2. Materials and Methods
2.1 Study Design
This study utilized the Delphi method to identify factors affecting urban housing development in Lusaka. The Delphi method is a systematic approach that emphasizes the importance of aligning research with real-world practices and decision-making (Ogunbayo et al., 2023). This technique relies on the principle that expert judgment on a specific issue becomes more reliable when a collective consensus is achieved. The Delphi method involves gathering input from a group of experts who anonymously express their views on a given topic until a consensus is reached (Shariff, 2015). McPherson et al. (2018) also note that this method allows researchers to leverage the experiential insights of participants regarding the topic under investigation.
The use of the Delphi technique in this study is supported by its recognized strengths. Aghimien et al. (2021) argue that the Delphi method equips researchers to better predict future trends compared to theoretical approaches or simple trend extrapolation. The Delphi method is particularly beneficial for policy and decision-makers because it generates actionable information (Aliu et al., 2021).
2.2 Selection of Delphi Panelists
The selection of Delphi panelists was based on several established criteria to ensure the reliability and validity of the findings. Various scholars have proposed different strategies for selecting Delphi experts. For instance, Aliu et al. (2021) suggest that criteria should include extensive work experience, a high level of involvement in jobs related to the topic, and sound knowledge and understanding of the study area. Similarly, McCarthy et al. (2023) emphasize the importance of selecting experts with direct involvement in the area of inquiry, significant knowledge of the subject, and relevant work experience.
Other Delphi studies, such as those by Shariff (2015) and Gunduz and Elsherbeny (2019), have considered additional factors for selecting experts, including broad work experience in the relevant field, a minimum of a bachelor’s degree, recent or ongoing involvement in similar projects, professional registration, willingness to participate in multiple rounds of surveys, and substantial understanding of the topic.
Studies by Gad and Shane (2017) and Kermanshachi et al. (2020) used selection criteria similar to those proposed by Hallowell and Gambatese (2010). These criteria include the experts' experience in delivering presentations or lectures, publishing books or articles on related topics, their education level, and professional experience in fields related to the study area. Given the comprehensive nature of these guidelines, this study adopted Hallowell and Gambatese's (2010) criteria for selecting experts to participate in the Delphi survey. This approach ensured a robust basis for generalization, as detailed in Table 2.
Table 2: Expert Panelists Composition: Legend: SIZ: Surveyors institute of Zambia, ZIA: Zambia institute of Architects, ZIP: Zambia institute of planners, EIZ: Engineering institute of Zambia: R#: Respondent.
|
Id
|
Institution
|
Highest degree
|
Peer Reviewed Journal articles
|
Presented at conference
|
Member or chair of a committee
|
Years of industry experience
|
Professional Affiliation
|
Job related to Housing
|
|
R#1
|
Academia
|
PhD
|
10
|
4
|
1
|
26
|
SIZ, VSRB
|
Yes
|
|
R#2
|
Academia
|
PhD
|
8
|
2
|
3
|
30
|
SIZ, EIZ
|
Yes
|
|
R#3
|
Local Authority
|
Masters
|
0
|
0
|
1
|
10
|
ZIP
|
Yes
|
|
R#4
|
Government Ministry
|
Master
|
0
|
0
|
1
|
20
|
ZIA
|
Yes
|
|
R#5
|
Government Ministry
|
PhD
|
4
|
1.5
|
1
|
22
|
ZIP
|
Yes
|
|
R#6
|
NGO
|
Masters
|
0
|
0
|
1
|
9
|
ZICA
|
Yes
|
|
R#7
|
Mortgage lender
|
BSc
|
0
|
0
|
1
|
13
|
SIZ
|
Yes
|
|
R#8
|
Quasi Gov.
Housing Institution
|
Masters
|
2
|
0
|
1
|
10
|
ZIA
|
Yes
|
|
R#9
|
Private consultant
|
Masters
|
8
|
1.5
|
1
|
20
|
ZIP
|
Yes
|
|
R#10
|
Private developer
|
BSc
|
0
|
0
|
1
|
14
|
ZIA
|
Yes
|
The composition of the panel of experts consisted of 3 architects (Resp 4, Resp 8, and Resp 10), 1 Quantity Surveyor (Construction Economics and Management) (Resp 2), 3 urban and regional planners (Resp 3, Resp 5 and Resp 9), 2 real estate/property professionals (Resp 1 and Resp 7), and 1 economic development professional representing the non-governmental organisations (Resp 6) as shown in table 3.
Table 3: Expert Panellists Qualification types.
|
Item no.
|
Type of Qualification
|
Number of Experts
|
|
1
|
Architects
|
3
|
|
2
|
Construction Economics & Management
|
1
|
|
3
|
Urban and Regional Planners
|
3
|
|
4
|
Real Estate or Property studies
|
2
|
|
5
|
Economics and Development
|
1
|
|
6
|
Total
|
10
|
An important aspect of the panel was the vast amount of cumulative experience that they had in housing development and planning. The cumulative experience was 174 years translating to an average of 17 years. More so, the panels consisted of experts from various sectors of housing development. All the panellists satisfied the conditions as set in Hallowell and Gambatese's (2010) guidelines.
The rationale behind the panel composition is that most of the sampled experts had academic qualifications in built environment or allied programmes, hence, they had the required level of understanding of housing development.
2.3 Number of Expert Panelists
There is no consensus in the literature on the minimum number of experts required for a Delphi study. However, several guidelines are available for consideration in scholarly research. For instance, Hallowell and Gambatese (2010) suggest that a panel of 8 to 12 experts is sufficient, while Alarabiat and Ramos (2019) propose a minimum of 10 experts. Similarly, Alomari et al. (2018) recommend a minimum of 7 experts, and Gunduz and Elsherbeny (2019) suggest selecting between 8 to 20 experts. Based on these varied recommendations, this study opted for a panel of 10 experts, which aligns with the guidance provided in prior Delphi studies. It is important to note that the sample size in Delphi studies is determined not by statistical power but by the expertise of the panelists and the quality of the consensus reached.
2.4 Iterative Rounds and Consensus Determination
The study began by compiling a list of factors from the literature, which were then used to develop a questionnaire for the expert panelists. The experts were asked to rate their level of agreement on whether each identified factor contributed to poor urban housing development in Lusaka using a scale of 1 to 10:
-
1–2: Strongly disagree
-
3–4: Disagree
-
5–6: Fairly agree
-
7–8: Agree
-
9–10: Strongly agree
The Delphi method was employed to achieve consensus among the experts through iterative rounds of questionnaires and controlled feedback. Different scholars have adopted various measures for determining consensus. While some assert that a 100% agreement among participants constitutes consensus, others believe that a two-thirds majority is sufficient (Somiah, 2019; Aghimien et al., 2021). In this study, a consensus was defined as 60% agreement among the experts on each statement.
The survey was conducted over two iterative rounds. After each round, the median, mean, standard deviation, percentages, and interquartile deviation (IQD) scores for each question were calculated. Following the first round, the questionnaire with the calculated group medians was sent back to the panelists. If any score was more than one unit above or below the group median, the experts were asked to provide detailed explanations for their responses. The survey proceeded to a second round, after which consensus was achieved on most factors influencing urban housing development in Lusaka.
The scale adopted for consensus determination, informed by Mambwe et al. (2021) and Yankah (2019), was as follows:
-
A group median of 9 to 10, with a mean of 8 to 10 and an IQD of ≤1, indicated a strong consensus.
-
A group median of 7 to 8.99, with a mean of 6 to 7.99 and an IQD between 1.1 and 2, indicated good consensus.
-
A group median of ≤6.99, with a mean of ≤5.99 and an IQD between 2.1 and 3, indicated weak consensus.
In Delphi studies, such as this one, the IQD obtained after iterative rounds serves as a robust indicator of expert agreement (consensus). Although reaching a consensus often involves up to three rounds, the actual number of rounds is less important than the level of agreement achieved at the conclusion of each round.
2.5 Ethical Considerations
Several ethical considerations were addressed in this study, including anonymity, iterations, statistical aggregation of group responses, and controlled feedback. Anonymity was ensured by preventing face-to-face interactions among the expert panelists to minimize groupthink and bias. The iterative rounds allowed the experts to review and, if necessary, revise their responses, thereby enhancing the reliability of the findings.
3. Results
3.1 Assessment of Key Factors Affecting Urban Housing Development in Lusaka
An assessment was conducted to identify the key factors affecting urban housing development in Lusaka. A list of factors compiled from the literature was presented to the expert panelists, who were asked to rate their level of agreement on whether each factor contributed to poor urban housing development in Lusaka. After the first round, all factors achieved group medians of at least 7, except for "inadequate housing legislations and policies," which scored a median of 5, as shown in Table 4. However, since the interquartile deviation (IQD) indicated a lack of consensus for all but two factors, a second round was conducted to reach a consensus.
Table 4: Key Factors Affecting Urban Housing Development in Lusaka. (Round 1).
|
Factors
|
Median
|
Mean
|
Std.
|
IQD
|
|
Low institutional capacity
|
8
|
6.90
|
2.64
|
3.25
|
|
Inadequate housing legislation and policies
|
5
|
4.40
|
1.84
|
1.75
|
|
Ineffective urban planning
|
8
|
7.50
|
2.12
|
3.00
|
|
Weak urban governance
|
9
|
8.40
|
1.43
|
2.50
|
|
Weak housing regulatory framework
|
7
|
6.70
|
2.79
|
4.50
|
|
Stakeholders disembodied approach
|
7
|
6.70
|
1.64
|
1.00
|
|
Political influence
|
10
|
8.10
|
2.64
|
2.75
|
|
Lack of budgets for cross-disciplinary works
|
8
|
7.30
|
2.41
|
4.75
|
|
Limited skills & incentives for planning institutions to work together
|
7
|
6.40
|
3.53
|
5.50
|
|
Poor linkage between infrastructure investment and service delivery
|
9
|
8.00
|
2.49
|
2.50
|
|
Low private sector and community involvement
|
7
|
6.50
|
2.72
|
3.25
|
|
Lack of access to affordable housing finance
|
9
|
8.30
|
2.16
|
2.00
|
|
Limited access to land
|
10
|
8.50
|
1.78
|
3.00
|
|
Corruption
|
8
|
8.00
|
1.76
|
3.50
|
|
High mortgage interest rates
|
10
|
9.10
|
1.20
|
1.00
|
Legend: Std: Standard deviation, IQD: Interquartile deviation.
After the second round, the findings revealed strong agreement on political influence, poor linkage between infrastructure investment and service delivery, lack of provision of housing finance, limited access to land, weak urban governance, Corruption, and high mortgage interest rates as key factors leading to poor housing development with the group medians in the range of 9 to 10. The IQD values were less or equal to one, except for weak urban governance and corruption which had IQD values of 1.50 and 2.00 respectively, further, their std values showed consistency.
Similarly, there was agreement on low institutional capacity, ineffective urban planning, weak housing regulatory framework, stakeholders' disembodied approach, lack of budgets for cross-disciplinary works, and low private sector and community involvement. These were factors identified as causes of urban housing development in Lusaka as denoted by the group medians of 7 to 8 with most of the IQD values indicating common consensus. However, attributes such as limited skills and incentives for planning institutions to work together had some far outliers, with (panellists) insisting that there are sufficient skills and incentives for planning institutions to work together as indicated with the IQD value of 3. Lastly, there was only 1 factor (inadequate housing legislations and policies) which was considered to have a fair contribution to poor urban housing development in Lusaka with a group median of 5 and IQD value of 1 as shown in Table 5.
Table 5: Key Factors Affecting Urban Housing Development in Lusaka. (Round 2).
|
Factors
|
Median
|
Mean
|
Std.
|
IQD
|
Rk
|
|
Political influence
|
10
|
9.80
|
0.42
|
0.00
|
1
|
|
High mortgage interest rates
|
10
|
9.80
|
0.42
|
0.00
|
2
|
|
Lack of access to affordable housing finance
|
9
|
9.30
|
0.67
|
1.00
|
3
|
|
Limited access to land
|
9
|
9.10
|
0.99
|
1.00
|
4
|
|
Weak urban governance
|
9
|
8.90
|
0.99
|
1.50
|
5
|
|
Poor linkage between infrastructure investment and service delivery
|
9
|
8.30
|
2.31
|
0.75
|
6
|
|
Corruption
|
9
|
8.60
|
1.58
|
2.00
|
7
|
|
Ineffective urban planning
|
8
|
7.90
|
1.79
|
0.75
|
8
|
|
Low institutional capacity
|
8
|
7.80
|
2.49
|
1.00
|
9
|
|
Lack of budgets for cross-disciplinary works
|
8
|
8.30
|
1.57
|
1.75
|
10
|
|
Low private sector and community involvement
|
8
|
7.70
|
1.77
|
1.75
|
11
|
|
Stakeholders disembodied approach
|
7
|
7.30
|
1.06
|
0.00
|
12
|
|
Weak housing regulatory framework
|
7
|
7.50
|
2.37
|
2.5
|
13
|
|
Limited skills & incentives for planning institutions to work together
|
7
|
7.00
|
2.75
|
3.00
|
14
|
|
Inadequate housing legislations and policies
|
5
|
4.50
|
1.27
|
1.00
|
15
|
Legend: Std: Standard deviation, IQD: Interquartile deviation, Rk: Ranking.
3.2 Reliability Statistics
In determining the internal reliability of the scores, Cronbach alpha was computed and the results yielded a value greater than 0.7 at 0.860, an indication of internal reliability (Aigbavboa, 2014) as shown in Table 6.
Table 6: Reliability Statistics.
|
Cronbach's Alpha
|
Cronbach's Alpha Based on Standardized Items
|
N of Items
|
|
.860
|
.923
|
15
|
4. Discussion
The study aimed to identify the key factors affecting urban housing development in Lusaka. The findings reveal several critical challenges, including low institutional capacity, ineffective urban planning, weak urban governance, an inadequate housing regulatory framework, a disjointed approach among stakeholders, political influence, insufficient budgets for cross-disciplinary initiatives, limited skills and incentives for planning institutions to collaborate, poor linkage between infrastructure investment and service delivery, low private sector and community involvement, limited access to affordable housing finance, restricted access to land, corruption, and high mortgage interest rates.
These findings are consistent with previous studies. For example, Lopes et al. (2020) and Grekou and Owoundi (2020) have highlighted the lack of a clear linkage between infrastructure investment and service delivery in many African countries and cities. Doebele (2022) and Nkubito (2022) further emphasize that poor and low-income households face significant challenges in accessing land due to the market regulation of well-located, registered land, which creates affordability issues. Additionally, other scholars have identified issues such as ineffective urban planning (Güneralp et al., 2017), political influence, weak urban governance, and a disjointed stakeholder approach (Hantalo et al., 2023; Jankauskaitė-Jurevičienė & Mlinkauskienė, 2021; Cartwright et al., 2018).
4.1 High Mortgage Interest Rates
The findings align with the literature that identifies high mortgage interest rates and the lack of affordable housing finance as significant challenges in housing development. Nakiwala et al. (2022) and Dafeamekpor et al. (2022) emphasize that access to cheaper, long-term funds is crucial for housing delivery. Scholars such as Asabere et al. (2016) and Udoka Kpataene (2017) argue that credit finance and mortgage loans positively impact housing development. Blackwell et al. (2017) support this view, noting that easy access to finance enhances housing supply. Bah et al. (2018) further highlight that the availability of housing finance facilitates decisions to acquire, build, or rent a house. Glaeser and Gyourko (2018) underscore that housing units are the most valuable assets for most families, reinforcing the need for accessible finance for both housing demand and supply. Edwin et al. (2023) suggests that measures facilitating access to housing finance can significantly improve housing development.
4.2 Legislation and Policies
The study's results are consistent with Munshifwa (2015), who highlights inadequacies in legislation and policies as barriers to housing development. Various scholars stress the importance of a legal framework in urban housing growth. Olonde et al. (2022) argue that integrated management of several elements, including legal aspects, is crucial for sustainable urban growth in housing. Mhlongo et al. (2022) emphasize that the legal framework should encompass all areas that determine the production and availability of affordable housing, including legislation affecting housing inputs like land and finance. McCawley (2019) notes that improving the legal and regulatory environment is vital for enhancing living conditions for the urban poor. Furthermore, Galster and Lee (2021) and Wetzstein (2022) reaffirm that a conducive policy environment is essential for housing development. Tiwari et al. (2016) underscore the need for laws related to land titles, tenure forms, and housing transactions to ensure efficient housing markets.
4.3 Stakeholder Disembodied Approach
The study confirms Yazdani et al. (2015) and Changula (2015)’s assertion that poor coordination among stakeholders contributes to inadequate housing development. Urban housing development requires input from government, civil society, and the private sector, necessitating both ‘top-down’ and ‘bottom-up’ feedback (Connective Cities, 2020). Effective implementation of the 2030 Agenda relies on coordinated planning and cross-sectoral cooperation (Horan, 2022). Torvinen and Haukipuro (2018) stress the importance of coordinating public and private stakeholders during and after construction projects. Raynor and Whitzman (2021) similarly advocate for intersectoral coordination among government institutions, private sectors, and NGOs. Successful urban development requires collaboration across various sectors (Ravetz, 2016; Chisumbe et al., 2024). Eweje et al. (2021) emphasize that the successful participation of all actors is crucial for achieving desired developmental targets.
4.4 Low Institutional Capacity
The findings also support Changula's (2015) and Emiru et al. (2023)’s assertion that low institutional capacity hinders urban housing development. According to Medeiros and Van Der Zwet (2020), effective urban growth requires strengthening capacities at all levels among all stakeholders, integrating individual, institutional, and policy dimensions. Satterthwaite (2016) highlights the importance of enhancing the capacity of national and local governments to meet urban sustainability commitments. Medina et al. (2015) suggest capacity-building measures, including interdisciplinary training and knowledge-sharing, to address urban challenges effectively.
4.5 Low Private Sector and Community Involvement
The results are consistent with Ramovha (2017), who argues that low private sector and community involvement negatively affects housing development. The private sector plays a crucial role in developing housing policies and programs, implementing projects, and providing affordable housing and finance (Ramovha, 2017; Tiwari et al., 2016; Okoro et al., 2023; Morakinyo et al., 2015; Kacaribu et al., 2022). Joseph et al. (2023) emphasize the importance of community participation in designing and delivering effective interventions. Chisumbe et al. (2022) and Fulcher et al. (2022) argue that community involvement is critical for sustainable housing growth, especially in decision-making processes regarding housing design and allocation.
4.6 Limited Access to Land
The findings on limited access to land are supported by Oladehinde et al. (2023), who assert that the lack of low-cost serviced land hinders urban housing development. Satterthwaite (2020) identifies land as a critical component in housing development, with delays in titling and land documentation discouraging investment. De la O Campos (2023) highlights that increased tenure security positively affects housing investment. Simwanda and Murayama (2018) note that the limited availability of land forces many urban residents to settle in unplanned areas, raising costs for low to middle-income earners.
4.7 Political Influence
The results indicate that political influence contributes to poor urban housing development, aligning with the literature (Cartwright et al., 2018; Jarah et al., 2019; Rodríguez-Pose & Storper, 2020). Political actors often exert influence on local authorities regarding land allocation, with decision-makers sometimes failing to adhere to plans due to job security concerns. Political resistance also poses challenges to slum upgrading and prevention efforts.
4.8 Weak Urban Governance
Weak governance is identified as a significant challenge, consistent with Cartwright et al. (2018) who noted the lack of governance capacities in many African cities. Scholars such as Olanrewaju et al. (2016), Zafarullah and Huque (2017), and Calder (2017) confirm a positive correlation between governance and housing supply. Effective governance is essential for communicative planning, transparency, and equitable development (Newman et al., 2020; Saidu and Yeom, 2020; Syed and Ying, 2019).
4.9 Implications and Future Directions
The findings suggest that improving urban housing requires efforts to prevent political interference in planning and development. Given that a large portion of the population consists of low to middle-income earners, inclusive financial models tailored to their needs are necessary. The study also emphasizes the need for an intersectoral approach in housing planning and the provision of basic utilities, such as water, electricity, sewer networks, and roads.
5. Conclusion
This study aimed to identify the key factors contributing to poor urban housing development in Lusaka, Zambia. The findings reveal that political influence, poor linkage between infrastructure investment and service delivery, lack of affordable housing finance, weak urban governance, and high mortgage interest rates are critical challenges affecting housing conditions in the city. These factors highlight systemic issues within urban planning and governance that require comprehensive and coordinated intervention by multiple stakeholders, including governmental authorities, private sector entities, and local communities.
To address these challenges, the study recommends that institutional stakeholders, including local authorities, housing ministries, and utility service providers, develop an integrated housing planning and development framework to improve the linkage between infrastructure development and service delivery. This involves capacity building through adequate staffing, professional development, and technology adoption. Additionally, the private sector should be encouraged to develop housing finance products tailored for low-income earners and those in the informal sector, recognizing the potential market within the informal economy as a significant opportunity for improvement. Governance principles should also be promoted by institutions such as anti-corruption bodies and audit offices to ensure accountability, transparency, and equality in housing planning and development.
The study underscores the importance of aligning infrastructure investments with effective service delivery to improve housing conditions. This alignment requires a coordinated approach among various stakeholders to foster collaboration and enhance urban planning processes. Improving access to affordable housing finance is also crucial, particularly for low-income earners and those working in the informal sector, to expand housing opportunities and meet the needs of the city's growing population.
The practical value of this study lies in its guidance for both state and non-state stakeholders on areas requiring intervention to enhance urban housing development in Lusaka. While the research provides valuable insights, its focus on a single city presents a limitation. Future research should explore housing finance models for low-income earners in other cities to provide a broader understanding of the challenges and potential solutions for urban housing development across different contexts.
Acknowledgements
Special appreciation goes to the CIDB Centre for Excellence and Sustainable Human Settlement and Construction Research, University of Johannesburg, for the support in preparing this paper.
Funding
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Conflicts of Interest
The authors declare that they have no competing or conflicting interests.
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.
Institutional Review Board Statement
The study was done in accordance with the Declaration of Helsinki principles and authorized by the University of Johannesburg's Institutional Ethics and Plagiarism Committee (FEPC) (protocol code UJ_FEBE_FEPC_00059).
CRediT author statement:
Conceptualization, S.C., C.A. and W.T; Data curation, S.C. and C.A.; Formal analysis, S.C. and C.A.; Funding acquisition, C.A., W.T. and E.M; Investigation, S.C.; Methodology, S.C., C.A. and W.T.; Project administration, C.A., W.T. and E.M; Resources, C.A., W.T. and E.M; Software, C.A.; Supervision, C.A., W.T. and E.M; Validation, C.A., W.T. and E.M; Writing - original draft, S.C.; Writing - review & editing, S.C., C.A., W.T. and E.M.
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