There is a paradigm shift happening in automotive industry towards electric vehicles as environment and sustainability issues gained momentum in the recent years among potential users. Connected and Autonomous Electric Vehicle (CAEV) technologies are fascinating the automakers and inducing them to manufacture connected autonomous vehicles with self-driving features such as autopilot and self-parking. Therefore, Traffic Flow Prediction (TFP) is identified as a major issue in CAEV technologies which needs to be addressed with the help of Deep Learning (DL) techniques. In this view, the current research paper presents an artificial intelligence-based parallel autoencoder for TFP, abbreviated as AIPAE-TFP model in CAEV. The presented model involves two major processes namely, feature engineering and TFP. In feature engineering process, there are multiple stages involved such as feature construction, feature selection, and feature extraction. In addition to the above, a Support Vector Data Description (SVDD) model is also used in the filtration of anomaly points and smoothen the raw data. Finally, AIPAE model is applied to determine the predictive values of traffic flow. In order to illustrate the proficiency of the model's predictive outcomes, a set of simulations was performed and the results were investigated under distinct aspects. The experimentation outcomes verified the effectual performance of the proposed AIPAE-TFP model over other methods.
The Deffuant model is a model of opinion dynamics based on the factor of the degree of doubt of agents, called uncertainty. Despite its simplicity, the Deffuant model turned out to be technically extremely difficult to analyze, and its basic convergence properties, which are easy to observe numerically, are only empirical results. In the presented work, the agent-based Deffuant model is implemented within the FLAME GPU framework, designed to parallelize simulations of agent-based models based on GPUs. The identity of the results with the original single-thread model is demonstrated. This approach allows us to study various characteristics of the model, its development, modification of the configuration of the ensemble of agents, to conduct various analyses, in particular, cluster analysis.
This study aims to identify effective responses to cyber crime in the insurance industry. Survey responses from Moscow-based employees holding key positions in the leading insurance companies have been collected. The study analyses awareness of, attitudes to, and approaches to cyber security, as well as the incidence and impact of breaches or attacks. According to the experts, complying with laws or regulations and preventing fraud or theft are the main reasons for investing in cyber security. Phishing, viruses, and unauthorised use of computers, networks or servers by staff are the most widely spread threats to cyber security. Russian insurers often undertake additional staff training or change their policies in response to cyber breaches. Strategic recommendations were elaborated for industry professionals.
Recent trends in communication technologies and unmanned aerial vehicles (UAVs) find its application in several areas such as healthcare, surveillance, transportation, etc. Besides, the integration of Internet of things (IoT) with cloud computing environment offers several benefits for the UAV communication. At the same time, aerial scene classification is one of the major research areas in UAV-enabled MEC systems. In UAV aerial imagery, efficient image representation is crucial for the purpose of scene classification. The existing scene classification techniques generate mid-level image features with limited representation capabilities that often end up in producing average results. Therefore, the current research work introduces a new DL-enabled aerial scene classification model for UAV-enabled MEC systems. The presented model enables the UAVs to capture aerial images which are then transmitted to MEC for further processing. Next, Capsule Network (CapsNet)-based feature extraction technique is applied to derive a set of useful feature vectors from the aerial image. It is important to have an appropriate hyperparameter tuning strategy, since manual parameter tuning of DL model tend to produce several configuration errors. In order to achieve this and to determine the hyperparameters of CapsNet model, Shuffled Shepherd Optimization (SSO) algorithm is implemented. Finally, Backpropagation Neural Network (BPNN) classification model is applied to determine the appropriate class labels of aerial images. The performance of SSO-CapsNet model was validated against two openly-accessible datasets namely, UC Merced (UCM) Land Use dataset and WHU-RS dataset. The proposed SSO-CapsNet model outperformed the existing state-of-the-art methods and achieved maximum accuracy of 0.983, precision of 0.985, recall of 0.982, and F-score of 0.983.
This book gathers the papers on digitalization of society, economics and management in post-pandemic period. It shares the latest insights into various aspects of the digitalization of the economy and the consequences of transformation in public administration, business and public life. Integrating a broad range of analytical perspectives, including economic, social and, technological, this interdisciplinary book is particularly relevant for scientists, digital technology users, companies and public institutions.
The goal of this research is to demonstrate model designs and approaches based on using modern paradigms and technological solutions in the field of simulation modeling of socio-economic processes and social forecasting that allow us to study complex dynamic occurrences in the development of socio-economic systems.
Strategic management of socio-economic system involves the analysis of structural changes and dynamic aspects of its development. The socio-economic system can be a specific dynamic behavior in terms of development. The search for an effective modeling constructs developing socio-economic systems due to several reasons, among which:
- necessity of choice and analysis of the trajectory of development in the conditions of formation of the strategy;
- structural changes and dynamic complexity of socio-economic systems;
- the need to consider behavioral aspects of individual social behavior and the activity of individual elements of a complex social system;
- the presence of self-organization in social systems where the dynamic behavior can occur spontaneously, depending on the internal structure and the influences from the external environment.
Observed in society and the socio-economic phenomena, the processes are similar to the processes studied in the area of systemological sciences, as synergetics. The article discusses the methodology and general technological approach to building simulation models describing such phenomena in socio-economic systems. Model design public system should link the micro level, where individuals (organization) decide and act and macro-level, describing the state, the basic structure and development of the system. All model variables are constantly changing for a long time under the influence of external factors and internal, in transforming the system of structures and properties of the socio-economic system. At the macro level model designs are produced by means of the aggregated system dynamics models describing the main elements and processes of development, the evolution of social systems: population, economy, production and social infrastructure, environment and other factors of social life. Through the description of microprocesses aggregated system dynamics model of socio-economic systems are complemented by agent-based models of individual social and economic behavior of decision makers, as well as describing the interaction of many social groups. The agent-based model allows to investigate the individual behaviour of different groups of agents, the specificity of their adaptation to the changing environment, and how the processes of self-organization influence the evolution and development of socio-economic system as a whole.
This approach in building a multi-model complexes based composite system dynamics and agent-based simulation models allows to investigate the dynamics and development of socio-economic processes through cyclical relationship of micro- and macro- levels in this socio-economic system.
As an integration base for creating a model set, the paper uses a suite of ontological models, whose framework is based on the conceptual approaches to the model set stratification proposed in the paper.
Research/ Practical/ Social/ Environment implications
A simulation model of the socio-economic system acts as the core of the procedure of strategic decision making in the information-analytical centers, along with the monitoring system, data analysis, methods of generating scenarios, the technology of the scenario studies and analyzing their results. Procedures expert of audit and expertise-cognitive analysis is used for stratification, ontological design simulated socio-economic systems, the formation of possible scenarios, playable on simulation models, and modelling "balance of interests".
Considered model construction by the socio-economic systems are considered and applied by the author of this article in the construction of dynamic models in the social sphere (health, housing, pension system), a regional system, the collaborative supply chain.
This book provides an explanation of nation branding theory and practice within the European context, exploring how countries build and manage their reputations globally. Each chapter focuses on a specific European country, selected from a cross section of large, medium-sized and small countries to provide a breadth of cases from across the continent. The chapters are written from a wide range of academic and practitioner perspectives. Nation Branding in Europe is valuable supplementary reading for advanced undergraduate, postgraduate and doctoral students interested in nation branding and will appeal to students from marketing, communications and international relations disciplines. Outside of academia, the book will be of interest to those working in the areas of public diplomacy and strategic communications, as well as public relations and branding practitioners involved in designing nation branding campaigns.
Globally and in the U.S. in particular, pharmaceutical fraud account for a large number out of all crimes in healthcare, which result into severe costs to the society. The Academy of Managed Care Pharmacists (2019) estimate that pharmacy fraud is 1% of costs, therefore estimating that pharmacy fraud costs at $3.5 billion, given that pharmacy costs are $358 billion (Statista, 2021).
This exploratory study aims to demonstrate a fraudster’s profile as well as to estimate average consequences in terms of costs and identify the loss predictors’ hierarchy in the pharmaceutical industry in the U.S.
Materials and methods
Data from the Corporate Prosecution Registry and mixed-effects models are utilized for this purpose. The dataset covers years 2001-2020 and 75 cases, falling into one of the following broad sub-categories: misbranding, counterfeit, off label use of drugs, off-label use of drugs / deceptive marketing; violation of the Food, Drug and Cosmetic Act.
The main factors positively associated with loss due to pharmaceutical fraud are (i) duration of (ii) the scheme and scheme being executed at a U.S. public company. Surprisingly, presence of collusion negatively and significantly effects the cost. Potential factors include (a) principal perpetrator being a white American and/or male, and (b) number of employees at individual and organizational level respectively.
This study empirically justifies considering loss, due to pharmaceutical fraud, from a multi-level perspective. Identified profiles of a typical fraudster helped to elaborate on specific practical recommendations aimed at pharmaceutical fraud prevention in the U.S.
There is growing awareness among leading responsible management scholars and practitioners that understanding global wicked problems is insufficient in effecting lasting engagement and changed behaviors. Research indicates that to impact behavior, the mindset has to shift, which leaves the question: How do you shift a mindset?
This book guides educators and practitioners, their students and colleagues for taking action on finding urgent solutions for the grand challenges stated in the 17 UN Sustainable Development Goals. A Sustainability Mindset is a way of thinking and being that results from a broad understanding of the ecosystem, from social sensitivity, and an introspective focus on our personal values and higher self, which finds its expression in actions for the greater good. By promoting a mindset shift, educators in very diverse contexts are laying the foundation for a resilient future. The book presents a collection of over 150 student voices depicting a transformative experience and shift in their mindset. Seventeen educator/student teams of contributing authors from across five continents describe in the activity that prompted those students’ reflections, and the conceptual frameworks that played a role in the selection of the learning goals and activities.
The book is written with academic and corporate educators, reflective practitioners, consultants, coaches, trainers and students in mind, and is invaluable in guiding the process of developing a sustainability mindset amongst participants in the training process.
Since 2014, Russia has been actively searching for internal sources of economic growth to replace the external ones that have been lost because of sanctions and countersanctions. As a result, goals and mechanisms of nation branding are changing. The article examines seven key components of the image of Russia. The author concludes that (1) these components are interrelated to various degrees and are managed in different ways; (2) only two of them are full-fledged nation brands whereas the others cannot be recognized as brands for various reasons; (3) there is no consistent nation branding strategy in Russia at the moment.
The purpose of this paper is to address issues related to better identification of strategic orientation of the firm and the impact of strategic orientation on sustainable development of the firm. The paper presents an overview of the existing literature on strategic orientation of the firm, reexamines the major findings and fills the discovered gaps in theoretical constructs and models by new models. In this paper a new model of strategic orientation is proposed based on the type of relationship of a firm with its stakeholders who are considered as suppliers of key strategic resources. Relationship between the firm and its particular stakeholder is presented on an input-output like scheme and the variants of the position of the firm towards all its stakeholders serve as foundation for determining strategic orientation types. Next we present orientation of firms of different strategic types towards sustainability. The paper outlines several novels problems for strategic management and organizational design theory. The paper provides a novel treatment of strategic orientation and particular strategic types.
Strategic transformation and logistic integration in supply chain management requires systematic strategic supply chain modeling, and modern simulation provides such opportunities for analysis and synthesis of efficient and integrated supply chains. Authors suggest a method of constructing and analysis of conceptual supply chain models. The following base levels of the supply chain representation are considered: object-based, configuration/network-based, process-based, and logistics coordination levels. A general simulation model of integrative supply chain is proposed based on technologies of hybrid process-and-agent-based simulation modeling. Literature review on simulation modeling application for integrative and collaborative supply chains is presented. Iterative simulation and optimization procedures for complex analysis and optimization of supply chains are proposed. The suggested approaches and techniques were tested in the case of strategic transformation of supply chain. Authors present and interpret the results of supply chain optimization и simulation modeling for a set of scenarios of logistic processes transformation and inventory management policies, interorganizational coordination mechanisms and related technological solutions.
In this research, the author explores the approaches to simulation of supply chains' strategic development specifically focusing on formation of cooperation strategies between supply chain partners. The objective of this paper is to suggest a conceptual scheme and stratification approaches that enable creation of a model reflecting polysystemic representation of the supply chain. The following base levels of the supply chain representation are considered: object-based, configuration/network-based, process-based, and logistics coordination levels. In the field of supply chains transformation and strategic development there is a strong need in concurrent and aligned usage of different supply chain representations. That defines the approach to building generic supply-chain representation based on composite simulation models. Depending on addressable tasks of supply chain analysis and synthesis, process and system dynamic simulation models of different degrees of detail may be used. Agent-based modeling is used to model interorganizational coordination between supply chain partners.
The purpose of this paper is to explore the effect of work values and socio-demographic characteristics upon the link between life satisfaction and job satisfaction.
The European Values Study (EVS) 2008–2009 is used as the dataset. The sample is limited to those who have paid jobs (28,653 cases).
Socio-demographic characteristics matter more than work values in explaining the effect of job satisfaction on life satisfaction. The association between life satisfaction and job satisfaction is stronger for higher educated individuals and those who are self-employed and weaker for women, married individuals, religious individuals and those who are younger. Extrinsic and intrinsic work values significantly influence life satisfaction independent of the level of job satisfaction.
It is important to pay attention to the working conditions and well-being of the core of the labour force, in other words, of those who are ready to invest more in their jobs. Also, special attention should be given to self-employment.
The paper compares the roles of work values and of socio-demographic characteristics as predictors of the association between job satisfaction and life satisfaction. It shows that the role of job in person's life depends largely on demographic factors, religiosity and socio-economic factors.
Background: In estimating the global burden of cancer, adolescents and young adults with cancer are often overlooked, despite being a distinct subgroup with unique epidemiology, clinical care needs, and societal impact. Comprehensive estimates of the global cancer burden in adolescents and young adults (aged 15-39 years) are lacking. To address this gap, we analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, with a focus on the outcome of disability-adjusted life-years (DALYs), to inform global cancer control measures in adolescents and young adults.
Methods: Using the GBD 2019 methodology, international mortality data were collected from vital registration systems, verbal autopsies, and population-based cancer registry inputs modelled with mortality-to-incidence ratios (MIRs). Incidence was computed with mortality estimates and corresponding MIRs. Prevalence estimates were calculated using modelled survival and multiplied by disability weights to obtain years lived with disability (YLDs). Years of life lost (YLLs) were calculated as age-specific cancer deaths multiplied by the standard life expectancy at the age of death. The main outcome was DALYs (the sum of YLLs and YLDs). Estimates were presented globally and by Socio-demographic Index (SDI) quintiles (countries ranked and divided into five equal SDI groups), and all estimates were presented with corresponding 95% uncertainty intervals (UIs). For this analysis, we used the age range of 15-39 years to define adolescents and young adults.
Findings: There were 1·19 million (95% UI 1·11-1·28) incident cancer cases and 396 000 (370 000-425 000) deaths due to cancer among people aged 15-39 years worldwide in 2019. The highest age-standardised incidence rates occurred in high SDI (59·6 [54·5-65·7] per 100 000 person-years) and high-middle SDI countries (53·2 [48·8-57·9] per 100 000 person-years), while the highest age-standardised mortality rates were in low-middle SDI (14·2 [12·9-15·6] per 100 000 person-years) and middle SDI (13·6 [12·6-14·8] per 100 000 person-years) countries. In 2019, adolescent and young adult cancers contributed 23·5 million (21·9-25·2) DALYs to the global burden of disease, of which 2·7% (1·9-3·6) came from YLDs and 97·3% (96·4-98·1) from YLLs. Cancer was the fourth leading cause of death and tenth leading cause of DALYs in adolescents and young adults globally.
Interpretation: Adolescent and young adult cancers contributed substantially to the overall adolescent and young adult disease burden globally in 2019. These results provide new insights into the distribution and magnitude of the adolescent and young adult cancer burden around the world. With notable differences observed across SDI settings, these estimates can inform global and country-level cancer control efforts.
Purpose – The purpose of this study is to identify hotel halal attributes demanded by the Russian customers. Following this, the study aims to investigate whether gender and types of travelers influence the demand for hotel halal attributes.
Design/methodology/approach – Semi-structured interviews were conducted to localize the list of hotel halal attributes for the Russian business context. A self-administrated online questionnaire was designed, distributed and collected from 191 Russian customers, who have experience of staying at halal hotels in the last 12 months. Data analysis includes t-test and analysis of variance (ANOVA).
Findings – The study revealed a list of halal attributes demanded by Russian hotel guests. Also, the findings indicate the list of the attributes demonstrated the differences in the demanded attributes between gender and types of travelers
Research limitations/implications – The study is limited to a leisure tourists’ sample. Also, the study limited to the majority of the respondents having university degrees.
Practical implications - The study provides a clear understanding of the hotel halal attributes demanded by Russian Muslims that can help hotel managers to tailor their hotel services to the needs of this group meeting, at the same time, the requirements of guests of different nationalities and religions.
Originality/value - This research contributes to tourism and hospitality management and consumer behavior literature, primarily, as this is the first research yielding insights on a new demographic within for the form of academic literature customers’ segment: Russian Muslim tourists
Paper type – Research paper
The crisis caused by the coronavirus pandemic has caused a significant drop in production performance in the passenger airline industry and has forced players to change their business models. Based on the references to the actions of airlines in 2020 and the first half of 2021 the author considers the applicability of the industry business model and the model of crisis response strategies in the Russian context. We determined the types of reactions of domestic airlines to the impact of the crisis and the elements, the depth of changes in business models taking into account regional specifics. The results of the analysis revealed a different from foreign airlines sequence of response of carriers to the crisis, expressed in a search for innovative solutions, the expansion of the value chain, in addition to reducing assets and applying for state support. Such behavior is related to regional peculiarities of the Russian market, expressed in institutional characteristics, market architecture and consumer behavior. Taken together, a comprehensive and chronological analysis over 1.5 years has also revealed a set of trends in the development of the passenger air transport market in Russia, the issue of the sustainability of which may be a subject for further case studies.
properly built risk assessment process could help to significantly reduce the overall level of a project uncertainty, which in turn will have a positive impact on the project outcome. Based on recommendation given in BABOK® Guide, a combined procedure for analysis of risks is built up, which allows performing risk assessment within the framework of the overall risk management process. The main groups of risks classified by their main origin are identified related to a reference IT-project applied in financial sphere. This makes the proposed procedure to be aimed at detailed risk analysiswhere not only the qualitative but also the quantitative measure of the risks, i.e., their probability and gravity of their consequences can be implemented. The process of risk assessment is chosen for the project consisting in creating and deploying a modern corporate data warehouse in a big Russian private bank. The procedure is extended by decision tree, concisely illustrating risk decomposition, which open the way to highly predictable further risk management process. The short feedback replies given by main stakeholders at the end of first stage are also presented.