The Last Mile Issue and Urban Logistics: Choosing Parcel Machines in the Context of the Ecological Attitudes of the Y Generation Consumers Purchasing Online

AbstractThe dynamic development of electronic commerce is affecting the manner of the organization of urban logistics. The last mile issue, that is the problem of the final stage of delivery of a parcel to a recipient, appears in full in urban areas. The problem of the last mile can be solved for the benefit of the environment through solutions called parcel machines.This paper aims to explore the relationship between environmental attitudes and behaviors of Generation Y and their propensity to make purchases over the internet and collect them using parcel machines.The study found that Generation Y respondents in Poland do not perceive parcel machines as an environmentally friendly method of delivery of products purchased online. On the other hand, young people would be willing to pay a bit more for an item if it were a form of an environment-saving measure. It is true that this correlation is not strong (r = 0.1785), but through a campaign dedicated to Generation Y (social media) environmental attitudes could be affected. There was no relationship between the amount of disposable income and the propensity among Millennials to use green solutions

F-LSTM: Federated learning-based LSTM framework for cryptocurrency price prediction

In this paper, a distributed machine-learning strategy, i.e., federated learning (FL), is used to enable the artificial intelligence (AI) model to be trained on dispersed data sources. The paper is specifically meant to forecast cryptocurrency prices, where a long short-term memory (LSTM)-based FL network is used. The proposed framework, i.e., F-LSTM utilizes FL, due to which different devices are trained on distributed databases that protect the user privacy. Sensitive data is protected by staying private and secure by sharing only model parameters (weights) with the central server. To assess the effectiveness of F-LSTM, we ran different empirical simulations. Our findings demonstrate that F-LSTM outperforms conventional approaches and machine learning techniques by achieving a loss minimal of $2.3 \times 10^{-4}$. Furthermore, the F-LSTM uses substantially less memory and roughly half the CPU compared to a solely centralized approach. In comparison to a centralized model, the F-LSTM requires significantly less time for training and computing. The use of both FL and LSTM networks is responsible for the higher performance of our suggested model (F-LSTM). In terms of data privacy and accuracy, F-LSTM addresses the shortcomings of conventional approaches and machine learning models, and it has the potential to transform the field of cryptocurrency price prediction

Distance Management of SMEs Using ICT Solutions

The paper contains a description of a research conducted in collaboration with some Erasmus for Young Entrepreneurs program Romanian students, concerning the use and implementation of ICT (Information and Telecommunication Technology), especially in distance managing Small and Medium Enterprises (SMEs). The paper is a response to the nature of contemporary business management, with the constantly increasing amount of work, bureaucracy and the necessity to travel on business combined with the need to manage the company being away. In the research the students assumed the roles of the employees and entrepreneurs simultaneously, to gain the perspective from both points of view – supervised by the authors. The aim was to find and test the effectiveness of the available ICT remote management instruments in the context of SMEs. The aim was to create a study of implementation in real-life conditions, considering the advantages and disadvantages of the solutions tested, including possible future trends. The result was a set of recommendations for business people. Apart from the educational value of the research, the unique, dual perspective assumed by the students participating in it, provided them with a practical insight and skills to better understand and make a better use of the conditions of managing and being managed. The results described here both practical and academic value. The resulting recommendations may constitute the basis of positive changes and improvement in the use of advanced technology in business activities. It is worth noting with its international character the study focuses not only on selected Polish enterprises, but the resulting contents reflects the situation in SMEs in the EU as well, thus it may be a starting point for analyzing other regions worldwide

IT SECURITY MANAGEMENT IN SMALL AND MEDIUM ENTERPRISES

The work concerns the problem of the management of security issues in Poland, especially in the perspective of Small and Medium Enterprises. The growth of Information and Telecommunication Technology has caused major impacts on business. Thus, serious security questions may be raised concerning small companies. Significant aspects of security issues are discussed, e.g. types of targets, types of attackers, legal issues and some recommendations for businessmen. The research is based on a review of works published in recent literature. The main method used in this inquiry was a case study. Additionally, the paper contains assumptions regarding further development of methods to secure information and communication systems. The results of the research reported here can be important both for business and academia. The recommendations may constitute the basis of improvement in the security area of activities supported by computers

BIG DATA IMPLEMENTATION IN SMALL AND MEDIUM ENTERPRISES IN INDIA AND POLAND

Today we are having a huge information explosion across the world. Earlier the amount of information was increasing arithmetically, but today, information has expanded in geometric series. The concept of big data has been around for years; most organizations now understand that if they capture all the data that streams into their businesses, they can apply analytics and get significant value from it. Big Data isn’t just for large enterprises with large budget. Today, small companies can have the benefits of the monumental amounts of digital data to make right and fast decisions to develop their enterprises. In fact, over the last couple of years, small and mid-size companies have seen more big date deployments than the big competitors. In India and Poland, the data boom isn’t just limited to big enterprises, the growth of big data startup/ technology vendors, is helping SMEs in scaling up infrastructure capabilities and driving insights from data. The increased availability of accessible, cheap data centres delivered by cloud vendors, has brought down the costs of upfront investment for small businesses, thereby reducing the market entry barrier. It is the question of choosing the right analytics vendors that fits the bill for small businesses. This paper aimed at designing a framework of Big Data implementation in SMEs. The reason for selecting these two countries is that there are international tie-ups between two universities of both countries

ML-Based Energy Consumption and Distribution Framework Analysis for EVs and Charging Stations in Smart Grid Environment

Electric vehicles (EVs) have become a prominent alternative to fossil fuel vehicles in the modern transportation industry due to their competitive benefits of carbon neutrality and environment friendliness. The tremendous adoption of EVs leads to a significant increase in demand for charging infrastructure. But, the scarcity of charging stations (CSs) concerns efficient and reliable EV charging. Existing studies discussed EV energy consumption prediction schemes at the CS without analyzing the affecting parameters such as energy demand, weather, day, etc. In this regard, we have proposed an energy consumption and distribution framework for EVs in a smart grid environment for efficient EV charging after analyzing the affecting parameters such as location, weekday, weekend, and user. Moreover, we have considered EV dataset to perform a detailed and deep analysis of energy consumption patterns based on the aforementioned parameters such as CS (Station ID) within the location (Location ID), weekday, weekend, and user (UserID). The main aim is to understand the smart grid-based electricity distribution to the CS by analyzing energy consumption patterns for reliable EV charging. We have done different analysis on different parameters and present their graphical representations