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Article

A Measurement Model for Stakeholders’ Participation in Urban Housing Development for Lusaka: A Neo-Liberal Perspective

by
Sampa Chisumbe
1,2,*,
Clinton Aigbavboa
3,
Erastus Mwanaumo
2,4 and
Wellington Thwala
2
1
Department of Environmental Health, Faculty of Health Sciences, Lusaka Apex Medical University, Lusaka 31909, Zambia
2
Department of Civil Engineering, College of Science, Engineering and Technology, University of South Africa, Pretoria 0003, South Africa
3
Sustainable Human Settlement and Construction Research Centre, Faculty of Engineering and the Built Environment, University of Johannesburg, Johannesburg 2006, South Africa
4
Department of Civil and Environmental Engineering, School of Engineering, University of Zambia, Lusaka 32379, Zambia
*
Author to whom correspondence should be addressed.
Urban Sci. 2022, 6(2), 34; https://doi.org/10.3390/urbansci6020034
Submission received: 29 March 2022 / Accepted: 14 April 2022 / Published: 24 May 2022
Browse Figure
Versions Notes

Abstract

:
Development of urban housing requires participation of various stakeholders, from the state, private sector, and community to the civil society organizations. Cognizant of that fact, this research sought to establish the measurement model for stakeholders’ participation in an urban housing development from the neo-liberal perspective. The study employed a quantitative approach, in which a structured questionnaire containing 25 indicator variables identified from literature was administered to a total of 214 respondents drawn from key institutions involved in housing development and planning in Lusaka, Zambia. Data collected were analyzed through exploratory factor analysis (EFA) as well as confirmatory factor analysis (CFA), with goodness-of-fit based on a two-index strategy used in determining model acceptability. Results revealed that stakeholders’ participation is defined by seven variables, namely: private sector participation in the provision of affordable housing finance; private sector participation through construction of rent-to-buy housing; private sector participation through partnering in the provision of basic services; community participation in the develop of housing programs; the state facilitating access to affordable housing finance; the state stimulating private sector involvement in affordable housing provision; non-governmental organizations participation by coordinating the communities. The study outlines roles of various actors in housing development from a developing country’s perspective.

1. Introduction

Housing encompasses several concepts such as to include comfort, protection, and identity; it is essential to everyone’s wellbeing and quality of life wellbeing, with substantial socio-economic implications. It is an important part of every country’s social and economic structure. No country has yet satisfied itself that the different economic classes that make up its population have received sufficient housing. More than 100 million people are projected to be homeless, with another one billion living in substandard housing around the world. Even though they make up a quarter of the world’s population, only a small percentage of them live in developed countries [1,2]. The most serious housing challenges and shortages are observed in developing countries where homelessness affects about a third of the population. The reasons and nature of these challenges differ from one country to another, depending on the socioeconomic and political climate. Low-income countries’ housing problems are somewhat different from those of developed countries; even more, urban and rural housing peculiarities also exhibit their challenges [3].
In Zambia, most urban dwellers in major cities live in squatter and unplanned settlements. As a result, the majority of city dwellers lack access to adequate housing and basic services, as well as other critical infrastructure such as roads and drainages. The underlying reason for this state of affairs is, among other reasons, due to lack of clear allocation of responsibilities among various players involved in housing development [4]. The roles of the private sector and individual developers are not well-defined in the overall development process. A lack of common strategy in the form of a framework to harmonize the input of various key players in the industry is evident [4]. This study sought to establish the measurement model for stakeholders’ participation in urban housing development for Lusaka, Zambia. The model is significant in outlining the roles of various actors in achieving improved urban housing.

2. Urban Housing Development in Zambia

The current national population for Zambia is estimated at 17.3 million people, with the housing stock at about 3.382 million. The housing deficit is estimated to be over 2.8 million [5] and projected to exceed 3 million units by 2030, if no major interventions are taken [6,7]. The average housing units in urban areas across Zambia are estimated at 43%. In 2015, 53.5% of Zambian households were either traditional huts or improved traditional huts, of which 82.5% were in rural areas. Further, of the total housing units in urban areas, 64.9% use pit latrines facilities, either their own or shared. Likewise, with regard to electricity connectivity, the national access to electricity averages at 31%, with 67% of the urban and 4% of the rural population having access to power [8]. Charcoal is still the most common source of energy for cooking and heating at 59.1% in urban households [9].
Within urban Zambia, as in many other African countries, there are two systems: the formal city, which has complete infrastructure, and the informal city, which has little or no infrastructure and people coping as best they can [10]. In Zambia, the urban growth has been taking place mostly in informal settlements, with the current housing stock being dominated by the informal units. Rural-urban migration trends in Zambia have led to high population growth in urban areas without corresponding improvements in housing and infrastructure for the provision of services. Provisions of urban infrastructure, such as roads, water, electricity, and sanitation, are an important component in the construction of the urban built environment in any city [11].
Historically, the government of Zambia has supported housing markets and development by providing urban infrastructure. By the 1980s, however, the state of infrastructure in many cities and towns had deteriorated to the point where local governments were no longer able to provide these essential services [12]. The private and informal sector arose to fill the void, created by the absence of state and local government provisions of housing and urban infrastructure [11].
The change of government in 1991 resulted in a shift in thinking about how the economy should be managed. The economy was liberalized and, in order to boost the housing sector, the government thought it was important to have a clear plan to look at the provisions of infrastructure, such as highways, water, street lighting, and sanitation, when formulating the National Housing Policy. Nonetheless, the condition did not significantly change over time. This was due to a lack of funds, repairs, and infrastructure refurbishment or replacement. Munshifwa [11] noted that the country has seen the refurbishment of urban roads in recent years, especially in old municipal townships, with the help of borrowed funds. However, he argues that there has been little progress in opening up new residential areas or upgrading informal settlements. In 2016, the Committee on Local Governance attributed lack of access to housing finance, low number of public private partnerships (PPPs), as well as low government investment in housing development to be among the factors contributing to poor urban housing in Zambia.

3. Neo-Liberalism in Housing Development

Neo-liberalism is generally viewed as an economic ideology aimed at limiting the scope of government. It is a way of governing that is taken up in different ways by different regimes, that is, as a political economic practice which contends that allowing individuals to exercise their entrepreneur liberties and abilities within an established framework marked by strong private property rights and liberalized markets, as well as free trade, is the best way to advance human well-being [13]. Garcia [14], p. 3, adds that “the role of the state is to create and preserve an institutional framework appropriate to such practices. More so, that if markets do not exist (in areas such as land, water, education, health care, social security, or environmental pollution) then they must be created, by state action if necessary. But beyond these tasks the state should not venture”.
Since the 1980s, neo-liberalism has dominated policy development and implementation, and it has had a major effect on the reshaping of urban housing delivery in various countries improving on urban housing [15]. Cognizance is taken of the fact that the state alone cannot manage to provide housing for all due to the limited financial resources against many conflicting needs, thereby, underscoring the need for private sector participation [16]. However, this has not been without any challenges; for instance, according to Taruvinga and Mooya [17], p. 136, “problems are likely to abound in adopting a neo-liberal housing policy in the low-income sector, chief amongst which is very low incomes among the targeted group to sustain mortgage finance. Volatile economies with high inflation, economic recessions and lack of primary mortgage instruments contribute towards hurdles in implementing a neo-liberal housing policy”. They added that, while neo-liberalism has progressed in making housing markets more functional, it also has the potential to alienate low-income earners from market participation if effective policy positions are not taken. Taruvinga and Mooya [17] further pointed out that neo-liberalism is not uniform; therefore, its implementation must take into considerations the prevailing local, macro-economic, and environmental factors.
In Zambia, currently, the national policy direction on housing, among other thrusts, is aimed at ensuring inclusivity (participation) and partnerships among stakeholders in achieving affordable and decent housing for all. It is premised on the principles of a free market economy (neoliberalism).

4. Stakeholders Participation

The complexity and multidimensionality of urban areas require multi-sectorial development approach, according to Majale [18], adding that single-sector interventions cannot sustainably improve the housing condition of the urban dwellers. Ochunga and Awiti [19] established that there is a significant positive correlation between optimum participation among stakeholders and sustainability of development. Aigbavboa and Thwala [20] posit that success of development is dependent upon the participation of beneficiaries and stakeholders. Participation of the state, private sector, and community have been identified to have positive impacts on housing delivery. Stakeholder participation is critical in attainment of desired urban housing development. Eisenbeiß [21] and Connective Cities [22] opined that in the creation and implementation of strategies for urban development, a diverse range of actors from the private sector, civil society organizations, and the government are required. Hence, in this study, stakeholder’s participation refers to the involvement and contribution of interested or concerned parties, which include the state either directly or through its institutions; the private sector, such as developers and financial institutions; non-governmental organizations; the community or individuals in urban housing development.

Selection of Indicator Variables for Stakeholder Participation

Literature review on housing studies revealed that most housing development models are in sync with the neo-liberal perspective of housing delivery, which postulates that housing provisions should not be left to the state alone, but rather require involvement of other stakeholders. Furthermore, it states that the state should participate by providing basic services as well as creating an enabling environment for housing development. Literature evidence revealed stakeholders’ participation as an essential recipe for housing development, among other variables.
The selection of indicator variable for the construct of stakeholders’ participation was informed by similar housing studies [18,23,24,25,26,27,28,29]. In a conceptual framework for urban housing for all, among the key determinant factors identified by Tiwari et al. [28] were private and state participation. Similarly, Amado et al. [29] outlined public sector participation, private sector participation, community participation, and stakeholder partnerships to be important factors in integrated urban regeneration strategy. Ramovha [30] identified private sector participation, state participation, and community participation. Likewise, in a pluralistic conceptual model for affordable housing by Ogunnaike et al. [26] key determinants were identified; these included private sector as well as state participation. Lastly, Majale [18] identified critical factors in an integrated approach to urban housing development; these included private, state, community, and NGOs’ partnership, among other factors. The detailed breakdown of the indicator variables for the construct of stakeholders’ participation is as shown in Table 1.

5. Materials and Methods

This study adopted a quantitative approach with data collected using a structured questionnaire, with a 5-point Likert scale. A structured questionnaire containing 25 indicator variables identified from literature was administered to a total of 214 respondents drawn from several key institutions involved in housing development and planning. These included government ministries, non-governmental organizations, private property developers, mortgage lending institutions, quasi-government institutions, and consultancy firms, as well as other housing-allied professions, as shown in Table 2. Literature evidence generally suggests having a minimum of 200 respondents for a study employing structural equation modeling [31,32,33,34,35].
The academic qualifications of the respondents were mainly in built environment programs and other housing-aligned fields. These included urban and regional planners (n = 39; 18.0%), architects (n = 40; 19.0%), quantity surveyors (n = 65; 30%), real estate/property valuers (n = 51; 24.0%), and other professionals (n = 18; 8.0%). However, one respondent did not indicate the professional qualification. Lusaka, which is the capital city of Zambia, was chosen because nearly 70 percent of all its housing stock is substandard and informal: a situation similar to many cities in the sub-Saharan African countries, hence making it more relevant for the study.
Collected data were analyzed in two stages; the first stage involved an exploratory factor analysis (EFA), while the second stage was a confirmatory factor analysis (CFA). EFA was used as a preliminary phase (first stage) to investigate the nature of the latent construct of stakeholders’ participation and gain an understanding of the relationships between the measured indicator variables and the corresponding latent factor (construct). Exploratory factor analysis is useful in the initial phases of development because it demonstrates how well items load on a non-hypothesized factor [36]. Its aim is to determine the optimal number of factors and to reveal whether there are reasonable indicators for various potential aspects of measured items (variables) [37,38]. However, the main objective of confirmatory factor analysis was to investigate whether the data fit the hypothesized measurement model which is based on a certain theory [39], in this case, the neo-liberal theoretical perspective.

6. Results

The results of the analysis, as informed by the two-stage approach, include both the exploratory factor analysis (EFA), as well as the confirmatory factor analysis (CFA).

6.1. Exploratory Factor Analysis

Exploratory factor analysis (EFA) was undertaken to assess the unidimensionality and reliability of stakeholder participation. Principal components with varimax rotation were input as extraction, as well as rotation, methods, respectively. The results revealed that the attributes of stakeholders’ participation had a KMO value of 0.907, and the Bartlett’s test of sphericity, which is significant (p = 0.000), is shown in Table 3. This indicated that the factor analysis was appropriate [40,41,42].
Principal component analysis (PCA) revealed five components with eigenvalues greater than one, accounting for 45.071%, 9.291%, 6.086%, 5.438%, and 4.878% of the variance, respectively. However, an examination of the scree plot showed a clear break after the second component. For further investigation, two components were retained based on the results of the scree test. Parallel analysis results verified this, with only two components having eigenvalues greater than the corresponding criterion values for a randomly generated data matrix of the same size (25 variables × 214 respondents). The two-component solution accounted for a combined total of 54.362% of the variance, with the first component accounting for 45.071%, whereas the second component added 9.291%, as shown in Table 4.
The rotated matrix based on two-factor extraction revealed that fourteen items (SPN5, SPN6, SPN4, SPN8, SPN9, SPN25, SPN7, SPN24, SPN14, SPN13, SPN3, SPN1, SPN10, and SPN2) were loaded on component one, while ten items (SPN12, SPN17, SPN20, SPN21, SPN18, SPN15, SPN16, SPN11, SPN22, SPN19, and SPN23) were loaded on component two. All of the factor loadings were significantly higher than the recommended value of 0.4 [43,44] as shown in Table 5. Enough evidence of convergent validity was provided for this construct, hence, the items were retained for further investigation.
The corrected item-total correlation was also greater than the required minimum of 0.3, indicating that the items accurately represented the element. Table 6 shows that Cronbach’s alpha value was higher than 0.7, at 0.947, indicating sufficient internal reliability, meaning that factor analysis could be performed on the data [45]. Hence, this was considered for further investigations.

6.2. Confirmatory Factor Analysis

The unidimensional model for stakeholders’ participation (SPN) construct is presented in this section. For this construct, a total of 214 cases were used for the analysis. Initially, the SPN construct was made up of 25 indicator variables, however, after conducting a confirmatory factor analysis, only seven indicator variables were retained for further analysis. The seven indicators that provided a good measure of residual matrix and evidence of convergent validity, and were thus included in CFA, were SPN4, SPN5, SPN6, SPN8, SPN13, SPN16, and SPN24. An examination of the Bentler-Weeks structure report revealed the presence of seven (7) dependent variables, eight (8) independent variables, and fourteen (14) free parameters, as well as eight (8) fixed non-zero parameters. The resultant stakeholders’ participation measurement model is as shown in Figure 1.
The seven dependent indicator variables retained for the stakeholders’ participation construct were private sector participation in the provision of affordable housing finance; private sector participation through construction of rent-to-buy housing,; private sector participation through partnering in the provision of basic services; community participation in the develop of housing programs; the state facilitating access to affordable housing finance; the state’s stimulating private sector involvement in affordable housing provision, as well as NGOs’ participation by coordinating the communities, as shown in Table 7. The analysis process for measurement model determination involved an inspection of the residual covariance matrix, goodness-of-fit statistical indices, and statistical parameter estimates’ statistical significance, as well as the check of internal reliability and construct validity.

6.2.1. Estimates of Residual Covariance Matrix

A diagnostic fit analysis of the unstandardized, as well as the standardized, absolute residual matrix values for the construct of stakeholders’ participation, revealed that all the values were close to the recommended zero. Scholars have recommended that “for a variable to be included in a CFA, thus enabling the model to be described as well-fitting, the distribution of residuals covariance matrix should be symmetrical and centred around zero” [46,47], with values of ±1.96 (p < 0.05) or ±2.58 (p < 0.01), suggesting a bad model-data fit [40]. For this construct, the unstandardized average off-diagonal residual value recorded was 0.0396, while the standardized average off-diagonal residual value recorded was 0.0371, as shown in Table 8 and Table 9. The results obtained for the stakeholders’ participation measurement model denoted an acceptable fit to the sample data. This was so because all the values recorded fell within the recommended threshold [46,47,48,49,50,51].
An inspection of the frequency distribution on the residual covariance matrix revealed that most residual values at about 99.99% were within an acceptable range of −0.1 to 0.1.
The results suggested that the stakeholders’ participation measurement model was well-fitting. As a result, further goodness-of-fit tests were considered to assess the measurement model’s suitability and fit.

6.2.2. Statistical Goodness-of-Fit Indices

The Satorra-Bentler scaled chi-square (S-B2) of 33.2347 with 14 degrees of freedom (df) and a probability of p = 0.00007 was obtained from the sample data in the stakeholders’ participation measurement model. The discrepancy between the sample data and the proposed stakeholders’ participation measurement model was negligible, according to this chi-square value. In addition, as shown in Table 10, the chi-square and degrees of freedom ratio was 2.37391, which was less than the suggested limit of 3.00 or 5.0 [52], suggesting a good-fit model.
Likewise, the standardized root mean square residual (SRMR) was found to be 0.042; this was less than the cut-off threshold value of 0.05 [53], and hence, an indication of a good-fit model. The root mean-square error of approximation (RMSEA) was found to be 0.080, which an indication of an acceptable fit [47,54]. Additionally, the CFI was found to be 0.913, which is greater than the threshold value of 0.90 [55], and hence, an indication of an acceptable fit.
An examination of the statistical goodness fit indices for stakeholders’ participation measurement model show that the populated model sufficiently describes the sample data and can thus be considered without further refinement.

6.2.3. Parameter Estimates’ Significance

Before concluding on the appropriateness of the measurement model for stakeholders’ participation, an inspection of the parameter coefficients, as well as the test statistics, was performed. The findings revealed that the values for standardized coefficients were less than 1.0. Likewise, the values for the Z-statistics were above the recommended 1.96 [41,47,56], with all signs being appropriate, as shown in Table 11. The results further showed that an indicator variable which recorded the highest standardized coefficient value was SPN4, having a value of 0.785. This variable referred to private sector participation in the provision of affordable housing finance.
Profoundly, all the variables revealed a high correlation with values being close to 1.0, although SPN4 was recorded to associate with the stakeholders’ participation construct more than any other variable. The high correlation values recorded for all variables imply that the indicator variables and the unobserved (stakeholders’ participation) variable have a high degree of a linear relationship. More so, the R-square output scores were close to the desired score of 1.00; this was an indication that the factors explained more of the variance in the indicator variables, with the exception of SPN8, SPN13, SPN16, and SPN24, which had values slightly below 0.50. The overall results, however, show that the predictor variables do predict the construct in a significant way. Hence, stakeholders’ participation is significantly associated with all the retained measured variables.

6.2.4. Scores’ Validity and Internal Reliability

An inspection of the output with regard to the internal consistency rho coefficient revealed a significant value of 0.877. This value was more than the required threshold of 0.70 [57,58]. Cronbach’s alpha was also higher than the minimum recommended threshold of 0.70 [59,60,61]. The results revealed the value of 0.874 as the Cronbach’s alpha, as shown in Table 12. The range of values for Cronbach’s alpha and rho are both within the required range for internal consistency and reliability. These findings show that the measurement predictor variables are indicative of the same construct (stakeholders’ participation).
An examination of the parameter coefficient estimates, signs, and reasonableness for construct validity revealed that all the values and signs were adequate to confirm validity. All the factor loading values were significantly high, with the lowest being 0.6081 between SPN24 and stakeholders’ participation, as shown in Table 11. An inspection of the internal reliability and construct validity for the stakeholders’ participation measurement model revealed that both the rho and Cronbach’s alpha values met the 0.70 cut-off criteria, and the factor loadings were high enough to indicate statistical significance. Scholars recommend that factor loading for a variable should be 0.5 or greater, and ideally 0.7 or more to explain about 50% of the variance in an indicator variable. However, they contend that a strong association between a measurement indicator variable and the construct can be explained with the factor loading of 0.5 [43,47,51].
Overall, the result indicated that the stakeholders’ participation (SPN) construct was measured by the seven (7) predictor variables, and that the predicted model for this construct had an appropriate fitting to the sample data and was thus considered appropriate in measuring stakeholders’ participation in urban housing development. This was premised on the fact that all the residual covariance matrix values, goodness-of-fit statistics, and statistical significance tests, as well as all internal reliability and validity scores, fell within the acceptable threshold and, hence, were considered statistically significant.

7. Discussion

The results of the CFA displayed that the interfactor correlations and the standardized factor values for the latent factor, stakeholder’s participation, were significant statistically, indicating a high level of linear correlation between the indicator variables and the construct (stakeholders’ participation). The scores were equally significant when the total variances accounted for by the variable in each test were examined. Profoundly, the results of this study inform that the stakeholders’ participation model is defined by seven variables, namely: private sector participation in the provision of affordable housing finance; private sector participation through construction of rent-to-buy housing; private sector participation through partnering in the provision of basic services; community participation in the develop of housing programs; the state facilitating access to affordable housing finance; the state stimulating private sector involvement in affordable housing provision; NGOs’ participation by coordinating the communities. Moreover, the findings indicate that all the variables retained in the model have a substantial influence on the development of urban housing, and the results generally agree with previous studies [17,26,62,63,64]. The consideration of the combined effect of the seven variables that define the construct, stakeholders’ participation, from the neoliberal perspective in this study, are peculiar relative to other housing studies.
Furthermore, among the seven variables, private sector participation in the provision of affordable housing finance is the leading variable contributing to the construct, stakeholders’ participation, having recorded a standardized coefficient value of 0.785. This result supports the assertion by the International Finance Corporation [62] that the private sector should participate by offering solutions in financing and innovative tenure models. Additionally, with regard to private sector participation, Morakinyo et al. [63] posit that the private sector has a role to play in the provision of housing by constructing houses for all classes of the population, either for renting out or for sales, as well as in the development of other critical infrastructure needed for human settlements. The International Finance Corporation [62] further adds that the private sector should participates by providing essential services such as transport, telecommunications, and water, as well as power, adding that these services are important to growth and improving people’s lives. Another way in which the private sector should participate is through public-private partnerships (PPPs). Literature evidence points out that public-private partnership is needed to resolve urban housing shortages, with the government’s position in the partnership—consisting of providing land and basic services such as roads, power, and a regulatory system, as well as conducting the procedure of obtaining permits, authorizing housing development plans, and registering land titles—being simpler. On the other hand, the private sector should participate in the actual development, financing, and manning of housing projects [26,65,66].
With regard to state participation, the results agree with literature, as well as the theory, that the state should play a significant role in facilitating housing development. As an enabler, the state should provide the necessary support base and stimulate optimum involvement of other actors in the housing development process. The state actualizes this by facilitating easier access to finance, as well as removal of restrictive legislation [26], and thereby stimulating private sector involvement in affordable housing provision. This further agrees with Taruvinga and Mooya [17], who posited that in order to encourage and stimulate private sector participation, the state needs to create an enabling environment and a suitable regulatory environment for housing development. A view is shared by other authors that it is the role of the state to protect and create prospects for the private sector involvement in the housing property market [16,64,66]. Though, Harvey [67] earlier argued that “whilst acknowledging the role of the state in enabling markets to work, it is important that state intervention be kept at a bare minimum because powerful interests can inevitably distort and bias state interventions for their own benefit”.
Similarly, on community participation in housing development, the results agree with literature evidence that as stakeholders in the housing sector, community members must participate in consultations and negotiations in order to make realistic decisions concerning their housing needs. The value of community engagement as consumers in the delivery of housing has been emphasized in many studies [68,69,70]. Community participation is a critical ingredient to housing development. “Community participation is understood in terms of the role of the target group and local organisations in design, implementation, maintenance and evaluation” [71,72]. Community involvement in decision making on the design of housing, as well as allocation of construction sites, is valuable in the development process [71,73,74,75]. Khan, Haupt [76], and Ellinger et al. [77] reaffirmed it by positing that the right to adequate housing contains entitlements, which include participation in housing-related decision making at the national and community levels.
On the other hand, the variable of NGOs’ participation by coordinating the communities contributed least to the construct of stakeholders’ participation, having recorded a standardized coefficient value of 0.608. Similarly, the finding agrees with literature; Keivani and Werna [78] posit that NGOs can aid squatter, as well as unplanned settlement dwellers, by assisting them in the establishment of appropriate community groups and mobilization, as well as providing technical and organizational expertise for self-help house construction. Pugh [79] holds that NGOs provide valuable links between communities and the state. The World Economic Forum [80] adds that NGOs “have a critical role in bridging the gap between governments and the private sector to improve the affordability of housing, as well as working with individuals to help them understand their options and make informed decisions”. Rahman [81] posits that if the poor are able to decide about their own needs, affordability, and goals, they will be able to share responsibility. NGOs, they argue, foster pluralism by including them in consultation, planning, decision making, and housing program implementation. Satterthwaite [82] shares the viewpoint by holding that “NGOs are significant because they partner with urban poor households and their community organisations and networks to increase their voice”.

8. Conclusions

Anchored on neoliberalism, this study identifies the factors which predict stakeholder participation in urban housing development from a developing country’s perspective. Using Lusaka as a case study, the results affirm that stakeholders’ participation in urban housing development can be measured and enhanced by ensuring stakeholders participation through: private sector participation in the provision of affordable housing finance; private sector participation through construction of rent-to-buy housing; private sector participation through partnering in the provision of basic services; community participation in the develop of housing programs; the state facilitating access to affordable housing finance; the state stimulating private sector involvement in affordable housing provision, as well as NGOs’ participation by coordinating the communities.
Further, this study highlights the roles of various actors, namely the state, private sector, and non-governmental organizations, as well as the community in urban housing development. Recognizing that it is difficult for the state to provide housing for all citizens, the neoliberal perspective as espoused in this study outlines how the state can bring in other actors, to participate in the provisioning of affordable urban housing by creating an enabling environment for investment/partnerships.
However, it is important to note that, though interesting and valuable findings have emerged from this study, it is not without limitations. The study targeted respondents who had academic qualifications mainly allied to the built environment, drawn from several institutions involved in housing development and planning. A study that includes other relevant stakeholders such as the community members could be conducted.

Author Contributions

Conceptualisation, S.C., C.A., W.T. and E.M.; Methodology, S.C., W.T. and C.A.; Software, C.A.; Validation, S.C., C.A., E.M. and W.T.; Formal analysis, S.C.; Investigation, S.C.; Resources, E.M., C.A. and W.T.; Data Curation, S.C.; Original Draft Preparation, S.C.; Writing—Review and Editing, S.C., E.M., C.A. and W.T.; Supervision, C.A., W.T. and E.M.; Project administration, S.C., C.A., W.T. and E.M.; funding acquisition, C.A., W.T. and E.M. All authors have read and agreed to the published version of the manuscript.

Funding

Though the study was self-sponsored, it would not have been possible to conduct this research without support from the University of Johannesburg and supervisors. The numerous support included acquisition of software, language editing, as well as settlement of a significant amount of university fees during the Doctorial study.

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Institutional Ethics and Plagiarism Committee (FEPC) of the University of Johannesburg (protocol Code UJ_FEBE_FEPC_00059 and date of approval: 6 June 2020).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy and ethical issues.

Acknowledgments

Appreciation is extended to the SARChi on Sustainable Construction Management and Leadership in the Built Environment, Faculty of Engineering and the Built Environment, at the University of Johannesburg, for the guidance and technical and administrative support in coming up with this manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

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Urbansci 06 00034 g001 550
Figure 1. Measurement model of Stakeholders’ participation.
Figure 1. Measurement model of Stakeholders’ participation.
Urbansci 06 00034 g001
Table
Table 1. Measurement indicator variables for stakeholders’ participation.
Table 1. Measurement indicator variables for stakeholders’ participation.
ConstructMeasurement VariablesLabel
Stakeholders ParticipationPrivate Sector
Participate in the provision of affordable housingSPN1
Provide rental housingSPN2
Participate in the development of housing policiesSPN3
Provision of affordable housing financeSPN4
Construction of rent-to-buy housingSPN5
Partner in the provision of basic servicesSPN6
Community
Participate in the develop of housing policiesSPN7
Participate in the develop of housing programsSPN8
Establishment of community saving schemesSPN9
Participation in implementation of programsSPN10
Construction of their housingSPN11
State
Develop housing policies and programsSPN12
Facilitate access to affordable housing financeSPN13
Provide housing subsidy to low-income earnersSPN14
Ensure availability of land for housing developmentSPN15
Stimulate private sector involvement in affordable housingSPN16
Provide serviced sites for housing developmentSPN17
Provide social housingSPN18
Performance monitoring of sector with minimal interventionSPN19
Enforcement of housing regulationsSPN20
Implementation of housing policiesSPN21
Non-Governmental Organizations
Develop housing policiesSPN22
Develop housing programsSPN23
Coordinating the communitiesSPN24
Participate in the provision of affordable housingSPN25
Stakeholders: Private Sector; Community; State; Non-governmental Organisations. Data from: [18,23,24,25,26,27,28,29,30].
Table
Table 2. Organizations or institutions sampled.
Table 2. Organizations or institutions sampled.
InstitutionFrequencyPercentage
Government ministries4822.4
Non-governmental organizations198.9
Private property developers2310.7
Mortgage lending institutions62.8
Quasi-government institutions2712.6
Consultancy firms6831.8
Others219.8
Did not indicate2.01.0
Total214100.0
Table
Table 3. KMO and Bartlett’s test of stakeholders’ participation.
Table 3. KMO and Bartlett’s test of stakeholders’ participation.
KMO and Bartlett’s Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.0.907
Bartlett’s Test of SphericityApprox. Chi-Square3891.012
Df300
Sig.0.000
Table
Table 4. Total variance explained by stakeholders’ participation.
Table 4. Total variance explained by stakeholders’ participation.
ComponentInitial EigenvaluesExtraction Sums of Squared LoadingsRotation Sums of Squared Loadings
Total% of VarianceCumulative %Total% of VarianceCumulative %Total
111.26845.07145.07111.26845.07145.0714.822
22.3239.29154.3622.3239.29154.3624.600
31.5226.08660.448
41.3605.43865.886
51.2204.87870.764
60.7943.17773.942
70.7482.99376.935
80.6702.68079.614
90.5422.16681.781
100.5092.03483.815
110.4541.81585.629
120.4301.72287.351
130.4221.68989.041
140.3891.55790.598
150.3331.33191.929
160.2931.17193.100
170.2781.11394.213
180.2661.06395.276
190.2350.93996.215
200.1990.79897.013
210.1920.76797.780
220.1720.68698.467
230.1530.61199.078
240.1320.52999.607
250.0980.393100.000
Table
Table 5. Rotated component matrix.
Table 5. Rotated component matrix.
Component Matrix
Component
12
SPN50.800
SPN60.788
SPN40.744
SPN80.701
SPN90.678
SPN250.661
SPN70.646
SPN240.615
SPN140.607
SPN130.561
SPN30.560
SPN10.550
SPN100.548
SPN20.535
SPN12 0.814
SPN17 0.782
SPN20 0.776
SPN21 0.753
SPN18 0.743
SPN15 0.734
SPN16 0.674
SPN11 0.658
SPN22 0.576
SPN19 0.562
SPN230.800
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization a.
Table
Table 6. Cronbach’s alpha.
Table 6. Cronbach’s alpha.
Corrected Item-Total CorrelationCronbach’s Alpha If Item DeletedCronbach’s AlphaNumber of Items (N)
SPN50.6240.9450.94725
SPN60.6250.945
SPN40.7180.943
SPN80.6220.945
SPN90.5720.945
SPN250.6130.945
SPN70.6740.944
SPN240.6070.945
SPN140.7080.943
SPN130.6850.944
SPN30.6250.945
SPN10.4610.947
SPN100.5990.945
SPN20.4710.946
SPN120.5300.946
SPN170.7040.944
SPN200.7000.944
SPN210.7050.944
SPN180.7020.944
SPN150.6180.945
SPN160.7420.943
SPN110.4490.947
SPN220.7290.943
SPN190.6890.944
SPN230.6020.945
Table
Table 7. Postulated stakeholders participation model.
Table 7. Postulated stakeholders participation model.
Latent ConstructIndicator VariablesLabel
Stakeholders ParticipationPrivate sector participation in the provision of affordable housing financeSPN4
Private sector participation through construction of rent-to-buy housingSPN5
Private sector participation through partnering in the provision of basic servicesSPN6
Community participation in the develop of housing programsSPN8
State facilitating access to affordable housing financeSPN13
State stimulating private sector involvement in affordable housing provisionSPN16
Non-Governmental Organizations participation by coordinating the communitiesSPN24
Table
Table 8. Stakeholders participation (SPN) model.
Table 8. Stakeholders participation (SPN) model.
Unstandardized Residual Covariance Matrix
SPN4SPN5SPN6SPN8SPN13SPN16SPN24
SPN40.000
SPN50.033−0.000
SPN6−0.0340.071−0.000
SPN80.044−0.0510.045−0.000
SPN13−0.051−0.041−0.001−0.035−0.000
SPN160.015−0.063−0.078−0.0050.154−0.000
SPN24−0.0110.004−0.009−0.0310.0310.0250.000
Average Absolute Standardized Residual = 0.0297. Average Off-Diagonal Absolute Standardized Residual = 0.0396. % falling between −0.1 and + 0.1 = 100%
Table
Table 9. Stakeholders participation (SPN) Model.
Table 9. Stakeholders participation (SPN) Model.
Standardized Residual Covariance Matrix
SPN4SPN5SPN6SPN8SPN13SPN16SPN24
SPN40.000
SPN50.029−0.000
SPN6−0.0310.058−0.000
SPN80.047−0.0470.044−0.000
SPN13−0.047−0.033−0.001−0.034−0.000
SPN160.016−0.057−0.074−0.0060.144−0.000
SPN24−0.0110.004−0.009−0.0330.0280.0260.000
Average Absolute Standardized Residual = 0.0278. Average Off-Diagonal Absolute Standardized Residual = 0.0371. % falling between −0.1 and +0.1 = 100%.
Table
Table 10. Robust fit indexes for the Stakeholders participation (SPN) construct.
Table 10. Robust fit indexes for the Stakeholders participation (SPN) construct.
Fit IndicesAcceptable Threshold
Levels		EstimatedComment
S-B 33.2347
DF 14
Chi-square (χ2/df)<3 (good fit)2.37391Good fit
<5 (acceptable)
Comparative fit index (CFI)>0.90 (acceptable fit)0.913Acceptable fit
>0.95 (good fit)
Standardized root mean
square residual (SRMR)		≤0.08 (acceptable fit)0.042Good fit
<0.05 (good fit)
Root mean square error of approximation (RMSEA)<0.05 (good fit)0.080Acceptable fit
0.05 < 0.08 (acceptable fit)
0.08–0.10 (moderate fit)
>0.10 (bad fit)
RMSEA 90% CI [0.045, 0.116]Acceptable fit
Table
Table 11. Factor loadings and Z-statistics of SPN.
Table 11. Factor loadings and Z-statistics of SPN.
IndicatorsUnstandardized CoefficientStandardized CoefficientZ-StatisticsR-SquareSig (5%)
SPN41.0000.785 0.617Yes
SPN51.1310.77413.2740.559Yes
SPN61.0660.76112.2300.579Yes
SPN80.7950.6599.2610.434Yes
SPN130.9860.69310.9220.481Yes
SPN160.8240.6659.8600.442Yes
SPN240.7830.6088.0560.370Yes
Table
Table 12. Reliability and construct validity of the stakeholders participation measurement model.
Table 12. Reliability and construct validity of the stakeholders participation measurement model.
IndicatorsFactor LoadingsCronbach’s AlphaReliability Coefficient RhoInternal Consistency Reliability
SPN40.7853
SPN50.7738
SPN60.76110.8740.8770.883
SPN80.6588
SPN130.6934
SPN160.6648
SPN240.6081
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Chisumbe, S.; Aigbavboa, C.; Mwanaumo, E.; Thwala, W. A Measurement Model for Stakeholders’ Participation in Urban Housing Development for Lusaka: A Neo-Liberal Perspective. Urban Sci. 2022, 6, 34. https://doi.org/10.3390/urbansci6020034

AMA Style

Chisumbe S, Aigbavboa C, Mwanaumo E, Thwala W. A Measurement Model for Stakeholders’ Participation in Urban Housing Development for Lusaka: A Neo-Liberal Perspective. Urban Science. 2022; 6(2):34. https://doi.org/10.3390/urbansci6020034

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Chisumbe, Sampa, Clinton Aigbavboa, Erastus Mwanaumo, and Wellington Thwala. 2022. "A Measurement Model for Stakeholders’ Participation in Urban Housing Development for Lusaka: A Neo-Liberal Perspective" Urban Science 6, no. 2: 34. https://doi.org/10.3390/urbansci6020034

APA Style

Chisumbe, S., Aigbavboa, C., Mwanaumo, E., & Thwala, W. (2022). A Measurement Model for Stakeholders’ Participation in Urban Housing Development for Lusaka: A Neo-Liberal Perspective. Urban Science, 6(2), 34. https://doi.org/10.3390/urbansci6020034

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