Narrow Results

Firms can have fundamental similarities and relatedness such as operating in the same geographic area and industries, being customers or suppliers. Understanding these connections has implications for cross-asset return predictability because information can flow through these linkages sluggishly. We introduce a novel peer momentum by linking firms that are co-searched by investors on the SEC EDGAR server. A trading strategy based on this peer momentum generates an annualized return of 13%, and it remains robust when controlling for other peer momentum, known asset pricing anomalies, and firm characteristics. Moreover, it outperforms the shared-analyst peer momentum identified by Ali and Hirshleifer (2020).

In this paper, we explore the use of opinion dynamics models to examine changes in opinions of lifelong learning, and to identify groups of people for targeted intervention to improve their reception to lifelong learning. This method has a multitude of potential applications related to clustering and segmentation. Singapore’s initiative for lifelong learning, SkillsFuture, serves as a case study for the application of the technique. We first found a positive correlation between how motivated people are to learn and a negative correlation between how much people know about SkillsFuture opportunities, with respect to their reception to SkillsFuture courses. Then, we used an opinion dynamics model to model the evolution of opinions to produce clusters of people whose opinions will converge. The clusters were then grouped into three groups: those with the largest increase, largest decrease and a middle group. Further examining the covariates of the people in each cluster (e.g., age, last drawn salary, etc.), we propose organizing sharing sessions for the group with the largest increase, intervention for the group with the largest decrease, and gathering more information about the motivations of the middle group.

We address the problem of finding large-scale functional and structural relationships between genes, given a time series of gene expression data, namely mRNA concentration values measured from genetically engineered rat fibroblasts cell lines responding to conditional cMyc proto-oncogene activation. We show how it is possible to retrieve suitable information about molecular mechanisms governing the cell response to conditional perturbations. This task is complex because typical high-throughput genomics experiments are performed with high number of probesets (10³–10⁴ genes) and a limited number of observations (< 10² time points). In this paper, we develop a deepest analysis of our previous work [Remondini et al., 2005] in which we characterized some of the main features of a gene-gene interaction network reconstructed from temporal correlation of gene expression time series. One first advancement is based on the comparison of the reconstructed network with networks obtained from randomly generated data, in order to characterize which features retrieve real biological information, and which are instead due to the characteristics of the network reconstruction method. The second and perhaps more relevant advancement is the characterization of the global change in co-expression pattern following cMyc activation as compared to a basal unperturbed state. We propose an analogy with a physical system in a critical state close to a phase transition (e.g. Potts ferromagnet), since the cell responds to the stimulus with high susceptibility, such that a single gene activation propagates to almost the entire genome. Our result is relative to temporal properties of gene network dynamics, and there are experimental evidence that this can be related to spatial properties regarding the global organization of chromatine structure [Knoepfler et al., 2006].

Dual-phase evolution (DPE) and the network theory help to analyze prominent properties of the complex adaptive systems (CASs) such as emergence and self-organization that are caused due to the phase transitions. These transitions are observed because of the increase and decrease in the number of system components and their interactions. The immune system, which is one of the CASs, provides an adaptive response to the foreign molecules. Prior to this response, the immune system is present in the circulation state and during the response, it moves into the growth state, where the number of immune cells and their cell–cell contacts increase rapidly. The phase transitions from the circulation state to the growth state and then back to the circulation state cause the emergence and self-organization of the immune system, respectively. There is a need to understand these complex cellular dynamics during the immune response. In this paper, we have proposed an integrated model of DPE, network theory, and the immune system that has helped to understand and analyze the phases and properties of the immune system. Analysis of the growth phase network is provided and it is concluded that this network exhibits scale-free nature following power law for the degree distribution of nodes.

This study identifies how relational and contractual governance mechanisms differently influence the distinct output of information systems development (ISD) performance at the project level. This study also reveals how the consequence of two modes of inter-organizational relationships (IOR) governance mechanism is affected by the gap of a dyadic partner’s centrality within the network — the client’s structural power (CSP). We collected dyadic samples of clients and vendors for 107 ISD projects and explored their governance mechanisms and project performances, all of which were evaluated by both parties. Our results first reveal a positive relationship between relational (or contractual) governance and qualitative (or quantitative) performance, respectively, but not vice versa. Second, the results incorporating a structural position within the network reveal that CSP facilitates the efficacy of relational governance to lead the quantitative performance, but surprisingly, CSP also mitigates the efficacy of contractual governance.

Because of its applications in network theory, the wide diameter of graphs has been studied extensively in recent years. It is still an open problem to compute the wide diameter of Cayley graphs. This paper investigates the wide diameter of Cayley graphs of ℤ_m, the cyclic group of residue classes modulo m. It is proved that the k-wide diameter of the Cayley graph Cay(Z_m, A) generated by a k-element set A is d + 1 for k = 2 and ≤ d + 1 for k = 3, where d is the diameter of Cay(ℤ_m, A).

We present a dynamic model based on the theories proposed by environmental criminologists to explain the emergence of crime hotspots within cities; a pervasive phenomenon that is largely independent of cities size and cultural differences. The model is defined on a multiplex network that represents a city spatial tiling with its corresponding urban transport infrastructure, allowing to explore the relation between crime hotspot locations and the network topological features. It also allows to explore the effects that cities time evolution and police checkpoints might have on the emergence of crime hotspots. For Mexico City, the model shows that heterogeneous distributions of criminal activity arise from a diffusion-driven instability, as a self-organizing process. The results obtained for this city are in line with several insights from environmental criminology, such as the relationship between urban layout and crime hotspots locations, or the conceptual label assigned to specific locations as crime generators. They also uncover new relationships between cities design and crime hotspot locations, and suggest that routine activity theory alone cannot explain the emergence of heterogeneous crime distributions.

Hydrogen bond is a key factor in the determination of structures and properties of room-temperature ionic liquids. Connections of these hydrogen bonds form a network. In this work, we analyzed the hydrogen bond network of 1-alkyl-3-methylimidazolium ionic liquids using network theory. A two-dimensional view of the hydrogen bond network has been generated, the connection pattern shown that the average length of line shape connection is 2.44 to 2.77 for six 1-alkyl-3-methylimidazolium ionic liquids, and the connection patterns are different for short and long alkyl side chain length. The degree of each ion was calculated and analyzed. The nodes with zero degree were adopted to detect the boundary of the clusters in the ionic liquids, which have no hydrogen bond connected with neighbor ions. This work indicates that the network analysis method is useful for understanding and predicting the structure and function of RTILs.

Informal entrepreneurship is a persistent and extensive phenomenon in both developed and developing countries and considerable efforts have been made to understand it from an ecosystem perspective. Nevertheless, literature that analyzes networks within and among individuals in the informal economic sector has received less attention. This study presents an interesting extension of Granovetter's “strength of weak ties” hypothesis. Until now, strong ties are perceived to be constraining and less beneficial than weak ties for the entrepreneurial activity. However, this paper critically examines this assumption in the context of informal entrepreneurship to explore in detail this networking dynamic and how it affects their financial and social performance. A qualitative approach using 50 face-to-face interviews in Mexico was conducted. Our findings demonstrate that strong ties provide the resources, support and information informal entrepreneurs need to reduce their adversity and vulnerable conditions, having a positive impact on their financial and social outcomes.

Primary myelofibrosis (PMF) is a pluripotent hematopoietic stem cell-derived malignancy, included in the heterogeneous group of myeloproliferative neoplasms (MPNs). PMF diagnosis is based on a composite assessment of clinical and laboratory data. The three major diagnostic criteria are: screening for driver mutations, exclusion of other conditions that can cause myelofibrosis, and bone marrow biopsy displaying megakaryocyte changes and fibrosis. PMF treatment options are only partially disease-modifying and consist mainly of symptom control. Recently, a new targeted therapy was introduced for PMF patients, JAK-STAT inhibitors (i.e. ruxolitinib). However, specific subgroups of patients do not benefit from the JAK-STAT inhibitors: (1) those who are carrying JAK2 mutations, but ruxolitinib does not reduce the spleen size; (2) triple negative patients (no JAK2, CALR, or MPL mutations); and (3) those who discontinue JAK-STAT therapy because of side effects. These subgroups are in need of new therapeutic approaches. Mature microRNAs (miRNAs) range from 16 to 28 nucleotides (nt) in length and regulate specific messenger RNAs at the post-transcriptional level. Numerous in vitro and in vivo studies have reported specific miRNAs, as well as complex miRNA networks, to be dysregulated in PMF. Several of these miRNAs were shown to be implicated in essential events of PMF pathophysiology: increase of bone marrow fibrosis, progression to acute myeloid leukemia, resistance to JAK-STAT inhibitors, and activation of differentiation of hematopoietic stem/progenitor cells into megakaryocytes. Hence, we propose miRNAs as a potential minimally invasive diagnostic tool for PMF and as therapeutic targets that could address the unmet medical needs of these patients.

This chapter is an introduction to complexity theory (encompassing chaos — a subset of complexity), a nascent domain, although, it possesses a historical root. Some fundamental properties of chaos/complexity (including complexity mindset, nonlinearity, interconnectedness, interdependency, far-from-equilibrium, butterfly effect, determinism/in-determinism, unpredictability, bifurcation, deterministic chaotic dynamic, complex dynamic, complex adaptive dynamic, dissipation, basin of attraction, attractor, chaotic attractor, strange attractor, phase space, rugged landscape, red queen race, holism, self-organization, self-transcending constructions, scale invariance, historical dependency, constructionist hypothesis and emergence), and its development are briefly examined. In particular, the similarities (sensitive dependence on initial conditions, unpredictability) and differences between deterministic chaotic systems (DCS) and complex adaptive systems (CAS) are analyzed. The edge of emergence (2^nd critical value, a new concept) is also conceived to provide a more comprehensive explanation of the complex adaptive dynamic (CAD) and emergence. Subsequently, a simplified system spectrum is introduced to illustrate the attributes, and summarize the relationships of the various categories of common systems.

Next, the recognition that human organizations are nonlinear living systems (high finite dimensionality CAS) with adaptive and thinking agents is examined. This new comprehension indicates that a re-calibration in thinking is essential. In the human world, high levels of human intelligence/consciousness (the latent impetus that is fundamentally stability-centric) drives a redefined human adaptive and evolution dynamic encompassing better potentials of self-organization or self-transcending constructions, autocatalysis, circular causation, localized spaces/networks, hysteresis, futuristic, and emergent of new order (involving a multi-layer structure and dynamic) — vividly indicating that intelligence/consciousness-centric is extremely vital. Simultaneously, complexity associated properties/characteristics in human organizations must be better scrutinized and exploited — that is, establishing appropriate complexity-intelligence linkages is a significant necessity. In this respect, nurturing of the intelligence mindset and developing the associated paradigmatic shift is inevitable.

A distinct attempt (the basic strategic approach) of the new intelligence mindset is to organize around human intrinsic intelligence — intense intelligence-intelligence linkages that exploits human intelligence/consciousness sources individually and collectively by focusing on intelligence/consciousness-centricity, complexity-centricity, network-centricity, complexity-intelligence linkages, collective intelligence, org-consciousness, complex networks, spaces of complexity (better risk management <=> new opportunities <=> higher sustainability) and prepares for punctuation points (better crisis management <=> collectively more intelligent <=> higher resilience/sustainability) concurrently — illustrating the significance of self-organizing capability and emergence-intelligence capacity. The conceptual development introduced will serve as the basic foundation of the intelligent organization (IO) theory.

In this chapter, an introductory analysis of human intelligence and consciousness is executed to establish a conceptual foundation for the intelligent organization theory. Fundamentally, the new intelligence mindset and thinking, and intelligence paradigm focus on high intelligence/ consciousness-centricity. It concentrates on human intrinsic intelligence/ consciousness sources (its intense intelligence and consciousness — awareness and mindfulness), and stipulates that organizing around intelligence (a strategic component of the complexity-intelligence strategy) is the new strategic direction to be adopted by all human organizations in the present knowledge-intensive, fast changing, and not always predictable environment (limited predictability). In addition, the characteristics and variation in capabilities of intelligence and consciousness are further scrutinized using an intelligence spectrum (compared to other biological intelligence sources on this planet — encompassing proto-intelligence, basic life-intelligence, basic human intelligence and advanced human intelligence). In the intelligent organization theory, consciousness (awareness, mindfulness) only exists in the living/biological world, and mindfulness is confined to humanity.

Subsequently, intelligence/consciousness management and its associated dynamics that are critical activities of intelligent human organization (iCAS) are more deeply examined with respect to complexity-centricity (encompassing attributes such as stability-centricity, autopoiesis, symbiosis, self-centric, network-centric, org-centric, independency, interdependency, intelligence-intelligence linkage, engagement, self-organization/ self-transcending constructions, local space, complex networks, constructionist hypothesis and emergence). Concurrently, the urgency and impact for nurturing the new intelligence mindset and intelligence paradigm is also discussed. In a situation with escalating complexity density, this paradigmatic shift in mindset and thinking in leadership, governance and management of human organizations is highly significant for higher functionality and coherency — to all human interacting agents (both leaders and followers), as well as the organizations themselves.

Another component of the complexity-intelligence strategy examined is the nurturing of an intelligent biotic and complex adaptive macro-structure that will serve all human organizations better (towards higher coherency, synergy and structural capacity). The analysis clearly indicates the necessity of systemic transformation or structural reform that is more coherent with intelligence/consciousness, and information processing and knowledge acquisition capability. In this case, a greater operational/ practical utility and higher structural capacity can be achieved with the presence of the intelligent biotic macro-structure and agent-agent/ system micro-structure (principle of locality) that concurrently supports the intelligent complex adaptive dynamic (iCAD) better — a finer synchrony between structure and dynamic — higher intelligence advantage.

The five earlier chapters introduced the basic foundation (co-existence of order and complexity, sensitive dependence on initial conditions, complexity <=> presence of in-determinism and unpredictability, necessities to change, the intelligence paradigmatic shift, structural reform, complex adaptive systems and dynamic, and some other fundamental and critical properties/characteristics involved) of the complexity theory and intelligent organization (IO) theory. This chapter introduces the global/holistic complexity-intelligence strategy (with two macro-paths) of the IO theory (although, some sub-strategies/models have been mentioned or partially analyzed in earlier chapters). The new strategy attempts to provide more comprehensive linkages and coverage on some specialized aspects indicating that human organizations must be led and managed differently in the current context because of high complexity density. In this chapter, three sub-strategies of the holistic complexity-intelligence strategy that is vital for nurturing highly intelligent human organizations (iCAS) are examined. They are namely, organizing around intelligence, nurturing an intelligent biotic macro-structure, and the integrated deliberate and emergent strategy.

The intelligence/conscious-centricity aspect begins with a deeper analysis on human level intelligence and consciousness, complexity, collective intelligence, org-consciousness and their associated dynamics relative to that of some other biological species (swarm intelligence), as well as other physical complex adaptive systems (CAS) characteristics. It has been observed that human interconnectivity, interdependency, selforganizing communications, truthful engagement, complex networks, collective intelligence, orgmindfulness, orgmind, and emergence can be significantly dissimilar. The four different perspectives of organizing around intelligence are examined.

Next, the intelligent biotic macro-structure (introduced earlier in Chapters 3 to 4) that resembles a highly intelligent biological being, and is more effective at exploiting information processing and knowledge accumulation, and a smarter evolver are more deeply scrutinized. There exists a high synchrony between organizing around intelligence and the presence of a biotic macro-structure. Thus, the advantages and significance for intelligent human organizations to possess such an inherent biotic macro-structure to better exploit certain biological and complexity associated characteristics and dynamics (including intelligence-intelligence linkage, complexity-centricity, complexity-intelligence linkage, more efficient natural decision-making node, information processing capability, learning and adaptation, knowledge acquisition and creation, organizational neural network, artificial node, and structural and dynamical coherency) to compete more effectively and efficiently in the current ‘raplexity’ context is also illustrated. In addition, the uniqueness and roles of artificial information systems (artificial nodes) is further examined.

Finally, the integrated deliberate and emergent strategy is scrutinized with respect to its significant association with the co-existence of order (deliberate planning, determinism, completeness and predictability) and complexity (continuous nurturing processes, in-determinism, unpredictability, unknown unknowns, risk management, new opportunity, crisis management, self-transcending constructions, futuristic and emergence) — in particular, highlighting the criticality of the deliberate and emergent auto-switch (better ambidexterity). Currently, the holistic integrated smarter evolver and emergent strategist approach is absent in most human organizations.

The first section of this chapter is an introduction to relativistic complexity (a significant component of the intelligent organization theory). The presence of intense intelligence/consciousness-centricity and 3^rd order stability-centricity in the human world renders complexity relativistic. The impact of the human mental space is so tremendous that complexity is in the mind of the beholder, and predictability becomes highly subjective. In this situation, the state of relativistic static equilibrium may be beneficial. Certain spaces of complexity appear as spaces of relativistic order with surface patterns becoming more apparent. Such spaces must be creatively explored and exploited (higher exploratory capacity) leading to a more advanced level of intelligence advantage. In this respect, effective self-transcending constructions, high self-organizing capacity and emergence-intelligence capacity are significant attributes that the new leadership and governance system in intelligent human organizations must exploit. Holistically, the two strategies focus on concurrent exploitation of intelligence/consciousness-centricity and relative complexity, and optimizing the more comprehensive contributions of the integrated deliberate and emergent strategy.

Many issues/problems that present human organizations (nations, political systems, communities, business organizations, markets) are encountering due to accelerating changes (mindset, thinking, values, perceptions, expectations, redefined boundaries and high interactive dynamics) that cannot be well-managed with traditional knowledge and hierarchical practices are affecting governance and governance systems. Fundamentally, governance deals with power, interest, and conflict. The traditional governance systems are hierarchical, highly directed, controlled and managed, and the relational aspect has not been allocated sufficient priority resulting in extensive disparities. In the current complex dynamical and high interdependency environment, its weaknesses and constraints are highly apparent. The latter includes ‘space-time compression’; incoherency in thinking, values, perceptions, and expectations between the leadership and the other agents; diversification in stakeholders’ needs not accommodated; and constraints of current governance theories. Thus, a new theory that provides a more ‘realistic’ foundation is essential for deeper contemplation.

Primarily, recognizing the inherent strengths of human agents and the fundamental constraints/weaknesses of human organizations is a key foundation towards better adaptation, leadership, governance, resilience and sustainability. In all human organizations, the agents are intrinsic intense intelligence/consciousness sources that could easily transform their behavioral schemata. This observation contradicts the Newtonian/design paradigm, as the organizational dynamic of human agents is complex, nonlinear, constantly/continuously changing with limited predictability. In addition, human agents are self-centric, self-powered, stability-centric, independent and interdependent, network-centric and self-organizing due to high awareness. In this situation, high self-organizing capacity and emergence-intelligence capacity are new niches. However, this phenomenon can create new opportunities, innovation, and elevates competiveness; or destruction.

In particular, effective leadership and governance are spontaneously emerging key requirements in all human groupings — a primary trait for human collective survival. Historically, many organizations disintegrated because of the weaknesses in leadership and governance. Currently, with more knowledge-intensive and higher participative new agents (self-powered intrinsic leadership) possessing modified attributes that are dissimilar from the older generations (also due to the deeper integration of the economic, social, political, and environmental perspective), reduces consensus and collaboration, and renders governance and leadership even more nonlinear or dysfunctional. In particular, the traditional governance systems of more organizations are manifesting their constraints and incompetency, including incoherency due to new values and cultural pressure, and the wider spread of self-organizing networks. The emergent of informal networks is a more commonly observed phenomenon worldwide. Apparently, a deeper comprehension on the diminishing effect of the traditional organizational thinking (political, social, economic), governance capacity, precise strategic planning, decision making, hierarchical structure, communications and engagement, empowerment leadership, management, operations, and the highly nonlinear relational parameter is essential. Apparently, new principles of governance must emerge (intelligent human organization > thinking system + feeling system).

The new paradigmatic path of the intelligence governance strategy that exploits intelligence/consciousness-centricity, complexity-centricity, and network-centricity concurrently, introduces a new basic strategic path towards better adaptive governance and acceptance governance. The latter focuses on integrating self-powered self-organizing governance, reducing direct governance, and increasing e-governance and network-centric governance as a new necessity. In this case, the merits of adopting the intelligence leadership strategic approach simultaneously are more apparent. Hence, the new governance focal points must include more and better interconnected actors, the critical ability of self-organizing communications (supported by mobile/social media development), immersion of leadership nodes in networks (better exploitation of e-governance), increasing coherency of complex networks (exploiting interdependency of network of networks, and better network management), and elevating self-transcending constructions capability (higher self-organizing governance capacity and emergence-intelligence capacity) that better facilitates emergence through multi-level and ‘multi-lateral’ dynamics (complex adaptive networks <=> intelligent networks). Thus, the intelligence governance strategy emphasizes that mass lateral collectivity (acceptance governance) rather than selective enforced hierarchical empowerment as the more constructive approach in the present contact. In particular, the stabilityinducing role of leaders and institutions are critical. Apparently, optimizing the ‘everybody is in charge’ phenomenon (whenever necessary) is a more viable option.

The chapter concludes the book by illustrating the potential of extending the boundaries of the intelligence mindset and its space of innovation and creativity. Some theories that could be integrated subsequently are mentioned briefly. In addition, a holistic view (new knowledge creation) of the intelligence paradigm, the complexity-intelligence strategy, and the intelligent organization theory is summarized through recollecting and amalgamating the various normative attributes, concepts, perspectives and strategies analyzed. Organizing around intelligence (including intelligence/consciousness management, complexity management and network management), and the integrated deliberate and emergent strategy (exploitation of the co-existence of order and complexity) are the (holistic) fundamental strategies that must be exploited in the present environment. Due to the current high complexity and nonlinearity, this paradigmatic shift is apparently beneficial. As indicated earlier, properties of complex adaptive systems and the complex adaptive dynamic must be better comprehended and exploited by all human organizations to elevate competitiveness, resilience and sustainability.

In summary, the intelligent organization theory introduced in this book contains concepts and ideas (including intelligence/consciousness-centricity, complexity-centricity, network-centricity, intelligence-intelligence linkage, complexity-intelligence linkage, self-organizing capacity, emergence-intelligence capacity, coherency, synergy, constructionist effect and mental cohesion) that are more holistic, integrative, and accurate manifestations of humanity and its organizations and agents. Thus, it is highly critical for the leadership, governance, strategy, and management in rapidly changing environment. Primarily, it is a new significant complexity-intelligence-relational/network domain (a more inherent aspect of nature and this universe) that must be better comprehended and exploited by all human organizations. As indicated, the complexity-intelligence strategy of the intelligent organization theory encompasses numerous components, including organizing around intelligence, integrated deliberate and emergent strategy, general information theory, 3C-OK framework, intelligent person model, intelligent multi-layer structure model, intelligence leadership theory/strategy, intelligence governance theory/strategy, and relativistic complexity.

Fundamentally, the new thinking emphasizes the significance and linkages of the human intelligence/consciousness sources, and stabilitycentricity at all levels (agent-centric, network-centric and org-centric), co-existence of order and complexity, and the attributes of swift information decoders, smarter evolvers and emergent strategists. The strategies and models/frameworks of the intelligent organization theory that focus on structuring, nurturing, leading, and governing/managing of highly intelligent human organizations (iCAS) that are orchestrated by the highly intelligent complex adaptive dynamic (iCAD) are briefly recaptured. Ultimately, it is the intention of the author that an omniscient understanding of this book will instill in leaders and actors the new critical intelligence advantage.