Search results

As they say, “Change is the only constant.” Thriving and surviving during a period of extraordinary collision of technological advances, globalization, and climate change can be daunting. At any given point in one’s life, a transition can be interpreted in terms of the magnitude of change (how big or small) and the individual’s ontological experience of change (whether it disrupts an equilibrium or adapts an emergent way of life). These four quadrants represent different ways to live in a highly dynamic and complex world. We share the resulting four-quadrant framework from a quantitative and a mixed methods study to examine responses to various ways we respond to transitions. Contingent upon these two dimensions, one can use a four-quadrant framework to mobilize resources to design a response and hypothesize a desired outcome. Individuals may find themselves at various junctions of these quadrants over a lifespan. These four quadrants provide “requisite variety” to navigate individual ontology as they move into and out of fluid spaces we often call instability during a time of transition. In this chapter, we identified social, cognitive, psychological, and behavioral factors that contribute to thriving transition experiences, embracing dynamic stability. Two new constructs were developed, the first measures the receptivity to change, Transformation Quotient (TQ) and second measures the range of responses to transitions from surviving to thriving, Thriving Transitional Experiences (TTE). We hope our work will pave the way for Thriving to become a “normal” outcome of experiencing change by transforming the lexicon and expectation of engaging with transitions.

The purpose of this paper is to outline and demonstrate a method for screening and selection of potential portfolio companies (PCs) during the screening phase in corporate venture capital.

The use of the data envelopment analysis (DEA) enables the consideration of individual, heterogeneous and multidimensional decision criteria in portfolio selection and the preceding screening process by the investor.

The result of this method is a relative ranking of the PCs, with all the PCs considered serving as peer group. A weighting of individual criteria is not necessary because it is part of the functionality of DEA. The authors validate the proposed approach in a case study and show that it can be well combined with other models and theoretical frameworks.

The method is particularly useful in two cases. First, if a highly specialized investor wishes to use a variety of individual selection criteria for portfolio selection. Second, if an investor only has insufficient (financial) data on potential PCs, but still wants to make a (pre-) selection based on observable (qualitative) characteristics. This model helps to make consistent, intersubjectively comprehensible decisions based on valid decision criteria and helps to optimize the decision-making process in the context of portfolio selection in CVC.

This method allows the systematic selection of an attractive group from a large number of potential PCs, based on observable characteristics and taking into account individual strategic investment objectives, without having to make assumptions about underlying distributions or weights of decision criteria.

The framework, methodology and development of pansystems cybernetics are introduced. Related contents include: the postmodernizational systems thought, the epitome of pansystems methods, hi‐tech mechanism, social cybernetics, pansystems views of value, labor, management and economics, pedagogy, history and futurology, systems mathematics, general clustering analysis, observocontrollability, generalized living systems, information metascience, regret information, general fuzzy control, generalized gray systems, entropy, large scale dynamical supercomplicated Shengke systems, function simulations, transformation theory, simplification, strengthening, forming substance of subsystems of living systems of Miller’s theory, etc.

This paper presents a new simplified text of some concepts of pansystems methodology and related applications to pedagogy, methods of teaching, study and creation, including certain principles of operations research, systems theory, cybernetics, etc.

The framework, panorama, related applications and development of pansystems thinking are introduced and some problems concerning generalized systems, derivatives, symmetry and quantification are investigated, a sort of difference‐identity theory within the framework of pansystems thinking is cultivated, and a new type of clustering method with many intertransformations among some important pansystems concepts is presented. Related contents include: pansystems combination of mathematics, systems, dialectics and poetry thinking, methodology to comprehend laws by pansymmetries or by moving networks, the pansystems views of generalized order, quotientization and series‐parallel relations, control‐reachability, duality transformation, discoupling principle, communication theorems, general parental relations, etc.

Exponential organizations (ExOs) are purpose-driven companies that leverage exponential technologies and exponential business practices to grow and scale rapidly, transform industries and create massive value and impact. In contrast, non-ExOs follow a linear approach to business and organizational strategy design and execution. This study aims to validate the hypothesis, based on financial metrics, that ExOs outperform their competitors and linear counterparts. Furthermore, it also brings a new understanding of the gap raised in the past eight years about how ExOs can achieve significantly better performance, measured with financial metrics.

For measuring how exponential an organization is, this study elaborated a completely new assessment tool called Exponential Quotient (ExQ). This study applied ExQ to the 100 largest US headquartered companies as ranked by Fortune magazine in 2014. Calculating the ExQ enabled this study to rank these Fortune 100 companies and identify the most and the least exponential firms. This study tracked these companies as to how they performed on different financial metrics over the eight years of 2014–2021 and analyzed the results.

Through the analysis, this study revealed that the top 10 ExOs have significantly outperformed their bottom 10 non-exponential peers, delivering 40x higher shareholder returns, 2.6x better revenue growth, 6.8x higher profitability and 11.7x better asset turnover. Furthermore, this study could identify commonalities and similarities between the two groups. This means that ExOs can thrive even in tough times and that accelerating technologies unlock abundance and allow every organization to become a disruptive innovator and stay ahead of the competition. These are novel results in the research focusing on the gap between exponential and traditional organizations.

Using the ExQ diagnostics tool, every organization can see how flexible, scalable and agile they are, which is the starting point for an exponential transformation program. Although this approach has already found its way into practice and is applied globally by thousands of organizations (startups, scaleups and incumbents), so far, the academic establishment is in its nascent phase. With this research, the authors wanted to extend this field of science. On the other hand, because of its novelty, no appropriate previous studies existed to compare the results.

The possible implications showed that there is a plannable way for significantly increasing an organization’s ExQ and advance it from a linear toward an exponential organizational model.

The results validated the robustness of the ExO framework and philosophy and shed light on the importance of exponential transformation – a proven method to increase an organization’s ExQ. This framework is not a “how to be successful” guide. Instead, it uncovered some of the previously unknown and universal mechanisms of scalability – which, in turbulent times, make companies successful (based on financial metrics). To the best of the authors’ knowledge, this study was among the first kind of in-depth analyses to validate the whole ExO model.

The purpose of this paper is to establish a version of a theorem that originated from population genetics and has been later adopted in evolutionary computation theory that will lead to novel Monte‐Carlo sampling algorithms that provably increase the AI potential.

In the current paper the authors set up a mathematical framework, state and prove a version of a Geiringer‐like theorem that is very well‐suited for the development of Mote‐Carlo sampling algorithms to cope with randomness and incomplete information to make decisions.

This work establishes an important theoretical link between classical population genetics, evolutionary computation theory and model free reinforcement learning methodology. Not only may the theory explain the success of the currently existing Monte‐Carlo tree sampling methodology, but it also leads to the development of novel Monte‐Carlo sampling techniques guided by rigorous mathematical foundation.

The theoretical foundations established in the current work provide guidance for the design of powerful Monte‐Carlo sampling algorithms in model free reinforcement learning, to tackle numerous problems in computational intelligence.

Establishing a Geiringer‐like theorem with non‐homologous recombination was a long‐standing open problem in evolutionary computation theory. Apart from overcoming this challenge, in a mathematically elegant fashion and establishing a rather general and powerful version of the theorem, this work leads directly to the development of novel provably powerful algorithms for decision making in the environment involving randomness, hidden or incomplete information.

Leadership development transforms the lives of many students and leadership educators regularly witness these changes. But little research has articulated what is being taught that facilitates this change, how we can make it happen more often, or how we can measure this change. These transformations contribute to desirable outcomes including student persistence and academic achievement. Leadership studies programs have great potential to contribute to these positive student outcomes especially with first-year students.

Using the Social Change Model of Leadership Development, we delineate how the study of leadership aids students in experiencing these transformations, as defined by Schreiner’s Thriving Model, along with example lessons that serve elements in both models. Significant implications are discussed, including greater engagement with first-year students and outreach to at-risk students. This is followed by recommendations for leadership educators and a discussion of future research focus areas.