Information Systems Innovation for Business: Change, Growth and Future Impact

A special issue of Data (ISSN 2306-5729).

Deadline for manuscript submissions: closed (30 November 2023) | Viewed by 2792

Special Issue Editors


E-Mail Website
Guest Editor
1. Multidisciplinary Research Centre for Innovations in SMEs (MrciS), GISMA University of Applied Sciences, 14469 Potsdam, Germany
2. Department of Digital Innovation, GISMA University of Applied Sciences, 14469 Potsdam, Germany
Interests: software engineering; business model innovation; innovation management
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Computer Science Engineering, Jaypee Institute of Information Technology, Noida 201014, India
Interests: software engineering; distributed software engineering; search based software engineering; project management; innovation management and cloud computing
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor

E-Mail Website
Guest Editor
1. Software Consultants International Limited, Auburn, WA, USA
2. Software Project Management, EMSE Program, Universidad Politécnica de Madrid, 28040 Madrid, Spain
Interests: software project management
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor

Special Issue Information

Dear Colleagues,

This Special Issue disseminates the extended version of the accepted and presented papers in the “International Conference on Sustainability in Software Engineering & Business Information Management: Innovation & Applications (SSEBIM)”, Olten, Switzerland. This Special Issue also invites other researchers who could not take part in the conference to submit their research papers falling within the Special Issue scope. This Special Issue invites research articles, empirical studies, and short articles addressing the alignment of business strategies with sustainability and the resulting impacts.

This Special Issue accepts two types of submissions: a) Methods: the Methods section publishes research articles, review papers and technical notes on methods for collecting, processing (treating), managing, storing and analyzing scientific and scholarly data. Related source code, if available, can be deposited as supplementary material. b) Data Descriptors: the Data Descriptors section publishes descriptions of scientific and scholarly datasets (one dataset per paper). Described datasets need to be publicly deposited prior to publication, preferably under an open license, thus allowing others to re-use the dataset.

This Special Issue is oriented toward (but not limited to) the following topics:

  • sustainability in business model innovation;
  • innovative and sustainable business practices;
  • sustainability in business management;
  • disaster and crisis management for supporting sustainable business models;
  • sustainable supply chain management;
  • human values, ethics, and responsibility;
  • social businesses, sustainable innovation practices;
  • value proposition innovation;
  • value architecture innovation;
  • tools, approaches and impact assessment in sustainable business models;
  • business experimentation for sustainability across organizational contexts;
  • best practices and case studies of business experimentation for sustainability;
  • policy implications for business experimentation for sustainability;
  • sustainable operational solutions;
  • sustainable consumer service;
  • sustainability in business economics;
  • green marketing; spirituality.

Dr. Varun Gupta
Prof. Dr. Chetna Gupta
Dr. Leandro Ferreira Pereira
Dr. Lawrence Peters
Prof. Dr. Antonio Ferreras
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Data is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • sustainability
  • spirituality
  • green marketing
  • social businesses

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

24 pages, 3472 KiB  
Article
A Wavelet-Decomposed WD-ARMA-GARCH-EVT Model Approach to Comparing the Riskiness of the BitCoin and South African Rand Exchange Rates
by Thabani Ndlovu and Delson Chikobvu
Data 2023, 8(7), 122; https://doi.org/10.3390/data8070122 - 24 Jul 2023
Viewed by 1236
Abstract
In this paper, a hybrid of a Wavelet Decomposition–Generalised Auto-Regressive Conditional Heteroscedasticity–Extreme Value Theory (WD-ARMA-GARCH-EVT) model is applied to estimate the Value at Risk (VaR) of BitCoin (BTC/USD) and the South African Rand (ZAR/USD). The aim is to measure and compare the riskiness [...] Read more.
In this paper, a hybrid of a Wavelet Decomposition–Generalised Auto-Regressive Conditional Heteroscedasticity–Extreme Value Theory (WD-ARMA-GARCH-EVT) model is applied to estimate the Value at Risk (VaR) of BitCoin (BTC/USD) and the South African Rand (ZAR/USD). The aim is to measure and compare the riskiness of the two currencies. New and improved estimation techniques for VaR have been suggested in the last decade in the aftermath of the global financial crisis of 2008. This paper aims to provide an improved alternative to the already existing statistical tools in estimating a currency VaR empirically. Maximal Overlap Discrete Wavelet Transform (MODWT) and two mother wavelet filters on the returns series are considered in this paper, viz., the Haar and Daubechies (d4). The findings show that BitCoin/USD is riskier than ZAR/USD since it has a higher VaR per unit invested in each currency. At the 99% significance level, BitCoin/USD has average values of VaR of 2.71% and 4.98% for the WD-ARMA-GARCH-GPD and WD-ARMA-GARCH-GEVD models, respectively; and this is slightly higher than the respective 2.69% and 3.59% for the ZAR/USD. The average BitCoin/USD returns of 0.001990 are higher than ZAR/USD returns of −0.000125. These findings are consistent with the mean-variance portfolio theory, which suggests a higher yield for riskier assets. Based on the p-values of the Kupiec likelihood ratio test, the hybrid model adequacy is largely accepted, as p-values are greater than 0.05, except for the WD-ARMA-GARCH-GEVD models at a 99% significance level for both currencies. The findings are helpful to financial risk practitioners and forex traders in formulating their diversification and hedging strategies and ascertaining the risk-adjusted capital requirement to be set aside as a cushion in the event of the occurrence of an actual loss. Full article
Show Figures

Figure 1

Back to TopTop