Scientific projects at the PUEB

Domestic and regional differences in the level and dynamics of development have been subject to extensive
research within economics and economic geography. The SARS-CoV-2 pandemic will significantly impact
these differences, leading to multi-faceted economic and social consequences. The negative consequences to
the so-called “inner peripheries” (permanently marginalised areas) may be particularly important. These areas
find it difficult to follow the growing economic cores located around big cities. The recent pandemic may
accelerate the social and economic divergence between these areas which will be undesirable from the point
of view of sustainable development.
The aim of the project is to identify the regularities of changes to the socio-economic development in selected
inner peripheries in Poland with special attention given to their sensitivity and resilience to the consequences
of the SARS-CoV-2 crisis, and the resulting recommendations for the changes in the development policy
interventions. The main goal of the project has been broken down to specific objectives of cognitive,
methodological and application-related nature.
In the project, a novel methodological approach has been adopted. Research team will use yet unpublished
data from the Ministry of Finance, data from the System of Self-Governmental Analyses and the results of in-
depth analyses provided by the Association of Polish Cities. In combination with an original geospatial
database of open and public data, and data provided by the Central Statistical Office on multi-faceted spatial
access to services and jobs, it should lead to a better understanding of the transmission of the effects of the
SARS-CoV-2 crisis on the specific industries and sectors of the economy as well as the inhabitants’ income.
Among the applied analytical approaches, also an innovative multi-variant approach to systematising inner
peripheries in Poland will be employed. It will take into consideration the impact of functional regions of
medium-sized and small towns on the surrounding underdeveloped areas. By making use of generally
available and unpublished sources of quantitative data it will be possible to apply models of spatial regression,
previously not used to this end or to this extent on a local level. Another value of the planned research is the
adopted structure based on identifying the factors of peripherality (factual and potential), and creating a system
monitoring the multi-faceted changes to inner peripheries in the country.

“There is no way of making an expected profit by extrapolating past changes in futures price, by chart or by any other esoteric devices of magic or mathematics” wrote one of the most famous economists of all times, Paul A. Samuelson, in 1965. And he was not alone in his views! For many decades, both stock market laypersons and scholars regarded the stock market as a casino. The prices fluctuated seemingly randomly without any order, turning some people into millionaires and others into beggars out of pure chance. From the perspective of the research discoveries of recent decades, it seems unbelievable how wrong we all were.

The last 20 to 30 years have produced a proliferation of studies on predicting stock returns and selecting securities. Researchers in the academic field called “asset pricing” have documented a preponderance of variables that may predict future returns. Recent surveys of the academic literature have collected literally hundreds of different predictors—based on prices, accounting data, or other types of information—that help to forecast which stocks will be winners, and which will become market laggards. Suddenly, after just a few decades of study, we are faced with predictor overload. Once, we knew no factors at all with which to predict stock prices; now, we are in a “factor zoo” and do not really know what to do with it.

The oversupply of predictors for the asset markets prompts numerous new questions for researchers. For example, which of them are real? Indeed, the return predictors tend to be driven by a sort of Murphy’s law: once discovered, they tend to quickly disappear. The reason might be that many of these variables are just statistical artifacts, resulting from intense data mining. If you search for patterns long enough, you will certainly find some regularities. As the Infinite Monkey Theorem states, if you give a sufficiently large number of monkeys typewriters and a lot of time, one of them will eventually write Hamlet. Other questions include: Do predictors really matter? Are all of them independent? Or are some of them simply proxies for or different measures of the same phenomena? Can we predict the performance of predictors? What is the role long-run structural changes in the market or extreme events and crises?

Answering such questions is difficult if you have only limited data. The majority of return predictors have been discovered in the U.S. stock market and are based on several decades worth of data. To check whether they are real, you need to go beyond this research sample. The data does not necessarily need to be fresher; it could also be much older. And using older data to extend the research sample is precisely what I do in this research project.

The main goal of the project is to develop methods for estimating the size of the foreign-born population in Poland and its characteristics using multiple data sources that contain potential errors. The aim of the project is twofold. On the one hand, we focus on estimating the size of the foreign-born population based on multiple, overlapping data sources that are likely to contain errors, such as administrative data. The main motivation behind this approach is to provide census-like statistics without conducting a traditional census. Secondly, characteristics of foreign-born populations included in administrative data are scarce and can be supplemented by non-probability samples, such as mobile big data derived from smartphones. The project aims to broaden the knowledge of the foreign-born population in Poland by using administrative data and other non-statistical data sources and developing sound and novel statistical methodology.

The results of the project should also contribute to producing more reliable estimates of the contribution of immigrants to the labour force and to GDP growth in Poland. Project results will be the basis for conducting statistical analyses on the socio-economic situation of Poland’s regions and for projections of their development. We also note that estimators and results of our study are not only limited to migration statistics but will also have an impact on other fields, such as macroeconomics, economic policy or sociology.

Project Description:

The aim of the planned scientific research is to identify potential factors influencing the independence of the internal audit function in this sector, both in organizational and operational aspects. The study is of a pilot nature. In the public finance sector, including the local government sector, internal audit operates based on the Public Finance Act of 2009. Considering that the territorial self-government in Poland is three-tiered, the pilot stage will include research on 16 voivodeship offices.

In these entities, due to their size and organizational complexity, the internal audit function is well-developed. Therefore, it can be assumed that the study will identify the most actual and hypothetical factors that may affect the independence of internal audit activities. The research will employ the method of in-depth individual interviews (IDI) conducted with internal audit managers in the surveyed units, based on an interview guide with open-ended questions.

The outcome of this scientific effort will be the development of a measurement instrument for the main study—a questionnaire in an electronic format, to be completed independently by respondents (Computer Assisted Web Interview – CAWI). In subsequent stages, the research will cover other local government units at the county and municipal levels. The main study will have a nationwide scope.

Project Description:

Thinking in terms of the life cycle in business practice is challenging. This stems from both a lack of competencies or other organizational barriers and specific issues faced by organizations (especially SMEs) that aim to adopt eco-design methods based on the life cycle concept. Considering the intensive efforts by the EU to increase the environmental efficiency of products, it is expected that Polish enterprises will soon face the necessity of broader identification and evaluation of the environmental aspects of their products. It is worth assessing the current status in this regard, especially since the conclusions of studies conducted so far have been very general.

The research problem, therefore, boils down to answering the question of whether and to what extent businesses in selected industries incorporate the life cycle perspective into their eco-design practices and what organizational factors support such actions from a practical standpoint.

The main goal of this scientific endeavor is to conduct a preliminary assessment of the degree to which the life cycle perspective is included in the eco-design practices of selected manufacturers and to gain a general understanding of the organizational factors that promote such activities.

Project Description:

As part of the ecorank project, we have created an innovative online platform that connects organizations with consumers, enabling transparent tracking and comparison of the effectiveness of pro-environmental actions. Our platform provides reliable data on organizations’ environmental impact, supporting informed purchasing decisions and promoting better environmental management practices. With ecorank, organizations can efficiently monitor their performance, while individual users gain access to comparable information, fostering sustainable development and ecological responsibility. The ecorank platform has reached the fifth level of technological readiness, meaning its solutions have been tested in a real operational environment and are ready for further development and large-scale implementation.

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https://ecorank.pl/

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Both organizations and consumers will benefit from the project results. Organizations will be able to effectively monitor and report their pro-environmental activities, improve their environmental performance, and adjust their management strategies. Consumers will gain access to transparent and comparable information about the environmental impact of various organizations, enabling them to make informed purchasing decisions. In the prototype version of the platform, we focused on six industries: the food sector – beverage and food producers; the cosmetics and household chemicals production sector; the electronics, appliances, and IT production sector; the clothing and footwear production sector; the vehicle production sector; and the retail trade sector.

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Watch the video

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The project was implemented by the Poznań University of Economics and Business (UEP) and was funded by the National Centre for Research and Development (NCBR) under the TANGO competition, agreement number TANGO-V-A/0043/2021-00.

Summary
This project aims at exploring the antecedents of legitimacy and performance of post-transition country firms in a more advanced country in terms of economic and institutional
environment. While German firms have long invested in Central Eastern Europe, particularly in Poland, the reverse trend is only recent. Thus, relatively little attention has been paid to market
entries of Polish firms in Germany, while scholars have concentrated on the emergence of Asian multinational firms and their investments in advanced economies. In fact, the phenomenon of Polish investment in Germany is important for both economies. For Poland, on the one hand, successful market entries in advanced countries can help fostering the competitiveness of national firms, in particular by establishing the operations in more innovation and knowledge-rich context. Germany, on the other hand, aims to attract foreign firms to generate jobs, increase employment on a domestic level and improve the efficiency of the economy. Particularly during economic crisis times, the entry of new entrepreneurial firms may help restructure enterprises facing difficulties. Therefore, the present study shall adopt the logic of institutional theory to address managerial decisions related to upmarket subsidiaries (i.e. foreign subsidiaries located in a more advanced host country as opposed to the home country of the parent firm). In particular, it will focus on the role of subsidiary management teams and their diversity in building up the legitimacy of the subsidiary in its host country context. Also, the project will address the role of local network ties in the legitimacy-building process. Ultimately, the project aims to investigate how these different legitimacy-related aspects translate into the performance of these subsidiaries. These relationships are formalised in a set of nine research hypotheses constituting a structural equation model (SEM) which will be subject to empirical verification.

In 2019, Google introduced Duplex, a bot that can make voice calls. A new feature of the bot was its
ability to imitate the way that humans speak so well, that people were not aware that they were speaking
to a machine and not a human. A year later, a computer based on a sophisticated natural language
processing model (GPT-3) co-wrote an article published in The Guardian.

Along with the advancement of bots, the influence of machines on our society will be enormous and
multidimensional. They will transform the way we use digital devices (mostly verbally), how we make
decisions (e.g., by letting them give us advice on various issues like a holiday destination), or how we do
our jobs or conduct business (e.g., by partnering with us in medical diagnoses). Therefore, it is crucial to
uncover the behavioral intricacies of human and machine communication and collaboration, so that we
may benefit from this technology as a society and not be harmed by it.

We still know little about how bots will influence decisions that have economic consequences. For
example, the process of interaction with a sophisticated bot may determine investment decisions, similarly
to what is currently happening with (less-sophisticated) robo-advisors (e.g., Betterment). In three themes,
we will investigate many (similar) behaviors that have economic undertones. It is now possible to use the
same algorithm that co-wrote the article in The Guardian (GPT-3), allowing researchers to look at how
people will interact with bots in the future.

The first theme concerns the question of how to avoid an unfavorable reaction of a human to a machine.
Earlier studies show that – in many cases – people dislike it when a machine (or an algorithm) tells them
what to do (instead preferring human advice). This is a phenomenon known as algorithm aversion.
Through our research, we will investigate if increasing the presence of a human in an interaction reduces
this aversion. We will also explore whether economic behavior will change if people interact with a
chatbot (instead of a static, non-conversational bot) or a bot that has been fine-tuned by a human with
high expertise (e.g., by an economist), or if they currently have less mental resources (are under cognitive
load).

The second theme concerns how machines can increase unethical or antisocial behavior. Existing research
shows an interesting “double effect”. On the one hand, machines are generally not preferred as the agents
that should handle issues that have moral undertones. On the other hand, machines are not judgmental,
making it less mentally exhausting for humans to behave unethically in front of them. We will use
methodological advancements to obtain a better understanding of how machines can increase our ability
to behave unethically. Moreover, we will test whether people will be more likely to behave unethically if
the bot has been fine-tuned by a person with a high moral standing (e.g., by an ethicist). Next, we will test
whether people become less prosocial and less trustworthy if they have a bot at their disposal to guide
their decisions, or if another person has such a bot. Finally, we will test whether interacting with machines
instead of humans makes it easier for people to make moral judgments that are not socially desirable.
The third theme concerns the “affective leverage” that bots can use, while trying to promote desired
behaviors. This is already happening. For example, in one company a machine listens to how employees
interact with customers and suggests what they should say in any given moment. In our project, we will
investigate how effectively bots can decipher what a person is thinking or feeling, in order to adjust how
they will interact with that person (and thus increase desired economic behaviors). We will also see
whether people find that it is socially acceptable for bots to behave this way.

We want to publish our most important findings in leading journals, e.g., Nature Communications, Nature
Human Behaviour or Science Advances. Publications in these journals should be written in a way that is
understandable by the society at large and scholars from other fields. We believe that this is important: it
will help build bridges between various different fields, inspiring new, breakthrough ideas.

Project Description:

The objectives of the project are to:

(a) Develop tools for assessing the impact of tax solutions on the development of business innovation and entrepreneurship among individuals,
(b) Define methods to improve the quality of tax record and balance of payments information systems while reducing administrative burdens for businesses,
(c) Estimate the scale of international profit-shifting phenomena related, among others, to intellectual property rights,
(d) Evaluate the spillover effects of foreign firms on the innovation and competitiveness of domestic companies,
(e) Propose methodological solutions for measuring the innovation potential of micro-enterprises, taking into account various accounting systems and the potential for obtaining R&D and IP Box tax relief.

The project aligns with the fourth research area of the Gospostrateg VI program: “The Trap of Institutional Weakness” and will consist of 12 tasks. The project will utilize data from GUS (Statistics Poland) studies (BBGD, SP-3, PNT-01, and PNT-02), Ministry of Finance (MF) data from PIT, CIT, JPK VAT, and IFT, as well as data collected from direct interviews and an economic experiment.

The project outcomes will include:

• Tools for estimating the effects of R&D and IP Box tax relief on innovation activities,
• Tools for assessing the phenomenon of profit shifting,
• Contributions to the WHTAX tax data warehouse and planned MF tax databases,
• Recommendations for including entities under reporting obligations and/or reducing administrative burdens by integrating the same data reported for different purposes,
• Methodological proposals for research on R&D activities and the innovation potential of micro-enterprises, as well as studies on the determinants of household entrepreneurship,
• Recommendations for creating the country’s balance of payments (integrating NBP reporting systems with data on international transactions from JPK VAT (Big Data) and, eventually, with eInvoice cloud data and IFT passive flow data).

Project Description:

The implementation of the Polish Deal (Polski Ład) at the beginning of 2022 will have a significant impact on Poland’s economic landscape. The Polish Deal, as a plan for rebuilding the Polish economy after the COVID-19 pandemic, aims to reduce social inequalities and create better living conditions for all citizens. Achieving these goals will be possible through the implementation of various initiatives outlined in different areas of the Polish Deal, which will affect the conditions in which enterprises operate (Republic of Poland Government Service, 2021).

This project aligns with the objectives of the Science for Society program by fostering collaboration between scientific institutions and socio-economic entities through the development of new knowledge and practical solutions to help businesses take advantage of the opportunities presented by the Polish Deal. The proposal draws from the latest scientific research (Bamiatzi et al., 2016) and fits within the current research trend (Cheong and Hoang, 2021) and extensive economic practice focused on using economic analysis of enterprises to improve decision-making quality.

In this application, a comprehensive analysis of available documentation (Ministry of Finance, 2021) was conducted, leading to the identification of key areas of the Polish Deal that are expected to have the most significant impact on the business environment. Subsequently, the effects of implementing the policies in these areas were conceptualized by defining “Polish Deal variables”—variables that describe the business environment and are most likely to be influenced by the Polish Deal (a catalog of these variables is included in the application).

Simultaneously, based on analytical and conceptual work and a critical review of the literature, economic constructs that most effectively describe the financial condition of businesses were selected and precisely conceptualized. These constructs—profitability and financial liquidity (Mikołajewicz and Nowicki, 2021)—are expected to be influenced by changes in the Polish Deal variables.