Browse

You are looking at 1 - 10 of 607 items for :

  • Mathematics and Statistics for Economists x
Clear All
Open access

Filip Grudzewski, Marcin Awdziej, Grzegorz Mazurek and Katarzyna Piotrowska

Abstract

VR technology is an emerging IT innovation that greatly affects consumer behaviour and consumer perception of products. The aim of this study is to examine how the virtual reality phenomenon can be used as a marketing communication tool and how its usage affects the reception of individual components of a marketing message. The research conducted examined the possible impact of virtual reality on message perception and attitude towards particular offers. Additionally the authors wanted to find out whether there was a relationship between the use of virtual reality and the acceptance of new technologies in marketing communication. To verify the stated hypotheses empirical research was conducted involving an experiment with 150 observations of respondents taking advantage of three different marketing communication tools including: VR presentation with Oculus Rift hardware, video and printed advertisements. The results obtained reveal that VR technology positively and significantly impacts the reception of the offer, the technology involved and the presentation itself.

Open access

Naeem Ahmed and Mudassira Sarfraz

Abstract.

This study examines the stock market volatility of German bench-mark stock index DAX 30 using logarithmic extreme day return. German stock markets have been analyzed extensively in literature. We look into volatility issue from the standpoint of extreme-day changes. Our analysis indicates the non-normality of German stock market and higher probability of negative trading days. We measure the occurrences of extreme-day returns and their significance in measuring annual volatility. Our time series analysis indicates that the occurrences of extreme-days show a cyclical trend over the sample time period. Our comparison of negative and positive extreme-days indicates that negative extreme-days overweigh the positive extreme days. Standard deviation, as measure of volatility used traditionally, gives altered ranks of annual volatility to a considerable extent as compared to extreme-day returns. Lastly, existence of extreme day returns can be explained by past period occurrences, which show predictability.

Open access

Edyta Rudawska, Ewa Frąckiewicz and Małgorzata Wiścicka-Fernando

Abstract

The aim of the paper is to assess the attitudes of company managers in the food and drink sector in Western Europe and Central-Eastern Europe towards implementing marketing strategies that take into account not only economic, but social and ecological aspects as well. Innovation is a growing topic among scholars when discussing issues related to the enhancement of company performance and competitiveness. Such innovation may refer to technological changes (new products, processes), as well as non-technological ones referring to various marketing and organizational methods. In the paper the authors focus on innovations in marketing activities arising from the application of a more socio-ecological orientation. The paper comprises two parts: one theoretical, one empirical. In the first part the role of innovation in the process of creating company competitiveness is presented, as well as the concept of an innovative marketing strategy. In the second part the results of international research are discussed.

Open access

Gencer Erdogan, Atle Refsdal, Bjørn Nygård, Ole Petter Rosland and Bernt Kvam Randeberg

Abstract

Background: During major maintenance projects on offshore installations, flotels are often used to accommodate the personnel. A gangway connects the flotel to the installation. If the offshore conditions are unfavorable, the responsible operatives need to decide whether to lift (disconnect) the gangway from the installation. If this is not done, there is a risk that an uncontrolled autolift (disconnection) occurs, causing harm to personnel and equipment. Objectives: We present a decision support model, developed using the DEXi tool for multi-criteria decision making, which produces advice on whether to disconnect/connect the gangway from/to the installation. Moreover, we report on our development method and experiences from the process, including the efforts invested. An evaluation of the resulting model is also offered, primarily based on feedback from a small group of offshore operatives and domain experts representing the end user target group. Methods/Approach: The decision support model was developed systematically in four steps: establish context, develop the model, tune the model, and collect feedback on the model. Results: The results indicate that the decision support model provides advice that corresponds with expert expectations, captures all aspects that are important for the assessment, is comprehensible to domain experts, and that the expected benefit justifies the effort for developing the model. Conclusions: We find the results promising, and believe that the approach can be fruitful in a wider range of risk-based decision support scenarios. Moreover, this paper can help other decision support developers decide whether a similar approach can suit them

Open access

Mohammad Ashraf and Bilal Ahmad Wani

Abstract

The purpose of this paper is to investigate identities with Jordan *-derivations in semiprime *-rings. Let ℛ be a 2-torsion free semiprime *-ring. In this paper it has been shown that, if admits an additive mapping D : ℛ→ℛsatisfying either D(xyx) = D(xy)x*+ xyD(x) for all x,y, or D(xyx) = D(x)y*x*+ xD(yx) for all pairs x, y, then D is a *-derivation. Moreover this result makes it possible to prove that if satis es 2D(xn) = D(xn− 1)x* + xn− 1 D(x) + D(x)(x*)n− 1 + xD(xn− 1) for all x and some xed integer n ≥ 2, then D is a Jordan *-derivation under some torsion restrictions. Finally, we apply these purely ring theoretic results to standard operator algebras 𝒜(). In particular, we prove that if be a real or complex Hilbert space, with dim() > 1, admitting a linear mapping D : 𝒜() → ℬ() (where () stands for the bounded linear operators) such that

2D(An)=D(An1)A*+An1D(A)+D(A)(A*)n1+AD(An1)

for all A𝒜(). Then D is of the form D(A) = AB−BA* for all A𝒜() and some fixed B(), which means that D is Jordan *-derivation.

Open access

Marko Bohanec, Mirjana Kljajić Borštnar and Marko Robnik-Šikonja

Abstract

Background: In practical use of machine learning models, users may add new features to an existing classification model, reflecting their (changed) empirical understanding of a field. New features potentially increase classification accuracy of the model or improve its interpretability. Objectives: We have introduced a guideline for determination of the sample size needed to reliably estimate the impact of a new feature. Methods/Approach: Our approach is based on the feature evaluation measure ReliefF and the bootstrap-based estimation of confidence intervals for feature ranks. Results: We test our approach using real world qualitative business-tobusiness sales forecasting data and two UCI data sets, one with missing values. The results show that new features with a high or a low rank can be detected using a relatively small number of instances, but features ranked near the border of useful features need larger samples to determine their impact. Conclusions: A combination of the feature evaluation measure ReliefF and the bootstrap-based estimation of confidence intervals can be used to reliably estimate the impact of a new feature in a given problem

Open access

Josip Arnerić, Tea Poklepović and Juin Wen Teai

Abstract

Background: Since high-frequency data have become available, an unbiased volatility estimator, i.e. realized variance (RV) can be computed. Commonly used models for RV forecasting suffer from strong persistence with a high sensitivity to the returns distribution assumption and they use only daily returns. Objectives: The main objective is measurement and forecasting of RV. Two approaches are compared: Heterogeneous AutoRegressive model (HAR-RV) and Feedforward Neural Networks (FNNs). Even though HAR-RV-type models describe RV stylized facts very well, they ignore its nonlinear behaviour. Therefore, FNN-HAR-type models are developed. Methods/Approach: Firstly, an optimal sampling frequency with application to the DAX index is chosen. Secondly, in and out of sample predictions within HAR models and FNNs are compared using RMSE, AIC, the Wald test and the DM test. Weights of FNN-HAR-type models are estimated using the BP algorithm. Results: The optimal sampling frequency of RV is 10 minutes. Within HAR-type models, HAR-RV-J has better, but not significant, forecasting performances, while FNN-HAR-J and FNNLHAR- J have significantly better predictive accuracy in comparison to the FNN-HAR model. Conclusions: Compared to the traditional ones, FNN-HAR-type models are better in capturing nonlinear behaviour of RV. FNN-HAR-type models have better accuracy compared to traditional HAR-type models, but only on the sample data, whereas their out-of-sample predictive accuracy is approximately equal.

Open access

Suleyman Mete, Zeynel Abidin Cil and Eren Özceylan

Abstract

Background: Bike-sharing programmes have become popular in a large number of cities in order to facilitate bicycle use. Determining the location of bike sharing stations is vital to success of these programmes. Objectives: In this paper, a case study is applied to the Gaziantep University campus in order to find possible locations of the stations for users (students). The purpose is to minimize the total walking distance. Methods/Approach: Set and maximal covering mathematical models are considered to decide on coverage capability of determined 20 demand points and 20 potential bike stations. Then, the mathematical models of P-center and P-median are used to build possible stations and to allocate demand points to the opened stations. Finally, an undesirable facility location model is used to find the bike stations, which have the maximum distance from demand nodes, and to eliminate them. Results: In computational results, it is clearly seen that the proposed approaches set the potential bike station covering all demand points. They also provide different solutions for the campus planners. Conclusions: The methodology outlined in this study can provide university administrators with a useful insight into locations of stations, and in this way, it contributes significantly to future planning of bike-sharing systems.

Open access

Joseph Menaker and Velga Ozoliņa

Abstract

The paper covers analysis of high-tech industry development in Latvia, as well as its facilitating and restricting factors. High-tech industries become more important in Latvia both in terms of export share and generated value added; also the number of enterprises and employees is increasing. A stable political system, enabling business environment, a relatively low corporate income tax rate, and government aid are considered as some of the most important facilitating factors. The paper emphasizes the government’s role in promoting and developing the high-tech manufacturing. The most significant limitations are the lack of skilled specialists and sophisticated real estate space, and the remote industrial supply companies and the service centres. Recommendations are given on the possible development directions, including improvements in manufacturing infrastructure, enhancements of the skill level of the labour force, and bringing up a new generation of entrepreneurs.

Open access

Andrea Insch