The increasing progress in artificial intelligence and respective machine learning technology has fostered the proliferation of chatbots to the point where today they are being embedded into various human-technology interaction tasks. In enterprise contexts, the use of chatbots seeks to reduce labor costs and consequently increase productivity. For simple, repetitive customer service tasks such already proves beneficial, yet more complex collaborative knowledge work seems to require a better understanding of how the technology may best be integrated. Particularly, the additional mental burden which accompanies the use of these natural language based artificial assistants, often remains overlooked. To this end, cognitive load theory implies that unnecessary use of technology can induce additional extrinsic load and thus may have a contrary effect on users’ productivity. The research presented in this paper thus reports on a study assessing cognitive load and productivity implications of human chatbot interaction in a realistic enterprise setting. A/B testing software-only vs. software + chatbot interaction, and the NASA TLX were used to evaluate and compare the cognitive load of two user groups. Results show that chatbot users experienced less cognitive load and were more productive than software-only users. Furthermore, they show lower frustration levels and better overall performance (i.e, task quality) despite their slightly longer average task completion time.

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.

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 presented provides a model for knowledge management support in SMEs in German-speaking countries. Further research will expand the empirical data on an international focus. Originality/value – The developed TSST Model is currently used for the implementation of knowledge management systems in Austrian SMEs. The developed TSST Model functions as a decision support framework for SMEs to select technical and social knowledge methods according to the corresponding knowledge processes.

Information about the paper titled "CITIZEN VS. PROFESSIONAL DEVELOPERS: DIFFERENCES AND SIMILARITIES OF SKILLS AND TRAINING REQUIREMENTS FOR LOW CODE DEVELOPMENT PLATFORMS" at IATED Digital Library

The role of information technology (IT) is transmitting from a support tool into a source of competitive advantages. Continuous change in business performance raises the pressure on IT to change at the same speed. To create sustainable value, it is necessary for organizations to link the development of an IT strategy to the business strategy. In this paper the authors address the issue of implementing IT Governance into the organizational context by introducing a decision support framework. The basic research framework is the IT Governance model by Weill and Ross (2004) with its five decision fields: IT principles, IT architecture, IT infrastructure, business applications, IT investment and prioritization. Using survey data from 480 large organizations in German-speaking countries (Austria, Germany, Switzerland), this paper investigates the use of IT Governance initiatives and their implementation. A decision support framework for organizations was developed to implement IT Governance successfully in the country-specific context.