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The purpose of this paper is to investigate how the pandemic affects tenants’ response to their lease obligations. This paper commences with examining the adopted tenant selection criteria during the COVID-19 pandemic. Then, this paper statistically tests if there is a relationship between selection criteria and response on whether the pandemic has effects or not. Then, this paper investigates the specific areas of impact on tenants’ ability to adequately keep to lease agreements in the Nigerian rental market. Finally, this paper proceeds to confirm if there is a relationship between selection criteria and the aspects of tenants’ deficiencies in rental obligations because of COVID-19.

Survey data, backed with interviews, is elicited from practicing estate surveyors and valuers and licensed property managers in Lagos, the largest property market in Nigeria and sub-Sahara Africa. Policy solutions and implications were solicited from personnel at the ministry of housing and senior professionals in the property sector. Data were analyzed using descriptive statistics, factor analysis and computer-aided qualitative data analysis, Atlas.ti.

Tenant’s health status is now accorded a priority together with others. Numbers of tenants are challenged with keeping to the prompt-rent-payment rule. Other areas of slight breaches included livestock rearing, subletting, alteration and repair covenants. Except for tenant reputation and tenant family size, there was no significant relationship between tenant’s health status consideration and the COVID-19 effect on tenant non-compliance with lease obligation. Tenants’ non-compliance with tenancy obligations has a connection with the tenants’ affordability, reputation, ability to sign an undertaking and health conditions during the pandemic. This paper recommends rental housing policy review.

It is recommended that the rental policy should be reviewed to give room for rental allowance or palliatives, private rental market regulation, exploration of the national housing fund and, if possible, social housing adoption policy in Nigeria.

This paper draws policymakers’ attention to the need to prepare for the future safety net that caters to citizenry welfare in challenging times.

Although microfinancing is considered a key tool for fostering women's entrepreneurship development, there is growing concern regarding the impact of loan repayment strategies on the mental health of women entrepreneurs. This study seeks to unravel the implications of microfinance loans on the mental well-being of women entrepreneurs.

A carefully structured questionnaire was distributed to a purposive sample of one hundred women entrepreneurs in Lagos State using a mixed-method research approach. Also, interviews were conducted using an interview guide, which directly mirrored the questionnaire administered to five focus groups within Lagos State.

The study found that loan repayment and recovery strategies positively and significantly impact women entrepreneurs' mental well-being, with psychological distress serving as a measure for measuring mental well-being. Additionally, other factors such as the number of dependants and household headship trigger psychological distress, while age in business was associated with a reduction in psychological distress.

This study contributes to the existing literature by delving into the psychological implications of loan repayment strategies on the mental health of female entrepreneurs in Lagos State, Nigeria. Furthermore, it employs a triangulation research approach to validate questionnaire responses through focus group discussions.

This study aims to examine the social inclusiveness of slum dwellers by focusing on three key institutions which are social relations, government and the labour market. The literature emphasises the activities of these three institutions as indicators of social inclusion. Also, they accurately describe the social interactions of slum inhabitants at different levels.

Three large slums (Makoko, Ilaje and Iwaya) in Lagos State were purposively selected for this study. Using a multi-stage sampling technique, there was the first level of cluster sampling across the communities and second-level random sampling of household heads in the clusters. In all, 400 respondents were sampled but 388 valid responses were used for the analysis.

The study found minimal levels of inclusion in many of the indicators. However, Makoko had a higher degree of inclusion with respect to social relations and political participation compared to the other locations. Due to the poor level of governance, the resilience of slum dwellers has waned.

The study was limited to three of the largest slums in Lagos State. Moreover, due to threats of eviction in recent times, many respondents were reluctant to provide adequate answers to some of the questions asked. However, the responses gotten were adequate to provide appropriate awareness and relevant recommendations.

The use of primary data made it possible for novel results to be generated on social inclusiveness in selected slums. The study extends the frontier of knowledge on social inclusion.

The purpose of this paper is to implement a genetic algorithmic geared toward building an optimized investment portfolio exploring data set from stocks of firms listed on the Nigerian exchange market. To provide a research-driven guide toward portfolio business assessment and implementation for optimal risk-return.

The approach was to formulate the portfolio selection problem as a mathematical programming problem to optimize returns of portfolio; calculated by a Sharpe ratio. A genetic algorithm (GA) is then applied to solve the formulated model. The GA lead to an optimized portfolio, suggesting an effective asset allocation to achieve the optimized returns.

The approach enables an investor to take a calculated risk in selecting and investing in an investment portfolio best minimizes the risks and maximizes returns. The investor can make a sound investment decision based on expected returns suggested from the optimal portfolio.

The data used for the GA model building and implementation GA was limited to stock market prices. Thus, portfolio investment that which to combines another capital market instrument was used.

Investment managers can implement this GA method to solve the usual bottleneck in selecting or determining which stock to advise potential investors to invest in, and also advise on which capital sharing ratio to reduce risk and attain optimal portfolio-mix targeted at achieving an optimal return on investment.

The value proposition of this paper is due to its exhaustiveness in considering the very important measures in the selection of an optimal portfolio such as risk, liquidity ratio, returns, diversification and asset allocation.

The study aims to develop a model that supports the application of data science techniques for real estate professionals in the fourth industrial revolution (4IR) era. The present 4IR era gave birth to big data sets and is beyond real estate professionals' analysis techniques. This has led to a situation where most real estate professionals rely on their intuition while neglecting a rigorous analysis for real estate investment appraisals. The heavy reliance on their intuition has been responsible for the under-performance of real estate investment, especially in Africa.

This study utilised a survey questionnaire to randomly source data from real estate professionals. The questionnaire was analysed using a combination of Statistical package for social science (SPSS) V24 and Analysis of a Moment Structures (AMOS) graphics V27 software. Exploratory factor analysis was employed to break down the variables (drivers) into meaningful dimensions helpful in developing the conceptual framework. The framework was validated using covariance-based structural equation modelling. The model was validated using fit indices like discriminant validity, standardised root mean square (SRMR), comparative fit index (CFI), Normed Fit Index (NFI), etc.

The model revealed that an inclusive educational system, decentralised real estate market and data management system are the major drivers for applying data science techniques to real estate professionals. Also, real estate professionals' application of the drivers will guarantee an effective data analysis of real estate investments.

Numerous studies have clamoured for adopting data science techniques for real estate professionals. There is a lack of studies on the drivers that will guarantee the successful adoption of data science techniques. A modern form of data analysis for real estate professionals was also proposed in the study.

The purpose of this paper is to examine the coffee culture of citizens of Southern Nigeria. Specifically, different scales were developed to measure coffee culture among the citizens which cover health, socialisation, elitism, culture and commercialisation factors.

A quantitative approach was adopted for the study, and factor analysis was used to analyse the data collected through an online survey. As a result, EFA and CFA showed the test of sphericity and the different fit indexes.

The findings revealed the experiences of consumers and their disposition to coffee consumption to establish coffee culture among the citizens. Largely, the findings revealed that coffee culture is still very low among the citizens and the summation that coffee culture is still in infancy.

Given the importance of coffee culture in the larger world, and acceptance of coffee as a global social drink, the design of a scale that focussed on socialisation, health, elitism, culture and commercialisation factors help to robustly investigate the state of coffee culture among the citizens.

Despite its health benefits, vegetable consumption is low in urban Nigeria. Interventions have been successful in increasing urban Nigerians' vegetable intake in the home environment, but interventions doing so for popular out-of-home consumption are lacking. This study aimed to design, implement and assess an intervention to increase the vegetable intake of urban Nigerians through street foods.

A quasi-experimental design was applied in Lagos, Nigeria. During the intervention, 12 trained street food vendors (SFVs) actively promoted the health benefits of vegetables to their customers (using marketing statements and posters) and provided the option to buy an additional green leafy vegetables (GLVs) side dish to their meal. Purchases were observed, and a survey was conducted before and during the intervention to measure perceived meal quality and satisfaction. Six to eight weeks after the intervention, a mystery shopper visited the vendor to assess if they were still selling additional GLVs.

Almost half (46%) of the 1,506 observed customers bought additional GLVs during the intervention. Both at baseline (N = 452) and during intervention (N = 564), meal satisfaction was high. Users were on average more educated and older than non-users. Most vendors did not perceive the sale of additional GLVs as additional work. Six to eight weeks after the intervention, nine vendors (75%) were still selling additional GLVs.

This study showed that SFVs informing consumers on the potential health benefits of vegetables and offering these vegetables in street food dishes at a commercially viable price is an interesting option to increase vegetable intake.