Forecasting, When Power Law Distributions Apply

This article discusses how intergovernmental organizations (IGOs) can use different strategic planning approaches in devising strategic plans to improve organizational performance. Six strategic planning approaches from the business sector are highlighted in this study. Each of the strategic planning approaches specifically addresses a core aspect of the strategic planning process. Thus, this article posits that an IGO must choose the most appropriate strategic planning approach depending on its specific organizational design features: membership, control, scope, centralization, flexibility, and independence. We argue that an IGO's design features affect its decision‐making, organizational performance orientation, and legitimacy, and these, in turn should determine whether it opts for member‐driven, results‐driven, or environment‐driven strategies. This article also explores how IGOs can complementary combine distinct approaches to maximize the benefits from strategic planning by determining how one approach compensates the limitation of another in devising strategic plans. This article ultimately produces a framework to provide propositions for researchers, and a tool for IGO leaders to identify the optimum strategic planning approach to help improve organizational performance.

Confusion between strategic planning and strategic thinking in the context of strategic leadership and its effect on competitive advantage was the foremost rationale for this study to come into view. Thereby, the aim of this study was to examine the role of two mediating variables, i.e., strategic planning and strategic thinking in the impact of strategic leadership on competitive advantage. Scoping health care sector in Jordan resulted in three public hospitals agreed to participate in the study. Data were gathered using a questionnaire developed on the basis of literature review. A total of 1000 questionnaires were administered to hospitals. A total 521 questionnaires were returned with a response rate of 52.1%. The results pinpointed that strategic leadership significantly predicted strategic planning, strategic thinking and competitive advantage. the results also revealed that strategic planning and strategic thinking significantly and positively related to competitive advantage. accordingly, it was approved that strategic planning and strategic thinking mediated the effect of strategic leadership on competitive advantage. Despite that the influence of strategic thinking on competitive advantage was greater than the influence of strategic planning on competitive advantage. The study hold the perspective that both strategic planning and strategic thinking were essential in the context of strategic leadership, since strategies are developed by strategic thinking and operationalized via strategic planning.

Topicality. The prolonged state of martial law in Ukraine has become a key precondition for transforming approaches to territorial development management, not only in terms of rapid response but also within longer planning horizons, particularly in the medium-term perspective. Strategic planning remains a core component of strategic governance, ensuring that decisions made by public authorities are aligned with defined development goals, functions, and mission. It is a multi-level process encompassing the prioritization of activities across central, regional, and local institutions, the selection of effective implementation mechanisms, and the allocation of resources in accordance with strategic objectives. This approach enables the alignment of regional development tasks with national policy priorities. Under current conditions, territorial development planning is undergoing significant transformation, shaped by the paradigm of “new regionalism,” which emphasizes institutional frameworks and the efficient development of territorial-economic systems. In the context of martial law, strategic planning is evolving toward forms that address not only immediate challenges but also medium-term security risks and the consequences of military conflict. Accordingly, the implementation of “new regionalism” principles—such as multi-level governance, stakeholder engagement, and partnership—is increasingly relevant. Given Ukraine’s European integration trajectory, adapting EU strategic planning practices is essential for building an effective model of socio-economic territorial development. Aim and tasks. The aim of this study is to examine the transformation of conceptual and methodological approaches to strategic planning for the socio-economic development of territorial-economic systems by identifying the key preconditions that shape the strategic planning process within the paradigm of “new regionalism” and under the conditions of martial law following the full-scale invasion of Ukraine. In order to achieve this aim, the study sets out the following tasks: (1) to analyze institutional shifts that significantly affect both the objects and subjects of strategic planning in the context of a globalized economy; (2) to explore the transformation of approaches to regional (local) development management through the lens of traditional models and the “new regionalism” paradigm; (3) to describe the implementation of new strategic planning approaches within the framework of “new regionalism” in Ukraine prior to the full-scale invasion and compare them with those applied under martial law conditions. Materials and Methods. The methodological framework of the study is based on the application of general scientific and specialized analytical methods. The method of generalization was employed to identify new approaches to strategic planning within the “new regionalism” paradigm in Ukraine. Comparative and synthesis methods were applied to examine preconditions for updating strategic planning approaches under wartime conditions. Research results. The article examines the conceptual and methodological foundations of strategic planning for the socio-economic development of Ukraine’s regions, both in the pre-war period and under current wartime conditions. Institutional transformations significantly influence the formation of strategic activity, altering both its objects and subjects. Globalization, technological progress, organizational diversification, and the growing autonomy of economic agents reduce the effectiveness of traditional state regulatory instruments while simultaneously standardizing the rules of economic interaction. The shift away from classical rationality toward network-based cooperation complicates strategic governance and necessitates new approaches to development policy. Under such conditions, the liberal model of economic interaction becomes dominant due to capital flexibility and limited state control. The European Union’s experience in regional development planning is grounded in the paradigm of “new regionalism.” Within this model, the role of multi-level governance, local self-government, and cohesion policy is strengthened, providing funding not only for lagging regions but also for advanced ones to support innovation, entrepreneurship, and cross-border cooperation. In Ukraine, the implementation of the principles of “new regionalism” prior to the outbreak of the full-scale war involved the modernization of strategic planning. However, the state of martial law necessitates the consideration of security constraints that affect the functioning of the state and its territorial-economic systems. Conclusion. The findings of the study indicate that, despite the onset of russia’s full-scale invasion, most approaches to regional development planning shaped within the European paradigm of “new regionalism” have retained their relevance. At the same time, the state of martial law necessitates consideration of security-related constraints that affect the functioning of the state and its territorial-economic systems. These conditions have led to increased centralization of regional policy, particularly through the suspension of decentralization reforms and the expansion of state authority. The updated State Strategy for Regional Development for 2021–2027 remains highly relevant; however, certain gaps persist in its content. Notably, the strategy does not account for the role of districts as intermediate administrative-territorial units, which limits the comprehensiveness of the territorial governance approach.

Designing minimum variance controllers (MVC) for nonlinear systems is confronted with many difficulties. The methods which are able to identify MIMO nonlinear systems are scarce, and linear models are not accurate in modeling nonlinear systems. In this paper, Vector ARX (VARX) models are proposed for designing MVC and generalized minimum variance controller (GMVC) for linear and nonlinear systems, and the accuracy of these models in approximating the nonlinear MIMO system is studied. However, the VARX is a linear model. It is shown that this model can identify some kinds of nonlinear systems with any desired accuracy. Therefore, the controller designed by the VARX is accurate, even for these nonlinear systems. The proposed controller is tested on a both linear system and a nonlinear four-tank benchmark process. In spite of the simplicity of designing GMVCs for the VARX models, the results show that the proposed method is accurate and implementable.

The purpose of this paper is to identify the role of strategic planning as a sustainable tool for regulating both the protection and development of historic urban landscapes, as well as developing an adequate and effective strategic model and management instruments for implementation. The role and importance of strategic planning are examined in the context of global transformative actions in the urban governance of community and private sector engagement and sustainable development on the local level. We argue that a specific—tailor-made—integrated strategic urban planning approach could be a useful model, both for development and urban regeneration and for the preservation of protected valuable historic urban landscapes, thus contributing to a sustainable urban revival of wider surrounding territories including cultural, social and economic development. We stand on the position that the sustainable approach to the protection and revitalization of the historic urban landscapes has to be in line with the acknowledgment of specific local community values, contemporary needs, their involvement, and, eventually, their satisfaction. The case study method was based on the example of a protected historic center of Novi Pazar in Serbia to test the possibilities of applying strategic planning model and management for the implementation tailored to the local context. Eventually, the scenario method was applied to test the possibilities of a simulation of the strategic planning model and management instruments for a protected historic center. We found that the appropriate combination and utilization of regulatory, economic and informational management instruments have to be in place in the specific context. We conclude and draw out theoretical and practical remarks from our research that integrated strategic urban planning model should consider the logic and the functioning of the competitive real estate markets, and the sustainable environmental, economic and social effects, potentials and benefits for the locality where they originate, in order to be utilized as the new generative value both for the protection and for the revival of historic city centers. The paper develops a conceptual strategic planning and management model for the regeneration of historic urban landscapes that capture the physical, environmental, economic, and social effects and indicators of a given space. Based on this input, an adequate initial stage of the conceptual strategy by the authors of the paper was developed for the regeneration of the historic urban city center.

During the 20th century, the electronics industry has evolved from radio, television, and audio systems to computer systems. The trace of evolution is clearly from linear systems to nonlinear systems. This is by no means accidental, and is due to the fact that nonlinear systems are more versatile than linear systems. As of now, the successful commercial optical instruments are all linear systems. From the entropy point of view, as the knowledge of human beings further expands, we need more powerful computing capabilities such as memory association and self organization. Based on the fundamental differences between the electron and the photon, this paper presents the argument that optical computing will provide memory association and self organization ability (which compliments the current electronic logical computing). Thus, one can infer that the main future thrust of the optical industry will be in nonlinear optical systems and hybrid combinations with nonlinear electronic systems in order to provide both self organization and logical computing (to emulate, more or less, the computing power of the human brain). Currently, the stat of the ar has already demonstrated successful combinations of linear optical system with nonlinear electronic systems (computers). These kinds of hybrid systems are called electro-photonic systems in the following curriculum. Based on the above vision for the future and taking into account the need for immediate employment, the following curriculum is designed to provide a core training to the students who are interested in choosing optics or electro-photonics as their career. This curriculum is being offered in the upper years at the Physics Department of Chung Yuan University. Electronics, Optics, Electro-photonic System Design and Analysis, Optical System Design and Analysis, Introduction to Optical Computing, Holography, Nonlinear Optics, The Experimental Technology for Electro- photonics (I), The Experimental Technology for Electro-photonics (II). The main thrust among all these courses is the system modeling and analysis. In this paper, the design of this curriculum will be elaborated and the topics for each course will be listed in detail.

Strategic planning can be a time-consuming task for academic departments. As such, an effective and efficient strategic planning approach is paramount. This paper presents a strategic planning approach using causal mapping to uncover the factors which faculty members believed would make their department (in the USA) more successful. The information gathered during the session was used as part of an AACSB accounting maintenance of accreditation process. The approach applied here elicits faculty involvement in ways which bring to the surface perspectives held by subgroups/factions of faculty. Additional perspectives are positive in a strategic planning context as they can contribute to devising strategies that might not have resulted by considering only majority views. Content analysis of the strategic plan suggests the range of views uncovered were integrated into the plan, including both the strategic factors and the relative importance of the factors.

Leader Roles for Innovation: Strategic Thinking and Planning

Observability and observable degree, which are derived from modern control theory and relative to control and estimation performances, are both important concepts for state estimation. For linear time-invariant systems, judgement of observability and evaluation of observable degree are irrelevant to filtering process and parameters. Thereby, it has limited application ability. Different from linear systems, observability and observable degree becomes more complex and are seldom studied deeply and integrally for nonlinear systems. Due to the complexity of nonlinear filtering, the observable degree depends strongly on filtering process, filter class and associated parameters. Thereby, we study the observable degree analysis of nonlinear estimation systems by using unscented information filter (UIF). A way to evaluate observable degree using singular value decomposition (SVD) of observability matrix is presented based on the UIF and the influencing factors are deeply analyzed. Moreover, differences of observable degree analysis are distinctly discussed between linear and nonlinear systems. The results reveal that evaluation of the observable degree for nonlinear systems can be affected by filtering estimate at last time, initial estimate and filter's parameters such as covariances of process and measurement noises. Some simulations are demonstrated to validate the results.

In this paper, we investigate the impulse effect in nonlinear singular system, since the existence of the nonlinear dynamics, we use the Differential Mean Value Theorem based method to transfer the nonlinear singular system into a linear parameter varying system. It should be noted that Differential Mean Value Theorem is an identical transmission, thus, for the nonlinear system, if we transfer the nonlinear system into a linear system via differential mean value theorem, the properties of the original system will not be changed. Based on this point, we try to analyze the transferred singular system by some existence method which applied to the linear singular system.

Concomitant with entering the decentralization period has had a significant effect on cities in Indonesia, and is seen as a new era for local life. The decentralization period has also generated sentiments which are locally bounded that can be identified in the discretion given to the local government in charge to rebranding the city. In this paper, the rebranding phenomena have learned from Pekanbaru city where has changed its city brand for few times. By using a qualitative research approach and combining multi methods to collect and process the data, this paper investigates that the rebranding city has found as a strategic approach in urban planning today that is used to inject more senses to the city and its local life by the local government. This research has confirmed, for almost two decades of the decentralization period, the rebranding phenomena are not only found to generate sense locally, but also as a power marker of the local regime.

A procedure based on neural networks for the classification of linear and nonlinear systems is presented, using excitation and response data under swept sine excitation. Special attention is paid to the classification and identification of linear and bilinear systems, the latter being considered since they exhibit typical characteristics of cracked systems. The computer simulations show that: (1) using the procedure presented in this paper the trained classification network can reliably classify a linear system and different nonlinear systems; (2) the output of the trained identification neural network for a linear system and a bilinear system can be used as a quantitative indicator of characteristics of bilinear systems having different stiffness ratios (k(x>0)/k(x<0)) with respect to the bilinear system used in the training stage; (3) for two-degree-of-freedom systems, the trained network can not only determine the existence of a bilinear stiffness and the magnitude of its stiffness ratio, but also specify which stiffness is bilinear, i.e. indicate its position. These results provide a possibility of using the trained neural networks to detect and locate structural cracks which have the characteristics of bilinear systems.

Numerous papers were published during the last decade on the normal forms of nonlinear control systems with applications in bifurcation and its control. The approach is motivated by Poincare’s theory of normal forms for classical dynamical systems using homogeneous transformations. In this paper, we summarize a variety of control system normal forms published in the literature so that the normal forms are derived in a same framework with consistent notations. Before we get into technical details, the rest of the introduction is a review of existing results on some related topics. It is well known that there are several normal forms for a linear control system. If the system is controllable then the system can be transformed into controllable or controller normal form. If the system has a linear output map and is observable then it can be transformed into observable or observer form. The nonlinear generalization of the linear controller normal forms were extensively studied during 1980’s, for instance, Krener [23], Hunt-Su [11], JackubczykRespondek [10], and Brocket [3], etc. If a nonlinear control system admits a controller normal form, it can be transformed into a linear system by a change of coordinates and feedback. Therefore, the design of a locally stabilizing state feedback control law is a straightforward task. In such a case, we say the system is feedback linearizable. On the other hand, most nonlinear systems do

The work presented in this dissertation was conducted in an effort to achieve improvement in conventional and digital control methods applied to chemical processes. Emphasis was placed on simplicity and effectiveness in an attempt to provide control improvements which are easily implemented and yet efficient in their tasks. In these studies digital simulation was used exclusively utilizing the IBM 7040 and 360 and the XDS Sigma V computers. Initially the inaccuracies involved in obtaining a firstorder plus dead time model graphically from an open loop response curve are discussed. It is pointed out that fine tuning of two and three mode controllers based on these inaccurate models is necessary and presently must be done by trial and error. Modifications of existing controller tuning relations are presented which guide fine tuning attempts and eliminate much of the trial and error procedure. Second, the subject of linear discrete models applied to sampled-data systems is considered. A multiple linear least squares technique is applied to sampled system input/output records to identify parameters of a linear discrete model. The method is demonstrated to give good results when applied xii to linear and non-linear systems with and without dead time. The simplicity and flexibility of implementing this modeling technique are discussed. Application of this method to systems with measurement noise are shown to be improved when the data are filtered. Third, the implementation of linear discrete models in Deadbeat, Dahlin and Kalman controller synthesis methods are presented. It is demonstrated that the form of the models fits well into each of these controller design philosophies. The Dahlin algorithms which incorporate a tuning parameter give the most consistent performance for model orders and sampling times considered. In general, the performance of controllers based on low order models is seen to compare well with that of higher order controllers. Fourth, utilizing the speed of the multiple linear regression identification, the application of this technique in an adaptive control scheme is presented. Applying a recursive solution of the regression equation enables the updating of the linear discrete model at each sample instant and subsequently the adaptation of the control strategy. This scheme is demonstrated to provide closer control of a non linear, time-variant system than is possible with a stationary model. xiii CHAPTER I The form of the transfer function, HG(z), comprised of the digital hold device and the process itself, is such that multiple linear regression techniques can be applied to identify the model constants (parameters). Model identification is then based only on a linear regression of the sampled-data records of the system input and output. A modeling technique based on multiple linear regression only requires the solution of a set of normal equa tions and therefore is rapid enough to be applied on-line. Model order can also be changed with relative ease requiring only an other pass through the system input/output response data already collected. The effectiveness of this identification method is demonstrated on linear systems as well as on a simulated non linear plug flow reactor system. The effect of measurement noise on modeling accuracy is also considered, and comparison of identification using both filtered and unfiltered data are presented. The advantage of filtering data under these operating conditions is illustrated. Linear discrete models obtained for the simulated reactor were demdnstrated in their capacities as both one step ahead predictor models and as free running models. In these studies the higher order models provided significantly better results. Digital controller synthesis methods are the subject of Chapter IV. The discrete form of the model fits well into these design methods. Flexibility in varying model order is carried over to allow: for flexibility in controller order. The advantages of this flexibility are illustrated with the Deadbeat, Dahlin and Kalman controller design algorithms. Controllers based on each of these design methods are implemented in the plug flow reactor system and compared as to overall control performance and manipulate variable action. Comparisons are made also for both fast and slow sampling rates. Finally, Chapter V incorprates the multiple linear regres sion modeling technique with a direct controller synthesis method in an attempt to achieve an adaptive control scheme. The intent here is to update the process model with each new sample taken, and therefore adapt the controller, which is di rectly based on this model to any variation in the operating levels of the system. Adaptive control in this fashion is demonstrated in application to the non-linear plug flow reactor system with a slowly changing feed rate. The result is a demonstration of an adaptive control strategy which has the capability to function in many possible process applications.

This article is a conceptual framework and literature review on strategic thinking. It examines some of the more recent definitions and identifies a number of key elements involved. Further analysis determines a number of situations that can improve strategic thinking capability in individuals and considers whether organizations can successfully adopt its conclusions to develop their managers and improve the business. The article briefly discusses the relationship between strategic thinking, strategic planning and emergent strategy and suggests that strategic thinking needs to precede both and is essential in making them more appropriate and effective. The authors believe that the greater the sum total of strategic thinking and thinkers in the organization the more readily and effectively it can respond to and take advantage of the vast array of changes occurring in today’s business environment. However, despite the significant levels of delayering and flattening of structures that has taken place in the last decade or so, some organizational barriers continue to stifle opportunities for strategic thinking by limiting the flow of experiences and insights to relevant corners of the firm. The authors suggest that knowledge management can have a significant role in increasing and improving strategic thinking by drawing such experiences and insights from all parts of the organization and making them available to points of strategic decision and action.