Start-up Technology

The publication looks at the Internet of Things, the origins of this concept, and how it can be used in an enterprise. The use of IoT creates new types of business and improves the efficiency of an existing business. Thus, the use of IoT has an impact on the business model, in addition to the use of IoT, and how the use of IoT changes the architecture of information systems. The main focus of the publication is on the changes in the business model that are taking place through the digital transformation and the integration of Internet of Things solutions into the existing business solution. The study analyzes the existing scientific research in this field published in the IEEE database and, based on theoretical knowledge, analyzes the problem situations and opportunities that arise in the implementation of the Internet of things in enterprise. Solutions, where the internet of things has been used in wind farm establishment and monitoring systems how this application has changed the enterprise environment, are analyzed. The publication analyzes the main problem situations in the development of wind farm management system and the involvement of condition-based maintenance (CBM) in business processes, discusses the issue of data standardization in wind farm management based on the current level of standardization and provides proposals for further standardization of wind farm monitoring data traffic to improve management efficiency, thereby improving business performance. The publication provides readers with an overview of the internet of things and its applications to the business environment, focusing on wind turbine monitoring and provides suggestions for future directions to streamline the analysis algorithm of the machine learning process by improving the data collection phase.

The information technology models improving security functioning of crowdfunding platforms and advice on a new type of business were developed. The article solves the problem of safety of crowdfunding platform functioning based on developed models: rating assignment system of unified assessment crowdfunding platforms; startup projects assessment; startup projects risk assessment concerning their financing safety level and criminal law protection of investors against the financial fraud. The models are based on the correct usage of fuzzy logic and fuzzy set device to reveal the uncertainty of experts’ consideration that insures authenticity of scientific results.

\n Com o avanço da internet, novos tipos de negócios surgiram. Por exemplo, o sistema de anúncios online: produtores de sites e diversos outros conteúdos podem dedicar em uma parte qualquer de sua página um espaço para a impressão de anúncios de diversas lojas em troca de um valor oferecido pelo anunciante. É neste contexto que este trabalho se insere. O objetivo principal é o desenvolvimento de algoritmos que preveem a probabilidade que um dado usuário tem de se interessar e clicar em um anúncio a que está sendo exposto. Este problema é conhecido como predição de CTR (do inglês, \\"Click-Through Rate\\") ou taxa de conversão. Utiliza-se para isto uma abordagem baseada em regressão logística integrada a técnicas de fatoração de matriz que preveem, através da obtenção de fatores latentes do problema, a probabilidade de conversão para um anúncio impresso em dado site. Além disto, testes considerando uma estratégia dinâmica (em função do tempo) são apresentados indicando que o desempenho previamente obtido pode melhorar ainda mais. De acordo com o conhecimento do autor, esta é a primeira vez que este procedimento é relatado na literatura.\n

The paper presents the characteristics of rural areas as complex natural and economic systems that perform important functions for the state. The article shows the role and influence of agrarian reforms on the state of agriculture, which is the basis for development rural areas, and, as a consequence, on the state of the social infrastructure of the village are shown. The importance of problems’ solution of rural areas’ achievement on the trajectory of sustainable development is confirmed both by the state policy implemented in the Russian Federation and by a significant number of scientific research in this area. The article contains a number of statistical data, on the basis of which the authors made conclusions about the presence of a whole complex of problems that not only were not solved despite the measures taken, but also are aggravated in a number of cases, what significantly reduces the level of quality of life in the countryside, including Volgograd region. The article examines the main factors under the influence of which the provision of rural areas of the region with labor resources is influenced. They are “aging” of labor resources, decrease in the number of economically active population, essence of modern migration fr om rural areas to cities wh ere the largest part has student youth. The paper mentions integrated the need for the development of the agricultural sector of Volgograd region, other new types of businesses, non-agricultural sector of rural areas for welfare growth of the population, reduce social tension. It seems important to resolve the issue of conditions’ creation which can be necessary for the attraction of young specialists to the countryside.

We consider the emerging trade in big data through commercial transactions. Through a wide ranging systematic literature review that covers both academic and practitioner perspectives, we first demonstrate that there is increasing interest in big data commercialization, which mostly consists of exploratory theoretical development and managerial prescriptions to date. We outline the new types of businesses that seek to create and appropriate value, including the data supplier, data manager, data custodian, data aggregator, application developer and service provider. Building upon this typology, we discuss the processes of business model emergence, and the importance of data ecosystems, reviewing both ecosystem structure and dynamics. We also highlight the challenges for the trade in big data, including IP protection, regulatory complexity, pricing, the development of data agreements and privacy concerns. We conclude with an outline for future research.

New Types of Business in Local Fisheries and Coastal Communities

Bridge financing during covid-19 pandemics: Nexus of FDI, external borrowing and fiscal policy

For the two last decades, people have tried to provide practical electronic cash schemes, with more or less success. Indeed, the most secure ones generally suffer from inefficiency, largely due to the use of restrictive blind signatures, on the other hand efficient schemes often suffer from serious security drawbacks. In this paper, we propose both a new tool providing scalable anonymity at a low cost, and a new Internet business: Anonymity Providers.Those Anonymity Providers certify re-encrypted data after having been convinced of the validity of the content, but without knowing anything about this latter. It is a very useful third party in many applications (e.g. for revocable anonymous electronic cash, where a coin would be a certified encryption of the user's identity, such that a Revocation Center, and only it, can recover this identity, if needed).With this new tool, each user can get the required anonymity level. depending on the available time, computation and/or money amounts. Furthermore, the Anonymity Provider may be a new type of business over the Internet, profitable for everybody: - from the provider point of view as he can charge the service; - from the user point of view as he can obtain a high level of anonymity at low computational cost. Moreover, a user who does not require anonymity has no extra computation to perform.This technique is quite efficient because of its optimistic orientation: in case of honest use, everything is very efficient. Some slightly more heavy processes have to be performed in case of fraud detection, but with overwhelming tracing success.

The present article aims to establish the current situation in relation to the knowledge of Spiritual Intelligence capacities and the practice needed to develop them by the people in charge to implement these practices on the Catalan organizations. The author develops the features and characteristics of Spiritual Intelligence that can be most useful in a corporation environment, those that can affect the implementation of a new type of business, fairer, more environmentally conscious and whose values are closer to citizen ethics. There is strong pressure from today’s society for organizations to assume a series of values that range from the social to the environmental and from the ethical to the fair, which are intimately related to Spiritual Intelligence.

ABSTRACTThe complexity of the business world has led to growing demands being made of companies regarding the information provided on their financial performance, corporate governance and contribution to developing sustainability. In response, some leading companies have begun to publish integrated reporting, in the form of a document providing a coherent summary of this information, thus facilitating stakeholder engagement.This paper examines the validity of the hypotheses of the theories of agency and of signalling, and analyses the political costs and those borne by owners in voluntarily developing this new type of business document. More specifically, in order to determine their prevalence among the suggested reasons for these paradigms, we analyse the effect of industry concentration, together with other factors, in the development of integrated reporting.The analysis of a non‐balanced sample of 1590 international companies for the years 2008–2010, in which a logistic regression methodology is applied to panel data, reveals the negative impact of industry concentration on the development of a more pluralist report, simultaneously taking into account stakeholders, sustainability and the long‐term viewpoint, as well as questions of responsible investment, business ethics and transparency. Copyright © 2012 John Wiley & Sons, Ltd and ERP Environment

The aim of the chapter is to present the genesis of 2 related phenomena: the sustainability and sustainable development concept, as well as the range of definitions in order to suggest a definition that can be applied in the whole e-book. The other objective is to present the Corporate Social Responsibility concept which, nowadays, is recognised as the process through which business contributes to sustainable development implementation. It was highlighted, however, that in the current situation, sustainable development may be achieved by new types of businesses built on the principles of saving resources (by recycling or reuse). For traditional businesses, based on non-renewable resources, CSR leading to sustainable development is a real challenge as it requires re-shaping business models.

Everyone can increase their income with various businesses, one of which is by opening a business, there are various types of businesses involved. Especially now that he is opening a business by utilizing technology and creativity, which is now known as a startup. Since 2015, the startup business has been introduced and has been growing since the pandemic hit the world in 2019. Startup businesses are increasingly mushrooming in Indonesia, supported by the government program “The National 1000 Startup Digital Movement”. So that the development of startups in Indonesia by Mr. Bonifasius Wahyu currently occupies the fifth position in the world with the largest number of startups in the world at 2,229 startups in April 2021. In running a startup business, it is very important to pay attention to external and internal factors, but in this study to analyze internal factors consisting of marketing, finance, human personal and operational communication. With a sample of 75 startup companies using a purposive sampling technique and processed with SPSS, by performing multiple regression analysis. The results show that internal factors, namely marketing communications, finance, human resources and operational activities, have a positive and significant impact on startup business performance, with a contribution of 0.871 or 87.1%. The variables that most influence the performance of startup companies are marketing communications, followed by human relationship, financial and operational.

Startup companies are a huge driving force for economic development, and the success of these high-risk companies can bring huge returns to venture capital companies. The ability to predict the success of startups is a great advantage for investors to overtake their competitors. With the development of information technology, highly reliable results can be obtained by using complex machine learning algorithms or data mining. Data were acquired from the world's largest structured database for startup companies. These data included nearly 40 characteristics of almost 22,000 companies. The main purpose of this research is to establish a model to classify start-ups and analyze the important features for the success of startup companies. Random Forest and Support Vector Machine were used to explore the important features that determine the success of startup companies and explain some of the features. It also compared the effects of different machine learning methods, illustrating the effectiveness of machine learning methods for investors to predict the success of startups. These analyses will provide investors and venture capital companies with effective methods, reduce their large manpower input for prediction, and improve the efficiency of their analysis of startup companies.

Urban rail transit features much strength, such as large capacity, safety and environment-friendliness, and it becomes a preferred choice for most passengers. It also plays a prominent part in solving urban traffic problems. In order to improve the operation efficiency of the urban rail transit system and achieve the goal of smart operations, this paper applies machine learning algorithms and completes the feature engineering of urban rail transit passenger flow data in terms of time, space and external factors. Based on passenger flow characteristics as collected, we build the short-term passenger flow forecast models, which include light gradient boosting machine (LightGBM) model, long short-term memory (LSTM) model, and LightGBM-LSTM fusion model. Besides, we construct the autoregressive integrated moving average (ARIMA) model and extreme gradient boosting (XGBoost) model for experiment comparison. Finally, we conduct the passenger flow forecasting experiments on the Hangzhou subway dataset based on the five prediction-models mentioned above. Then, five types of subway stations are selected (residential type, occupation type, residential-occupation type, business type, and transportation hubs type) and three accuracy evaluation indicators are chosen (mean absolute error, root mean square error and mean absolute percentage error) to evaluate the prediction accuracy of the five prediction models. The experimental results show that, the multi-feature machine learning model can effectively forecast urban rail transit short-term passenger flow which is difficult for the traditional time series model. However, the single model has poor adaptability to different types of subway stations. Compared with a single model, LightGBM-LSTM model equipped with merits of multiple models, fulfills a better function in forecasting and a better adaptability to different types of urban rail transit stations.

While these current and potential entrepreneurs face numerous hurdles, the evidence clearly shows that the difficulties of financial intermediation for small and medium-sized enterprises are both significant and costly. Overcoming this barrier represents both a major profit opportunity for lenders and a major development opportunity for society at large, including of course entrepreneurs themselves. New tools that allow for screening and risk evaluation for small and medium-sized enterprises with low transaction costs and without depending on pre-existing information like borrowing history or business plans could represent a breakthrough in solving this problem. We have proposed one such tool, the use of psychometric tests, and evaluated its potential both conceptually, based on past studies, and based on a newly collected international dataset. The results show that there are some psychometric dimensions that have statistically and economically significant relationships with business profitability, which is of significant interest to investors, entrepreneurs, and capacity builders, and also that have significant relationships with default risk, which is of significant interest to lenders. Some of them are found to hold with surprising stability across a wide variety of countries, cultures, and business types. These questions could provide the boost to predictive power needed to bring millions of striving small business owners into the formal financial system and give them the capital they need to grow their businesses, if they can be successfully leveraged for credit screening. The Entrepreneurial Finance Lab (or EFL for short) is a company set up to work with banks to deploy this technology and realize this potential. Since 2010, the company has been implementing a credit-screening tool including psychometric content similar to that reviewed above, and modeled using the Bayesian hierarchical methodology.KeywordsBank LoanDefault RiskWoman EntrepreneurFemale EntrepreneurSmall Business OwnerThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.