Potential impact of property management on the market value of dwellings in multi-owned housing

The expanding role of property management services and the increasing share of multi-owned housing in many housing markets raises issues concerning the impact of such services on property value in this sector. The presented study investigated the potential impact of property management on the market value of dwellings in multi-owned housing developments. This impact was identified based on estimated implicit values of the extracted common property attributes dependent on property management services. An original research methodology tailored to the institutional arrangement in multi-owned housing developments was used, involving the estimation of hedonic regression models. Empirical research was conducted on representative samples of multi-owned housing developments in the housing market of the city of Olsztyn, Poland. The results showed that common property attributes such as building condition, building accessibility, cleanliness and orderliness, and land development significantly influenced dwelling prices and thus their market value. In extreme cases, the cumulative potential impact of property management services estimated on this basis can reach up to ca. 30% of the dwellings’ value. These findings have far-reaching policy and practical implications for urban development policies, including the built environment, land use and local housing, as well as for housing market investors and developers, homeowners associations, dwelling owners and property managers. Hence, it is recommended to expand research on this topic to other housing markets functioning in different institutional arrangements.


Introduction
Housing property management has changed immensely over the past century and is now arguably more professional and sophisticated than at any point in the past. Traditionally, a property manager has been viewed as someone who deals with the day-to-day activities that result from the use of a property, including collecting rents, paying the owner's bills, maintaining the physical condition of the property and securing basic services for residents, such as cleaning and security. However, over time, the role, tasks and responsibilities of a property manager have expanded and become increasingly complicated (Goss & Campbell, 2008;Alexander & Muhlebach, 2016). As a result, property management (PM) has become proactive, and those working in the field are now called on to participate in a diverse array of activities that reach far beyond the short-term tasks specified in the traditional approach to this issue (e.g. Kucharska-Stasiak 2000; Kaganova, 2012;Yau & Lau, 2016;Read & Carswell, 2019;Muczyński, 2022). For example, it is no longer uncommon for property managers to prepare budgets, analyze financial reports, conduct market research, negotiate contracts and evaluate proposed capital improvement projects in addition to completing day-to-day operational tasks. Some property managers are also charged with managing marketing and arranging financing for the property, handling risk management issues, developing and/or implementing corporate social responsibility and environmental platforms for the owners they represent, or even creating and executing long-term investment strategies in often challenging market environments (e.g. Glickman 2004;Kyle et al., 2005Read & Sanderford, 2018;Węgrzyn & Najbar, 2020). In this regard, it is increasingly recognized that property managers, by achieving various short-and long-term objectives that seek to control the interests of owners and potential buyers, can have a significant impact on their value in the marketplace. This paper focuses on the problem of the impact of PM on the property value in multiowned housing (MOH for short) developments in Poland. MOH is a generic term introduced by Blandy et al. (2010), including various forms of housing ownership, particularly such as condominiums, cooperatives and planned unit developments, with condominiums being the most prevalent form in the world (Lehavi, 2015). Distinctive features of most forms of MOH developments are that they consist of both separate housing units (dwellings) that are exclusively owned by individual owners (private sphere) and common elements, which encompass areas, facilities and common parts of buildings (common property) that are coowned by all unit owners (public sphere) (Yau, 2014). All unit owners usually form an owners' organization that has primary rights and responsibilities for the management of the common property ( Van der Merwe, 2015). In Poland, such an organization -referred to as a Homeowners Association (HOA) -is compulsory and formed upon the establishment of separate ownership of the first unit in the condominium scheme, and membership of each unit owner in it is mandatory. It is widely recognized that PM in MOH developments, focusing mainly on the common property (public sphere), is much more complicated than in single-owner housing because satisfying the interests of many interdependent owners proves to be challenging, while the considerable area of common property and the sophistication of the installed building services requires significant manpower and professional skills. Hence, PM services are commonly outsourced to third-party managers (agents). The significance of these services in MOH is well documented, especially in aspects such as maintaining the common property (building) in good condition, minimizing operating costs, and providing a safe and hygienic living environment and well-being for residents. It has also been noted that PM in MOH developments is becoming increasingly important in determining the market value (both price and rent) of managed properties (e.g. Wilhelmsson 2008;Yau & Ho, 2009;Hui et al., 2011Hui et al., , 2016Li and Monkonnen 2014;Carswell 2018;Muczyński, 2020, Mesthrige, 2021. However, there is still no consensus among researchers on this issue, as evidenced by the fact that empirical estimation of PM variables has been largely ignored in real estate research. The reason for this is, on the one hand, that PM is often considered to have a negligible impact on property value compared to other attributes such as property location or amenities, which, however, should not be underestimated in MOH developments due to the crucial role of PM in enhancing the positive image of the common property in the eyes of potential dwelling buyers. On the other hand, this is due to the difficulties in measuring the impact of PM services on property value in MOH that arise, particularly from its collinearity with other building variables and subjective quality assessment (Hastings et al., 2006). However, expanding roles of PM with the increasing share of MOH developments in housing markets make it necessary to study its impact on property values in this sector, especially since such studies have not yet been conducted in Poland.
The main aim of the study was to investigate the potential impact of property management on the market value of dwellings in MOH developments. The starting point for achieving this aim stems from the general assertion that the market value of a property is the most probable selling price that can be obtained for the property in a transaction between a willing buyer and a willing seller under normal market conditions. It is estimated based on an analysis of available transaction prices of similar properties (Baum et al., 1997;Mackmin & Emary, 2000;Źróbek, 2009). More precisely, the market value constitutes the estimated amount for which the property should exchange on the date of valuation between a willing buyer and a willing seller in an arm's-length transaction after proper marketing wherein the parties had each acted knowledgeably, prudently and without being under compulsion (European Parliament & Council of the European Union 2013). In a micro-perspective, prices of dwellings as non-homogenous commodities depend on a wide range of attributes that are categorized by researchers in different ways. For example, a frequently cited categorization of these attributes in the literature is their classification into locational, structural and neighborhood factors (e.g. Chin & Chau 2003;Malpezzi, 2008). Many of these attributes are independent of property managers, but several can actually be dependent on the services they provide (Hui et al., 2011). In MOH developments, the situation is quite specific insofar as PM services mainly concern the common property, which itself has no market price (and market value) since it as such cannot be traded on the market. This means that the possible impact of PM services on the property market value in MOH developments can only be manifested in dwelling prices, and thus should be estimated based on those prices. This impact has a permanent basis as dwellings are structurally related and inseparable from the common property. Since property value is created in the minds of property market stakeholders (Appraisal Institute, 1994), to achieve the aim of the study, it was assumed that the intensity (extent) and quality of PM services primarily impact those attributes of the common property that are observable (visible) by potential dwelling buyers during their visits to the property. Therefore, the research hypothesis was that there are statistically significant positive relationships between observable common property attributes dependent on PM services and dwelling prices in MOH developments. If this hypothesis is positively verified by empirical research, it means that the considered impact of PM services on dwelling prices (and thus on their market value) in MOH developments really does exist in the studied housing market. However, this is only a potential impact because it is not directly isolated from the transaction prices.
Following the Introduction, this paper contains fourth sections. The second section outlines a literature review on selected empirical results and research concepts from previous studies on the impact of PM on property prices and values; the third section covers the material and methods used for achieving the aim of the study; the fourth section presents and discusses the results of the empirical research; the fifth section concludes the research findings and outlines their policy and practical implications, with formulated recommendations for further research.

Literature review
From the perspective of institutional economics, PM in MOH developments is defined as the governance of property rights with the functions of exclusion and internal conflict resolution among co-owners (Yiu et al., 2006). Thus, adaptation of institutional arrangements in MOH developments is a key role of PM. Hastings et al. (2006) examined the relationship between property price and different institutional arrangements in MOH in Hong Kong, including management by a contractual owners' committee, a statutory incorporation of unit owners, or a PM company. The results of the study indicated that the appointment of professional PM agents in buildings with a contractual owners committee increased property prices by about 15%, and where a statutory, as opposed to a contractual, owners' organization formalized the governance arrangements, a further price premium of about 8% can be achieved. The authors stated that in the absence of mandatory management, property prices are increased in those cases where dwelling owners have chosen to resolve the difficulties of collective decision-making by forming incorporate groups and employing professional PM services.
The property value enhancement effects of PM depend on the intensity (extent) of these services. Yau and Ho (2009) examined which building management practices add value to properties in Hong Kong using the hedonic pricing model. Based on the empirical findings, the authors concluded that not all building management practices currently adopted are positively valued by the housing market. In particular, they found that property value was enhanced by practices like keeping as-built architectural drawings and incident records (good documentation), setting out emergency plans and conducting regular fire drills (thoughtful emergency planning) and taking out property-all-risk insurance for common areas. The results obtained give practitioners insight into which management practices are most valued by market players, which helps them formulate better business strategies. In addition, it was stated that if the value enhancement through the building management practices is well publicized in the society, a building care culture can be supported by market forces. Homeowners are more likely to actively manage their buildings with a view to the premium added to the value of their housing units. The authors also suggested that the preliminary value enhancement study can be extended to cover other typical management practices such as the implementation of planned maintenance and the cleaning of common areas.
Property buyers can always have different choices and they have bargaining power on the property price, while it is recognized that property price might be influenced, directly or indirectly, by the quality of PM services (Scarrett 1983;Benjamin & Lusht, 1993;Edington, 1997;Tempelmans, 2001;Sanderson & Read, 2020). Given that the market value is the most probable property price, some authors have linked the value enhancement effects of PM with the quality of these services. A more detailed study was conducted by Hui et al. (2011), who investigated the significance of the PM quality to property buyers in MOH developments in Hong Kong. The authors applied a hedonic pricing model to determine the impact of PM quality on property prices. ISO 9001 Certification and the HKMA Quality Award (HKMAQA) were used to measure the PM quality as companies that implement these certificates had been able to improve the standard of their service quality by establishing, documenting, and maintaining an effective and efficient management system. The study indicated that PM has a significant and positive relationship with property prices as the empirical results showed that a PM company having ISO 9001:2000 and HKMAQA increased the property price by 4.92% and 2.84% respectively, and if it had both certifications, then the increase in price occurred by 7.76%. The authors concluded that the quality of PM services could be served as an advantage of developers if they use their subsidiary PM company as a PM agent in their newly established MOH development. The quality of PM services then acts like a promise from the developer that the property value of the property would not go down after the buyer moves into the dwelling. Providing quality PM services to buyers allows the developer to grow their goodwill and increase their profit margin because buyers are willing to pay for it. Furthermore, it was stated that quality PM services not only increases the price of new properties, but also attracts potential buyers to the second-hand property market. Since improvements in PM service quality keeps the MOH building in better condition, it performs well in many different aspects such as security, hygiene, cost savings, minimum wear and tear, depreciation and breakdowns. These provide a positive image of the property in the eyes of potential buyers. In this way, the competitiveness of the building can be improved and the property, whether it is first or second hand, can be sold at a higher price. Thus, although people may not have complete knowledge of the PM company when buying a property, the quality of PM services is implied in the performance of the property. It was also noted that the quality of PM services that are brought into the property by certified PM companies could attract people through their building conditions, which increases people's awareness as they build confidence in professionals. It enhances the positive impression of potential buyers towards properties managed by these PM companies, resulting in those properties possibly being sold at higher prices than others. The implications of the study suggest that a well-recognized PM attracts property buyers and that a quality PM increases property prices, thereby enhancing their value. In turn, Mesthrige (2021), in a recent study, analyzed the impact of PM quality certification (PMGT) on property value using a fixed-effects modelling approach. The results showed that such certification raises property prices by an average of 3.3-3.9%. This premium was interpreted as the compensation that residents of MOH developments would be willing to pay to remove the "tragedy of the anti-commons" problem in order to maintain the value of the property by keeping it in good physical condition.
In the PM quality research stream, it is worth citing the study conducted by Li and Monkkonen (2014), who noted that assessing the value of PM services is challenging due to the collinearity between the quality of the property and the quality of PM companies. To overcome this challenge and isolate the impact of PM services, the authors used an experimental approach to measure the value of PM services in MOH in Hong Kong. The results showed that PM does add value, especially to older and more dilapidated properties. It was found that the difference in PM service quality can lead to a difference in property values by up to almost 25%. These results are encouraging for PM professionals since they show that criteria such as the achievement of ISO certifications and industry awards really do matter. Many authors in this stream have also investigated the impact of various environmental certifications on property prices/rents in the MOH sector. For instance, a certification called the Green Mark Scheme resulted in an additional price premium in Singapore of about 4% (Deng et al., 2012), while new condominiums with a "green" label in Tokyo were about 5% more costly than others without the same labels (Shimizu, 2010). A study on the Dutch housing market showed that prices of housing properties with a "green" label were 3.7% higher, and a Class A property was 10.2% more expensive than a similar property with a D rating (Brounen & Kok, 2011). More recently, Hui et al. (2016) conducted an assessment of the impact of green PM, reflected by the acquiring of various environmental management certifications, on property prices in MOH developments in Hong Kong. The findings showed that ISO 14,001 certification itself was not statistically significant in explaining property prices. It was only when the PM company obtained other local environmental management certifications that varying levels of positive premiums in property prices were found.
There are also some studies exploring how property owners and other professionals in the real estate management industry (e.g. asset and portfolio managers) perceive the impact of PM on property value creation. It turns out that many of them view PM as a commodity, which all passive real estate investors must procure, rather than a value-added professional service that positively contributes to investment performance (Read et al., 2016. Research on this topic has been further explored in a recent interview-based study conducted with real estate executives throughout the USA by Read and Carswell (2019). Interviewees were asked to discuss their perceptions about the roles property managers play in the value creation process and views about whether property managers generally have the skills and autonomy required to make value-accretive decisions. The findings suggest that significant perceptual cleavages exist in the real estate industry, with some executives believing property managers are incredibly important to the value creation process and others believing they play a much more modest role. Thus, the responses showed a considerable number of real estate executives continue to perceive property managers primarily as property value maintainers, as opposed to property value maximisers and perhaps too frequently dismiss their ability to independently leverage operational expertise to drive investment returns. Some of the responders still doubt whether property managers have the financial acumen or market knowledge necessary to improve the financial performance of real estate assets on a regular basis. These results emphasize the need for the PM industry as a whole to continue its efforts to gain recognition as a value-added professional service and for PM companies to actively take steps to differentiate themselves from competitors if they hope to avoid commodification and fee compression.
Nowadays, PM is increasingly considered as a branch of management science that emphasizes planning, organizing, motivating (people), and controlling (coordinating) property-related activities to achieve the owner's designated short-and long-term objectives, especially those related to enhancing the value of the managed property (Yiu et al., 2006;Muczyński et al., 2015;Marona, 2018). From this perspective, it is worth noting an interesting attempt by Uhruska (2016) to adapt the concept of Value-Based Management (VBM) from the business enterprise management domain to commercial property management in Poland. According to the author, implementing the VBM concept in the sphere of commercial PM is not to achieve a short-term increase in property value but to consciously use the potential of a property and its environment in order to maintain the property value at the highest level in the long-term. Therefore, systemic efforts to maximize the property value requires a comprehensive management strategy that ensures proper coordination of complex activities carried out in all PM areas while preserving an appropriate balance between the economic, technical and social objectives of this management, taking into account the interests of all stakeholders. Using the core assumptions of the VBM concept, the author developed a universal model of property value management, including its four basic functions and three task areas, such as technical, financial and space (and lease) management. The functions and task areas distinguished in the model were assigned specific management objectives (tasks) and performance measures within the process of commercial property value management. At the same time, the author concluded that this model is a simplified one, because due to the unique and sophisticated nature of each property, creating its value is a highly individualized process. Hence, it is extremely important in such a process to properly identify all factors determining the property value, which enables the managers to identify their real opportunities to impact this value and sets the direction and scope of their further actions.
In conclusion, the review of selected empirical results and research concepts showed that the impact of PM on property value in MOH is a topical and important problem but of a complex nature, as it is dependent not only on the institutional arrangement in such developments but primarily on the intensity (extent) and quality of services provided in this regard. It is generally believed that this impact is positive, but the opinions of researchers and professionals on its magnitude vary, as confirmed by reported findings. This is due not only to the different specifics of local housing markets but also to objective methodological difficulties in direct empirical measurement of the impact in question.

Methodology and data
In light of the reported literature studies and own research to date, as well as practical experience in property valuation, the hedonic regression method, also called the hedonic pricing method (model), was applied for empirical verification of the set research hypothesis and achieving the main aim of the paper. The method has its roots in Lancaster's (1966) consumer theory of complex goods. The theoretical concept was adapted by Rosen (1974), who developed the empirical framework of the method. The hedonic pricing method (HPM) is based on the hypothesis that goods are valued for their many utility-bearing attributes, each of which has an implicit price. The core assumption is that the price of each heterogeneous good is a function of its attributes. In hypothesizing the form of such a function, the method allows decomposing the known total prices of heterogeneous goods into measurable implicit prices of their individual components. Since housing properties are among the heterogeneous goods which price is a function of myriad attributes (locational, structural, neighborhood, etc.), this method enables to extract the implicit price (value) of separate property attributes from transaction prices. In general, the impact of individual attributes on property value is estimated using a regression model in which the price of a property is the response (dependent) variable, whereas its quantitative and qualitative determinants are explanatory variables. The strength and direction of this impact for the separated determinants are assessed by regression coefficients, which must meet certain statistical requirements. It is emphasized that since housing researchers cannot conduct controlled experiments in the laboratory, the HPM is the major scientific method by which one can observe the impact of housing attributes on housing prices, with the other factors holding constant (Chin & Chau, 2003). As one of the workhorse models of urban economics (Li & Monkkonen, 2014), the HPM has been frequently applied to housing markets in the world, including in the Polish context (e.g. Belniak & Wieczorek 2017;Trojanek and Głuszak 2018;Cellmer & Trojanek 2020).
In line with the research hypothesis, the HPM in this study was used to examine relationships between observable common property attributes dependent on PM services and dwelling transaction prices in MOH developments. The estimated influence (implicit values) of these attributes is expected to provide empirical evidence to identify the potential impact of PM services on the market value of dwellings in MOH developments in the studied housing market.
The research procedure used to accomplish the aim of the study involved the following stages: 1. Identifying an initial set of dwelling attributes as candidates for the role of independent variables explaining dwelling transaction prices in MOH developments, followed by defining measurement scales for these variables and determining ways to transform their values expressed on different scales to an ordinal scale in order to standardize the description (quantification) of the variables. 2. Collecting empirical data on transaction prices of dwellings (as the dependent variable) and their market attributes (as potential explanatory variables) in the sample of MOH developments in a given housing market during the period under study and updating the gathered dwelling prices as of a selected time point in order to eliminate the effect of the time factor on those prices. 3. Determining the strength and direction of statistical relationships between dwelling prices and their pre-selected attributes (potential explanatory variables) based on the values of calculated correlation coefficients, and performing the final selection of explanatory variables by reducing their initial set by those variables that are not correlated with the response (dependent) variable at the assumed level of statistical significance. 4. Choosing the analytical form of the hedonic regression model describing the hypothetical functional relationships between the transaction prices of dwellings and the established set of explanatory variables, followed by estimating the structural parameters of the model. 5. Statistical verification of the estimated model, which involved testing whether it meets standard statistical postulates regarding the significance of the structural parameters and the desired characteristics of the residual components and assessing the degree of its adaptation to empirical data. 6. Substantive verification of the estimated model involving the assessment of its consistency with theoretical and practical knowledge about the phenomenon under study, including the assessment of the strength and direction of the influence of explanatory variables on the response variable. 7. Identifying the potential impact of PM services on the market value of dwellings in MOH developments in the studied housing market on the basis of the estimated influence (implicit values) of the common property attributes on dwelling prices in positively verified regression models.
One of the key methodological problems was the choice of the analytical form of the regression function, especially since many various forms of modelled functional relationships are used in housing research, and hardly any consensus was reached in this regard. However, based on frequency, the log-linear form was probably the most popular form in applied research dealing with implicit values of housing attributes (Trojanek and Głuszak 2018).
The popularity of the log-linear form of regression function stems from its three major advantages (Malpezzi, 2008). First, this form allows the value added to adjust proportionally to changes in the dwelling attributes. Second, the estimated implicit values of independent variables (expressed by regression coefficients) are relatively easy to interpret. The coefficient of a given variable can be defined as a percentage change of the dwelling price caused by the unit change of that variable. Third, the log-linear function often reduces problems connected with heteroscedasticity in the model. Due its popularity among housing researchers and the advantages described above, the log-linear form of the regression function was chosen for the models describing the hypothesized functional relationships between dwelling prices in the MOH developments and their explanatory variables. The basic hedonic regression model was given by the formula: where: P -dwelling price per unit area as the dependent variable (in PLN per m 2 of useable floor area); X i -independent variables explaining the dwelling price including in MOH developments both the dwelling property and the common property attributes; β 0 , β i -the structural parameters (regression coefficients) of the model, including the coefficient β 0 as the intercept term and the coefficients β i (i = 1,…,k) reflecting implicit values of the independent variables; with each interpreted as the percentage change in dwelling price resulting from an additional unit of the corresponding variable); ε -the random error. Data on transaction prices of dwellings in MOH developments and their attributes potentially influencing those prices were collected on the local housing market of the city of Olsztyn in Poland (Fig. 1). This is a voivodeship capital city situated in the northeast of the country, which at the end of 2019 had 171,979 inhabitants and a total housing stock of 79,461 dwellings, most of which were in MOH developments. The highest percentage in this housing market was for 2-3 room dwellings with a usable area between 40 and 60 m 2 . The main research sample (S1) included the representative set of 150 MOH developments, consisting of three equally numerous subsamples (50 objects each), where PM services were provided by three different types of property managers: municipal companies (sample S2), housing cooperatives (sample S3) and private firms (sample S4). From each of the MOH developments, one typical dwelling transaction that took place from the last quarter of 2018 through the fourth quarter of 2019 was chosen. Those transactions for which there were doubts about their free-market nature (e.g. debt collector sales) were excluded. Data on dwelling transactions were obtained from primary information sources such as the public register of property prices of the Cadastral Office in Olsztyn and the property price registers provided by housing cooperatives. Data contained in the registers enabled to establish, in addition to the date and transaction price, the floor area of a dwelling and the floor level on which it is located. The data concerning the other attributes potentially influencing dwelling prices, therefore, were completed by additional methods. The locational attributes were measured using the Street View application on maps.google.com. In turn, the collection and assessment (measurement) of baseline data on the qualitative common property attributes was conducted by the direct observation method. In order to minimize the subjectivity of measuring these attributes, observations were conducted by two independent local housing market experts using equal assessment criteria.

Results and discussion
In identifying the initial set of attributes potentially influencing dwelling prices, the literature was analyzed, including selected meta-analyses (Chin & Chau, 2003;Sirmans et al., 2005) and prior studies on the property value enhancement effects of PM services in the housing sector (Hastings et al., 2006;Yau & Ho, 2009;Hui et al., 2011Hui et al., , 2016Mesthridge 2021). Besides theoretical premises, the empirical knowledge of the analyzed housing market and the aim of the research referring to modelling the market value of a property were important motives determining the initial set of the discussed attributes. The point is that this category of property value is created in the mind of typical market participants who are usually able to consider only a limited array of property characteristics when deciding on its price, and, for this reason, the initial set of dwelling attributes in practice should not be very numerous. Considering this rationale, eight attributes were selected for the initial set of independent variables explaining the transaction prices of dwellings in MOH developments, which were divided into two categories. The first included typical dwelling property attributes (DPA) such as overall location (OL), neighborhood location (NL), floor level (FL), and dwelling  Table 1. The values of the quantitative DPA attributes expressed on the ratio scale (OL, NL, DA) and interval scale (FL), respectively, were transformed to the ordinal (rank) scale according to the key in Table 1. In turn, the values of the qualitative CPA attributes were measured directly on the ordinal (rank) scale following the criteria described in Table 1. The adopted quantification manner of variables made it possible to achieve value comparability of the quantitative and qualitative variables at the cost of some loss of original measurement precision of the former. However, the quantification manner used was found to be acceptable as the benefits of its application exceed the losses, especially since typical market participants are generally not guided in their pricing decisions by the results of a very precise measurement of the quantitative variables under study.
After completing empirical data on dwelling prices in the sampled MOH developments and describing (quantifying) their attributes, in order to simplify the estimated models and obtain more accurate results on the impact of PM services on property value, all the collected prices were updated at the end of 2019 by simple regression method. On the basis of such processed data, the strength and direction of statistical relationships between dwelling prices and their pre-selected attributes were determined by correlation analysis. Due to the inclusion of the independent variables on the ordinal scale and relatively small research samples, Spearman's (r S ) and Kendall's (τ) rank correlation coefficients (Siegel & Castellan, 1988) were used in the correlation analysis. These coefficients take values between <-1.1 > but have different interpretations: the former can be treated in terms of the percentage of explained variability, while the latter is based on the difference between the probability that two variables are ordered in the same order and the probability that their ordering is different. The synthetic results of calculating coefficients are shown in Table 2.
The results presented in Table 2 indicate that the strength of the statistical relationship between dwelling price and individual attributes (at the significance level of p < 0.05) was mostly at the medium level (correlation in the range of 0.3-0.5). Considering the number of statistically insignificant coefficients, it can be noted that the common property (CPA) attributes were found to be more frequently correlated with a dwelling price than the dwelling property (DPA) attributes, especially in the main sample S1, where all CPA attributes proved to be statistically significant. In addition, the CO (cleanliness and orderliness) and LD (land development) attributes were found to be positively correlated with dwelling price in all samples, and their correlation coefficients took relatively high values, sometimes reaching the level of high correlation. All of the pre-selected attributes were described in such a way that their ranks increase as their expected influence on dwelling price rises. This means that the direction of statistical relationships revealed was generally positive, which was evident from the fact that almost all correlation coefficients revealed positive signs. The regularity was true for all presented attributes except the OL (overall location) attribute, for which the regression coefficients (both r S and τ) indicated negative signs with particularly high values in the main sample S1 and in sample S4 for MOH developments managed by private firms. An inverse correlation between dwelling prices and their overall location values is a phenomenon frequently observed in Polish cities. In the discussed study, this was due to negative effects on prices of relatively cheap and large dwellings located close to the city center in older (post-municipal) MOH buildings that were in poorer condition. How-  Technical condition of the MOH building. This variable was rated directly on the ordinal (rank) scale according to the technical condition of the common parts of the building: 1poor condition, need for major repairs due to significant wear and tear; 2 -moderate condition with minor wear and tear and damage, need for routine maintenance and minor repairs; 3 -good condition, no visible wear and tear or damage, no need for repairs or improvements. Building Accessibility (BA)

X 6
Accessibility of the MOH building (dwellings) to the elderly or people with disabilities. The attribute was rated directly on the ordinal scale according to the degree to which the building was provided with proper amenities to enhance this accessibility: 1 -no amenities for the disabled; 2 -providing the building with a ramp and elevator; 3 -providing the building with a ramp and elevator and ensuring parking spaces for cars used by the disabled. Cleanliness and Orderliness (CO) Cleanliness and orderliness on the common property. The attribute was rated directly on the ordinal scale according to the state of cleanliness and orderliness of common areas in and around the MOH building: 1 -bad state: neglected staircases, dirty floors, lingering trash in and around the building; 2 -medium state: staircases clean, single trash in and around the building; 3 -good state: staircases and the area in front of the building kept clean and in good order. Land Development (LD) X 8 Development of common areas surrounding the MOH building.
The attribute was rated directly on the ordinal scale according to the extent to which these areas were provided with outside facilities (improvements): 1 -no green areas, footpaths and roads in poor condition, no parking spaces; 2 -green areas, footpaths and roads neglected, limited number of parking spaces, no leisure and recreation facilities; 3 -green areas well maintained, footpaths and roads in good condition, arranged leisure and recreation facilities, sufficient number of parking spaces. ever, this resulted from positive effects on prices of relatively expensive and small dwellings located in the peripheral city zones in newer (sub-developer) buildings being in better condition. Based on the results of the correlation analysis, the initial set of dwelling attributes as potential independent variables explaining their prices was reduced in all research samples by those variables for which both correlation coefficients proved to be insignificant at the accepted level of statistical significance. It should be noted that positively verified independent variables by the correlation analysis were correlated with each other much weaker than with the dependent variable. Thus, the principle that a regression model should include variables that are highly correlated with the response (dependent) variable and at the same time relatively weakly correlated with each other was fulfilled.
Using the basic analytical form of the regression function (1) and the reduced sets of explanatory variables, hedonic pricing models were estimated for the main sample S1 (model M1) and the subsamples S2, S3 and S4 (models M2, M3 and M4, respectively) of MOH developments in the studied local housing market. Estimation of the structural parameters of the models was performed using the ordinary least squares (OLS) technique. Since outlier observations can significantly bias the regression equations, the estimation procedures for each of the models were conducted in two steps. First, the originally estimated models were subjected to residuals analysis, which allowed to eliminate the most outlier observations from the originally formed observation sets S1-S4 based on the Cook's distance criterion (Cook & Weisberg, 1982). On the outlier-cleaned samples, the final regression models M1-M4 were then estimated. These models showed a better fit to empirical data, higher parameter stability, and lower estimation errors compared to the originally estimated models. Standard statistical tests (following Aczel 2006;Goryl et al., 2009), such as Fisher-Snedecor (F) statistics, Student's tests, and Durbin-Watson (DW) statistics, were used to statistically verify the finally estimated models. In addition, coefficients of determination (R-squared and adjusted R-squared) and standard errors of estimation (S e ) were calculated. The hedonic regression results in the estimated models are presented in Table 3.
Based on these results, it was stated that the estimated models meet standard statistical postulates as the regression coefficients obtained were statistically significant (at p < 0.05), the residuals were symmetric, random in nature and revealed no autocorrelation. Moreover, given complex dependencies and conditions concerning property transactions in the housing market, it can be considered that the estimated models are characterized by the required (satisfying) adaptation to empirical data. This is evidenced by the relatively high values of R-squared coefficients (63.4-73.2%) and low values of standard errors of estimation S e (0.0447 to 0.0997), which, in relative terms, indicate the accuracy of estimating dwelling values with these models ranges from ± 0.6% to ± 1.2%. The obtained results, therefore, confirmed the statistical validity of the estimated models, including the correctness of the choice of the analytical form of the regression function and the sets of explanatory variables that significantly influence the dependent variable. Thus, the models provide a reasonable tool to assess the influence of the individual explanatory variables ceteris paribus on the dwelling value in each sample of MOH developments. Within substantive verification of the estimated models, their consistency with theoretical and practical knowledge of price formation and market value determination of dwellings in MOH developments was assessed. It should be noted that the regression analysis in models M1, M3, and M4 resulted in the further reduction in the sets of explanatory variables previously verified by correlation analysis. In consequence, the following variables were eliminated: X 8 (land development) in model M1, X 2 (neighborhood location) and X 5 (building condition) in model M3, and X 1 (overall location) in model M4, which can be justified by the relatively high correlation of variable X 8 with variables X 6 and X 7 in sample S1 and the low correlation of variables X 2 and X 5 with the response variable in sample S3, or the location specificity of MOH buildings in sample S4. Secondary reduction of the explanatory variables was, therefore, a logical extension of the correlation analysis. The strength and direction of the influence of extracted explanatory variables on the dependent variable were taken as the main criteria of substantive assessment of the models. This was carried out by assessing the consistency of signs and values of the regression coefficients located at individual variables. On the one hand, given the adopted way of variable description, the signs of the estimated regression coefficients were found to be consistent with a priori expectations. This is due to the fact the direction of influence of the individual explanatory variables on the dependent variable was generally positive. It should be emphasized that this regularity occurred for all common property variables (X 5 -X 8 ) in each of the estimated models. The only exception was variable X 1 (overall location) in model M1, whose influence proved to be negative again, which was expected given the correlation results and was explained above. On the other hand, taking into account the presented interpretation of regression coefficients in log-linear models, the values of the estimated coefficients were considered to be reasonable, as they were consistent with the theory of property valuation and corresponded to the practical experience of real estate appraisers on the analyzed housing market. The estimated values of these coefficients indicate that the average strength of the influence of a unit change in particular common property variables ranged, ceteris paribus, respectively: 3.3% for X 5 (building condition), 3.8% for X 6 (building accessibility), 4.7% for X 7 (cleanliness and orderliness), and 3.6% for X 8 (land development). Noteworthy is the variable X 7 , which revealed a relatively high influence on the market value of dwellings in all estimated models, and which remains under the direct control of the property manager. To enable easier comparison of regression coefficients in the estimated models, they are listed separately in Table 4  The obtained findings have therefore confirmed that there are statistically significant positive relationships between observable common property attributes dependent on PM services and dwelling prices in MOH developments in the studied housing market. This makes it possible to conclude that the research hypothesis posed in the introduction was positively verified by empirical research. In other words, the extracted common property attributes were actually perceived by market participants as value drivers, as evidenced by their significant impact on dwelling prices in that market. Since these attributes are dependent on the intensity and quality of PM services, the estimated influence of them on dwelling prices identifies the potential impact of PM services on the market value of dwellings in MOH developments. This means that if the property manager (or owner) made decisions and actions to introduce the new and/or maintain the existing state of the considered common property attributes as part of the PM services, it was statistically proven that this had an impact on the market value of dwellings in MOH developments in the studied housing market. This is a potential impact because for it to manifest itself, it is necessary to include active influence on individual common property attributes in the scope of PM services, and furthermore, it is difficult to conclusively determine to what extent managerial and to what extent executive activities have contributed to changes in these attributes, which, as a result, have had an impact on the market value of dwellings. The magnitude and structure of this impact are also determined by the estimated implicit values of the common property attributes. Determining the real impact of PM services on the market value of dwellings in the presented methodology requires further in-depth object-oriented research to assess the factual contribution of these services in shaping the value-creating attributes related to both common and individual properties.

Conclusions
Given the expanding role and importance of property management in many housing markets, the impact of these services on property market value is undoubtedly a topical research problem of a global scope and a complex nature. This problem takes on special relevance in MOH developments, various forms of which are increasingly proliferating in different parts of the world, currently comprising a large proportion of the world's housing stock. Although many authors have emphasized the impact of PM on the market value of a managed property, there have been relatively few efforts to measure it quantitatively, and there is still no consensus among researchers and professionals on the issue. This is particularly true for empirical studies in MOH developments, where the issue is largely ignored for various reasons. In an attempt to contribute to filling the gap, in this preliminary study, the potential impact of PM services on the market value of dwellings in MOH developments existing under Polish conditions using a selected local housing market was investigated. The methodological achievement of this paper is the conceptualization and operationalization of an original research methodology based on the triangulation of research methods tailored to the institutional arrangement in MOH developments. It assumes that PM services in such housing properties are mainly focused on the common property, but their potential impact on the property market value can only be manifested in dwelling prices since the common property, as such, cannot be traded on the market. Therefore, the said impact of PM services was estimated from dwelling prices, however, not directly, but in an indirect way, based on its symptoms reflected in common property attributes. In turn, the empirical achievement of this paper is to empirically evidence by means of hedonic regression models the influence of the common property attributes, observable by potential dwelling buyers and simultaneously dependent on PM services, on the market value of dwellings in MOH developments in the studied housing market. The implicit values of these attributes identify the magnitude and structure of the potential impact of PM services on the market value of dwellings in MOH developments in this market. In synthesizing the findings obtained, it can be concluded that, in extreme cases, this impact can reach, in average terms, the level of 15.4% of the market value of dwellings with cumulative unit changes in all common property attributes, and even the level of 30.8% of the value with cumulative double-unit changes in those attributes. Thus, these findings suggest that real efforts of property managers to improve the common property attributes may significantly add value to dwellings in all studied types of MOH developments.
The research conducted has its limitations as the constructed hedonic pricing models are, as usual, location-specific, so it is difficult to generalize them to different locations, all the more so since this study is pioneering in Polish conditions and the scope of empirical research was limited to the selected housing market. Therefore, these models are primarily used for an understanding of the "psyche" of the particular housing market. However, they can also give ideas about those characteristics of dwellings in MOH developments that are consistently valued by dwelling buyers across different locations. Other limitations of this research may be due to the relatively small sample sizes and the problem of omitted variables. However, given the modeling aim, which was the market value of dwellings created by typical local market participants, the adopted sample sizes were considered sufficient. From this point of view, the omitted variables problem is very limited as the models omitted only a few dwelling attributes that may possibly be influenced by PM services (e.g. increased rent incomes, cost savings, etc.). However, it raises the question of whether data on such attributes were available and relevant to dwelling buyers in the market. In turn, limitations due to measuring the subjectivity of qualitative attributes were minimized with the help of experts who mapped the way these attributes were assessed by typical participants in the local market.
Good insights into which dwelling attributes in MOH developments are positively valued by the market, and by how much, might have far-reaching policy and practical implications. These policy implications relate to the use of such knowledge to improve urban development policies, particularly concerning the built environment, land use and local housing through relevant plans, decisions and actions made by local governments, city planners, housing politicians, and other public administrators. Moreover, those insights help institutional and individual housing market investors to make better business strategies and investment decisions. In turn, practical implications of insights into how common property attributes dependent on PM services are valued by the market relate primarily to MOH developers and HOAs, as well as to individual owners and potential buyers of dwellings and property managers. Such knowledge gained by developers can drive changes in designs and amenities applied to MOH buildings, and in the ways common areas are developed around the buildings. In contrast, for HOAs and individual dwelling owners, it can become an attractor for a more active repair and investment policy on common parts of buildings and jointly owned areas, as well as increasing social awareness in caring for common property. It might, consequently, cause more interest among HOA members in increasing the extent and quality of PM services contracted and the need to build trust in professionals. Wellpublicized knowledge in society on the dwelling value-enhancing effects by improving common property attributes drives potential dwelling buyers to pay price premiums added for dwellings in more attractive and better-maintained MOH developments. These effects identify the potential impact of PM services on dwelling prices, thereby indicating ways by which property managers can play an active role in the value-creation processes of dwellings in the marketplace. Thus, they create needs and reveal opportunities for advancing property management in MOH developments as a property value-enhancing professional service. This preliminary study is part of a research stream promoting the improvement of PM services in such a direction. Further research on the topic is recommended to explore the conditions, ways and ranges in which property managers really impact the market value of housing units in MOH developments located in other markets operating under different institutional arrangements.
Author contributions The paper has a single author, which means Conceptualization, Methodology, Formal analysis and investigation, Writing -original draft preparation, Writing -review and editing, Funding acquisition, Resources, Supervision, etc. were done by Andrzej Muczyński.
Funding Partial financial support was received from the University of Warmia and Mazury in Olsztyn, Faculty of Geoengineering, Institute of Spatial Management and Geography, Prawocheńskiego 15, 10-720 Olsztyn, Poland.

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