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This chapter analyzes the technological growth of the modern Russian economy through the prism of evaluating its effectiveness from the position of costs and profits. It also determines the factors of this growth and develops recommendations for managing them in the interests of acceleration of rate and increase of effectiveness of technological growth of the modern Russian economy. While technological growth in Russia shows high effectiveness, the model of technological growth in Russia has its specifics, connected to the unconventional influence of a standard set of the factors on technological growth. The influence of the factor of the number of organizations that implement R&D is insignificant, and the influence of the number of personnel involved with R&D, volume of private expenditures for R&D, and the number of used leading production technologies is negative (reverse). We offer recommendations for increasing the effectiveness of technological growth of the modern Russian economy, which are connected to increase of the volume of state expenditures for R&D (recommended volume – USD 35.09, its growth as compared to 2018 constitutes 191.76%) and increase of the number of developed leading production technologies (recommended number of these technologies – 2350.05, its growth as compared to 2018 constitutes 62.34%).

In the last few decades, there has been growing interest in forecasting with computer intelligence, and both fuzzy time series (FTS) and artificial neural networks (ANNs) have gained particular popularity, among others. Rather than the conventional methods (e.g., econometrics), FTS and ANN are usually thought to be immune to fundamental concepts such as stationarity, theoretical causality, post-sample control, among others. On the other hand, a number of studies significantly indicated that these fundamental controls are required in terms of the theory of forecasting, and even application of such essential procedures substantially improves the forecasting accuracy. The aim of this paper is to fill the existing gap on modeling and forecasting in the FTS and ANN methods and figure out the fundamental concepts in a comprehensive work through merits and common failures in the literature. In addition to these merits, this paper may also be a guideline for eliminating unethical empirical settings in the forecasting studies.

Introduction: With the accelerated process of building metropolitans, more and more people tend to live in cities. So, to deal with this, the need has arisen to make smart everything that we have around us even when we arrived at the term of the smart city. All of this produces data we call big data that is generated by citizens.

Aim: So, cloud computing is the main idea implementation which we can use ineffective from all of these services which we call smart. And taking into account all of this, in this literature review, we have used different techniques to extract the most relevant papers on our topic. Mainly, we focus on smart cities and their taxonomy of it such as smart homes, smart buildings, traffic monitoring, security and emergencies, and so on. For a smart city, we discussed different proposed system architectures which represent the real work of researchers.

Results: In this way, we mention services that are offered and have the base services cloud services. Also, the articles we used are extracted and analysed from the most powerful and relevant databases such as IEEE, ACM, Elsevier, Science Direct, and so on. In total, we take 88 papers, and from all of these papers we have extracted 53 with different methods. This Systematic Literature Review presents building and using smart cities inside of cloud computing services.

Conclusion: However, a different implementation idea to do better life for all of us is by converting our lifestyle into a new form of living. The only form of implementation is by digitalising and implementing everything around us which means making every service in one place, where you can have access from anywhere, anytime. So, the smart city is the future.

Originality/value: This systematic literature review contributes to everyone who expresses interest to implement and provides additional evidence for existing studies in smart city patterns which used cloud services. Researchers offer various implementation forms of different models and express the impact of cloud services, especially for placements, where there are more people populated. Also, this study identifies a major weakness in existing smart city implementation by using cloud services, which have identified the main obstacles now and it needs to reanalyse the form of implementation for more complex systems in the future.

This chapter reviews the key results obtained in previous studies of airline mergers. It is found that the effect of mergers on airfares is dependent on the network configurations of merging airlines. Fare increases are frequently observed on overlapped routes. However, if the networks of two merging airlines are complementary, the expanded network after the merger leads to cost savings, increase in travel options, and improvement in service quality. Therefore, in a deregulated market, with few entry barriers, relaxing merger regulations is likely to improve welfare. However, most welfare evaluations do not incorporate quality changes or dynamic competition effects. Empirical investigations are primarily ex post analysis of mergers that have already passed antitrust reviews. The relationship between market concentration and welfare might be nonlinear and market specific. Therefore, airline mergers and alliances should be reviewed case by case. Methodological improvements are needed in future studies to control for the effects of complicating factors inherent in ex post evaluations.

The five countries in Central Asia, namely Uzbekistan, Kazakhstan, Turkmenistan, Tajikistan, and Kyrgyzstan, are landlocked and therefore rely critically on aviation for passenger travel and express cargo logistics. However, despite substantial growth in the past decade, the aviation market in the region is still not realizing its full potential. This chapter reviews the development status of the international air travel market from Central Asia, with an aim of identifying the key barriers for industrial development and growth, and possible remedies to address these challenges. Overall, our study suggests that international market growth from the region is significantly influenced by historical patterns and political ties with Russia. Whereas markets linking selected countries such as Turkey and the UAE have experienced substantial growth, further liberalization is needed for the region to achieve better connectivity with major trade partners and aviation markets.

Institutional actors are critical allies for grassroots movements, but few studies have examined their effects and variations within the non-democratic context. This chapter argues that while institutional allies are heavily constrained and unlikely to give open endorsement to grassroot activists, some institutional activists indirectly facilitate movement mobilization and favorable outcomes in the process of advancing their own political agendas. Drawing upon in-depth interviews conducted in 2008 and 2012, I illustrate this argument by examining the Anti-PX Movement – a landmark grassroots environmental movement against a chemical plant – in Xiamen, China. I find that the environmental institutional actors were constrained and divided, yet some still fostered opportunities for movement mobilization and in turn exploited the opportunity created by the protesters to pursue their policy interests, thus facilitating positive movement outcomes. As long as the claims are not politically subversive to the authoritarian rule, this type of tacit and tactical interaction between institutional activists within the state and grassroot activists on the street is conducive to promoting progressive policy changes.

This chapter explores a descriptive theory of multidimensional travel behaviour, estimation of quantitative models, and demonstration in an agent-based microsimulation.

A descriptive theory on multidimensional travel behaviour is conceptualised. It theorizes multidimensional knowledge updating, search start/stopping criteria, and search/decision heuristics. These components are formulated or empirically modelled and integrated in a unified and coherent approach.

The theory is supported by empirical observations and the derived quantitative models are tested by an agent-based simulation on a demonstration network.

Based on artificially intelligent agents, learning and search theory, and bounded rationality, this chapter makes an effort to embed a sound theoretical foundation for the computational process approach and agent-based microsimulations. A pertinent new theory is proposed with experimental observations and estimations to demonstrate agents with systematic deviations from the rationality paradigm. Procedural and multidimensional decision-making are modelled. The numerical experiment highlights the capabilities of the proposed theory in estimating rich behavioural dynamics.