Using Systems Dynamics to Operationalize Process Theory in Information Systems Research

The nature of quantitative research in information systems has been dominated by variance theories. Variance theories comprise constructs or variables and propositions or hypotheses linking them. Typically, researchers identify independent variables and a dependent variable and collect data to verify the hypothesized relationship between the two sets of variables. One of the major shortcomings of such an approach is that the temporal dimension is often lost because data are collected at a given point in time. In this paper, we present a research method that operationalizes process theory. Process theory recognizes that variables change over time and interact with each other. This approach is particularly useful to study the conversion of IT investments into IT assets, or the conversion of IT assets into organizational value. This conversion process, which is often subsumed into the black box that lies between the input (independent) variables and output (dependent) variable in variance theories, is recognized and formalized in process theory. We show how systems dynamics modeling can be used to operationalize process theory in the context of IS use. We demonstrate how we can study complex IS problems by developing dynamic hypotheses and then using systems dynamics modeling. The approach that we employ incorporates both qualitative (soft) and quantitative aspects and complements variance theory. We conclude by highlighting the contribution of this approach and the study results to both theory and research. Specific theoretical contributions lie in developing and communicating archetypal patterns of IS use as well as the ability to incorporate the effects of feedback in the context of IS use. An important contribution to research lies in the ability to explicitly relate IS use to productivity. The implication of such contributions to both theory and research is that practitioners can benefit from directly applicable results, especially when it comes to deciding management policies and strategies

Spectral Modes of Network Dynamics Reveal Increased Informational Complexity Near Criticality

What does the informational complexity of dynamical networked systems tell us about intrinsic mechanisms and functions of these complex systems? Recent complexity measures such as integrated information have sought to operationalize this problem taking a whole-versus-parts perspective, wherein one explicitly computes the amount of information generated by a network as a whole over and above that generated by the sum of its parts during state transitions. While several numerical schemes for estimating network integrated information exist, it is instructive to pursue an analytic approach that computes integrated information as a function of network weights. Our formulation of integrated information uses a Kullback-Leibler divergence between the multi-variate distribution on the set of network states versus the corresponding factorized distribution over its parts. Implementing stochastic Gaussian dynamics, we perform computations for several prototypical network topologies. Our findings show increased informational complexity near criticality, which remains consistent across network topologies. Spectral decomposition of the system's dynamics reveals how informational complexity is governed by eigenmodes of both, the network's covariance and adjacency matrices. We find that as the dynamics of the system approach criticality, high integrated information is exclusively driven by the eigenmode corresponding to the leading eigenvalue of the covariance matrix, while sub-leading modes get suppressed. The implication of this result is that it might be favorable for complex dynamical networked systems such as the human brain or communication systems to operate near criticality so that efficient information integration might be achieved

Measuring the knowledge base of regional innovation systems in Sweden

Within the literature on innovation systems, there are a growing number of scholars emphasizing the importance of differentiated knowledge bases underlying innovation activities. The existing work on knowledge bases is largely grounded on in-depth case studies; while surprisingly little effort has been done so far to operationalize the concept in a more systematic manner. In this paper, an attempt is made to develop a scheme of analysis to identify the knowledge base of a regional economy. We suggest using occupation data in association with a location quotient analysis, to assess whether a regional economy has a particular strength in one (or more) knowledge bases. To bring the analytical scheme into practice and assess it, we apply it on the county level in Sweden. The results are explained and contrasted with insights on the regional economies taken from secondary sources. We conclude that the proposed scheme of analysis leads to fairly reliable results, and could stimulate further empirical research on differentiated knowledge bases.differentiated knowledge base; regional innovation system; Sweden

Interaction and Experience in Enactive Intelligence and Humanoid Robotics

We overview how sensorimotor experience can be operationalized for interaction scenarios in which humanoid robots acquire skills and linguistic behaviours via enacting a “form-of-life”’ in interaction games (following Wittgenstein) with humans. The enactive paradigm is introduced which provides a powerful framework for the construction of complex adaptive systems, based on interaction, habit, and experience. Enactive cognitive architectures (following insights of Varela, Thompson and Rosch) that we have developed support social learning and robot ontogeny by harnessing information-theoretic methods and raw uninterpreted sensorimotor experience to scaffold the acquisition of behaviours. The success criterion here is validation by the robot engaging in ongoing human-robot interaction with naive participants who, over the course of iterated interactions, shape the robot’s behavioural and linguistic development. Engagement in such interaction exhibiting aspects of purposeful, habitual recurring structure evidences the developed capability of the humanoid to enact language and interaction games as a successful participant

Carving out new business models in a small company through contextual ambidexterity: the case of a sustainable company

Business model innovation (BMI) and organizational ambidexterity have been pointed out as mechanisms for companies achieving sustainability. However, especially considering small and medium enterprises (SMEs), there is a lack of studies demonstrating how to combine these mechanisms. Tackling such a gap, this study seeks to understand how SMEs can ambidextrously manage BMI. Our aim is to provide a practical artifact, accessible to SMEs, to operationalize BMI through organizational ambidexterity. To this end, we conducted our study under the design science research to, first, build an artifact for operationalizing contextual ambidexterity for business model innovation. Then, we used an in-depth case study with a vegan fashion small e-commerce to evaluate the practical outcomes of the artifact. Our findings show that the company improves its business model while, at the same time, designs a new business model and monetizes it. Thus, our approach was able to take the first steps in the direction of operationalizing contextual ambidexterity for business model innovation in small and medium enterprises, democratizing the concept. We contribute to theory by connecting different literature strands and to practice by creating an artifact to assist managemen

Party system institutionalization and the quality of democracy in eastern Europe

Almost two decades have passed since the Third Wave of democratization brought an avalanche of new, relatively unstable democracies into being in Eastern Europe. Although democracy and a market economy seem to have taken firm root, at least for the ten Eastern European countries currently members of the European Union (EU), in the light of the complicated post-communist legacy, this may have not been enough time for their political parties and party systems to institutionalize. Moreover, a well-rehearsed litany of complaints has been recited against the countries in the region encompassing, inter alia, weak governability and accountability, a representation deficit; corruption and clientelism, populism, and threats to democratic stability; raising once again the question, "How important the former (i.e. political parties and party systems) are for the quality of democracy?