Call for papers - Special Issue (PDF Flyer)

Machine learning and deep learning for time series analysis


Assoc. prof. Petr Doležel, University of Pardubice, Czech Republic

Background and motivation:

Time series analysis have been an object of interest in various fields, such as engineering, economics, medicine, or humanities. Conventional methods for time series manipulation are summarized in Hamilton (1994). Moreover, traditional machine learning-based methods for time series analysis can be found in Tang et a. (2022).

Most studies using machine and deep learning to analyze time series focus on modelling and prediction. As an example, authors in Adusei et al. (2022) dealt with modelling of municipal waste disposal behaviors in relation to meteorological seasons using recurrent neural networks, and Bhoj et al. (2022) proposed an architecture for a robust hybrid deep learning model which can be used for the granularity of data to make accurate predictions of energy consumption of homes.

Nevertheless, classification and anomaly detection are also not uncommon for use in time series analysis. Chen et al. (2021) introduced the combination of a multi-scale neural network and an attention mechanism for time series classification. Moreover, the team of Julien Audibert reflect on the benefits of deep networks for anomaly detection (2022).

As a summary, the field of machine learning and deep Learning has attracted a lot of interest in the past few years. A comprehensive survey of the entire record of improvements that led the topic to its current state-of-the-art can be found in Schmidhuber (2015). A higher attention on the novelties from the last years is provided in Lin et al. (2022). In this special issue, we proceed to improve the potential of machine learning and deep learning models in time series analysis, with a focus on applications such as sales forecasting, inventory analysis, stock market analysis, price estimation, feature extraction, and decision support.

Topics of interest in this special issue include (but are not limited to) the following methods and tools.

  • Preprocessing or fusion of time series data
  • Mapping, monitoring, and characterization of dynamical systems with time series
  • Machine learning and deep learning models for time series analysis and time series processing
  • Feature extraction from big datasets
  • Probabilistic forecasting using deep learning, temporal fusion transformers, explainable time-series forecasting

Positively reviewed papers in special issue will get 50% discount from APC.

Important dates:

Deadline for submissions: June 15, 2023

Review process: on a rolling basis from February 2023 to June 2023

Submission guidelines:

Kindly submit your paper to the Special Issue SI: Machine learning and deep learning for time series analysis through the online submission system of SciPap. All submissions should follow the general author guidelines of SciPap.

Call for papers - Special Issue

Towards a Business Model Innovation for a Circular Economy


Prof. Petr Hajek, University of Pardubice, Czech Republic

Assoc. Prof. Viktor Prokop, University of Pardubice, Czech Republic

Background and motivation:

In response to recent changes in business innovation strategies, interest in Business Model Innovation (BMI) has increased dramatically. Specifically, two complementary roles for business models in strengthening innovations have been identified, namely their crucial role in commercializing innovations and their source of future value as well as a powerful competitive tool. In addition, BMI has an important role in achieving more resource effective economic ecosystems. Indeed, synergies between BMI and circular economy are currently explored in newly defined integrated frameworks. This special issue aims to establish conceptual models, investigate new business model concepts for circular economy, and explore the potential for empirical contributions.

Important dates:

Deadline for submissions: September 15, 2022

Review process: on a rolling basis from March 2022 to October 2022

Submission guidelines:

Kindly submit your paper to the Special Issue SI: Towards a Business Model Innovation for a Circular Economy through the online submission system of SciPap. All submissions should follow the general author guidelines of SciPap.

Call for papers (PDF Flyer)

Public Policies and Responses of Various Policy Actors during the COVID-19 Pandemic in 2020:

Experience and preliminary lessons from the Czech Republic and Slovakia

Guest editors:

Daniel Klimovský (corresponding guest editor)
Affiliation: Comenius University in Bratislava, Slovakia / University of Pardubice, Czech Republic
Research/teaching focus: public administration, policy design, local government

Juraj Nemec (guest editor)
Affiliation: Masaryk University in Brno, Czech Republic / University of Matej Bel in Banská Bystrica, Slovakia
Research/teaching focus: public finance, public management

Geert Bouckaert (guest editor)
Affiliation: Public Governance Institute, KU Leuven, Belgium
Research/teaching focus: performance management, public sector reform, financial cycles, public management, policy design


Word count:

8,000 max. (incl. references)


  • 10 January 2021: submission of abstracts, working titles and keywords to the corresponding guest editor (This email address is being protected from spambots. You need JavaScript enabled to view it.)
  • 30 January 2021: submission of full papers (for internal review by the guest editors of the special issue)
  • 10 February 2021: final decisions of the guest editors (the positively evaluated papers will be submitted further to the SciPap for double blind review)
  • 25 February 2021: results of the 1st round review
  • 5 March 2021: revision according to the requirements and/or recommendations of the 1st round review, and re-submission
  • 15 March 2021: results of the 2nd round review
  • 31 March 2021: finalization
  • 15 April 2021: online publication

 Context and expected contents:

This call is issued in the context of enormous public policy challenges raised by the COVID-19 pandemic. In general, the pandemic offers a unique natural experiment in comparative public policy and public administration. Both the Czech Republic and Slovakia were really successful in managing the spread of COVID-19 during the first phase of the pandemic   in spring 2020, but at the cost of heavy burden on their national economics and by the questionable restrictions of some human rights. However, both countries totally failed to prevent the expected second phase of the COVID-19 pandemic. For instance, some relevant data from September and October 2020 showed that the countries lost their positions of leaders in fighting against the pandemic and they dropped down in international rankings among the worst cases worldwide. While the Government of the Czech  Republic  implemented  a  hard  nationwide  lockdown,  the  Slovak  Government  decided to combine a soft lockdown with a blanket testing of its entire population. In the late October, Slovakia became the first EU country to attempt a similar feat. Obviously, the eyes of many epidemiologists and medical scientists were focused on these small EU countries thanks to these measures. However, their policy design, implementation as well as effects were carefully observed by various social scientists, too.

The already existing knowledge as well as experience opens many different directions for academic research. The crisis evoked by the pandemic  has  enhanced,  for  example,  the  visibility  of  public  value, a concept  now  representing a superordinate goal uniting all sectors. It has also tested policy-making and administrative capacities of all governments. Obviously, some policies were affected more than the others but proper research is needed in all cases. A positive and/or negative role of traditional media and social media in preventing the infection spread is another interesting question that needs to be reflected by relevant research. There is much to learn about public private interface, public service management and service delivery. Last but not least all these phenomena have already had significant impacts on public budgeting at all levels, because high level of uncertainty leads always to some difficulties in planning and strategic decision making.

This special issue is focused on experience of the Czech Republic and Slovakia. Both countries have at least partly followed neoliberal ideology when solving critical impacts of the pandemic crisis on their business sectors. Resilient services should be built by allowing for innovation, transformation and enrichment of processes and human activities. However, are these countries working on public service resilience during the COVID-19 era? And what resilience could be expected towards allocation and distribution of public resources? We call for diverse scholarly contributions. We encourage especially empirical contributions on different aspects of the COVID-19 pandemic in the Czech Republic and Slovakia with special regard to various public policies and related budgeting challenges as well as other social, political and economic issues. For example, the following issues can be covered:

  • What have we learned from the first phase and/or the second phase of the COVID-19 from perspective of public policy, public management and public administration?
  • To what extent made the effects of the COVID-19 pandemic strategic decision making more difficult? To what extent and in what ways did it influence public budgeting at all levels?
  • How did governments at various levels manage to adopt various measures while fighting against

the COVID-19 spread? What are the limitations and/or requirements of political and administrative leadership in the face of scientific evidence about the COVID-19 pandemic?

  • What shifts in powers could be related to blame avoidance or credit claiming strategies between various levels of government and how did it influence vertical/horizontal intergovernmental relations?
  • How public policies and public services responded to the crisis? What impact could the pandemic have for the future design of public services?
  • What alternative ways of public service delivery (co-production, out-sourcing, ) were used by the governments during the COVID-19 pandemic?
  • What innovation solutions did we experience in the field of public service delivery through digital infrastructure and digital inclusion?
  • What are the short-term effects (and possible long-term effects) of the policy measures taken during the COVID-19 pandemic on equity and quality of
  • Is it possible to identify some similarities if we compare the effects of the COVID-19 pandemic

with the recent global financial crisis? What kind of similarities should be taken into account by relevant decision makers at different political levels?

Call for Chapters (PDF Flyer)

Book Title: Circular Economy oriented Business Model Innovations: A European Perspective


Viktor Prokop (University of Pardubice, Czech Republic); editor-in-chief

Jan Stejskal (University of Pardubice, Czech Republic); corresponding editor

Jens Horbach (University of Applied Sciences Augsburg, Germany); editor

Wolfgang Gerstlberger (Tallinn University of Technology, Estonia); editor


In recent years, interest in Business Model Innovation (BMI) has increased dramatically (Velter et al., 2020). This expanding interest has led to wide, fragmented, and confused research across various fields, including the innovation management, strategic management, and entrepreneurship literature (Yang et al., 2020). The general definition of a company’s business model (BM) defines it as system of interconnected and interdependent activities that determines the way the company ‘does businesses with its customers, partners, and vendors (Amis & Zott, 2012). Recently, BMI has received increasing attention in specific areas (e.g. the circular economy, sustainability, servitization, digitization, and social innovation). Due to the importance of these concepts in their individual investigation fields, different ‘sub-streams’ have emerged (Pieroni et al., 2019). 

The sustainability-oriented BMI sub-stream has evolved significantly over the past decade and incorporates sustainability principles as guidelines for BM design, adding complexity to the conventional BMI process. On top of generating superior customer value to achieve competitive advantage and capture economic value, it also seeks to contribute positively to society and the environment. On the other hand, currently, the newest concept for the pursuit of global sustainability is a circular economy (CE) strategy, while the most important benefit of a more CE-based approach is the possibility of retaining the added value in products for as long as possible, extracting their maximum value and eliminating waste (Smol et al., 2017). Research on CE-oriented BMI is even more recent than that on sustainability-oriented BMI but has grown rapidly in the last five years (e.g. Diaz Lopez et al., 2019; Pieroni et al., 2019; Konietzko et al., 2020). In general, in a circular economy, the linear flow of ‘resources – products – waste’, typical of the traditional business models of companies, is replaced by the pattern ‘resources – products – waste – renewable resources’ (Urbinati et al., 2017). Moreover, as a response to the increasing pressure on natural resources, CE aims to create multiple types of value, with the ultimate goal of achieving a more resource-effective and efficient economic system. CE-oriented BMI incorporates principles or practices from CE as guidelines for BM design. It aims to boost resource efficiency and effectiveness (by narrowing or slowing energy and resource loops) and ultimately close energy and resource flows by changing approaches to economic value and the interpretation of products.

Cross-agent cooperation and partnerships have gained an important role in the innovation process at the firm and country level, while universities, industries, governments, and civil society are becoming the engines and core players (agents) of these processes. Cooperation at the University–Industry level allows knowledge flows through multiple channels. It comprises, for example, the exchange of codified academic research results in the form of publications, licensing and patents, or improvements in the quality of research and teaching through learning in the context of application (Franco & Haase, 2015). On the other hand, governments tend to promote research environments (ecosystems) conducive to cooperation between academic researchers and private companies and attempt to push academic researchers toward research and related interactions with industry and society (Boardman, 2009; Oskam et al., 2020). Meanwhile, sustainability has become critical in recent years due to global concern about the impact of business on resources, the environment, and society; the quadruple-helix theory further introduces the roles of civil society, media, and the culture-based public (Yun & Liu, 2019).

Innovation ecosystems (IE) gained importance, especially in the last ten years, because they differ from other earlier concepts and approaches (e.g., national and regional innovation systems, innovation clusters, and innovation milieus). IE are more explicitly systemic, show a greater appreciation of the connections among the many innovation actors (cross-agent cooperation), recognize the role of information and communication technologies, emphasise the differentiated roles (or niches) occupied by organizations and industries, and analyse the importance of market forces relative to government (Oh et al., 2016). The IE concept deals with a new role for public authorities, brings new understanding of firms´ performance, and requires a change in how the strategy and the innovation literatures have traditionally linked industry dynamics to firm performance. 

However, nowadays, we can see crucial differences between countries (Pinho, 2017) and in their innovative ecosystems (e.g. degree of preparedness, networking, availability of infrastructure, functioning public administration, available funding opportunities, trust among stakeholders, and other components of civil society) that create challenges for future research. Similarly, we can see a crucial difference between firms and their BMI. The dynamic process of BMI can have different intensities, related to the degree of novelty introduced (i.e. ‘new to the firm’ or ‘new to the industry’) and the scope of changes (i.e. individual components or systemic/architectural structure). Moreover, different triggers (internal or external), such as changes in the competitive environment or legislation, can stimulate BM changes (Pieroni et al., 2019). Therefore, there is a need to identify the different practices in innovation environments (ecosystems) of National Innovation Systems with distinctive graduation levels, e.g. advanced (innovation leaders) vs. in development (modest innovators). Most of these differences directly affect the degree of cross-agent interaction within innovation ecosystems and between them and outsiders (e.g. foreign firms, universities, etc.), the diversity of actors, and the relationship rules, which are key elements of these systems (Mathieu & Delai, 2019). Consequently, there is a need to identify existing and effective CE-oriented business models and, based on them, to design a suitable BMI for firms from Central and Eastern European (CEE) countries as well as Inclusiveness Target countries (ITC) that are lagging behind Western European countries, specifically in cases of innovation performance and competitiveness (see below). It is also necessary to identify the roles of governments and universities in these processes and to allow the emergence of equal opportunities for men, women, and young research generations.

From a methodological side of view, the book is open for CE-oriented conceptual papers, case studies or econometric analyses.

As we can see, there are growing challenges in dealing with Business Models Innovations and Innovation Ecosystems, within EU countries, and especially in the growing era of the circular economy that has gained greater attention from governments, industry, and academia (the triple-helix entities). These issues are becoming fundamental to sustaining societies’, firms’, and countries' innovation and sustainable competitive advantage.

Important Dates

January 31, 2021: Book Chapter Proposal

February 28, 2021: Accept/Reject Notification

November 30, 2021: Full Chapter Submission

January 31, 2022: Accept/Reject Notification

March 31, 2022: Submission of the final paper

October 31, 2022: Final Print Version Available

Submission Procedure

Chapter proposal submissions are invited from researchers and practitioners on or before January 31, 2021. Proposals should be limited to between 1000-2000 words, explaining the mission and concerns of the chapter and how it fits into the general theme of the book. Only electronic submissions in MS Word format will be considered. Please send your proposal via email to corresponding editor (This email address is being protected from spambots. You need JavaScript enabled to view it.). Your submission must be made on or before the due date specified. Submissions will be reviewed in a single-blind manner. Notifications regarding the status of the chapter proposal will be made available to authors by February 28, 2021.