integrates knowledge processes, methods and software tool for decision support making is given. Finally, the social view of knowledge management to SMEs is discussed, showing that the use of information technology is currently far more important than the integration of a social-cognitive perspective.

Balanced system for knowledge process management in SMEs

Purpose – The specific challenges which small and medium‐sized enterprises (SMEs) face lead to a special knowledge management system with harmonised methods and supporting software tools. This paper seeks to address this issue.Design/methodology/approach – A theoretical framework is proposed as a layer concept to describe the special situation of knowledge management in SMEs. Based on this framework empirical studies were conducted in German‐speaking countries to find out the relevant methods and tools supporting knowledge management in SMEs.Findings – The outcome of the empirical study describes methods of knowledge management supporting the four key knowledge processes in SMEs, i.e. knowledge identification, knowledge acquisition, knowledge distribution and knowledge preservation. The results are explained in the developed “TechnicalSocialSocialTechnical Model” (TSST Model), which is a balanced system for technical and social knowledge applications.Research limitations/implications – The empirical study...

KNOWLEDGE DIFFUSION THROUGH SME WEBSITES

AbstractThe discipline of knowledge management (KM) is no longer emerging in large organizations, but also small and medium-sized (SME) organizations are focusing on finding the right process that will allow them to make advantages of their intellectual capital. In this article the authors suggest a three-dimensional research framework for the determination of knowledge diffusion in SMEs. The research framework can be described by the following dimensions each being detailed through factor tables: (1) Data/Information/Knowledge, (2) information technology, (3) cognitive/social aspects of knowledge diffusion. The article presents the results of an empirical study investigating the knowledge diffusion process through SME websites in Austria, Germany, and Switzerland. The study provides evidence that the knowledge diffusion through SME websites is an unbalanced system regarding the three-dimensional research framework.

Data Driven Knowledge Discovery for Continuous Process Improvement

Knowledge is recognized as an organizational resource for business value creation. The work with knowledge—knowledge work—is thus an important part of value-adding processes in organizations. The ability of knowledge workers to analyze complex phenomena, interpret them and develop meaningful actions is one central part of knowledge work. The advancements of digital aids and especially the ability to analyze big amounts of data is a new phenomenon that is increasingly seen in organizations. In this work, we assume that there needs to be an interplay between digital aids and knowledge workers to allow new, deep insights into phenomena and support business value creation. We develop a model that describes how this interplay could look like and critically discuss it using real-world cases. From that, we find that it is crucial (1) separating data-driven and expert-based analysis in knowledge discovery, (2) clearly describing the problem that should be solved by the analysis, (3) understand the particular domain that analysis is applied to, (4) complement data-driven with expert-based analysis and (5) understand the entanglement of analysis and action implementation.

A Model for Data Analysis in SMEs Based on Process Importance

Data analysis technology enables businesses to enrich their business value creation by extracting knowledge. This knowledge extraction is done by knowledge workers. Businesses are seldom able to analyse all their data because the workload for the responsible persons would be too high. So the question which most of the businesses have to deal with is: “Where to start the data analysis” with the fundamental view of increasing the quality of business decisions and process stability. Therefore, the authors conducted a qualitative study based on expert interviews (n = 12) to select the important business processes in a company to start with data analysis enabling efficient business decisions. The result of the study is a set of factors which allows knowledge workers to filter the important knowledge intensive business processes to focus on.

Integration von IT-Governance in die Unternehmensstrategie

Eine wesentliche Aufgabe des Managements ist die Ausrichtung des Unternehmens an der Informationsfunktion, um die Geschaftsprozesse zu optimieren. Die Rolle der Informationstechnologie ist nicht eine reine Querschnittsfunktion, sondern kann als eine Steuerungsfunktion betrachtet werden. Informationstechnologien tragen schon heute zum Unternehmenserfolg bei und auch in Zukunft werden Wettbewerbsvorteile sowie Produktivitatssteigerungen erzielt. Somit liegt es in der Verantwortung des Managements nicht nur Corporate Governance Strategien zu entwickeln, sondern die Informationsfunktion in die Unternehmensstrategie und –ziele zu integrieren. Eine in 480 Unternehmen durchgefuhrte Studie vom Institut fur Wirtschaftsinformatik, Produktionswirtschaft und Logistik/Universitat Innsbruck bildet die Grundlage fur die Entwicklung eines Vorgehensmodells zur Einfuhrung von ITGovernance in Unternehmen.