The Wheel of Business Model Reinvention: How to Reshape Your Business Model and Organizational Fitness to Leapfrog Competitors

In today's rapidly changing business landscapes, new sources of sustainable competitive advantage can often only be attained from business model reinvention, based on disruptive innovation and not incremental change or continuous improvement. Extant literature indicates that business models and their reinvention have recently been the focus of scholarly investigations in the field of strategic management, especially focusing on the search for new bases of building strategic competitive advantage, not only to outperform competitors but to especially leapfrog them into new areas of competitive advantage. While the available results indicate that progress is being made on clarifying the nature and key dimensions of business models, relatively little guidance of how to reshape business models and its organizational fitness dimensions have emerged. This article presents a systemic framework for business model reinvention, illustrates its key dimensions, and proposes a systemic operationalization process. Moreover, it provides a tool that helps organizations to evaluate both existing and proposed new business models.

The Organizational Fitness Navigator: Creating and Measuring Organizational Fitness for Fast-Paced Transformation

In the fast-changing environment of today dynamic capabilities to manage organizational transformation are regarded as crucial for business survival and improved performance. Although dynamic organizational capabilities have been receiving intense scrutiny by researchers and practitioners in the past few years, relatively little attention has been directed towards creating a systemic model of dynamic capabilities, and how to effectively measure what the authors call organizational fitness capabilities. This paper builds on the concepts of organizational fitness and its profiling (OFP), and proposes the organizational fitness navigator (OFN) as a systemic model of dynamic organizational capabilities. Part of the OFP model is a systemic scorecard (SCC) as a measurement tool for organizational fitness - in contrast to the well-known balanced scorecard (BSC) - for improving business survival and performance in increasingly networked environments.dynamic capabilities, organizational fitness, organizational fitness profiling, organizational fitness navigator, systemic scorecard

Single-Trial Phase Precession in the Hippocampus

During the crossing of the place field of a pyramidal cell in the rat hippocampus, the firing phase of the cell decreases with respect to the local theta rhythm. This phase precession is usually studied on the basis of data in which many place field traversals are pooled together. Here we study properties of phase precession in single trials. We found that single-trial and pooled-trial phase precession were different with respect to phase-position correlation, phase-time correlation, and phase range. Whereas pooled-trial phase precession may span 360°, the most frequent single-trial phase range was only ∼180°. In pooled trials, the correlation between phase and position (r = −0.58) was stronger than the correlation between phase and time (r = −0.27), whereas in single trials these correlations (r = −0.61 for both) were not significantly different. Next, we demonstrated that phase precession exhibited a large trial-to-trial variability. Overall, only a small fraction of the trial-to-trial variability in measures of phase precession (e.g., slope or offset) could be explained by other single-trial properties (such as running speed or firing rate), whereas the larger part of the variability remains to be explained. Finally, we found that surrogate single trials, created by randomly drawing spikes from the pooled data, are not equivalent to experimental single trials: pooling over trials therefore changes basic measures of phase precession. These findings indicate that single trials may be better suited for encoding temporally structured events than is suggested by the pooled data

Robust Organizational Fitness for Reinventing Strategy in Rapidly Changing Industry Landscapes

In fast-changing industry landscapes, companies are often engaged in both adaptive (reactive) and inventive (proactive, newly-shaping) change processes, and these require different types of organizational fitness capabilities. Our research of more than a decade conducted in a wide range of industries (See "About our Research") reveal that many companies are predominantly focused on past successes and internal difficulties, and do not possess the necessary robust capabilities to also inventively deal with rapidly changing industry landscapes. This seems due to the fact that many individual and group managerial minds are not able to view organizational fitness in its proper perspective, because of inadequate traditional strategy approaches being utilized. The paper provides insights into the concept and application of organizational fitness, and indicates how managers could benefit from guidelines to develop and manage robust organizational fitness capabilities.

The medial entorhinal cortex is necessary for temporal organization of hippocampal neuronal activity.

The superficial layers of the medial entorhinal cortex (MEC) are a major input to the hippocampus. The high proportion of spatially modulated cells, including grid cells and border cells, in these layers suggests that MEC inputs are critical for the representation of space in the hippocampus. However, selective manipulations of the MEC do not completely abolish hippocampal spatial firing. To determine whether other hippocampal firing characteristics depend more critically on MEC inputs, we recorded from hippocampal CA1 cells in rats with MEC lesions. Theta phase precession was substantially disrupted, even during periods of stable spatial firing. Our findings indicate that MEC inputs to the hippocampus are required for the temporal organization of hippocampal firing patterns and suggest that cognitive functions that depend on precise neuronal sequences in the hippocampal theta cycle are particularly dependent on the MEC

Spiking Neurons Learning Phase Delays

Time differences between the two ears are an important cue for animals to azimuthally locate a sound source. The first binaural brainstem nucleus, in mammals the medial superior olive, is generally believed to perform the necessary computations. Its cells are sensitive to variations of interaural time differences of about 10 μs. The classical explanation of such a neuronal time-difference tuning is based on the physical concept of delay lines. Recent data, however, are inconsistent with a temporal delay and rather favor a phase delay. By means of a biophysical model we show how spike-timing-dependent synaptic learning explains precise interplay of excitation and inhibition and, hence, accounts for a physical realization of a phase delay

How spiking neurons give rise to a temporal-feature map

A temporal-feature map is a topographic neuronal representation of temporal attributes of phenomena or objects that occur in the outside world. We explain the evolution of such maps by means of a spike-based Hebbian learning rule in conjunction with a presynaptically unspecific contribution in that, if a synapse changes, then all other synapses connected to the same axon change by a small fraction as well. The learning equation is solved for the case of an array of Poisson neurons. We discuss the evolution of a temporal-feature map and the synchronization of the single cells’ synaptic structures, in dependence upon the strength of presynaptic unspecific learning. We also give an upper bound for the magnitude of the presynaptic interaction by estimating its impact on the noise level of synaptic growth. Finally, we compare the results with those obtained from a learning equation for nonlinear neurons and show that synaptic structure formation may profit from the nonlinearity

The shape of ecological networks

We study the statistics of ecosystems with a variable number of co-evolving species. The species interact in two ways: by prey-predator relationships and by direct competition with similar kinds. The interaction coefficients change slowly through successful adaptations and speciations. We treat them as quenched random variables. These interactions determine long-term topological features of the species network, which are found to agree with those of biological systems.Comment: 4 pages, 2 figure

Frequency-Invariant Representation of Interaural Time Differences in Mammals

Interaural time differences (ITDs) are the major cue for localizing low-frequency sounds. The activity of neuronal populations in the brainstem encodes ITDs with an exquisite temporal acuity of about . The response of single neurons, however, also changes with other stimulus properties like the spectral composition of sound. The influence of stimulus frequency is very different across neurons and thus it is unclear how ITDs are encoded independently of stimulus frequency by populations of neurons. Here we fitted a statistical model to single-cell rate responses of the dorsal nucleus of the lateral lemniscus. The model was used to evaluate the impact of single-cell response characteristics on the frequency-invariant mutual information between rate response and ITD. We found a rough correspondence between the measured cell characteristics and those predicted by computing mutual information. Furthermore, we studied two readout mechanisms, a linear classifier and a two-channel rate difference decoder. The latter turned out to be better suited to decode the population patterns obtained from the fitted model