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This chapter argues that a recent backlash against multiculturalism in Australia is not about ‘multiculturalism’ as much as it is about the accommodation of Muslim minority groups in multicultural states. The chapter seeks to address concerns that some multicultural policies pose a threat to the cohesion of society and place women in a particularly vulnerable position. Drawing on the work of Will Kymlicka and Tariq Modood, we argue that multicultural policies have an important place in liberal democratic states and contribute to integration of minority groups into the wider society. Using a theoretical framework of Foucault’s work on power and resistance, and drawing on new empirical data, we argue that multicultural policies facilitate Muslim women’s resistance to existing discourses. We explore issues of Australian Muslim women’s agency, multiculturalism and Shari’a in select areas of Muslim women’s lives including their choice of dress, access to and utilization of both Australian and Islamic Family law, and participation in a key area of Australian cultural life, that of sport.

Biosimilar medicines have shown similarity with the originator biologic and offer a similar clinical outcome generally at a lower cost. This paper identifies benefits of off-patent biologics and biosimilars, and illustrates these benefits with empirical data from Europe. We provide a narrative review of published literature on values and benefits of biosimilars in Europe. The results describe cost savings as the key driver stemming from the lower price of biosimilars, than that of originator products, and from price competition between biosimilar(s), originator, and next-generation products. Cost savings may then translate into a number of other associated benefits. The lower price of biosimilars and similar effectiveness to the originator biologics improve cost effectiveness, implying that reimbursement can be granted or extended to other patient groups, or that the biologic therapy can be moved to an earlier line of treatment. Cost savings from biosimilars can be used to increase patient access to therapy or to increase the number of healthcare professionals. Finally, competition between off-patent biologics and biosimilars may stimulate an innovation in the formulation and development of next-generation biologics. Our paper illustrates that the benefit of off-patent biologics and biosimilars is not restricted to cost savings, but that these medicines may contribute to an expansion of medical treatment options for patients, hence concomitantly contributing to the long-term sustainability of the healthcare system. This review provides a broader view for clinical and economic decision makers and healthcare professionals on the added benefits of off-patent biologics and their use in clinical practice. ispartof: BIODRUGS vol:34 issue:2 pages:159-170 ispartof: location:New Zealand status: published

The university is moving on uncertain terrain. As we are writing this introduction, we are coming close to completing the first year of the pandemic (but possibly not the last). As a consequence, and due to the massive changes and restrictions, the last year has seen a disruption of some of the recent global drivers within higher education, such as student (and staff) mobility, internationalization, and professionalization of higher education. On the other hand, we have seen a major increase in, and push for, the digitalization of the university as many courses, conferences, and projects have had to move either partly or entirely online. Further, habitual research practices have been influenced as well. Collecting empirical data, field work, and the use of university facilities such as laboratories, media labs, office facilities, and libraries have, for periods of time, been either closed off altogether or have been open with restrictions to physical access and on numbers of people allowed.

Demand side management (DSM) is seen as a promising, cost-effective measure to cope with high shares of intermittent renewable energy in the electricity grid system. As the regulatory framework in Europe is changing in favor of opening up new market opportunities for DSM, the question is answered, which potentials are effectively available in the tertiary sector today and in the future. Results in this study are based on empirical data gathered from services companies. The collected data is of high quality and rich in detail and is of utmost importance for relevant model-based analyses. Additionally, the discussed acceptance rates of new technology or behavioral trends have a high impact on the results of the model analyses.

This chapter will do three things. First, it will describe the relationship between how a political party campaigns and the way they organise themselves, drawing on much of the classic literature in the field. Second, it will discuss the literature on data-driven campaign practices. This includes the evidence about how these practices are affecting political parties and democracy. Third, I set out my original theoretical framework, the data-driven model of campaigning. I argue that this framework, built on insights from the empirical data collected for this project and the secondary literature, provides a way forward for scholars trying to understand different types of data-driven practices, including how these affect political parties in advanced democracies such as Australia.

This chapter combines insights from the capability approach and the embeddedness approach. We introduce the notion of capability to participate in adult education and argue that it is richer than that of participation in adult education. The chapter proposes a theoretical framework which can underpin the building of an integrative adult education participation model, capturing the influence of not only factors at micro, meso, and macro levels but also the interactions between them. Its analysis of empirical data reveals that the impact of individual characteristics on one’s capability to participate in adult education is embedded in different socio-economic, institutional, and cultural contexts.

The rapid development of digitalization has led to a more or less endless variety of ways for individuals to communicate and interact with the outside world. However, in order to take advantage of all the benefits of digitalization, individuals need to have the necessary skills. Seniors represent a group that, compared to other groups, lives in a digital exclusion to an excessive extent, mainly due to the fact that they lack the necessary knowledge to use digital technology and digital services. Based on empirical data collected from seniors partaking in digital training, we have analyzed their perceptions of why they and other seniors are digitally excluded. Our findings point out that a major barrier for seniors to be more digitally included is different variants of fear of using digital technology and digital services. The common denominator can be traced down the possibilities to be exposed to frauds, scams, viruses, and faulty handling, which in turn cause undesired consequences. Consequently, we propose a research agenda where digital training and digital inclusion measurements should be studied side by side with cybersecurity behavior. Thus, making cybersecurity a fundamental part of digital inclusion has the potential to minimize the fears identified in this research as inhibitors to technology adoption.

Fuzzing has become one of the most popular techniques to identify bugs in software. To improve the fuzzing process, a plethora of techniques have recently appeared in academic literature. However, evaluating and comparing these techniques is challenging as fuzzers depend on randomness when generating test inputs. Commonly, existing evaluations only partially follow best practices for fuzzing evaluations. We argue that the reason for this are twofold. First, it is unclear if the proposed guidelines are necessary due to the lack of comprehensive empirical data in the case of fuzz testing. Second, there does not yet exist a framework that integrates statistical evaluation techniques to enable fair comparison of fuzzers.

The global pandemic of COVID-19 has a significant impact on the public transportation (PT) sector and users’ perception. This study aimed to assess the public transportation users’ perceptions, needs, and preferences during the COVID-19 pandemic in Amman, Jordan. A cross-sectional correlation design was used to recruit 510 participants between March 2020 - October 2020. We used an online survey that included the users’ sociodemographic data sheet, frequency of using PT and other traveling modes, and travelers’ perception towards PT before and after the pandemic. This study indicated a dramatic decrease in using PT during the pandemic, reaching 50%, and a reduction in the frequency of PT daily usage from 16% to 4%, however, all other traveling modes experienced an increase. In addition, 50% of the participants indicated that social distancing was the most important criterion to choose the mode of traveling during the pandemic, while equally 22% of the participants considered the duration and cost before traveling as an important criterion. A significant correlation between the frequency of using PT during the pandemic and anxiety was observed. However, the frequency of using PT or walking indicated a significant correlation with education levels only before the pandemic. Besides, 50% and 40% of the participants reported that neither public transportation nor walking infrastructure conditions were appropriate, respectively. The study yielded important empirical data that can be employed in PT planning and understanding users’ preferences during this pandemic and for anticipated coming waves.

Due to the pandemic of 2020, many teaching and research institutions are confronted with extraordinary working conditions. In order to enable empirical data collection under these special circumstances, teachers and scientists need to respond flexibly and new concepts need to be developed. This paper deals with the challenges that arise in day-to-day teaching and provides different approaches to meet these challenges. It covers quantitative surveys, remote UX-testing methods as an alternative to eye tracking studies in the lab, as well as face-to-face user experience testings under strict hygiene measures.

This chapter completes the discussion around the consequences of environmental fraud. Based on the results from a series of event studies, Volkswagen Dieselgate’s impact on the market value of the company is approached in more detail. Similarly, the losses caused for investors of firms that orbit the German company (e.g. suppliers, competitors) are analyzed. Beyond the objective examination of empirical data, the chapter offers a theoretical discussion around the diverse constructs connected to the theme. Among them, the notions of market value and value per se are advanced, along with various explaining factors for value loss. In addition to contributing to the literature on the causes, means, and consequences of market value fluctuations, the conceptual considerations aim to allow for the generalization of ideas to other contexts. This would include other types of environmental fraud, and its occurrence in other industries beyond the automobile one.

To support the process of identifying and scoping data-driven innovation, we are introducing the data-driven innovation (DDI) framework, which provides guidance in the continuous analysis of factors influencing the demand and supply sides of a data-driven innovation. The DDI framework describes all relevant aspects of any generic data-driven innovation and is backed by empirical data and scientific research encompassing a state-of-the-art analysis, an ontology describing the central dimensions of data-driven innovation, as well as a quantitative and representative research study covering more than 90 data-driven innovations. This chapter builds upon a short analysis of the nature of data-driven innovation and provides insights into how to best screen it. It details the four phases of the empirical DDI research study and discusses central findings related to trends, frequencies and distributions along the main dimensions of the DDI framework that could be derived by percentage-frequency analysis.

In recent years, there is a growing focus on the role of small and mediumsized enterprises (SMEs), and their development towards Industry 4.0. One way of supporting SMEs in this effort, is by utilizing the method of strategic roadmapping. This article presents a) a theoretical framework for the use of strategic roadmapping towards industry 4.0, and b) insights from a validation of the framework in four pilots - Norwegian manufacturing companies. The framework offers a systemic view of the company by focusing on five dimensions: business and strategy, product, customers and suppliers, production processes, and factory and infrastructure. Simultaneously, the framework offers a stepwise method to look at these five dimensions from a strategic perspective in a holistic way. The empirical data from the pilot companies offer insights on how the companies take up the strategic roadmapping method into their strategic operations, as well as which topics related to Industry 4.0 get integrated into their future vision, strategies and plans. The results indicate that the use of the strategic roadmapping method supports companies in seeing diverse routes towards Industry 4.0 and provides support in prioritizing relevant projects and activities.

This chapter analyzes the experiences of labor insertion of 30 Paraguayan women in the Parana Tri-Border Area (TBA) (between Argentina, Brazil, and Paraguay). Through their stories, it inquires into how they develop trade strategies to face the slowdown of the most popular commercial circuit in the Parana Tri-Border Area (TBA), known in the literature as the circuito sacoleiro [bag-carriers’ circuit]. The first section starts by giving the theoretical background based on studies that show the articulating relationship between border trade and the women’s experience in this region. Then, analyzing in depth the empirical data, the chapter shows how trade is a fundamental labor niche for the interviewees, which allows them to develop strategies to reconcile their productive and reproductive overloads. Furthermore, it describes the women’s experiences in three commercial niches: on street stalls on the Paraguayan side of the border, in stores or on street stalls on the Brazilian side, and the cross-border smuggling of agricultural products from Brazil to Paraguay. By considering the empirical evidence collected, it concludes with some analytical reflections that complement the previous debates.

This contribution evaluates the economic utility and effectiveness of class actions in Quebec based on empirical data obtained at the Class Actions Lab over a period of 25 years. The University of Montreal Faculty of Law’s Class Actions Lab is conducting this study in the course of its “Class Action Compensation Project”. The Project began in the summer of 2015 and is scheduled to conclude in 2022. The Project seeks to compile and compare take-up rates in various class action files, as well as per-plaintiff recovery data. Ultimately, it measures the end product of class action litigation, the value and benefit of this kind of litigation, and, incidentally, its costs as assumed by the parties and the system. The Project has identified specific parameters that can be used to evaluate empirically class action costs and benefits, and a significant list of criteria directly associated with higher rates of participation and compensation. This is the first Canadian study of its kind. The contribution shows that class actions are instruments of compensation of class members, but that this compensation remains imperfect by way of the number of members compensated, the extent to which they are compensated and the exorbitant costs of bringing such actions.

Electrical recordings of neural mass activity, such as local field potentials (LFPs) and electroencephalograms (EEGs), have been instrumental in studying brain function. However, being aggregate signals that lack cellular resolution, these signals are not easy to interpret directly in terms of neural functions. Developing tools for a reliable estimation of key neural parameters from these signals, such as the interaction between excitation and inhibition or the level of neuromodulation, is important both for neuroscience and clinical applications. Over the years we have developed tools based on the combination of neural network modelling and computational analysis of empirical data to estimate neural parameters from aggregate neural signals. The purpose of this paper, which accompanies an Invited Plenary Lecture in this conference, is to review the main tools that we have developed to estimate neural parameters from mass signals, and to outline future challenges and directions for developing computational tools to invert aggregate neural signals in terms of neural circuit parameters.

Southwest China plays a key role in global hydropower; its current installed capacity is roughly equal to that of the rest of Asia. This immense hydropower capacity stems from some of the world’s largest dams as well as the world’s greatest density of smaller projects. However, our knowledge about the region’s hydropower utilisation patterns and spatio-temporal impacts is based on limited empirical data. This chapter provides a detailed analysis of the uneven spatio-temporal hydropower development in the area and the fluctuating oversupply of hydroelectricity. While as of 2019 hydropower development is advanced in Sichuan (77 GW, 316 TWh) and Yunnan (64 GW, 270 TWh), it is still in an early stage in Tibet. However, Tibet’s hydropower development might even surpass both provinces in the future. The second part of the chapter analyses the utilisation of hydroelectricity, with an emphasis on Yunnan. Our analysis focuses on the trade-offs (benefits, disadvantages, and current trends) related to large-scale power exports to coastal load centres, mapping out these exports for all of Southwest China. Further, we discuss the unique role of power-intensive industries within Yunnan and the impacts of rural electrification on local utilisation of hydropower.

This chapter examines various levels of human and non-human-mediated forms of bias in place-based predictive policing that may lead to discriminatory outcomes. Informed by science and technology studies (STS), and drawing on empirical data on the implementation and utilization of crime prediction software in Germany and Switzerland, we grasp predictive policing as a socio-technical assemblage, encompassing not only the technical predictions themselves but also the enactment of the predictions on the street level by police—which can also have serious ramifications including discrimination. Further, we consider the broader socio-political and historical contexts of these predictive technologies and dispute technocentric accounts of discrimination in predictive policing. Rather, we argue for greater attention to be paid to the socio-political and historical contexts from which such technologies and practices emerge. Hence, we contend that STS approaches are vital for an appropriate understanding of the discriminatory potency of (place-based) predictive policing, as we need to decenter technology in accounts of discrimination in predictive policing. Our argument unfolds across four steps. First, we present a short introduction to predictive policing and highlight its socio-technical nature. Second, we analyze the main dimensions of discrimination sources in place-based predictive policing. Third, we argue for the need to decenter technology and call for an appreciation of broader socio-political and historical perspectives in the analysis of predictive policing. Fourth and finally, we argue for the need to incorporate science and technology studies (STS) into the analysis of the discriminatory potential of predictive policing.

Chapter Three unpacks an unique case of ATM hacking that occurred to the First Commercial Bank (FCB) in Taiwan. To facilitate readers’ assessment of the uniqueness and generalizability of the case, Taiwan’s social-historical context is introduced, followed by briefing its two major law enforcement agencies. The FCB case is thoroughly discussed, including the group actions by cyber criminals—Carbanak/Cobalt—and law enforcement agencies’ responses. Multiple sources of empirical data and documents are used to portray the incident in a chronological order.

Coworking spaces have received a lot of attention from both practitioners and social science scholars in recent years. They host self-employed professionals, freelancers, entrepreneurs, and employees of large enterprises in the same office environment with shared facilities. Recently coworking spaces have become the primary location for many entrepreneurs as they offer a resourceful environment. However, how coworking spaces enable their participants to access various resources is an open question. In this chapter, we study two prominent and distinctly different coworking spaces in Istanbul. In analyzing our empirical data, we employ the forms of capital framework of Bourdieu (The forms of capital. In J. G. Richardson (Ed.), Handbook of theory and research for the sociology of education (pp. 241–258). Westport, CT: Greenwood, 1986) to understand the underlying mechanisms of resource acquisition enabled by coworking spaces. Based on our results, we develop a theoretical framework explaining what mechanisms cultivate tangible and intangible resources for the participants of coworking spaces. We outline our contributions and potential lines for further research.

The chapter introduces the rationale for the comparative research in the book and its objectives. It situates this first assessment of the energy-efficiency retrofit programs in the social housing sector of Canadian cities in a theoretical framework focused on policy design. The chapter outlines an analytical framework for evaluation of program efficiency and effectiveness with links to key policy instruments—regulatory, financial and institutional—in relation to major results achieved. The approach is interdisciplinary, supported by rich empirical data from case studies, observations and interviews. The structure of the book systematically presents the results of decade-long energy efficiency retrofit programs in Toronto, Vancouver, Edmonton and Calgary. It offers valuable lessons for the design, planning and implementation of energy retrofit programs in Canada and beyond.

Managers of engineered assets have to make decisions to acquire, utilise, and retire equipment, machinery, and such man-made facilities. On the one hand, manufacturers, suppliers and vendors of machinery and equipment continuously seek to sustain their businesses. On the other hand, asset owners and users seek to achieve better performance of assets. Given the advent of the fourth industrial revolution technologies and globalization 4.0 business models, the question arises as to what level of product-to-service transformation is appropriate in a given user-manufacturer/supplier/vendor setting, and what should be the extent of the corresponding product-service system? This paper discusses an investigation into product-to-service transformation in terms of strategies adopted by equipment and machinery manufacturers, suppliers and vendors on the one hand, and also of asset owners and users on the other hand. Empirical data and information from the respective sides are summarily presented with regard to the effect of product-to-service transformation on the user-side management of engineered assets.

Future managers act as agents of change in today’s business environment. In this regard, the formation of managerial competencies in view of readiness to fulfill their professional duties in conditions of uncertainty is relevant. In this regard, it is important to assess the readiness of future management personnel for change in modern conditions. The aim of this study is to provide empirical data on the established attitudes of future management personnel towards uncertainty during a period of change. Among the available variety of questionnaires, the PCRS (Personal change readiness survey) technique was chosen thanks to its multi-factor model, which allows you to study not only individual significant personality characteristics in a volatile environment, but also their relationship with the relation to uncertainty.

The research responds to calls in the literature for a more systematic study of the problem of entrepreneurs’ access to the most effective types of financing. The purpose of the study is to evaluate indicators describing the financing of business creation and start-up at the expense of entrepreneurs’ own funds and informal investments. We used empirical data obtained from surveys conducted during the implementation of the Global Entrepreneurship Monitoring Project for 2019–2020 for 50 countries. In the course of the work we assessed the indicators describing the existing levels of informal investments in small businesses; investigated the level of participation of the population in investments; proved that the number of early entrepreneurs self-financing the creation of their new business significantly exceeds the number of those using informal investments; set the values of the average amounts of informal investments; demonstrated the differentiation of the indicators by country; identified countries with high and low levels of the considered indicators.

Statistical AI is cutting-edge technology in the present landscape of AI research whilst Symbolic AI is generally regarded as good old-fashioned AI. Even so, we contend that induction, i.e., learning from empirical data, cannot constitute a full-fledged form of intelligence on its own, and it is necessary to combine it with deduction, i.e., reasoning on theoretical grounds, in order to achieve the ultimate goal of Strong AI or Artificial General Intelligence. We therefore think of the possibility of integrating Symbolic and Statistical AI, and discuss Quantum Linguistics by Bob Coecke et al., which, arguably, may be seen as the categorical integration of Symbolic and Statistical AI, and as a paradigmatic case of Integrated AI in Natural Language Processing. And we apply it to cognitive bias problems in the Kahneman-Tversky tradition, giving a novel account of them from the standpoints of Symbolic/Statistical/Integrated AI, and thus elucidating the nature of machine biases in them.

Data from A-share listed companies in Shanghai and Shenzhen stock markets, 2013–2018, was utilized in this study to explore the impact of internal control quality and analyst following on debt financing costs. A significant negative correlation was found between the quality of internal control and the costs of debt financing. Analyst following presents a substitution effect in the relationship between internal control quality and debt financing costs. The impact of analyst following and internal control quality on reducing debt financing costs also differs significantly among companies with different ownership, region, industry, and market position characteristics. These results may provide empirical data support as Chinese decision-makers improve internal control quality and optimize the investment environment to effectively mitigate the financing constraints on listed companies.

Healthcare systems are challenged to deliver high-quality and efficient care. Studying patient flow in a hospital is particularly fundamental as it demonstrates effectiveness and efficiency of a hospital. Since hospital is a collection of physically nearby services under one administration, its performance and outcome are shaped by the interaction of its discrete components. Coordination of processes at different levels of organizational structure of a hospital can be studied using network analysis. Hence, this article presents a data-driven static and temporal network of departments. Both networks are directed and weighted and constructed using seven years’ (2010–2016) empirical data of 24902 Acute Coronary Syndrome (ACS) patients. The ties reflect an episode-based transfer of ACS patients from department to department in a hospital. The weight represents the number of patients transferred among departments. As a result, the underlying structure of network of departments that deliver healthcare for ACS patients is described, the main departments and their role in the diagnosis and treatment process of ACS patients are identified, the role of departments over seven years is analyzed and communities of departments are discovered. The results of this study may help hospital administration to effectively organize and manage the coordination of departments based on their significance, strategic positioning and role in the diagnosis and treatment process which, in-turn, nurtures value-based and precision healthcare.

There is a gap in most countries’ legal frameworks regarding their ability to connect vacant land and urban gardens. Hence, research is needed to understand how regulation on vacant land might be designed to promote a more sustainable purpose to it. Urban gardens are a type of urban agriculture that could be potentiated by such regulation. The aim of this paper is to show how that can be done through the Municipal Master Plans (MMP) legal and regulatory framework for the Portuguese case, by reviewing worldwide good practices on vacant land restorations for urban sustainable development. The paper comprises a literature review on good practices adopted in different countries regarding vacant lot restoration. The evaluation of good practices is built on the achievement of the three pillars of sustainability. Five Portuguese MMP were used, as empirical data, to support the design of a new legal and regulatory framework. The goal is to enhance the sustainable destination of vacant land by converting it into urban gardens. The analysis of these MMPs demonstrated that they disregard urban gardens as a tool to promote urban sustainability in spite of global trends to make urban territorial planning and management instruments greener. An additional outcome of this paper is to categorise different types of vacant land in the five municipalities under analysis according to their suitability for urban garden conversion. The design of the legal framework enhancing the conversion of vacant land into urban garden will contribute to the 2030 international agenda goals’ achievement. The proposal would create an innovative legal framework in the case of Portugal that could be replicated by other countries.

In this chapter, the empirical data are presented as a typology of narratives in which experiences and activities in virtual space and the real world are interwoven, along with ideas and wishes for the future, what has happened in the past, and what is happening in the present. They run like a subterranean web through the narrators’ lives, initiating patterns of thinking and doing which revolve around a specific focus. The following types of narrations were identified: stories about interconnectedness, self-staging, supplying and selling, managing boundaries, and transformation, as well as setting out and breaking away.

The main aim of this chapter is to examine the applicability of praxeological theory to the evaluation of innovative projects in the healthcare sector. We propose a set of project evaluation criteria and indicators. The empirical data used in the pilot study was taken from projects carried out by a Contract Research Organization. The analyzed projects regard R&D as well as clinical and observational studies. Interviews were conducted with experienced people in the R&D projects management, projects carried out jointly by scientific units, along with commercial projects in the medicine and pharmaceutical industry. The results of the conducted analyses formulate key criteria and indicators (based on effectiveness, economicality, and efficacy) for evaluating the performance of innovative healthcare projects. The conclusions drawn from the research results allow to claim that it is possible to use praxeological theory in the evaluation of healthcare projects. The chapter presents current problems important from the point of view of management sciences and undertaken research development.

A comprehensive treatment of wireless underground channel modeling is presented in this chapter. The impacts of the soil on bandwidth and path loss are analyzed. A mechanism for the UG channel sounding and multipath characteristics analysis is discussed. Moreover, novel time-domain impulse response model for WUC is reviewed with the explanation of model parameters and statistics. Furthermore, different types of the through-the-soil wireless communications are surveyed. Finally, the chapter concludes with discussion of the UG wireless statistical model and path loss model for through-the-soil wireless communications in decision agriculture. The model presented in this chapter is also validated with empirical data.

This chapter sets out the historical, theoretical and methodological mise-en-scene for all our subsequent analyses. We engineer an encounter between the sinologist philosopher Francois Jullien’s work on the Chinese concept of shi (势) and Western theories of urbanism, cinema, assemblages and semiocapitalism. We thereafter strive to explain how theory and empirical data become articulated and synthesised during our studies of: surreal real estate showrooms; a fragmented history museum building; a simulacral educational “theme park”; gamified “any-now(here)-spaces” and one of China’s new “old towns.” We also work to define and illustrate a series of four (or so) interrelating concepts important to these analyses, including what we mean by cinematicity and shi-nema, as well as our Realist fractal modelling and 4E Psychogeographic approaches.

The article presents a mathematical model of the influence of transnationalization on the Russian agricultural machinery market that provides multi-parameter typing and system identification based on empirical data with the use of automated system-cognitive analysis and its own software tool – an intelligent system called “Eidos”. The ASC-analysis makes it possible to justify the dual effects of transnationalization on the formation and development of the Russian agricultural machinery market. An analysis of the results of a numerical experiment shows that the “Eidos” intelligent system can be used to solve the problems of forecasting, making decisions, and researching a simulated subject area by studying its model in other subject areas. #CSOC1120

The purpose of the paper is to study the social disclosure of information related to their environmental performance in 30 Russian industrial companies. It also attempts to investigate to which extent social disclosure can have an impact on the firm value. The article surveys both Russian and international literature on environmental disclosure. The authors also fully describe the research methodology and present the empirical data that served as the basis for calculations and conclusions. The findings of the study demonstrate that there is no significant relationship between a firm’s ecological disclosure and its stock market performance. The article also stresses the importance of the university and in-house eco-training in industrial companies.

The number of people with diabetes is increasing and today more than 8.5% of the adult population is diagnosed with diabetes. People with diabetes must make significant changes to their life and habits and adjust it to the recommendations for diabetic treatment to avoid or delay complications related to the illness. In this paper, we present empirical data from a survey, experience sampling data and interviews that addresses people with type 1 diabetes’ adherence with the recommended blood sugar measurements, their physical activity level and motivational factors. This information is used to understand and explain people with diabetes’ adherence to follow the recommendations using theories about self-efficacy and motivation. Finally, we give recommendations for how digital solutions can be designed that can aid the users and motivate them to follow the recommendations and hereby potentially improve the quality of life for diabetes patients.

Whilst debate continues regarding how to define moral distress (MD), one constant has been the belief that healthcare professionals often experience MD during end-of-life (EoL) care. In this chapter, we will discuss the concept of MD in the context of EoL care, drawing on a recent case that has attracted global attention and empirical data drawn from Morley’s doctoral studies exploring MD in nursing. We argue that the empirical data supports a broader understanding of MD and that the occurrence of MD during EoL care can highlight other morally complex issues that warrant further exploration.

The paper presents an analysis of the failures of components of the mechanical part of 2ES6 Sinara main electric locomotives in operation at the West Siberian Railway operating domain. The causes and consequences of failures of the most vulnerable components are determined. The task is to determine the level of dynamic loading in the “bogie – rod - traction electric motor” subsystem to reduce the dynamic effects in the “locomotive - track” system. The urgency of the problem of increased dynamic loading of components of the mechanical part is proved, and a mathematical model of vertical oscillations of traction rolling stock is formed on the basis of the second-order Lagrange equation in the form of a system of equations that allows assessing the load of components in operation. The spectral density of random perturbations was chosen—an approximation of random perturbations using the spectral density of the track roughness of Professor A. I. Belyaev. Using a computer, values were calculated, and graphs of the amplitude-frequency characteristics of vertical displacements, maximum accelerations of the body, bogie, traction electric motor and wheelset of the considered conditional uniaxial electric locomotive were built. A comparative analysis of the calculation results and empirical data is carried out. The task is to change the existing design of the suspension system of the traction electric motor of the electric locomotive under consideration and to analyze the oscillations of its components in further studies.

Rurality, access, participation, and achievement lie at the heart of inclusivity in education. This is a social justice issue that has undeniably permeated many rural schools in many countries in Sub-Saharan Africa for an extensive period of time. This chapter explores how rural and flood-prone schools commit to delivering a socially-just educational experience and comparable learning outcomes in terms of access, participation, and achievement. In particular, the chapter explores the realities of rural education and how these schools confront serious challenges in delivering access to education to learners. The chapter is based on empirical data drawn from a larger doctoral study on epistemological access, conducted between 2013 and 2016 in five rural flood-prone schools in Kenya.

In this chapter, Demeter presents a great volume of empirical data on the science output of different world regions. Analysis shows that while different disciplines have a different distribution of academic capital, the center/periphery structure of the field of knowledge production is rather similar in the case of all disciplines with the absolute hegemon position of the US, the UK and other developed countries of Western Europe. Demeter also argues that the exclusion of the periphery and the excessive brain drain and reeducation practices maintain global North hegemony to a great extent, while potentially causing even the most successful peripheral authors to lose their authentic voices. As counterexamples, the author presents the more adaptive, state-funded tactics of some BRICS countries.

This chapter thematises gender and educational choices through a close-reading of three Norwegian women’s stories about choosing physics-related STEM subjects (Science, Technology, Engineering, Mathematics) in order to explore how the act of choosing an education may be identified as a sociomaterial practice. Often, people choose a particular educational path because they are interested in a subject. Campaigns to recruit women to the STEM subjects have, therefore, focused on what they believe attracts women to the sciences. In this chapter the authors turn from focusing on gender as a variable for explaining interest in STEM, to examine empirical data concerning women’s educational choices. The interaction between human and material factors also involves embodied experiences, something which gives gender agency. This discussion contributes a greater understanding of the factors that come into play when one chooses a path for education and the ways that educational choices can be influenced through material experiences and practices both in and outside educational institutions.

Digital disruption is propelling manufacturers to move on towards digital transformation and deliver digital services based on predictive analytics. The literature agrees that digital technologies (i.e. big data) facilitate the service innovation of manufacturers by creating digital servitization. However, little research has specifically focused on the empirical data that analyze use of digital technologies in manufacturing firms in terms of technological intensity. The present study investigates the interaction between big data analysis, as a digital service, and firm characteristics (i.e. firm size and technological intensity). Our analysis used the Serbian dataset of 240 manufacturing firms from the European Manufacturing Survey conducted in 2018. The empirical results show that, in manufacturing firms, digital service based on predictive analytics is highly utilized in medium size firms. Furthermore, results indicate that high technology manufacturing firms in Serbia are not yet utilizing digital technologies to facilitate the service innovation in comparison to other innovation intensity characteristics.

The fate of a high-growth company in Russia often turns out to be dramatic. Yesterday’s leaders slow down, introducing an imbalance in the economy and reducing its potential, sometimes go bankrupt. The study aims to identify economic, institutional, and administrative factors that cause rapid growth or consequent fall of fast-growing firms in Russia. The article based on the results of the analysis of 104 high-growth Russian companies that included in the national rating. This paper is used empirical data from different sources and also regression models. This research is limited in time (2010–2017) and space (Russian economy). Also, limitation of the research is data source—not all Russian private high-growth firms are transparent and accessible disclose information about its success story. The main findings are the importance of industry affiliation of company, entrepreneurial nature of the firm, and lack of influence of administrative power on long-term business success.

In this chapter, the authors report on the construction of a new framework for simulating mixed traffic consisting of cars, trams, and pedestrians that can be used to support road management, signal control, and public transit. More specifically, a layered road structure, originally designed for car traffic simulations, was extended to interact with a one-dimensional tram model and one-/two-dimensional pedestrian models. The newly implemented pedestrian models and interaction rules were verified through simulations involving simple road environments, and the resulting simulated values were found to be in near agreement with the empirical data. The proposed framework is then used to assess the impact of a tramway extension plan for a real city. Those simulation results showed that the impact of the proposed tramway on existing car traffic would not be severe, and by extension, implied that the proposed framework could help stakeholders decide on expansion scenarios that would be agreeable to both tram users and private car owners.

Vehicular cloud is a group of vehicles whose corporate computing, sensing, communication and physical resources can be coordinated and dynamically allocated to authorized users. One of the attributes that set vehicular clouds apart from conventional clouds is resource volatility. As vehicles enter and leave the cloud, new compute resources become available while others depart, creating a volatile environment where the task of reasoning about fundamental performance metrics such as job completion time becomes very challenging. In general, predicting job completion time requires full knowledge of the probability distributions of the intervening random variables. However, the datacenter manager does not know these distribution functions. Instead, using accumulated empirical data, she may be able to estimate the first moments of these random variables. In this work we offer approximations of job completion time in a dynamic vehicular cloud model involving vehicles on a highway where jobs can be downloaded under multiple stations.

This new emerging and innovative concept of Building Information Modelling (BIM) has delivered changes in terms of the efficiency and effectiveness of management in the construction industry. However, several constraints in the implementation of BIM are indicated notably people, process and technological constraints. In Malaysian quantity surveying profession, several quantity surveying firms are developing 3D model for taking-off and cost estimating preparation based on the standard method of measurement owing to the infancy stage of BIM implementation. This is still not a conventional work task in the quantity surveying profession. To promote the usage of 3D modelling which is far different compared to the traditional method, it is crucial to understand the constraints of 3D modelling and BIM. Therefore, this paper aims to compare the constraints of BIM and 3D Modelling in quantity surveying profession. Eleven semi-structure interviews have been conducted with the experienced quantity surveyors who are practising 3D modelling for quantities and cost estimation purposes to collect experts’ comments on the constraints of 3D modelling compared to BIM implementation. The content analysis which focuses on describing and quantifying phenomena is selected as a research analysis method for the diverse empirical data. The research finding indicated that technological constrains are significantly affecting the 3D modelling implementation while people and process constraints are less significant. This research finding serves as a guidance for quantity surveyors who are willing to take initiatives in implementing 3D modelling in quantity surveying profession.

Social media facilitates and enhances communication between businesses and customers. Nowadays, although it is commonly recognised that companies implement social media into their marketing activities, it is also acknowledged that companies struggle to calculate the return on investment (ROI) from social media marketing efforts as most of them focus only on certain tangible outcomes such as the impact on sales and purchases. Attempts have been made by researchers to identify how to measure key impacts of social media in relation to marketing; however, there remains a lack of empirical data and no comprehensive overview of what “ROI” can mean for an organisation seeking returns on their social media adoption. By knowing how to measure ROI from social media, companies can produce valuable insights which can help enhance marketing strategies in promoting their products/services. Thus, the aim of this chapter is to provide a review of ROI in social media marketing with a particular focus on intangible outcomes such as brand awareness, customer engagement/relationship and eWOM.

The effectiveness of innovative processes in higher education largely depends on how these innovations will be accepted by those who depend on their direct implementation. The aim of this article is to study the subjective attitude of teachers of higher education to some changes and innovative processes taking place in the system of higher education. The following changes are highlighted for analysis: introduction of competence approach, reduction of the share of classroom time, technologization of training, introduction of an effective contract for teachers, increase of the share of distance learning, and tightening of discipline. The study was conducted using the author’s methods. Of particular interest are the results of a pilot study of subjective attitude of university teachers to changes in modern higher school. The article assesses the impact of these changes in three directions: on content, effectiveness, and specifics of work. The empirical data obtained in the course of the study may be of interest to direct managers in the system of higher education (heads of departments or heads of educational programs), as well as for the administration of universities for development and implementation of personnel management programs in the educational organization.

There have been several longitudinal studies concerning the learners’ acceptance of e-learning systems using the higher educational institutes (HEIs) platforms. Nonetheless, little is known regarding the investigation of the determinants affecting the e-learning acceptance through social media applications in HEIs. In keeping with this, the present study attempts to understand the influence of social media practices (i.e., knowledge sharing, social media features, and motivation and uses) on students’ acceptance of e-learning systems by extending the technology acceptance model (TAM) with these determinants. A total of 410 graduate and undergraduate students enrolled at the British University in Dubai, UAE took part in the study by the medium of questionnaire surveys. The partial least squares-structural equation modeling (PLS-SEM) is employed to analyze the extended model. The empirical data analysis triggered out that social media practices including knowledge sharing, social media features, and motivation and uses have significant positive impacts on both perceived usefulness (PU) and perceived ease of use (PEOU). It is also imperative to report that the acceptance of e-learning systems is significantly influenced by both PU and PEOU. In summary, social media practices play an effective positive role in influencing the acceptance of e-learning systems by students.

Although social media usage in higher education has been frequently examined, little is known regarding the differences in students’ attitudes towards its use in the Omani higher education. Therefore, this study provides an opportunity to advance the understanding of these differences in attitudes by focusing on three different attributes, namely age, gender, and social media application. A total of 169 students enrolled at Sultan Qaboos University in Muscat, Oman took part in the study by the medium of an online survey. The empirical data analysis triggered out that there was a significant difference in attitudes with regard to age groups, in which students aged between 18 and 22 years old are much interested in using social media than the others. Nevertheless, the findings also showed that there was no significant difference in attitudes with respect to social media application and gender. More interesting, the outcomes pointed out that WhatsApp is the most frequent application used by students for educational purposes.

A tremendous amount of research indicated that KM factors have significant impacts on different technologies at the organizational level. What is not yet clear is the influence of these factors on technology adoption at the individual level. On the other hand, the understanding of students’ behavioral intention to use m-learning systems is still an ongoing research issue. Thus, the main theoretical contribution of this study is to investigate the impact of KM factors (i.e., acquisition, sharing, application, and protection) on m-learning adoption at the individual level, and to identify the importance and performance of each factor using the importance-performance map analysis (IPMA) technique through SmartPLS. A total of 319 IT undergraduate students enrolled at Al Buraimi University College in Oman took part in the study by the medium of online survey. In terms of importance, the empirical data analysis through IPMA exhibited that knowledge protection is the most important factor in determining the students’ behavioral intention to use m-learning. Concerning performance, the findings also triggered out that both knowledge sharing and knowledge protection perform well in determining the students’ behavioral intention to use m-learning.