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In recent years, anthropogenic climate change became a major global concern. Studies indicate that the earth's increased atmospheric temperature is warming streams and rivers, affecting local ecosystems and thereby resources. Temperature is a central variable for fundamental aquatic processes like oxygen dissolution or metabolic rates and determines the ecological niches. Temperature hence influences river ecosystems on all scales, from the molecular level to community composition. However, apart from air temperature, river temperatures are affected by numerous parameters and long-term, comprehensive studies on river water temperature dynamics are scarce. This study examines Germany-wide thermal stream measurements, collected between 1981 and 2019 in a consistent framework to assess trends in river water temperatures and their dependence on spatial characteristics. In doing so, long-term mean trends are quantified on a national scale under consideration of seasonal differences and topographic as well as geographic variables such as stream order, altitude and distance to urban areas, providing an improved understanding of spatial drivers in river water temperature dynamics. The calculated annual trends indicate an average water temperature increase of 0.25°C ±0.28°C/decade with autumn exposing a particularly high inclination of 0.43 ±0.49°C /decade on a seasonal scale. Latitude, longitude and baseflow index expressed the highest correlations to the determined trends over all analyses. However, fall presented exceptional results again. There, precipitation, latitude and solar radiation resulted in the highest explanatory coefficient values of the entire analyses. The results aid with predicting future trends and thereby serve as the basis for preventive measurements in river-, resource-, and risk management.

The decision-maker(s) need to control inventories in a way that minimizes holding, shortage and ordering costs. While the markets are evolving and more innovative products are introduced, the demand which firms face becomes more unpredictable. To balance the costs and more reliably forecast the demand for perishable products, firms can utilize the newsvendor problem, or one of its many variations. To produce the optimal ordering quantity for the situation, the problem and its variations take into consideration different aspects which affect the demand and costs regarding the product(s) in question. The objective of the research is to investigate the newsvendor problem’s variations and their application areas. To investigate the topic, a literature review is conducted which mainly focuses on inventory control for perishable products and the different variations of the newsvendor problem. This study concludes that the newsvendor problem is a versatile tool, which can be used in almost any industry and even in complex situations. When the settings are fitting, the problem can even be utilized in situations where non-perishable products are in question. The variations of the problem take into consideration key aspects that affect the demand, that the original model assumes to be irrelevant and thus are a valuable addition for inventory control. The thesis is limited to taking only the most common and important variations and distributions into account. The other methods for inventory control for perishable products are not in the scope of this study and the theory is limited to operational management and its subsets. Päätöksentekijöiden pitää hallita varastoja tavalla, joka minimoi varastointi-, puutetila- ja tilaamiskustannukset. Kysynnän ennustaminen hankaloituu jatkuvasti markkinoiden kehittyessä ja innovatiivisten tuotteiden takia. Tasapainottaakseen kustannuksia ja ennustaakseen kysyntää luotettavammin pilaantuville tuotteille, yritykset voivat hyödyntää newsvendor-mallia ja sen variaatioita. Malli pyrkii ratkaisemaan optimaalisen tilausmäärän ja tämän tehdäkseen se ja siihen liittyvät variaatiot ottavat huomioon eri tekijöitä, jotka liittyvät tuotteen kysyntään ja ominaisuuksiin. Työn tarkoitus on tutkia newsvendor-mallin variaatioita ja käyttötarkoituksia. Tutkimuksessa on suoritettu kirjallisuuskatsaus, joka keskittyy pilaantuvien tuotteiden varastonhallintaan ja newsvendor-mallin eri variaatioihin. Tutkimuksen perusteella voidaan todeta, että newsvendor-malli on monipuolinen työkalu, jota voidaan käyttää lähes kaikilla aloilla, sekä monimutkaisissakin tilanteissa. Tietyissä tapauksissa malli voi ottaa huomioon myös ei-pilaantuvat tuotteet. Mallin variaatiot ottavat huomioon erilaisia aspekteja, jotka vaikuttavat kysyntään, joita ei ole huomioitu tavallisessa mallissa, minkä takia muunnokset ovat tärkeä lisä varastonhallintaan. Työ ottaa huomioon vain osan mahdollisista variaatioista ja todennäköisyysjakaumista mutta huomioon otetut ovat tärkeimpiä ja yleisimmin käytettyjä. Työ ei ota huomioon muita menetelmiä pilaantuvien tuotteiden varastonhallintaan, sekä teoria on rajoitettu operatiiviselle ja sitä alemmille tasoille.

The increasing popularity of cryptocurrencies underscores the importance of comprehending the factors that impact users' trust and their intentions to utilize and invest in these digital assets. This comparative study between Finland and Iran explores user trust in cryptocurrency adoption and its relationship with perceived usefulness, perceived ease of use, and users' intention to adopt and invest in cryptocurrencies. The study employs a literature review, survey questionnaire, and data analysis to explore these factors. In this research, we first provide an overview of the research topic, highlighting the growing interest in cryptocurrencies and the need to comprehend user perceptions and attitudes. We compare user perceptions of trust related to the adoption of cryptocurrencies in Finland, a developed country, and Iran, a developing country. The purpose of this study is to contribute to the emerging field of cryptocurrency research by identifying specific factors that contribute to user perceptions of trust in different economic contexts. Our findings support the proposed hypotheses and emphasize the significant role of trust, perceived usefulness, and perceived ease of use in shaping users' intentions. Trust emerges as a crucial factor, underscoring the need for a secure and reliable cryptocurrency system. Furthermore, the study identifies interrelationships between these factors and recognizes the variations observed between Finland and Iran data samples. Practical implications of this study include focusing on emerging markets, enhancing trust through security measures, improving usability, and utilizing perceived usefulness to build trust. The study suggests recommendations for policymakers and practitioners. However, it acknowledges limitations such as the sample size and self-report measures. Overall, this research contributes to the understanding of trust and intention in the adoption of cryptocurrencies by emphasizing the significance of trust, usefulness, and ease of use in shaping users' intentions. By providing insights into user trust factors and cryptocurrency adoption, this study aims to inform policymakers, industry practitioners, and researchers in improving cryptocurrency adoption and trust.

The increasing share of weather-dependent renewable energy in the electricity grid requires different balancing solutions. This provides business opportunities for large-scale stationary lithium battery energy storage systems (LiBESS). In this master's thesis, the profitability of the LiBESS investment is investigated in two different scenarios from the perspective of a case company focused on the development of solar power projects. The first scenario focuses on evaluating the profitability of the electricity reserve market. The second scenario evaluates the profitability based on possible savings from avoiding the imbalance costs of the solar power plant. The results of the master’s thesis showed that the case company's requirement of 7% internal rate of return (IRR) for the LiBESS investment was not achieved in either scenario. The yearly reserve market scenario was clearly closest to the target with an IRR of 5,21% which was achieved with the revenue from frequency containment reserve for normal operation (FCR-N). Therefore, this scenario was further evaluated with a partial sensitivity analysis. The results of the sensitivity analysis emphasized the importance of LiBESS service life, capex development and the reserve market price as key factors of profitability. The conclusion from the results was that the case company should not invest in LiBESS when developing solar power plants. However, the most critical variables from the sensitivity analysis results should be followed because relatively small changes in their values could turn the investment profitable in the future. Sääriippuvaisen uusiutuvan energiantuotannon osuuden kasvaessa sähköverkossa tarvitaan uusia verkontasapainotusratkaisuja. Tämä tarjoaa liiketoimintamahdollisuuksia kiinteille suuren mittaluokan litiumakkujärjestelmille. Tässä diplomityössä näitä mahdollisuuksia tarkastellaan kahden eri skenaarion kautta aurinkovoiman hankekehitykseen keskittyvän yrityksen näkökulmasta. Ensimmäinen skenaario keskittyy arvioimaan litiumakkujärjestelmän kannattavuutta sähkön reservimarkkinoilla. Toisessa skenaariossa puolestaan arvioidaan kannattavuutta aurinkovoimalan tasekustannussäästöjen pohjalta. Diplomityön tulokset osoittivat, että case-yrityksen litiumakkujärjestelmäinvestoinnille tavoittelemaa 7 % sisäistä korkoa ei saavutettu kummassakaan skenaariossa. Selvästi lähimmäs kannattavuustavoitetta päästiin taajuusohjatun käyttöreservin (FCR-N) vuosimarkkinalla, joka tuotti 5,21 % sisäisen koron. Näin ollen tätä skenaariota tarkasteltiin tarkemmin osittaisherkkyysanalyysin avulla. Herkkyysanalyysin tulokset korostivat akkujärjestelmän käyttöiän, pääomakustannusten kehityksen sekä reservimarkkinahinnan merkitystä keskeisinä kannattavuuteen vaikuttavina muuttujina. Johtopäätöksenä tuloksista case-yrityksen ei tulisi investoida litiumakkujärjestelmään osana aurinkovoimahanketta. Herkkyysanalyysissä esiin nousseita kriittisiä muuttujia tulisi kuitenkin seurata jatkossa, koska suhteellisen pienet muutokset niiden arvoissa voivat kääntää investoinnin kannattavaksi tulevaisuudessa.

Major environmental challenges, such as water scarcity and quality issues, excess use of virgin nutrients, air pollution and global climate change, have given rise to an urgent need to reduce the environmental impacts of production and consumption and to develop and implement actions towards environmental sustainability. Life cycle assessment-based methods are traditionally used to measure the lifetime environmental impacts of products and services and to detect life cycle stages with the highest emission reduction potential. In addition to measuring the adverse impacts of offerings, there is a need to evaluate and compare solutions to determine which among them are the most beneficial to the environment. With regard to greenhouse gases, the carbon handprint approach can be used to evaluate the positive climate impacts of products and services when used by customers. However, the methods focusing on positive contributions in terms of other environmental impacts and in application scopes other than products and services are still scarce. The main aim of the present study was to develop a handprint method for quantifying and communicating the environmental benefits of products and services in terms of air quality, nutrient use and water use and quality. To this end, the specific requirements of different impact categories were identified. Another objective was to widen the application scope of carbon handprint assessment from the product level to regional consideration as cities and regions have a focal role in climate work. The method was developed based on the principles of life cycle assessment, footprinting and the carbon handprint approach. Additionally, four case studies concerning different environmental and application scopes were conducted. The results obtained from the present study show that different environmental impact categories have specific requirements when applied to the handprint context. As central issues, the need to recognise suitable and relevant indicators regarding different environmental scopes, acknowledging the origin of emissions in the context of locality and globality of impacts and selecting between the inventory and impact assessment levels should be considered. According to the case studies, handprints are feasible indicators of positive environmental impacts. Thus, this dissertation presents a coherent environmental handprint framework across different environmental scopes and stepwise calculation guidelines. The environmental handprint approach provides a necessary addition to the existing life cycle methods as it offers a scientific-based means of quantifying and communicating the positive contributions of products, services and regions to the environment. Most importantly, handprints can provide reliable information in different decision-making situations, such as in the business and political contexts, but they can also be used for communication and marketing purposes. In particular, environmental handprints can be used to promote circular economy targets and green transition to sustainable production and consumption patterns. From a regional perspective, handprints can be important drivers of novel sustainable solutions and regional viability and attractiveness.

Carbon capture has been recognized as one of the key elements of the future’s sustainable energy production system. The largest carbon dioxide emitting sector, energy production, needs efficient and feasible carbon capture technologies. Hot potassium carbonate (HPC) process is a chemical absorption-based carbon capture technology, using potassium carbonate solvent. Its advantages are cheap solvent, low regeneration energy and non-toxicity, but it suffers from poor capturing efficiency with low CO₂ concentration flue gas. The technology has been utilized in gas industry carbon capture for over 70 years and now its performance for power plant carbon capture is evaluated. In this thesis, a HPC simulation model is created with Aspen Plus for Sumitomo SHI FW Oy to evaluate its performance when applied to power plant carbon capture. The key performance indicators are capturing efficiency and specific energy demand. First, carbon capture configurations and technologies are introduced with the focus on HPC. Performance promoting modifications for HPC configuration are introduced and utilized in described simulation model creation process. In the first phase of simulation, multiple key design parameters are varied to find out their effect on the capturing process. Based on the results of the first phase, design parameters are chosen for the second phase of simulation, in which optimized final model is simulated. Finally, results and model development are discussed. The simulation model was found to be an effective tool for preliminary evaluation of the technology. The performance was evaluated to be competitive with power plant flue gases. The introduced process modifications proved to improve both key performance indicators significantly, especially specific energy demand. Despite the satisfactory results, further development of the model was stated to be essential for the professional use in the future. Hiilidioksidin talteenotto on nimetty yhdeksi tärkeimmistä tekniikoista tulevaisuuden kestävässä energiantuotantojärjestelmässä. Energiantuotanto on suurin yksittäinen päästöjen tuottaja maailmassa ja tarvitsee siksi tehokkaita ja toteuttamiskelpoisia hiilidioksidin talteenottotekniikoita. Kuuma kaliumkarbonaattiprosessi (HPC) on kemiallinen absorptiopohjainen hiilidioksidin talteenottotekniikka. Sen etuja ovat liuoksen edullisuus, vähäinen energiantarve regeneroinnissa ja myrkyttömyys, mutta sen talteenottohyötysuhde on heikko. Tekniikkaa on käytetty kaasuteollisuudessa jo yli 70 vuoden ajan, mutta nyt sen suorituskyky arvioidaan voimalaitosten hiilidioksidin talteenottotekniikkana. Tässä työssä luodaan HPC-simulaatiomalli Aspen Plus -ohjelmalla Sumitomo SHI FW Oy:lle, jolla arvioidaan tekniikan suorituskyky voimalaitosolosuhteissa. Suorituskykymittareina toimivat talteenottohyötysuhde sekä ominaisenergiantarve. Aluksi hiilidioksidin talteenottokokoonpanot ja -tekniikat esitellään keskittyen HPC-tekniikkaan. Suorituskykyä parantavat muutokset esitellään sekä sisällytetään malliin samalla kun sen luomisprosessi kuvataan. Simulaation ensimmäisessä vaiheessa selvitetään suunnitteluarvojen vaikutus prosessin toimintaan arvoja muuttamalla. Toisen vaiheen suunnitteluarvot valitaan ensimmäisen vaiheen tuloksiin perustuen ja optimoitu malli simuloidaan. Lopuksi käsitellään simulaation tulokset sekä mallin jatkokehityskohteet. Simulaatiomalli osoittautui tehokkaaksi työkaluksi arvioida tekniikan suorituskykyä. Suorituskyky arvioitiin kilpailukykyiseksi myös voimalaitosten savukaasuilla. Suorituskykyä parantavat muutokset näkyivät etenkin ominaisenergiantarpeen vähenemisenä. Hyviin tuloksiin pääsemisestä huolimatta mallin jatkokehityksen todettiin olevan välttämätöntä sen tullessa yrityksen käyttöön tulevaisuudessa.

In recent years, much effort has been invested in the development of waste-to-energy (WTE) technologies that might reduce the volume of waste and ameliorate its negative environmental consequences. This study examines the countries which have the fastest transition from landfilling to WTE treatment and the impact of this transition on the environment during their transition period. The study evaluates the speed of the transition by calculating the annual percentage of WTE treatment and decrease of landfilling and assesses the environmental impact in terms of greenhouse gas (GHG) emissions and dioxin emissions. The results showed that the annual rate of WTE progress based on the share of WTE of the total generation (and treatment) of municipal solid waste (MSW) was in the range of 0,53 %-points/a, and 5,26 %-points/a, also the annual rate of landfill reduction was in the range of 0,63 %-points/a, and 6,63 %-points/a. Furthermore, the results in the environmental impact showed that the changes of GHG emission caused by each kt of treated MSW by WTE and landfill methods were in the range of -0,924 kt CO2eq/kt (landfill +WTE) and 0,421 kt CO2eq/kt (landfill +WTE). Furthermore, the GHG emission factor for WTE plants was determined for the countries over the period. Finally, the dioxin emission changes were roughly estimated for the case countries, and the dioxin emission changes were decreasing and between 3,14 mg-TEQ/kt landfill+WTE and 7,61 mg-TEQ/kt landfill+WTE. The study concludes that WTE is a quick and effective method to reduce environmental impact and generate energy and can be a valuable opportunity for other countries to improve their waste management systems.

Cancel culture is a global phenomenon that has become common in the fashion industry. The term refers to a phenomenon in which companies or individuals are being held accountable, for their actions that are considered unethical, or socially unacceptable. The phenomenon has become more common with the growth of digital platforms, which have acted as suitable platforms for individuals to gain attention to their opinions and find other like-minded people. In addition, digitalization has made it easier to gain access to information, which has caused consumers to become smarter, and demanding. This research was performed with the objective to understand if cancel culture changes consumers' attitudes or behavior toward fashion brands, and if it drives the consumer attitude-behavior gap. The objective was defined by identifying a research gap in existing studies. The research was performed as qualitative research, with inductive reasoning. Data was collected through semi-structured one-to-one interviews. The theoretical framework was built around consumer behavior and the different factors that affect it. In addition, the theory focused on the concept of consumer attitude-behavior gap and cancel culture as a phenomenon. Five voluntary consumers from Finland were interviewed in a Teams setting. The results were analyzed using thematic methods and put into a codebook. The results of the study suggest that cancel culture has a negative impact on consumers' attitudes. However, cancel culture does not directly change consumers' behavior. What defines if consumers change their behavior is if the value the company brings to them reduces. Even if consumer attitudes become negative due to cancel culture, it does not change their behavior, unless the company does not serve value anymore. The results indicate that cancel culture causes negative changes in consumer attitudes, but not enough to change their behavior. Therefore, we can conclude that cancel culture widens the consumer attitude-behavior gap. Cancel-kulttuuri on maailmanlaajuinen ilmiö, joka on yleistynyt viime vuosina maailmalla. Termi viittaa ilmiöön, jossa yritykset tai yksilöt joutuvat vastuuseen toimistaan, joita pidetään yleisesti epäeettisinä tai sosiaalisesti haitallisina. Ilmiö on yleistynyt digitaalisten alustojen kasvun myötä. Digitaaliset alustat, kuten sosiaalinen media, ovat mahdollistaneet sen, että yksilöt voivat saada huomiota mielipiteilleen ja löytää muita samanhenkisiä ihmisiä. Lisäksi digitalisaatio on helpottanut tiedonsaantia, mikä on tehnyt kuluttajista älykkäämpiä sekä vaativampia. Tämän tutkimuksen tarkoituksena oli ymmärtää, muuttaako cancel-kulttuuri kuluttajien asenteita tai käyttäytymistä muotibrändejä kohtaan ja ajaako se kuluttajien asenteiden ja käyttäytymisen välistä kuilua. Idea tutkimukselle löydettiin käymällä läpi aiempia tutkimuksia, joissa tuntui olevan tutkimusaukko tämän Pro Gradun aiheelle. Tutkimus toteutettiin kvalitatiivisena tutkimuksena, jossa hyödynnettiin induktiivista päättelyä. Tutkimusaineisto kerättiin puolistrukturoiduilla yksilöhaastatteluilla. Teoreettinen viitekehys rakentui kuluttajakäyttäytymisen ja siihen vaikuttavien eri tekijöiden ympärille. Lisäksi teoriassa keskityttiin kuluttajan asenteiden ja käyttäytymisen välisen kuilun sekä cancel-kulttuurin taustojen ymmärtämiseen. Viittä vapaaehtoista suomalaista kuluttajaa haastateltiin Teams-sovelluksen kautta. Tulokset analysoitiin temaattisin menetelmin ja koottiin koodikirjaan. Tutkimuksen tulokset viittaavat siihen, että cancel-kulttuurilla on kielteinen vaikutus kuluttajien asenteisiin. Cancel-kulttuuri ei kuitenkaan suoraan muuta kuluttajien käyttäytymistä. Se, muuttavatko kuluttajat käyttäytymistään, määräytyy enemmänkin sen mukaan, väheneekö yrityksen kuluttajalle tuottama arvo. Vaikka siis kuluttajien asenteet muuttuisivat, ei se muuta heidän käyttäytymistään, ellei yrityksen tuottama arvo kärsi tämän seurauksena. Yhteenvetona voimme sanoa, että cancel-kulttuuri aiheuttaa kielteisiä muutoksia kuluttajien asenteissa, mutta ei tarpeeksi, jotta he muuttaisivat käyttäytymistään. Tästä syystä voimme todeta, että cancel-kulttuuri kasvattaa kuluttajien asenteiden ja käyttäytymisen välistä kuilua.

The modeling and simulation of fluid power systems are essential parts of the real-time simulation of virtual prototypes of mobile working machines. In several cases, in the dynamic simulation of such fluid power systems, a longer simulation time is required. This makes the traditional mathematical models inefficient for real-time simulations, particularly when simulating fluid power systems because of the small volumes in stiff differential equations of pressure. On the other hand, the accuracy and stability of the traditional models also suffer from a numerical stiffness problem, while these models are accelerated by a reduction of the integration time steps. To solve the problem of small volumes in stiff fluid power circuits, different explicit and implicit solvers are used. The most common methods are pseudo-dynamic methods and singular perturbation theory-based solvers. This dissertation, in addition to the existing methods, demonstrates various advanced methods and models to improve the simulation speed of stiff fluid power circuits in the presence of small volumes, and to keep the accuracy at a high level compared to the slower traditional mathematical models of such circuits. Based on the results of the experiments performed with several fluid power circuits, which contained small volumes in their structure, the model for the Advanced Pseudo-Dynamic Solver was formulated. There are two main differences between the Advanced Pseudo- Dynamic Solver in comparison with the classical pseudo-dynamic solver. First, the calculation of the outlet volume flow rate related to the small volume is included in the inner loop of the solver, which allowed the numerical stability of the solution to be increased. In addition, the adaptive convergence criterion is proposed in the model, which allowed to increase the simulation speed and accuracy of pressure and piston position response. Obtained simulation results confirmed that the proposed solver is much more efficient in the solution of the fluid power circuits than the conventional lumped fluid theory-based method, as well as the classical pseudo-dynamic solver. Finally, the Advanced Pseudo- Dynamic Solver-based model can be calculated faster than the conventional model of the fluid power circuit with small volumes owing to the possibility of the application of a larger integration time step. Another effective method for the simulation of fluid power circuits is the Method of Multiple Scales. This method is based on the singular perturbation method used earlier for the real-time simulation of stiff fluid power circuits in the presence of small volumes. The results of the research showed that the method of multiple scales is much more accurate than the traditional mathematical model of fluid power circuits. Even more, the method demonstrated better accuracy performance compared to the classical singular perturbation theory-based method due to the elimination of cumulative error. The tested simulation speed of the proposed method allows for the simulation of stiff fluid power systems in real time and makes it possible to use this method in different real-time or faster than real-time applications. The third method proposed in this dissertation is a novel hybrid model for the simulation of stiff fluid power circuits. The main feature of the model is the utilization of a recurrent neural network instead of stiff differential equations of pressure with small volume. At the same time, the dynamics of the rest system are traditionally presented with algebraic and differential equations. The testing results of the introduced hybrid model showed that this novel method can reduce the simulation time, which makes the model suitable for real-time applications. Moreover, the accuracy of the model remains at a fairly high level compared to traditional mathematical models.

IPO underpricing refers to the phenomenon where shares offered by companies during their initial public offerings tend to be underpriced, leading to substantial increases in share prices during the early trading days. This subject has received considerable attention in the past decades, with previous research aiming to identify the factors driving initial IPO returns. This thesis investigates the explanatory factors and current state of IPO underpricing in Nordic countries. The study covers the time frame from 2010 to 2022 and examines the underpricing of Nordic IPOs by analyzing the initial returns following the offering. To explore the factors explaining IPO underpricing, the study employs multivariate linear regression models. Additionally, classification tree models are utilized to determine the key variables for predicting IPO pricing. This study focuses on variables related to asymmetric information and market conditions in explaining IPO underpricing. The findings of this thesis indicate significant underpricing in Nordic IPOs from 2010 to 2022. The study provides support for asymmetric information and market conditions in explaining IPO underpricing. Market conditions were found to have a particularly significant impact on the underpricing of initial public offerings the Nordic countries. Based on the findings of this thesis, it would be recommended to include also other factors such as behavioral factors alongside market condition- and information-based variables when studying the explanations for IPO underpricing. Listautumisannin alihinnoittelulla tarkoitetaan ilmiötä, jossa yritysten listautumisannissa tarjoamat osakkeet ovat alihinnoiteltuja, mikä johtaa osakkeiden hintojen huomattavaan nousuun ensimmäisten kaupankäyntipäivien aikana. Aihe on saanut paljon huomioita tutkijoilta viime vuosikymmenten aikana, ja aiemmissa tutkimuksissa on pyritty tunnistamaan syitä listautumisantien jälkeisille tuotoille. Tässä tutkimuksessa tutkitaan listautumisannin alihinnoittelua selittäviä tekijöitä ja nykytilaa Pohjoismaissa. Tutkimus kattaa ajanjakson 2010–2022. Listautumisantien alihinnoittelua tutkitaan analysoimalla osakkeiden tuottoja ensimmäisten kaupankäyntipäivien aikana. Alihinnoittelua selittävien tekijöiden löytämiseksi tutkimuksessa käytetään usean muuttujan lineaarisia regressiomalleja. Lisäksi tutkimuksessa käytetään luokittelupuumalleja selvittämään keskeisiä muuttujia, joiden avulla voidaan ennustaa listautumisantien hinnoittelua. Listautumisantien alihinnoittelun tutkimisessa keskitytään epäsymmetriseen informaatioon ja markkinaolosuhteisiin liittyviin muuttujiin. Tutkimuksen tulokset osoittavat merkittävää alihinnoittelua pohjoismaisissa listautumisanneissa vuosina 2010–2022. Tutkimus osoittaa, että epäsymmetrinen informaatio ja markkinaolosuhteet selittävät listautumisantien alihinnoittelua. Erityisesti markkinaolosuhteilla todettiin olevan suuri vaikutus listautumisantien alihinnoittelun Pohjoismaissa. Tämän tutkielman tulosten perusteella olisi suositeltavaa ottaa markkinaolosuhteisiin ja informaatioon perustuvien muuttujien rinnalle myös muita tekijöitä, kuten käyttäytymiseen liittyviä tekijöitä tutkittaessa syitä listautumisantien alihinnoittelulle.