Housing logic: Rationalities behind housing choice behavior in coping housing market dynamics among urban residents in Sebeta Town, Ethiopia

Debele, Efa Tadesse; Negussie, Taye Article Housing logic: Rationalities behind housing choice behavior in coping housing market dynamics among urban residents in Sebeta Town, Ethiopia Research in Globalization Provided in Cooperation with: Elsevier Suggested Citation: Debele, Efa Tadesse; Negussie, Taye (2022) : Housing logic: Rationalities behind housing choice behavior in coping housing market dynamics among urban residents in Sebeta Town, Ethiopia, Research in Globalization, ISSN 2590-051X, Elsevier, Amsterdam, Vol. 5, pp. 1-11, https://doi.org/10.1016/j.resglo.2022.100099 This Version is available at: https://hdl.handle.net/10419/331026 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes. You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public. If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by-nc-nd/4.0/ Research in Globalization 5 (2022) 100099 Available online 29 September 2022 2590-051X/© 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/bync-nd/4.0/). Housing logic: Rationalities behind housing choice behavior in coping housing market dynamics among urban residents in Sebeta Town, Ethiopia Efa Tadesse Debele a , * , Taye Negussie b a Research in Globalization, Samara University, Afar, Ethiopia b Addis Ababa University, Addis Ababa, Ethiopia ARTICLE INFO Keywords: Housing logic Housing market dynamics Housing choice behavior Coping ability ABSTRACT Urban residents do have rationalities and justifications for the housing situation they are living in. This research is aimed to address the research question that proposed why housing choice behavior is different from person to person and why residents choose the housing type that they are living in given that in the dynamic housing market there are different housing options. The researchers are dedicated to investigating housing logic that guides urban housing choice behavior as a response to housing market dynamics. Understanding the housing logic behind the housing choice behavior of urban residents in a dynamic housing market is a logical basis of this research. This study benefited from both theoretical and empirical analysis because the literature review was supported by empirical observation. To achieve the research objective, the explanatory mixed-method sequential research design was employed where quantitative data were collected from 384 respondents who were randomly selected whereas qualitative data were collected via in-depth interviews and focus group discussion. Urban residents decided to utilize housing type that fits their overall socio-economic capacity and coping abilities. Findings indicated that urban residents shifted their housing choice from formal to informal markets which imply the logic of housing choice behavior. This shifting has happened due to the lowered extent of supportiveness of formal housing market dynamics and the decline of coping abilities that was associated with the socio-economic crisis. The authors came up with the conclusion that the major housing choice logic of urban residents is affordability, accessibility, adequacy, and aptness factors. The authors would like to suggest to the municipality to strengthen the formal housing market given that the informal housing market is likely to aggravate social injustices and inequitable housing development. Introduction Housing market dynamics have resulted in multiple housing options that urban residents could choose among existing housing types by considering coping factors. Housing choice has its logic that influences the housing situation residents can live in. This study was proposed to uncover the housing logic underlying the housing choice behavior of urban residents. Housing logic is the new housing research concept that authors are motivated to ground on it in understanding the housing choice behavior of urban residents. This research question is intended to contribute to housing literature thereby promoting theoretical and analytical development of housing study. In this regard, Gilbert and Varley (2002) argued that self-help homeownership is the primary choice of urban residents because it provides multiple advantages but the unavailability of housing land significantly decreases formal homeownership aspiration. It was identified that public housing has been the most preferable accommodation for the urban poor even though the current demand for public housing is decreasing (Williams, 2004). In this article researchers identified housing logic that guides the housing choice behavior of urban residents. Housing logic is unique and has a contribution to the housing literature since it constitutes a fundamental idea that governs the housing system and guides the housing choice behavior of urban residents. Housing status and housing choice behavior of urban residents are influenced by dynamics in disposition, social networks, and institutions. Housing status and housing choice behavior are largely determined by the extent of structural supportiveness. Understanding housing connections with other social structures and their functions in the overall structure gives better insight into the housing question of why residents choose different housing categories (Madden and Marcuse, 2016). * Corresponding author. E-mail addresses: [email protected], [email protected] (E.T. Debele). Contents lists available at ScienceDirect Research in Globalization journal homepage: www.sciencedirect.com/journal/research-in-globalization https://doi.org/10.1016/j.resglo.2022.100099 Received 31 July 2022; Received in revised form 17 September 2022; Accepted 28 September 2022 Research in Globalization 5 (2022) 100099 2 Housing choice of urban residents is determined by tenurial suitability, adequacy of housing supply, financial affordability, level of formal housing accessibility, and overall housing market supportiveness (Fitzpatrick and Watts, 2017; Larsen et al., 2019; Beswick et al., 2019; Debele, 2019). The empirical findings confirmed that addressing the housing question via the housing logic theoretical framework has relevant to vibrant housing literature and debate which is likely to make local and international readership to be interested in the argument. Housing tenure type and housing choice behavior are influenced by the level of housing policy supportiveness, affordability of the housing market, accessibility of desirable housing types, the adaptive capacity of residents, and suitability of housing tenure (Kettunen and Ruonavaara, 2020; Issar, 2020; Robinson et al., 2020; Andersson et al., 2020). Authors argue that housing logic has the potential to add value to existing housing knowledge other than the different case study contexts by engaging with and contributing to wider academic discussion and debate. This affirms that the conclusion of the paper has contributed beyond the different geography of the study area. The unaffordable housing market, unsupportive structures, crisis in coping capacity, the extent of tenure security, and accessibility of desirable housing tenure affect the housing choice behavior of urban residents (Wimark et al., 2020; Matznetter, 2020; Stephens, 2020; OECD, 2020; Preston et al., 2021; Bangura et al., 2021; Weinstein, 2021). Unsupportive institutions which accompany urban residents’ adaptive capacity decline contribute to deteriorated informal housing situation (G.Berhanu et al., 2022). Furthermore, so far housing literature has provided an inadequate framework to understand housing research and is ineffective to address the housing question. Thus, the researchers are motivated to address the research question that proposed why housing choice behavior is different from person to person and why residents choose the housing type that they are living in given that in the dynamic housing market there are different housing options. Empirical research findings indicated that self-housing or homeownership, cooperative housing, informal housing, rental housing, social housing, etc are major housing options from which residents can choose the most suitable one. Housing logic is a key theoretical framework that researchers applied in this paper to understand the housing choice behavior of urban residents. Thus, researchers aimed to identify strategies that urban residents apply to cope with housing dynamics, uncover the set of principles underlying housing choice behavior, and establish the causal relationship between housing market dynamics and the logic of housing choice behavior of urban residents. Despite its major strong points, the argument of housing logic lacks adequate theoretical evidence on certain variables. This has happened due to either the housing logic concept was not scientifically noticed or the researchers were unsuccessful to access them. In addition, taking into consideration resources and time to be taken, this study could not address all aspects of housing. This implies housing research is an untapped research area that interested researchers of different disciplinary backgrounds could engage in it. Literature review A rigorous literature review has been undertaken thereby linking gaps in the literature to the research question of the study. Housing logic is a useful approach to understanding housing questions compared to previous housing research approaches and theoretical frameworks. Researchers reviewed works of previous literature to confirm the strength of housing logic as alternative new housing research approach. Acquisition of preferred housing option is associated with affordability, procedural serviceability, housing availability, absence of residential segregation, spatial hospitability, equitability of housing opportunities, purchasing and renting capacity, disposability of income, and enabling political-economic conditions (Issar, 2020; Wimark et al., 2020; Ng et al., 2020; Fields and Rogers, 2021). Previous housing researches provide an inadequate theoretical framework that can contribute to a better understanding of empirical housing situations. In this regard, this study was framed to provide an adequate theoretical, analytical, and empirical framework for housing research. Achieving desirable adequate housing type requires the existence of security, comfort, potential longevity, sufficient basic facilities, spatial friendly, infrastructure development, accessible mortgage, legal ownership, satisfaction, and the existence of sufficient housing units (McArthur and Stratford, 2020; Teodorescu and Molina, 2020; Charitonidou, 2021). Housing choice behavior is a dynamic activity. Thus, the fulfillment of certain requirements for housing questions does not guarantee a concluding statement for housing choice behavior. In this regard, housing logic is proposed to address theoretical, analytical, and empirical knowledge gaps that exist in the housing literature. Choosing a desirable housing tenure type is influenced by housing policy, housing market affordability, housing resources, suitability of tenure, housing safety and security, level of state intervention, social factor, cultural factor, and spatial factor (Kettunen and Ruonavaara, 2020; Issar, 2020; Robinson et al., 2020; Andersson et al., 2020). It was noticed from the reviewed literature that establishing a causal relationship between housing market dynamics and the logic of housing choice behavior was not realized yet. Previous literature provides inadequate research schemes to frame housing research with a theoretical and analytical framework that can guide empirical housing research. The political economy of housing, subsidization of housing, minimum housing quality standard, the habitability of residence, safety, family factor, socio-economic status, degree of tenure security and freedom, level of legal protection, mortgage situation, financial strain, and rental factors influence residents’ decision to choose the appropriate housing category (Robinson et al., 2020; Harrison et al., 2020; Bierre and Howden-Chapman, 2020; Wimark et al., 2020; Ng et al., 2020; Foye, 2021; Preston et al., 2021; Mehdipanah et al., 2021). Housing research needs a unifying theoretical and analytical framework that corrects fragmented housing research and housing literature. In this regard, this paper filled the gaps in previous literature by exhaustively and carefully incorporating theoretical, analytical, and empirical frameworks. Dynamics in the housing market, demand and supply imbalances, unsupportive structures, unaffordable rental options, income dynamics, level of tenure security, socio-economic status disparities, housing price, legal protection, and eviction situation are major factors that influence the housing choice of urban residents (Wimark et al., 2020; Matznetter, 2020; Stephens, 2020; OECD, 2020; Preston et al., 2021; Bangura et al., 2021; Weinstein, 2021). Even though previous literature contributed to housing studies, they provide an inadequate theoretical, analytical, and empirical framework that is more likely to advance understanding of housing issues. Housing logic is an innovative research approach that researchers used in this study which was proven to be a relevant and useful approach for housing research. It is believed that housing choice behavior leads to interaction and exchange in which some cost burden and others enjoy gains. Unfair housing development necessitates a coping mechanism that addresses minimal survival questions. Housing land market affordability problems and formal housing procedural challenges are major reasons that restrict the housing choice of urban residents to the rental sector (Shitaye, 2022). Even though there are bundles of housing options for one’s choice, homeownership has been symbolized as a major life change in one’s life that reflects housing development. Any housing category is the outcome of a system or a set of principles that are underlying the housing choice behavior of urban residents. Given that affordability, accessibility, adequacy, and aptness (4As) are the foundational elements of the theory of housing logic in this study. The hypothetical relationship between the rationalities of urban residents and their housing choice behavior was tested in empirical research (see Fig. 1). E.T. Debele and T. Negussie Research in Globalization 5 (2022) 100099 3 Methodology Description of the study area The study area is longitudinally located at 44◦36′30′to 44◦40′30′ East whereas its latitudinal location is 8◦54′56′North. Relatively, Sebeta town is located southwest of Addis Ababa city, southeast of (Fig. 2.) Burayu town, west of Akaki Kality Sub-city, and North of Tefki town. Research approach In this study, the pragmatism paradigm is supposed to guide the mixed method. Accordingly, triangulation of quantitative and qualitative data was done. Survey questionnaires, in-depth interviews, and focus group discussions were principal data collection tools. This was intended to substantiate theoretical and empirical knowledge gaps by the process of synthesizing findings obtained from quantitative and qualitative analysis. Source of the Data: Primary and secondary data sources In this study, both primary and secondary data sources were used. Primary data were collected through questionnaires, in-depth interviews, and focus group discussions. Secondary data was collected from various archives like journal articles, books, suggestion boxes, and governmental and non-governmental organization relevant documents. Archival data sources were official reports, profiles, suggestion boxes, websites of organizations, and personal diaries. Thus, the researchers intended to extract those data from housing institutions’ recollections. 3.4.Study population The study population consists of the urban residents living in Sebeta town. Urban residents are the target population regardless of their social positions. They share a common trait or characteristic that helped the researchers to use a stratified survey for the quantitative part whereas factory workers, officials, experts, renters, owners, brokers, and informal settlers were included in the qualitative part. The researchers argue that information taken from all categories of urban residents can fully reveal the existing housing situation and housing problems. This shows studying housing market dynamics, the logic of choosing a housing type, and housing choice behavior is viable and plausible. Sample size estimation The study population lives in a large geographical area which complicates the sampling procedure. The researchers decided that the target population is urban residents. Residents are scattered throughout the sample area, so grouping the target population based on their living Fig. 1. Conceptual framework of rationalities of housing choice behavior (Debele and Negussie, 2022). Fig. 2. Map of Ethiopia, Oromia, and Sebeta town (Debele and Negussie, 2022). E.T. Debele and T. Negussie Research in Globalization 5 (2022) 100099 4 place is crucial. This leads to the stratified sampling technique or stratified proportional sampling. Cockerham’s single population proportion formula is crucial and effective when there is no list of population or sample frame. Thus, the researchers decided to apply this formula expecting a larger sample size that yields more reliable data. The largest possible proportion (p) of the target population with housing characteristics important to the study is 0.50 (50 %), the allowed margin of error (d) is 5 %, desired reliability (alpha) is 95 % (0.95), and the most confidence level value which is 1.96 taken by assuming that it gives more reliability and precision. The estimated design effect (DEFF) is 1 because the prevalent attributes of the groups are the same; there is no significant disparity in characteristics. So, the estimated sample size (n) can be computed as follows: Sample size estimation equation. n=(z α 2)2p(1−p) (d)2 n=(1.96)2.5(1−.5) (.05)2 n=(3.8416)(.25) (.0025) n=0.9604 0.0025 n=384 By considering the subgroup size, the researchers selected the respondents through proportional sampling techniques. Since the size of the sample for each group was proportional to the size of the subpopulation in each stratum, it was said to be stratified proportional sampling. Then the required number of samples within each subgroup was drawn by using a systematic sampling technique which was stratified systematic sampling techniques. In using this design researchers had to first establish the sampling interval using this formula: Sampling interval computation. k=N n Where: k =is the sampling interval. N =is the total number of the population. n =is the total number of the sample. Computation of substratum sample size. nk=Nk.n N The researchers incorporated 384 respondents from ten administrative units located in Sebeta town. Proportional sampling techniques were employed to select respondents from each unit proportionally based on the subgroup population size. Thus, it was assumed that the stratified proportional sampling technique was better to reveal existing housing development in the study area. Data collection tools Survey questionnaire The questionnaire is prepared by using multiple choices and scaling types of response variables. The researchers incorporated 384 respondents from ten administrative units located in Sebeta town. In collecting data, 10 skilled or experienced data collectors who are Sebeta town residents and fluent in local languages were recruited. These data collectors were given short training on data collection procedures. During the training, the data collectors were briefed on the designed questionnaire, data collecting techniques of the study, and possible challenges during questioning and responding. Each enumerator collected data for 2 days and each data collector was assigned to a single unit. For better data management and research work effectiveness as well as to avoid unnecessary repetition and missing, each data collector was assigned a specific unit. Accordingly, the data collectors randomly went to homes of households living in each village to get in touch with the respondents and extracted data. In the course of questioning, the data collector approached respondents who were systematically chosen. In-depth interview The informants were assumed to be more knowledgeable than the other members of the community owing to their socio-economic position as per information obtained from each village administrative office. Thus, 40 more knowledgeable research informants were purposively selected (purposive sampling) as interviewees. This tool was expected to address sensitive issues such as pains, suffering, injustices, tragedies, and catastrophic conditions in the housing sector. Accordingly, private homeowners, real estate owners/delegates, renters, officers, representatives of housing cooperation, agencies, brokers, squatters, etc were interviewed. The interview was conducted by the investigator using interview guiding questions. During each in-depth interview, the same flow of discussion was tried to follow and notes were taken down. An interview was held at a secured place where there was no interruption; the privacy of the interviewee was well maintained after obtaining verbal consent from the informants. Focus group discussion This tool was used to get adequate and timely data through an interactive mode of information exchange. This data-gathering instrument is believed to be very important since it gives freedom for the informants to express their ideas, opinions, views, and understanding of the housing situation. FGD was intended to generate data on residents’ views about the issues of housing market dynamics, coping mechanisms, and logic of housing choice behavior. FGD informants were in five groups (1. housing officers, 2. owners, 3. renters, 4. brokers, and 5. squatters) and each of the groups had 8 informants which means there were a total of 40 informants. The process involved the researchers as moderators and note-takers, and the facilitator was chosen from residents who shared similar characteristics with the discussants. Homogenous FGD informants were selected based on housing-related job categories, involvement in any housing-related affairs, and housing status categories of people whose residence was confined to Sebeta town, and the researchers selected discussants judgmentally from the rest of the urban residents. The discussion was held in the appropriate place for FGD participants and was suitable for discussion. Permission was obtained from the local administrator for a place to conduct a focus group discussion (FGD). The researchers moderated the discussion in the local language using guiding questions. Data analysis and presentation The quantitative and qualitative data obtained through the predetermined data collection tools were analyzed using appropriate methods of analysis as explained below. Quantitative data analysis and presentation The quantitative approach exploits statistical analysis. The quantitative data were coded and entered into a computer for analysis. The SPSS version 20 software was used as an analysis tool. The association between variables was checked or tested by chi-square tests. This test statistic determines the correlation between the extent of supportiveness of housing market dynamics and the housing situation. Accordingly, frequencies, percentages, tables, graphs, chi-square test, and association analysis were employed. Qualitative data analysis and presentation The qualitative data were analyzed by organizing, summarizing, and E.T. Debele and T. Negussie Research in Globalization 5 (2022) 100099 5 interpreting the data collected qualitatively. In short, thematic analysis was used. In other words, qualitative data were analyzed descriptively in the form of narration. This part dealt with the results extracted from the in-depth interview and focus group discussion. Results and discussion Background information of respondents Gender Housing development requires confrontation of structural challenges. It seems that males and females are likely to differ in confronting structural challenges in the context of this particular study. Males are more likely to defend against structural challenges than females. Females are mainly expected to bargain either by providing money or being sexually abused. It is found that sexual harassment and genderbased violence are common in service delivery. Females abstain from making effort to own their house by fearing gender-based challenges. Relatively, males can either confront or indulge in corrupting activities just to enter homeownership status. Culturally, females are expected to be submissive to their husbands. This expectation discourages females to be owner-occupiers because they believe that homeownership can be achieved via their partner. Even supposing out of this study scope, research participants seemed to think that females were more likely to prefer to marry homeowner males. Table 1 indicates that 43.8 % of male respondents are homeowners, while only 19.3 % of female respondents are a homeowner. It also seems that males are more likely to squat (22.2 %) than females. It found that females (70.2 %) are more likely to be renters than males (34.0 %). Table 1 shows that the association between gender and housing status has a statistically significant relationship. The Chi-square test confirms that gender and housing status variable is related to each other. This does not mean that gender is a predictor variable of a resident’s housing status. It is expected that the gender characteristics of individuals can influence their housing development and homeownership aspiration. Migration status The geographical background is usually considered a criterion for social group formation. Social groups formed by geographic background can create enabling situations for urban residents’ homeownership and housing development in general. It seems that the migration history of residents contributes to their housing status. In this regard, residents look for their fellow locals, in so doing form enabling social networks that facilitate housing development. Local social associations, such as ’Iqub and Afosha’, 1 mostly made their bases on the resident’s birthplace history. This creates trust among residents that help them to form enabling the situation to enter homeownership. The migration history of residents is found to be contributing factor to the housing development of residents. Table 2 shows that 77.9 % of indigenous residents are homeowners, while only 12.9 % of migrants are a homeowner. It seems that migrants are more likely renters than indigenous residents. Indigenous residents are found to have better comparative advantages for homeownership than migrants. Indigenous residents are assumed to have parents that have tenurial rights in the town. This parental factor contributes to the homeownership of children. Indigenous residents are expected to have access to urban land and can afford collateral requirement that facilitates their homeownership. On the other hand, migrants lack local advantages that constrain them to join homeownership. Most migrants found rental housing their accommodative housing option. Economically powerful migrants are more likely to enter homeownership than poor migrants. It is found that individuals who engage in constant mobility lack housing opportunities anywhere. Migrants that decided to settle permanently in a certain area are more likely to enter homeownership than migrants that move from one town to another town. Migration affects the overall housing development of individuals and the homeownership rate. The finding shows that indigenous residents are more likely to enter homeownership than migrants. It was explained that indigenous residents have more comparative advantages that facilitate the housing ladder. The local position of residents and parental housing history intersection creates different rates of homeownership among indigenous residents and migrants. In this intersectional modeling, indigenous residents are twice as migrant residents’ homeownership likelihood. Migrants are doubly disadvantaged because of immigrant and parental indifference whereas indigenous residents are doubly advantaged because of locals and parental supportiveness. Migration history of residents is found to be a factor that impacts homeownership inequalities and beneficiary of housing opportunities. It is found that migration history is not necessarily a sufficient condition to affect residents’ rates of homeownership but its intersection with other enabling and constraining factors are important factors. Ethnic category Ethnicization of housing development is common in many urban centers including in the study area where ethnic background affects the homeownership opportunity of residents. Residents are either privileged or underprivileged because of their ethnic background if the housing is intended to be a source of political bargaining. Political actors know that the critical urban problem is the housing problem. Presenting housing as bargaining apparatus and exploiting political support is quite common. It is believed that inequitable housing development is associated with ethnic factors. The absence of an inclusive and rational housing policy opened the door for the prevailing ethnicization of urban housing. Residents consider ethnicity as bargaining power with the political structure. Ethnic factors determine the housing category of residents by gathering the same ethnic group to capitalize on their social capital and convert this bondage into economic capital. Findings revealed that ethnic factors alone do nothing but intersect with political affiliation. It seems that ethnic factors have two dimensions. It is a risk factor if incompatible with a political affiliation that increases housing vulnerability, but a prospective factor if intersects with political affiliation. This was/is a practical housing reality in the Ethiopian context. Table 3 shows that some ethnic groups are more likely to be homeowners, while others are more likely renters and squatters. Typically, 57.1 % of respondents who are of Tigre ethnic background are homeowners while 17.9 % of respondents who are of Oromo ethnic background are homeowners. On the other hand, 73.2 % of respondents who are of Oromo Ethnic background are renters, while only 28.6 % of respondents who are of Tigre ethnic background are renters. This implies ethnic background and housing status are related variables. The Chisquare value and probability value indicate that the ethnic category and housing category are unlikely independent of each other. Table 3 confirms that Tigre ethnic backgrounds are more likely homeowners, while Oromo ethnic backgrounds are more likely renters. This statistical significance is supported by substantive significance. Last three decades TPLF ruled Ethiopia by making ethnic federalism its core value of governance. The regime abused ethnic federalism by exploiting material and nonmaterial resources. Sebeta town was the regime’s laboratory of exploitation. It has taken long periods when the regime encroached on Sebeta lands in different strategies of exploitation. The collaboration between investors and the regime on resource exploitation in most cases land resources made Sebeta the most victimized town during the last three decades. Corruption has become a mainstream culture of the regime and still now its existence is beyond reminiscence. Ethnicization was the paramount political economy of the TPLF-led regime. Its impact resulted in a formidable mafia that exploits public resources directly or indirectly. The ethnic background of residents may affect their housing 1 The informal association organized by locals for social and economic purposes. E.T. Debele and T. Negussie Research in Globalization 5 (2022) 100099 6 development either positively or negatively. Table 3 statistics show that the Oromo ethnic category negatively associates with homeownership while Tigre ethnic background positively associates with homeownership. Housing market dynamics and coping behaviors Urban housing is categorized into formal and informal housing typologies based on tenurial rights and legal title. Researchers conducted a qualitative study concerning the extent and prevalence of both housing categories. It happened that dynamics in the urban housing sector produce structural tensions between formal and informal tenancies. Interviewees (Brokers) who had developed broking experience in both formal and informal housing reported that the informal housing category is getting predominance over formal housing. The interviewees justified that formal housing is unaffordable and its bureaucratic challenge pushed residents towards informal housing. Informal housing is relatively cheaper and free of bureaucratic challenges. Table 1 Gender *housing category crosstabulation. Your housing status Total Homeowner Renter Squatter Gender category male Count 89 69 45 203 % within the Gender category 43.8 % 34.0 % 22.2 % 100.0 % female Count 33 120 18 171 % within the Gender category 19.3 % 70.2 % 10.5 % 100.0 % Total Count 122 189 63 374 % within the Gender category 32.6 % 50.5 % 16.8 % 100.0 % Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square 48.656 a 2 0.000 Likelihood Ratio 49.841 2 0.000 N of Valid Cases 374 Table 2 Migration status*housing category crosstabulation. Your housing status Total Homeowner Renter Squatter Migration status Indigenous residents Count 88 4 21 113 % within Migration status 77.9 % 3.5 % 18.6 % 100.0 % Migrant Count 33 183 39 255 % within Migration status 12.9 % 71.8 % 15.3 % 100.0 % Total Count 121 187 60 368 % within Migration status 32.9 % 50.8 % 16.3 % 100.0 % Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square 172.657 a 2 0.000 Likelihood Ratio 195.749 2 0.000 N of Valid Cases 368 Table 3 Ethnic category*housing category crosstabulation. Your housing status Total Homeowner Renter Squatter Ethnic category Oromo Count 30 123 15 168 % within Ethnic category 17.9 % 73.2 % 8.9 % 100.0 % Amhara Count 40 30 27 97 % within Ethnic category 41.2 % 30.9 % 27.8 % 100.0 % Tigre Count 4 2 1 7 % within Ethnic category 57.1 % 28.6 % 14.3 % 100.0 % Gurage Count 27 16 11 54 % within Ethnic category 50.0 % 29.6 % 20.4 % 100.0 % Silte Count 14 10 5 29 % within Ethnic category 48.3 % 34.5 % 17.2 % 100.0 % other Count 3 2 2 7 % within Ethnic category 42.9 % 28.6 % 28.6 % 100.0 % Total Count 118 183 61 362 % within Ethnic category 32.6 % 50.6 % 16.9 % 100.0 % Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square 68.296 a 10 0.000 Likelihood Ratio 69.485 10 0.000 N of Valid Cases 362 E.T. Debele and T. Negussie Research in Globalization 5 (2022) 100099 7 Informal housing is generally initiated and facilitated by brokers. Interviewees stated that brokers identified the profile of potential land for informal housing. Brokers disclosed that it is possible by using GPS coordinate point (XY) to identify the pattern of housing in a given area. Brokers further revealed that they are expected to approach an ICT expert who knows the plan of the required place. If the area is planned for housing it is more likely to be squatted. Researchers asked about the possibility of legalizing informal housing and brokers clarified that the cooperation of farmers makes the legalization process easy and effective. Farmers defend squatters claiming that he or she was their son or daughter. This is believed that farmers have complained about compensation and many of them did not receive compensation. They fear the upcoming development project may displace them. The compensation is in most cases inadequate to rehabilitate and substitute their lost agricultural output. Brokers further indicated that higher officials receive money while the legalization process takes place. They take much money from squatters and easily formalize illegally built housing. Brokers play a mediation role. Brokers confirmed that officials support them by facilitating the legalization process. This implies that existing structural actors deliberately paralyze formal homeownership aspiration and incentivize informal housing by engaging in it directly or indirectly. Formal housing development is more likely to deteriorate whereas informal housing becomes more preferable housing tenure. Focus Group discussants addressed that customers that cannot pay cannot access housing services. The modus operandi appears to be ‘no pay, no services’. This trend makes residents suffer from bad bureaucratic procedures. In nutshell, the principle of first pay first served has become a pragmatic office service principle. Interviewees asserted that informal housing is found to be more affordable than formal housing. Researchers probed why that was the case and the interviewee stated that money-oriented services make official housing procedures easy and viable. On the other hand, formal housing is procedurally difficult and economically expensive and its achievement is bureaucratically cumbersome. Bureaucrats know that formal housing customers do not pay money because they are legally safe but informal housing customers pay any amount to compensate for tenurial insecurity. Before coming up with a conclusion on the subject of effects influenced by housing market dynamics unsupportiveness on the coping ability of homeownership, the measures of association were executed in Table 4 to determine the association between the coping ability and extent of housing market supportiveness. Accordingly, the hypothesis of independence can be rejected if the chi2 value is greater than the critical value (from the test statistic table) at alpha 0.05 and the significance value is less than the alpha value. Then the claimed hypothesis is accepted and strengthened by significance value to make the certain tough relationship between coping ability and extent of housing market dynamics supportiveness. For this reason, the hypothesis of independence is incorrect since chi2 is greater than the critical value at four degrees of freedom (74.27 >9.488) and the significance value (0.000) is less than alpha (0.000 <0.05). This indicates chi-square statistic of association is significant at the 5 % level. This shows the level of coping ability to meet homeownership aspiration and the extent of housing market dynamics supportiveness is significantly correlated. Thus, the above evidence is enough to reject the statement that hypothesizes the capacity of meeting homeownership aspiration and the extent of housing market dynamics supportiveness is unrelated. In another word, it is enough evidence to accept the claim and infer the capacity of meeting homeownership aspirations and the extent of housing market dynamics’ supportiveness are related. Table 4 shows that degree of housing market dynamics supportiveness is more likely to impact the capacity of achieving homeownership. The finding also has revealed that the coping ability of the residents and the level of housing market dynamics challenges are inversely and significantly related. Unsupportive housing market dynamics compared to the supportive housing market dynamics, has more likelihood of affecting the coping ability of homeownership aspiration negatively. This implies as the extent of housing market dynamics’ unsupportiveness increases, ceteris peribus, the residents’ coping ability to achieve homeownership aspiration is more likely to go down. Furthermore, the fact in the study validates the same thing. Accordingly, it is clear that from Table 4 it can be easily comprehended the majority of the households (75.8 %) responded their coping ability is worse off due to housing market dynamics unsupportiveness and only 18.1 % of respondents said they have a better off capacity of achieving homeownership aspiration while the structure is unsupportive to them. Fig. 3 shows that nearly half of the respondents (46.65 %) found to make private rental housing their first tenable housing option. One-third of the respondents confirmed that looking for cooperative housing is the most tenable housing option for them. A self-help homeownership housing strategy is found to be possible only for 10 % of respondents. This implies homeownership aspiration is in severe decline whereas private rental housing is found to be the prevailing housing option. This seems that the coping ability of residents to achieve homeownership is declining or worse. Table 4 Crosstabulation of housing dynamics*coping ability of residents. Ability to cope with housing dynamics? Total Better off Worse off No change Level of overall housing dynamics supportiveness Supportive Count 53 30 8 91 % within the level of housing dynamics supportiveness 58.2 % 33.0 % 8.8 % 100.0 % Unsupportive Count 47 197 16 260 % within the level of housing dynamics supportiveness 18.1 % 75.8 % 6.2 % 100.0 % Somewhat moderate supportive Count 2 12 6 20 % within the level of housing dynamics supportiveness 10.0 % 60.0 % 30.0 % 100.0 % Total Count 102 239 30 371 % within the level of housing dynamics 27.5 % 64.4 % 8.1 % 100.0 % Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square 74.273 a 4 0.000 Likelihood Ratio 66.470 4 0.000 N of Valid Cases 371 E.T. Debele and T. Negussie Research in Globalization 5 (2022) 100099 8 Even if formal housing initiation such as social housing boosts urban housing stock and helps some residents to cope with the housing crisis, it has been criticized for inducing considerable spatial and socio-economic challenges (Delz, 2014). The existing housing supply failed to meet the shelter need of the poorest social group. It has widened housing disparity, and spatial, and social segregation. So far housing standardization imposes cost pressure, inconvenience, implausibility, and needless urban sprawl. Degree of tenure security, presence and absence of leasing, the existence of adequate rental options, availability of affordable housing finance options, degree of housing market supportiveness and affordability, and presence and absence of state contribution in housing provision determines the housing choice of urban residents (Fitzpatrick and Watts, 2017; Larsen et al., 2019; Beswick et al., 2019; Debele, 2019). Rationalities behind housing choice Behavior: 4A principles Residents have their reasons to choose a given housing category. Researchers asked interviewees what influence them to choose their current preferable housing category among existing housing options. The first interviewee stated that the affordability of housing is the main criterion to choose the housing category. The interviewee justified that due to income reasons the current housing category is found to be the first housing option. The next interviewee reflected on family-related reasons. He reasoned that the current housing is adequate for family needs. After marriage housing mobility is expected because family life and single life need different housing adequacy. This implies housing adequacy for family life cycle change necessitates housing choice adjustment. Further information from probed interview shows that security related to working, political factors (affiliation), economic factors (mortgage), and accessibility factors to housing category affect housing choices. Finally, interviewees addressed that spatial factors associated with suitability for cultural life and adaptation to the area affect their housing choices. The finding shows that the housing category of residents is affected by different structural and dispositional factors. Residents cope with housing challenges via the dynamic process of adjustment. The reality in the study area verifies this assumption. It is possible to observe from Fig. 4 that half (49.6 %) of the sample respondents reported that income is their primary reason to choose their housing category, while fewer proportions (33.24 %, 9.12 %, and 8.04 %) reported that their reasons to choose current housing category are family life, work life, and cultural life respectively. This shows income factors are more likely to influence the housing choice of residents. FGD discussants affirmed that the limited income of residents influences their housing choices to be limited. They agreed that the existing housing market does not enable residents to overlook income factors and prioritize others. It seems that residents are more likely to compromise family life than the income factor. Work-life is less likely to affect housing choice than family life. Cultural life is less likely to influence the housing choice of residents. This implies housing choice of residents needs to entertain economic (affordability factor), political (accessibility factor), social (adequacy factor), and cultural (suitability factor) interactional factors. Affordability Research participants via in-depth interviews reported that residents highly suffered from housing unaffordability problems. No housing option is said to be affordable but residents choose housing option which is comparatively believed to have less financial stress. Interviewees reported that rental fees and paying capacity of residents are mismatched. Owners increase rent by presenting reasons such as an increase in electricity and water bill charges to cover that cost. Owners rise rent even when no income increases but inflation rises. They do not concern themselves with the income of renters. Renters are obliged to move from unaffordable areas to where rent is relatively lower. Interviewees complained that majority of owners unreasonably increase rent. Residents’ income determined their housing category choice. The need and aspirations of residents are constrained by financial capacity. Income level plays determining role in choosing the housing category. Income factors either constrain or enable housing choice. Private rental housing market affordability problems, the rising price of condominium houses, the lower purchasing power of residents, lowincome group paying ability, accessibility to financial institutions, the Fig. 3. Distribution of respondents and their viable housing coping mechanisms. E.T. Debele and T. Negussie