Guiding Situational Applications from a Structuration Perspective

Situational applications are a new breed of software assumed to fit to the types of tasks and contextual requirements encountered in dynamic work environments described as weakly structured, highly diverse and fast-changing. The aim of this paper is to discuss the characteristics of situational applications and how organizations can benefit from them with the help of Structuration Theory. Concepts from Structuration Theory allow us to differentiate situational applications from traditionally developed business applications according to the specifics of design and development, the resulting product as well as its deployment and usage. Theoretical implications of this discussion are a much more concise description of situational applications and a host of potential research avenues to further explore research questions on situational applications while managerial implications not only call for creating an organizational and technological infrastructure in support of situational applications, but also for guidance of these grassroots approaches to software development and use

Organisational Memory Systems Application of Advanced Database and Network Technologies in Organisations

This paper deals with Organisational Memory Systems (OMS) which are seen as a new kind of information systems. OMS result from the application of advanced database and network technologies to support Organisational Memory concepts and approaches. It is suggested to take Organisational Memory concepts as a vision for the future development of corporate Intranets

SimKnowledge - Multi agent-based simulation of knowledge sharing

Even though there is abundant literature on successful cases of organizations applying knowledge management (KM) instruments, many KM initiatives have failed to achieve their knowledge and business goals. In order to foster decisions about the design of such initiatives, information is required on success factors and barriers when selecting KM instruments. Multi-agent based simulation (MABS) is suggested as an instrument to investigate potential effects of KM instruments on dependent variables such as knowledge goals, e.g., sharing of knowledge in organizations, or business goals, e.g., business performance. For such a simulation, the concept of knowledge sharing, influencing factors and their impact on business and knowledge goals have to be operationalized. This paper presents such a model which is based on an extensive multidisciplinary literature survey. The model is implemented in a MABS tool used for a series of experiments contrasting results with/without KM instruments. Finally, the paper discusses results, limitations, further enhancements and practical implications of the simulation

The Ends of Knowledge Sharing in Networks: Using Information Technology to Start Knowledge Protection

Organisations need networks to leverage external knowledge, particularly for SMEs with their limited resources. Organisations use networks for knowledge sharing to foster innovation. This use of networks bears risks like the unwanted spill-over of knowledge. Consequently, organisa-tions need to balance sharing and protecting knowledge. While scholars have extensively inves-tigated the sharing perspective, they have so far neglected knowledge protection in network set-tings and especially the interplay between sharing and protection. This paper illuminates the motives and practices of network members switching from open sharing to stronger protection on the basis of 53 interviews with members from 10 SME networks. We describe three patterns of switching behaviour and explain how the interviewees adapt the use of collaborative IT to manage the switches. Employees switch from sharing to being open to (a) a certain extent, (b) a certain group, or (c) a certain topic. We find that the three types of switching behaviour are re-lated to network characteristics and to corresponding adaptions in using collaborative IT. Col-laborative IT does not necessarily hamper knowledge protection, but adapted use can support both knowledge sharing and knowledge protection. We argue that organisations should develop protection capabilities to manage the switches

Comparing Pineapples with Lilikois: An Experimental Analysis of the Effects of Idea Similarity on Evaluation Performance in Innovation Contests

Identifying promising ideas from large innovation contests is challenging. Evaluators do not perform well when selecting the best ideas from large idea pools as their information processing capabilities are limited. Therefore, it seems reasonable to let crowds evaluate subsets of ideas to distribute efforts among the many. One meaningful approach to subset creation is to draw ideas into subsets according to their similarity. Whether evaluation based on subsets of similar ideas is better than compared to subsets of random ideas is unclear. We employ experimental methods with 66 crowd workers to explore the effects of idea similarity on evaluation performance and cognitive demand. Our study contributes to the understanding of idea selection by providing empirical evidence that crowd workers presented with subsets of similar ideas experience lower cognitive effort and achieve higher elimination accuracy than crowd workers presented with subsets of random ideas. Implications for research and practice are discussed

Human-Robot Interaction: Mapping Literature Review and Network Analysis

Organizations increasingly adopt social robots as additions to real-life workforces, which requires knowledge of how humans react to and work with robots. The longstanding research on Human-Robot Interaction (HRI) offers relevant insights, but the existing literature reviews are limited in their ability to guide theory development and practitioners in sustainably employing social robots because the reviews lack a systematic synthesis of HRI concepts, relationships, and ensuing effects. This study offers a mapping review of the past ten years of HRI research. With the analysis of 68 peer-reviewed journal articles, we identify shifting foci, for example, towards more application-specific empirical investigations, and the most prominent concepts and relationships investigated in connection with social robots, for example, robot appearance. The results offer Information Systems scholars and practitioners an initial knowledge base and nuanced insights into key predictors and outcome variables that can hinder and foster social robot adoption in the workplace

IT Enablers for Task Organization and Innovation Support to drive Team Performance

Teams drive organizational innovation by applying knowledge to solve complex problems. However, many teams underperform and organizations do not sufficiently harvest the benefits they could gain from effective IT support for team processes consisting of creative (exploration) and structurally controlled (exploitation) processes. This paper investigates the impact of knowledge application on support for innovation, task organization, and team performance in a mixed method case study in two medium-sized, knowledge-intensive, information technology-affine organizations. We surveyed 204 employees and found that knowledge application positively affects task organization. Knowledge application and task organization positively affect support for innovation. Both, task organization and support for innovation positively affect team performance. Subsequent focus group interviews with 16 employees provided us with an in-depth understanding of factors that support team performance. Qualitative content analysis resulted in nine IT enablers, which can be adapted by organizations to foster coordination while at the same time promote innovation

Weak positive cloud-to-ground flashes in Northeastern Colorado

The frequency distributions of the peak magnetic field associated with the first detected return stroke of positive and negative cloud-to-ground (CG) flashes were studied using lightning data from northeastern Colorado. These data were obtained during 1985 with a medium-to-high gain network of three direction finders (DF's). The median signal strength of positive flashes was almost two times that of the negatives for flashes within 300 km of the DF's, which have an inherent detection-threshold bias that tends to discriminate against weak signals. This bias increases with range, and affects the detection of positive and negative flashes in different ways, because of the differing character of their distributions. Positive flashes appear to have a large percentage of signals clustered around very weak values that are lost to the medium-to-high gain Colorado Detection System very quickly with increasing range. The resulting median for positive signals could thus appear to be much larger than the median for negative signals, which are more clustered around intermediate values. When only flashes very close to the DF's are considered, however, the two distributions have almost identical medians. The large percentage of weak positive signals detected close to the DF's has not been explored previously. They have been suggested to come from intracloud discharges and thus are improperly classified as CG flashes. Evidence in hand, points to their being real positive, albeit weak CG flashes. Whether or not they are real positive ground flashes, it is important to be aware of their presence in data from magnetic DF networks