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Toimialan taloustieteen tutkimuksia terveydenhuollon sekamarkkinoista ja odotusajoista
No full textThis dissertation consists of three unpublished essays on different aspects of the Finnish dental care industry. All essays are representative of the modern industrial organization as they employ structural models adjusted to fit the characteristics of the dental care industry as their methodological approach. Moreover, all essays use individual-level data on visits to dental care providers. The first essay uses visits to Finnish private dental care providers, while the second and the third essays use visits to both public and private dental care providers. These data allow me to observe visit level prices, waiting times and what dental care procedures are performed on the consumers.
The first essay estimates the magnitude of choice frictions in the Finnish private dental care industry. Choice frictions make switching a dental care practice costly and I find that in this setting consumers only rarely switch their dental care provider. However, two competing hypotheses can explain the lack of switching. First, consumers might be facing choice frictions. Second, consumers might have heterogenous preferences for dental care providers, and thus, the lack of switching might simply result from consumers repeatedly visiting their most preferred dental care practice over years as their preferences remain unchanged. I disentangle the choice frictions from the unobserved preference heterogeneity by controlling for consumers’ time invariant practice specific preferences. I find that choice frictions are important in the Finnish dental care industry and their magnitude is similar as moving the average consumer’s dental practice of choice 21% closer to the consumer.
The second essay studies how reducing waiting times at public dental care providers by increasing their production capacity affects market outcomes, when consumers can bypass the queue by paying more at a private alternative. I construct and estimate a model of the industry with consumer demand, public practice waiting times and private practice prices as equilibrium objects. In my counterfactual simulations I increase the number of full-time equivalent dentists at the public dental care providers by 20%. I find that waiting times decrease by only 1.5 days or 5%, because the initial decrease in waiting times after the capacity increase is offset by a large demand increase. Private practices do not decrease their prices, even though they lose on average 0.5 percentage points of market share, as the consumers most sensitive to prices switch away from private practices. Finally, consumer welfare and the use of dental care increases for all consumers, but less for the consumers with the lowest income. The lowest income consumers are not very likely to visit a public dental care provider, and they dislike waiting the least among all consumers, and thus they benefit the least.
The third essay studies how public dental care providers prioritize consumers with more severe oral health conditions and how the prioritization affects consumers’ welfare and their choices of dental care providers across public and private providers. We first obtain a measure of consumers’ oral health using machine learning and then estimate demand models separately for consumers with better and worse oral health. Healthier consumers wait on average 30 days, while sicker consumers are prioritized and wait seven days less. We find that consumers with worse oral health are willing to pay twice as much to wait a day less compared to consumers with better oral health. In our counterfactual simulation, where the consumers with worse oral health wait as long as the healthier consumers, consumer welfare per capita decreases by 5.9 euros for the consumers with worse oral health. Equalizing waiting times prompts these consumers to switch from public to private providers, and some ultimately go without care.Tämä väitöskirja koostuu kolmesta julkaisemattomasta esseestä, jotka käsittelevät suomen suun terveydenhuollon toimialaa eri näkökulmista. Kaikki esseet edustavat modernia toimialan taloustiedettä, sillä ne hyödyntävät suun terveydenhuollon toimialan erikoispiireisiin mukautettuja rakenteellisia malleja. Lisäksi kaikki esseet hyödyntävät yksilötason suun terveydenhuollon käyntiaineistoa. Ensimmäinen essee analysoi Suomen yksityistä suun terveydenhuoltoa, kun taas toinen ja kolmas essee tarkastelevat yksityistä ja julkista suun terveydenhuoltoa.
Ensimmäinen essee keskittyy valinnan kitkojen estimointiin yksityisessä suun terveydenhuollossa. Valinnan kitkat tekevät hammaslääkäriaseman vaihtamisesta haastavaa, ja havaitsenkin aineistostani, että kuluttajat vaihtavat hammaslääkäriasemaa harvoin. Tälle ilmiölle on kaksi kilpailevaa selitystä. Joko kuluttajien valinnat ovat kitkaisia tai kuluttajat käyvät samalla hammaslääkäriasemalla, koska he pitävät kyseisestä hammaslääkäriasemasta, eivätkä heidän mieltymyksensä muutu. Erottelen nämä kaksi selitystä menetelmällä, joka mahdollistaa kuluttajien hammaslääkäriasemaa koskevien mieltymyksien kontrolloinnin joustavasti. Tulokseni viittaavat siihen, että valinnan kitkat ovat merkittävä tekijä suun terveydenhuollon markkinoilla. Estimaattieni mukaan valinnan kitkat vaikuttavat kuluttajien valintoihin yhtä paljon kuin jos matkaa keskimääräisen kuluttajan valitsemaan hammaslääkäriasemaan lyhennettäisiin 21 %.
Toinen essee analysoi miten julkisen suun terveydenhuollon odotusaikojen lyhentäminen tuotantokapasiteettia kasvattamalla vaikuttaa jonoihin sekä muihin markkinatulemiin, kun kuluttajat voivat välttää jonottamisen maksamalla enemmän yksityisen sektorin palveluista. Rakennan ja estimoin Suomen suun terveydenhuollon toimialaa kuvaavan rakenteellisen mallin, jossa tasapainotulemia ovat kysyntä, julkisen sektorin odotusajata sekä yksityisen sektorin hinnat. Kontrafaktuaalisessa simulaatiossa tutkin mitä tapahtuisi, jos julkisen suun terveydenhuollon hammaslääkäreiden lukumäärää kasvatettaisiin 20 %. Tuloksieni mukaan odotusajat lyhenisivät ainoastaan 1.5 päivää tai 5 %, sillä kapasiteetin lisäyksen vaikutus jonoihin osittain mitätöityy lyhyempien odotusaikojen aiheuttaman kysynnän lisäyksen vuoksi. Yksityisen sektorin hinnat eivät laske, vaikka yksityisen sektorin hammaslääkäriasemat menettävät keskimäärin 0.5 prosenttipistettä markkinaosuutta. Kuluttajien hyvinvointi ja suun terveydenhuollon käyttö kasvaa kaikilla kuluttajilla, mutta pienituloisimmat kuluttajat hyötyvät vähiten.
Kolmas essee tutkii priorisoiko julkinen suun terveydenhuolto sairaampia potilaita ja miten priorisointi vaikuttaa kuluttajien hyvinvointiin ja valintoihin yksityisen ja julkisen suun terveydenhuollon välillä. Ensiksi mittaamme kuluttajien suun terveydentilan käyttämällä koneoppimisen menetelmiä. Julkinen suun terveydenhuolto priorisoi sairaampia kuluttajia: terveemmät kuluttajat odottavat keskimäärin 30 päivää julkisessa suun terveydenhuollossa ja sairaammat kuluttajat odottavat seitsemän päivää vähemmän. Toiseksi estimoimme kysyntämallit kummallekin kuluttajaryhmälle erikseen. Tuloksiemme mukaan sairaammat kuluttajat ovat valmiit maksamaan kaksi kertaa enemmän yhden päivän lyhennyksestä odotusaikaan kuin terveemmät kuluttajat. Simulaatiossa, jossa asetamme sairaammille kuluttajille terveiden kuluttajien odotusajan, sairaampien kuluttajien ylijäämä laskee keskimäärin 5.9 euroa per kuluttaja. Odotusaikojen yhtäläistäminen saa sairaat kuluttajat vaihtamaan julkiselta yksityiselle lyhyempien jonotusaikojen perässä. Osa sairaammista kuluttajista lopettaa suun terveydenhuollon palvelujen käytön kokonaan.navigointi mahdollistakuvilla vaihtoehtoiset kuvauksettaulukot saavutettaviastrukturell navigationalternativa textuella beskrivningar för bildertabeller tillgängligastructural navigationalternative textual descriptions for imagestables accessibl
Infectious Confidence: Unraveling the Effects of Confidence Contagion on Overfunding in Equity Crowdfunding
No full textEquity crowdfunding campaign overfunding occurs when a campaign generates funds in excess of the funding goal and has hence been touted as the mark of an extraordinarily successful campaign. However, a novel theoretical lens is needed to comprehend funders’ enthusiasm in their support of such campaigns. Building on the extant literature on contagion effect, we constructed a research model that posits confidence contagion invoked by confidence cues embedded in campaign materials as a key driver of overfunding. Our hypotheses were validated in two complementary empirical studies. In Study 1, we manipulated confidence cues in a controlled experiment to verify the activation of confidence contagion at the individual level. Analytical results indicate that individual funders detect self-confidence traits from confidence cues embedded in campaign materials and assimilate the fundraiser’s confidence via a spontaneous social appraisal mechanism. In turn, confidence contagion drives funders to congregate and invest in campaigns. In Study 2, we analyzed a secondary dataset collected from a leading equity crowdfunding platform to discern how confidence contagion drives overfunding at the collective level. By modeling funding activities as a Hawkes process, we derived three key metrics that govern the emergence and magnitude of funding surges. We demonstrated that these metrics of funding surges mediate the impact of confidence cues on the level of overfunding for equity crowdfunding campaigns. The findings from this study could inform future research seeking to untangle the interdependencies between individual and collective mechanisms underlying crowd phenomena, provide strategic guidance to fundraisers interested in promoting the overfunding of their campaigns, and help crowdfunding platforms predict the potential extent of overfunding and advise fundraisers accordingly.Peer reviewe
Responsible investing: Costs and benefits for university endowment funds
No full textPublisher Copyright: © 2025We examine the adoption rates of responsible investment (RI) policies among university endowments. Adoption rates are higher among universities that face stakeholder pressure and are donation-dependent. Policy adoption predicts greater abnormal donations totaling 12 % of endowment assets, especially from “socially conscious” donors and during periods of higher media attention to climate change. Universities also experience greater student applications following adoptions. RI endowments have greater management costs, greater return volatility, and similar overall asset growth (donations plus net-of-cost investment income) compared to non-RI endowments. We conclude that RI policies are an important part of the optimal contract between universities and their stakeholders.Peer reviewe
Advancing an LDA-GMM-CorEx topic model with prior domain knowledge in information systems research
No full textPublisher Copyright: © 2025 Elsevier B.V.Embedding topic models with domain knowledge is deemed to be effective in bolstering the models’ interpretability. Nevertheless, contemporary topic modeling techniques introduced in past studies lack consideration for circumstances in which prior domain knowledge either does not exist or becomes obsolete quickly. Combining the latent Dirichlet allocation (LDA) with the Gaussian mixture model (GMM) and the anchor correlation explanation (CorEx) topic model, we advanced a novel LDA-GMM-CorEx topic modeling approach to enhance the domain knowledge model's adaptability and improve the interpretability of topic modeling. We further verified the effectiveness of our proposed topic modeling approach on two separate datasets from different domains, thereby attesting to its general applicability.Peer reviewe
Resilience-oriented proactive operation strategy of coupled transportation power systems under exogenous and endogenous uncertainties
No full textPublisher Copyright: © 2025 Elsevier LtdThis paper proposes a proactive resilience enhancement strategy for power systems under hurricanes, focusing on the coordinated scheduling of coupled transportation power systems (CTPS) with rail-based energy storage transportation (REST). To capture the strong uncertainties of hurricanes on CTPS, a hybrid endogenous and exogenous uncertainty set is developed. In the proposed uncertainty set, the pre-layout and trail accessibility of REST is endogenous, i.e., decision-dependent, and the operating state of transmission lines is exogenous, i.e., decision-independent. An innovative two-stage decision-dependent robust optimization (T-D2RO) problem is formulated to enhance the economic feasibility of the CTPS and meet load survivability requirements during hurricane. In particular, we introduce the structure of a mixed-integer programming problem with a maximum-minimum objective, ensuring post-event service protection by jointly optimizing the REST routing, load shedding, and generation curtailment in the worst-case scenario. The T-D2RO problem is addressed using a customized parameterized column-and-constraint generation (C&CG) algorithm, leveraging the structural characteristics of this complex problem. Numerical results for the exemplary CTPSs demonstrate that proactive deployment and adaptive routing of REST provide economically viable solutions for achieving grid resilience objectives. Moreover, the customized parameterized C&CG algorithm exhibits superior performance that reduces the computation time compared to nested C&CG, thus enabling efficient emergency response via coordinated network operations.Peer reviewe
Basalt mineralization with soda saline soil for enhanced CO sequestration : An experimental study
No full textPublisher Copyright: © 2025 Elsevier Ltd.Global warming, driven by rising CO concentrations, demands urgent mitigation strategies. Among these, Basalt mineralization offers a promising method for large-scale carbon sequestration. Adding alkaline substances to the basalt mineralization reaction can expedite the process. Soil salinization, a widespread and severe problem in China, particularly in the northeastern regions, is characterized by the presence of soluble salts and high alkalinity. These soda saline soils could potentially enhance the efficiency of basalt mineralization. This study explores a novel enhancement approach: leveraging soda saline soils to accelerate basalt carbonation. A series of reactor experiments varying basalt-to-saline soil ratios, particle sizes, and solid-liquid ratios were conducted. The mineralization reaction mechanism of basalt in the presence of saline soil was investigated. The minerals of the reaction products were analyzed and the mineralization efficiency and sequestration capacity of each set of experiments were evaluated. The results showed that the saline soil enhanced the mineralization and carbon sequestration of basalt, increasing the efficiency by more than three times compared to basalt alone. This study demonstrates the potential of saline soil as a low-cost accelerant in carbon capture technologies.Peer reviewe
Experimental study of thermal comfort by variable temperature and velocity air supply system in operating room
No full textPublisher Copyright: © 2025 Elsevier LtdIn operating room, conventional unidirectional air supply system with constant supply temperature and velocity cannot satisfy the thermal comfort need of the surgical team. Therefore, a novel variable temperature and velocity air supply system is introduced. Indoor thermal environment and thermal comfort parameters through simulated surgical experiments were tested, where thermal sensation changes, skin temperature and thermal comfort of medical staff with different duties under different air supply conditions were analyzed. Thirty-five experimental personnel were recruited as medical staffs with five different roles. It is shown that there are significant differences in the perception of thermal comfort of medical staff under the conventional unidirectional air supply system. The thermal comfort of medical staff can be improved with variable temperature and velocity air supply system. Especially the comfort conditions of the surgeon and the anesthesiologist has been significantly improved. The proportion of medical staff feeling comfortable with variable temperature and velocity air supply system reaches 64.0%, while it is only 42.7% with conventional unidirectional air supply system. By adjusting the air supply temperature and velocity in different zones, the thermal sensation of the personnel in the critical operating zone tends to be moderate, which reduces the occurrence of local discomfort. This study shows that enough attention should paid on the thermal comfort condition of medical staff during the design and operation of the operating room. The variable temperature and velocity air supply system could be a promising solution to improve thermal comfort level in operating room.Peer reviewe
Comparative analysis of machine learning methods for the prediction of brake power and rate of revolution for bulk carriers
No full textPublisher Copyright: © 2025 Elsevier LtdIn the preliminary ship design process, key aspects such as machinery and powering must be specified, which involves estimating the brake power and rate of revolution of the main engine. Traditionally, these parameters are derived from existing ship databases; however, conventional estimation methods are often limited by outdated models, inadequate noise handling, and restricted capabilities for capturing nonlinear relationships, leading to reduced accuracy and generalization. This study employs a range of machine learning approaches to develop predictive models for estimating the brake power and rate of revolution of bulk carrier main engines. Special emphasis is placed on mitigating noise in both input and output data through the application of a spline smoothing technique. Accordingly, a data preprocessing workflow is proposed, incorporating spline smoothing to enhance the generalization potential of the machine learning models. A comprehensive comparative analysis is conducted across various methods, including four linear regression models, three regression trees, four Gaussian process regression models, two tree ensemble methods, and five neural network models. The performance of the employed machine learning models, evaluated using both raw and smoothed data, is compared in terms of accuracy and generalization capabilities. Results obtained using the smoothed data indicate that the hypertuned Gaussian process regression model exhibits superior accuracy in both validation and testing phases. Furthermore, linear regression models based on smoothed data demonstrated sufficient accuracy for practical implementation, leading to the development of simple predictive formulae for brake power and rate of revolution that are applicable in early-stage ship design.Peer reviewe
Design Science Methodology for AI-Based Contract Design Research
No full textPublisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.Contract design matters. The literature confirms that different contract designs can induce varying emotions, feelings, behaviour, and views of the contractual relationship. Specifically, prevention- and promotion-framed contracts and contract clauses seem to induce different emotions, which have been shown to impact the development of trust and even relationship performance. In addition, as many traditional contracts lack a design perspective, they may induce many negative emotions, such as confusion and frustration, among contract users. On the other hand, well-designed contracts can empower and engage contract users. Although (emotional) AI enables new venues for contract design and legal technology related research, it requires the adoption of new research methodologies. This chapter presents a novel methodology for legal research—design science methodology—that originates from computer science and serves a dual purpose: creating new scientific knowledge while developing and evaluating an information systems artefact. To illustrate how the methodology can be applied in practice, the chapter presents a research setting in which design science methodology can be used for developing and evaluating an AI-based contract design tool that is based on the guiding principles of proactive contract theory and that takes into account the social and psycho-cognitive effects of contracts.Peer reviewe
Risk-averse energy management for integrated electricity and heat systems considering building heating vertical imbalance: An asynchronous decentralized approach
No full textPublisher Copyright: © 2025 Elsevier LtdTo improve the energy efficiency of integrated electricity and heat systems (IEHS) with the flexibility of buildings, this paper proposes a risk-averse decentralized energy management strategy for IEHS with intelligent buildings (IBs). First, a thermal dynamic model for IBs considering building height is formulated based on the building's thermal inertia and vertical heating structure. Then, to alleviate the negative effects of uncertainties from renewables and energy prices, a stochastic optimization model for IEHS with IBs is formulated. Further, a conditional value-at-risk (CVaR) based risk evaluation method is integrated into the overall model to avoid over-optimistic solutions. Finally, to protect the privacy of scheduling information among different networks and mitigate computational burdens, the two-stage accelerated asynchronous decentralized alternating direction method of the multipliers (TSA-AD-ADMM) algorithm is proposed to solve the risk-averse energy management problem in a parallel way. The results show that the thermal dynamic model with building height describes the vertical imbalance of the heating network, besides, the risk-averse decentralized operation method effectively limits the system risks and significantly enhances the solving efficiency.Peer reviewe