When does low interconnectivity cause systemic risk?

We analysed a systemic liquidity crisis by using a unique money market data-set in which the coded identity of the counterparties of each trade is known. Contrary to recent findings, we did not observe a positive relationship between interconnectivity and systemic risk. We have concluded that our conflicting findings can be related to the degree of market concentration on the borrowing side of the funding market. High level of concentration in the borrowing side led to lower interconnectivity but higher systemic risk prior to the crisis. We conclude that measures of market heterogeneity should be used to generalize the relationship between systemic risk and interconnectivity.     

Designing an electronic auction market for complex ‘smart parts’ logistics: Options based on LeBaron's computational stock market

Modern technologies, such as RFID, offer never-before seen learning abilities to parts moving in supply chains. Logistics systems may be understood as complex adaptive logistics systems (CALS). They also may be conceived as electronic auction markets as ‘smart parts’ bid for the best routing and pricing from transportation firms. To ensure the world-wide functionality and efficiency of CALS transportation markets, we suggest the utility of an agent-based computational market design based on Blake LeBaron's stock-market model. Given that parts may be more or less smart, markets more or less complex, and self-organizing CALS systems probabilistically subject to the bullwhip effect, we suggest nine different computational CALS market-design options, offering more adaptivity to unexpected environmental contingencies.     

Evaluación del efecto de la psicología del inversionista en un mercado bursátil artificial mediante su grado de eficiencia

The main objective in this paper is developing a cellular automaton model where interact more than one kind of broker, where the use and exchange of information between the investors explain the complexity through the Hurst coefficient estimation, this, represents an efficient or random market when the value is equal to 0.5. Due to the variants proposed in this research it can be determined that should exist a rational component in the simulator in order to generate an efficient behavior.     

Investigating science for governance through the lenses of complexity

This paper assesses the contributions of complexity theory to post-normal science. The oversupply of facts in science for governance is explained as a matter of complexity, defined as irreducible pluralism in the knowledge base. The paper shows how complexity provides an interface to engage with the multiple facts of science through three different examples. First, water narratives are used to show how different scales of analysis produce contradictory scientific representations of the same system. Second, smart electricity grids are assessed to demonstrate how different levels of uncertainty are associated with different representations. Third, the case of slum upgrading is used to discuss the need to take into account stakes in science for governance.     

The rebound effect: An evolutionary perspective

The rebound effect presents a major flaw in to energy conservation policies that aim to reduce energy consumption through energy efficiency development. Economics and energy related disciplines have thus far developed tools to measure such a phenomenon. This paper attempts to explain this seeming paradox using a thermodynamic-evolutionary theoretical framework in addition to the traditional economic approach. We here propose that evolutionary systems, such as biological or even economic systems, may rearrange themselves in a more complex fashion under the pressure of an increasing flux of energy, driven by the higher conversion rate of greater efficiency. Higher complexity, due to a greater energy density rate, counteracts the positive effects of energy efficiency. We investigated this hypothesis in the context of the road freight transport system and the productive structure. The qualitative analysis in this paper, further substantiated by figures, provides a link between the dynamics of production patterns and the effect of efficiency in the light of the macro-economic effects of increased energy demand. The analysis departs from a rigorous investigation of the actual energy efficiency evolution in the road freight transport system to develop through a survey of the subsequent worldwide economic revolution in the production system. It is then shown how outsourcing, the key feature of globalization, can be identified as the main source of traffic density growth. Finally, four paradigms are used to stress how the shift in the production system must be considered a leap in structural complexity that consequently serves to increase the frequency of components’ interactions.     

新古典经济学在中国转型实验中的作用有限

“华盛顿共识”和“休克疗法”是新古典宏观经济学派反凯恩斯革命的新浪潮。他们否认大萧条的基本教训,无视历史的多样性和经济的复杂性。他们自上而下设计的自由化与私有化政策,导致苏东(前苏联和东欧)经济在过去十余年间的大幅下跌。中国和苏东转型实验的比较研究,促使我们重新检验经济学的基本问题,例如均衡学派与非均衡演化学派关于经济波动本质的争论。转型萧条的惨重代价,使我们加深理解新古典经济学的误区,例如价格的线性供求理论、预算软约束理论、宏观经济的微观基础理论,以及新制度经济学的趋同理论。中国基于学习、创新和分散试验的新经验,将使经济学超越均衡优化的古典规范,去探索非均衡演化的复杂经济学。     

Bounded interpersonal inferences and decision making

Summary. Individual decision making is based on predictions about other players' choices as well as on valuations of reactions to predictions. In this sense, a player has a prediction-decision criterion for decision making. We develop a theory of prediction-decision criteria, which enables us to capture new phenomena on individual decision making in games. The decision making situation is described in the epistemic logic GL of shallow depths. There, each player considers his and other players' decision making down to some shallow depths. It is a point of our theory to investigate inferential complexities of interpersonal introspections. In particular, we can discuss a minimal epistemic inferential structure for prediction-decision making. We will find parallel structures in decision making and prediction making, which is called an inner parallelism. The climax of the paper is the consideration of inner parallelisms of prediction-decision making. Received: August 31, 2000; revised version: April 9, 2001     

Simplicity is not key: Understanding firm-generated social media images and consumer liking

Social media platforms are becoming increasingly important marketing channels, and recently these channels are becoming dominated by content that is not textual, but visual in nature. In this paper, we explore the relationship between the visual complexity of firm-generated imagery (FGI) and consumer liking on social media. We use previously validated image mining methods, to automatically extract interpretable visual complexity measures from images. We construct a set of six interpretable measures that are categorized as either (1) feature complexity measures (i.e., unstructured pixel-level variation; color, luminance, and edges) or (2) design complexity measures (i.e., structured design-level variation; number of objects, irregularity of object arrangement, and asymmetry of object arrangement). These measures and their interpretability are validated using a human subject experiment. Subsequently, we relate these visual complexity measures to the number of likes. The results show an inverted u-shape between feature complexity and consumer liking and a regular u-shape relationship between design complexity and consumer liking. In addition, we demonstrate that using the six individual measures that constitute feature- and design complexity provides a more nuanced view of the relationship between the unique aspects of visual complexity and consumer liking of FGI on social media than observed in previous studies that used a more aggregated measure. Overall, the automated framework presented in this paper opens up a wide range of possibilities for studying the role of visual complexity in online content.     

Complexity thinking in public administration’s theories-in-use

A compressed overview of complexity theory in public administration creates a starting point for comparison with other theories-in-use. The underpinning methodological traditions of extant theories of public administration are compared for compatibilities with complexity theory. Concepts generally acknowledged as within the scope and interest of public administration scholars (actors, policy processes, decisions, power, information and values) are used to extend the analysis of complexity theory’s contribution. The paper concludes that understanding the complexity friendliness of extant theories will both facilitate the greater use of complexity theory in PA and extend the explanatory capacity of the existing compatible theories.     

What a difference a word makes: Understanding threats to performance in a VUCA world

VUCA is an acronym that has recently found its way into the business lexicon. The components it refers to—volatility, uncertainty, complexity, and ambiguity—are words that have been variously used to describe an environment which defies confident diagnosis and befuddles executives. In a ‘VUCA world,’ both pundits and executives have said, core activities essential to driving organizational performance—like strategic planning—are viewed as mere exercises in futility. VUCA conditions render useless any efforts to understand the future and to plan responses. When leaders are left with little to do other than wring their hands, organizational performance quickly falls at risk. In this installment of Organizational Performance, we demonstrate that by overlooking important differences in the conditions that volatility, uncertainty, complexity, and ambiguity describe, we have disempowered leaders. We show how leaders can appreciate the differences among each of these challenging situations in order to properly allocate scarce resources to preserve and enhance organizational performance.