RENT DETERMINANTS FOR RETAIL SHOPPING MALLS IN SOUTHERN NIGERIA

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1 International Journal of Mechanical Engineering and Technology (IJMET) Volume 9, Issue 9, September 2018, pp , Article ID: IJMET_09_09_055 Available online at ISSN Print: and ISSN Online: IAEME Publication Scopus Indexed RENT DETERMINANTS FOR RETAIL SHOPPING MALLS IN SOUTHERN NIGERIA Dr. Omolade A. Akinjare, Dr. Caleb A. Ayedun, Dr. Afolasade O. Oluwatobi, Department of Estate Management, College of Science and Technology P.M.B. 1023, Covenant University, Ota, Ogun State Victoria A. Akinjare Department of Banking and Finance, College of Business Studies P.M.B. 1023, Covenant University, Ota, Ogun State ABSTRACT This study attempts to determine the factors influencing the rentals of major shopping malls in Southern Nigeria by focusing on Lagos and Port Harcourt. By means of a questionnaire survey, a response rate of 62.3% was attained and the data collected was analysed using the linear regression model and ranked arithmetic mean. Findings indicate that the rentals of anchor tenants are a function of the four factors namely: projected financial turnover of the anchor tenant, anchor tenant s potential customer pull, location and physical characteristics of the mall and type and market weight of anchor tenants. In addition, the rents of satellite tenants was found to be anchored on the six factors of : area of the shop, potential to draw customers, size of market being serviced by the mall, location of the mall, location of shop within the mall and potential to draw tenants. The study concludes that mall rents are basically a function of three encapsulating factors namely: Physical, business and lease factors. The study recommends creation of smaller shops within malls in order to increase affordability to prospective mall tenants of lower financial standing. This in turn would ensure affordability and the loyalty of satellite tenants would metamorphose into renewed leases, thus securing mall profitability. Key words: Scan SAR narrow beam, Morphological operation, ENVISAT ASAR, Oil spill. Cite this Article: Dr. Omolade A. Akinjare, Mrs. Victoria A. Akinjare, Dr. Caleb A. Ayedun, Dr. Afolasade O. Oluwatobi, Omololu K. Ibhahulu, Tejiri O. Orlu-Makele and Mary Oluwaseyi Bamisaye, Rent Determinants for Retail Shopping Malls in Southern Nigeria, International Journal of Mechanical Engineering and Technology 9(8), 2018, pp editor@iaeme.com

2 Rent Determinants for Retail Shopping Malls in Southern Nigeria 1. INTRODUCTION The advent of retail mall in Nigeria began in 2005, when The Palms Mall, opened for business as the first major American styled, Nigerian mall in Lekki, Lagos (Estate Intel, 2016). Sequel to the huge success of the Lagos mall, the increased presence of mall investors in the country became inevitable (Ibhahulu, 2017). The Nigeria Real Estate Guide (2015) noted that at the end of 2015, there were ten fully operational malls, eight malls at different stages of completion and many more billed for construction across the country (Awolesi and Ayedun, 2012). The success of the malls became inevitable as shoppers helplessly littered the malls, virtually all day, to window shop, purchase items ranging from ice-cream to electrical goods or to seek for entertainment. Facilitated by the rich variety of goods offered for sale by both local and foreign brands, malls seemed to have become the perfect convergence point for both retailers and their customers (Bamisaye, 2016). With rent affordability being a crucial factor determining the presence of retailers in these malls, the need for an in-depth investigation in to mall rents in Nigeria arises. Consequently, this paper seeks to investigate mall rents and its determinants within the locational context of southern Nigeria. 2. LITERATURE REVIEW According to the College of Estate Management (1975), shopping centre developers and retailers utilise different basic approaches in the assessment of rentals. While retailers use the residual method of rental assessment, developers prefer a variety of methods depending on the peculiarity of the mall. Rent determination may then vary from the rental comparison method to the use of potential turnover rent. The potential rent turnover system of rent determination consists of three possible variants namely; an agreed base rent plus a percentage of the turnover of the shop unit, the greater of an agreed base rent or a fixed percentage of the turnover, and a strata system with decreasing percentage rates for increasing levels of turnover. In literature, studies on mall rent determination were found to be extensive especially with emphasis on commercial retail within the foreign scenery. Early works comprised: Trott, (1980); Fraser, (1988); Sirmans and Guidry, (1992); Tay, Lau and Leung, (1996); Kihore, (1996); Karytinos and Vlachostergiou, (2001) and of recent, Wickramanayake and Weerakoon, (2014). Within the Nigerian framework, Bello, (2012) pioneered studies on shopping center rents and still is the only published work on the subject. The findings of authors have varied just as the studies themselves have varied overtime. Mall rents in Baton Rouge, USA, in accordance with Sirmans and Guidry, (1992), was found dependent on the four factors of; customer drawing power, building configurations, location and better market conditions. Rents were also discovered to be dependent on three major factors. Tay, Lau and Leung (1996) opined these three factors to be physical, business and lease factors. These three factors could be simplified as; the physical characteristics of the units, retailers attributes and terms of lease respectively. Physically, the differentiation of retail units were found to influence rents as tenants who were more concerned about the location of stores within the shopping center were willing to pay higher premiums for units that were prominently and conveniently advantageous. Thus, retail units on the ground floor or floors with connecting footbridge or subways were found to command higher rents. These selective spaces were often secured on a long term basis by chain stores, financial institutions, fashion boutiques and luxury-goods dealers as store image was generally more vital to their businesses. Karytinos and Vlachostergiou (2001) uncovered the reliance of locational and physical factors to the rents of commercial shopping centers in the Greek property market, within the city of Athens. This was similar to the findings of Wickramanayake and Weerakoon (2014) editor@iaeme.com

3 Dr. Omolade A. Akinjare, Mrs. Victoria A. Akinjare, Dr. Caleb A. Ayedun, Dr. Afolasade O. Oluwatobi, where distance to the main road intersection (location) was found most significant of eight factors comprising physical factors such as size of the premises, condition of the building, safety of the building, facing to the main road, display area of the property/ Frontage, availability of parking facilities and availability of convenience. Within the Nigerian clime, Bello (2012) assessed the determinants of rents for shopping center rents in Akure, Ondo state using the questionnaire responses of eighty three retail shops within five shopping centers and the only twenty registered and practicing estate surveyors and valuers in the city based on the 2011 directory of the Nigerian Institution of Estate Surveyors and Valuers (NIESV). The data collected were subjected to the multiple regression model and weighted mean score in determining opinions of the shop occupiers and the estate surveyors and valuers. Findings revealed that the seven factors of influenced the rents of age of mall, area of shop, location, vacancy of shop, gross turnover of sales, population of customers and retail mix were significant determinants of rents for shopping centers. The study recommended the use of qualified estate surveyors and valuers in the management of the retail centers rather than the patronage of charlatans. Based on this backdrop, this paper attempts to examine the factors determining the rents of both anchor and satellite tenants of shopping malls (using the ICSC standard) from the perspectives of both the mall managers, anchor and satellite tenants in Southern Nigeria. 3. STUDY AREA According to International Council for Shopping Centers (ICSC, 1999) standards, only enclosed shopping centers with centrally controlled atmosphere, having at least a total retail area of 10,000sqm are classified as malls. Therefore, only shopping centers meeting this criterion were considered for survey within the geographical confines of South-western Nigeria. Jurisdically, the malls utilized for this study were located in Lagos and Port Harcourt as the two active malls in Effurun (Delta State) and Enugu were not surveyed. Lagos was considered prime as it accommodates more shopping malls than any other state within both the South West Nigeria and Nigeria as a whole. Furthermore, the malls in Benin City, Onitsha and Aba were not operational as at the time of this study but were at different levels of development. Thus, of the eleven malls located within Southern Nigeria (The Nigeria Real Estate Guide, 2015), a total of six malls (five in Lagos and the only mall in Port Harcourt - Port Harcourt Mall) were surveyed in this study. 4. DATA COLLECTION AND RESEARCH METHODS Table 1Mall Characteristics Mall Location Let-able space square metres retail stores Anchor tenants void stores Occupied stores Retrieved Questionnaires Percentage Retrieved (%) Rent per square metre per month The Palms 20, $80 Novare Mall 22, $35 Circle Mall Lagos 13, $44 Festival Mall 11, $34 Ikeja City Mall 23, $75 Total Port Harcourt Mall Port Harcourt 16, % Overall % editor@iaeme.com

4 Rent Determinants for Retail Shopping Malls in Southern Nigeria Data on a ten-year rent, for the selected nine malls were collected via the use of questionnaires distributed to both managers and tenants of the malls. The tenants were further categorised into anchor and satellite tenants and a response rate of 62.3 percent and 56.5 percent was achieved for malls in Lagos and Port Harcourt respectively as depicted by Table 1. Furthermore, the responses of tenants were subjected to multiple regression analysis. In its simplest form, a multiple regression equation can be stated as: R v = α + β ax1 + β bx2 + β cx3 + β dx4 + β exn + e...eqn. 1 Where; R v = a vector of observed rental values α = summarizes the effect of various variables not included in the model β a X1..β ex4 = the unstandardized Beta values of various elements influencing rental value e = the standard error of estimates Finally, the response of the mall managers was collated using a 5 point likert scale. The number 5 was assigned Very High Influence, 4 - High Influence, 3 - Moderate influence, 2 - low influence while 1 signified uncertain influence. Afterwards, the mean score was derived and the result was presented in ranked values. 5. DATA PRESENTATION In ascertaining the determinants of rent, the analysis was segmented into four categories namely: rent determinants for anchor tenants viewed from the perspectives of both the anchor tenants and the mall managers and rent determinants for satellite tenants also viewed from the perspectives of satellite tenants and the mall managers. This was deemed necessary as a pilot study earlier conducted had shown a differential rent payment for the two categories of tenants and in a bid to generate a balanced assessment, the mall managers needed to be assessed. Also, tenants indicated the factors thought to influence rent and same was graded along a 5 point impact scale. The responses for the two categories tenants were then subjected to separate multiple regression analysis Rent Determinants for Anchor Tenants - The Perspective of Anchor Tenants The data collated from the anchor tenants pertaining rent determination was analysed separately using the multiple regression model as seen in Table 2. Table 2 Analysis of Rent Determinants for Anchor Tenants Variables Dependent Independent Rent (Anchor Tenant) Financial contribution of anchor tenant to mall construction Unstandardized Beta Anchor tenant s bargaining power Location and physical characteristics of the mall * Anchor Tenant s Potential to Customer Pull * Occupancy ratio Type and market weight of anchor tenant * Projected financial turnover of the anchor tenant * Number of anchor tenants present in the mall * Sig R 2 F Significant at P> editor@iaeme.com

5 Dr. Omolade A. Akinjare, Mrs. Victoria A. Akinjare, Dr. Caleb A. Ayedun, Dr. Afolasade O. Oluwatobi, Table 2 indicates that five of the eight variables determined rent paid by anchor tenants at different rates based on a 0.5 significance level. These were: projected financial turnover of the anchor tenant (F= 2.752, P<0.036), anchor tenant s potential customer pull (F= 2.752, P<0.038), number of anchor tenants present in the mall (F= 2.752, P<0.044), type and market weight of anchor tenants (F= 2.752, P<0.046) and location and physical characteristics of the mall was least significant at (F= 2.752, P<0.048). Furthermore, an R square of signified that the five significant factors constitute 59.5 percent (roughly 60 percent) of possible determinant of anchor tenant rent. Consistent with equation 1, these five factors are captured in equation 2 as: R AT = PTAT ATPCP NAT TMWAT LPCM Eqn. 2 Where; R AT = Rent paid by Anchor Tenant α= β PTAT = 0.04 PTAT = Projected financial Turnover of Anchor Tenant β ATCP = 0.09 ATPCP = Anchor Tenant s Potential Customer Pull β NAT = NAT = Number of Anchor Tenants in the mall β TMWAT = 0.15 TMWAT = Type and Market Weight of Anchor Tenant β LPCM = LPCM = Location and Physical Characteristics of the mall 5.2. Rent Determinants for Anchor Tenants The Mall Managers Perspective In creating a balanced result, the responses of the mall managers were analysed using the arithmetic mean and Relative Importance index. The analysis is as tabulated in Table 3. Table 3 Analysis of Determinants of Anchor Tenants Rent - Mall Managers Perspective Impact Scale (IS) Mean Ranking Factors Score freq. x IS Financial contribution of the anchor tenant to - 8(2) 2(3) th construction of the mall Anchor tenant s bargaining power (4) 9(5) nd Location and physical characteristics of the (4) 1(5) rd mall Anchor tenant s potential customer pull (4) 1(5) rd Occupancy ratio (5) st The type and market weight of anchor Tenant (4) 1(5) rd Projected financial turnover of the anchor (4) 1(5) rd tenant The number of anchor tenants present in the mall 7(1) 2(2) 1(3) th editor@iaeme.com

6 Rent Determinants for Retail Shopping Malls in Southern Nigeria From the foregoing analysis, occupancy ratio influenced the rents of anchor tenants the most. This was followed by anchor tenant s bargaining power after which four variables tying with a mean score of 2.73 ranked third. These were: location and physical characteristics of mall, anchor tenant s potential customer pull, type and market weight of anchor tenant and Projected financial turnover of the anchor tenant. Finally, the two other variables found insignificant were financial contribution of the anchor tenant to construction of the mall and the number of anchor tenants present in the mall having a mean score of 1.47 and 0.93 respectively Rent Determinants for Satellite Tenants The Perspective of Satellite Tenants In determining the variables influencing the shopping mall rent for satellite tenants, the primary data collected from the satellite tenants were also subjected to multiple regression analysis. The analysis is summarized in Table 4. Dependent Rent (SatelliteTenant) Table 4 Analysis of Rent Determinants for Satellite Tenants Variables Independent Unstandardized Beta Part Correlation Potential to draw tenants * Potential to draw customers * Design functionality Location of the mall * Location of shop within the mall * Size of market being serviced by the mall * Area of each shop * Vacancy ratio of mall Gross turnover of sales Population of customers Retail mix Significant at P>0.05 Sig R 2 F The analysis of Table 4 showed that of the eleven variables signified by satellite tenants to influence rents, only six were found significant at a 0.5 level. Foremost of the factors was area of the shop which was found significant at (F = 1.156, P > 0.021). Others were: potential to draw customers (F = 1.156, P < 0.025), size of market being serviced by the mall (F = 1.156, P < 0.029), location of shop within the mall (F = 1.156, P < 0.035), location of the mall (F = 1.156, P < 0.040), and finally, the least impactful factor was found to be potential to draw tenants (F=1.156, P<0.045). All of the six significant factors accounted for 69.9 percent (roughly 60 percent) of possible determinants of rent as signified by R 2. The significant factors can be summarized in equation 3 stated as: R ST = AS PDC SMSM LoM LSwM PDT...Eqn. 3 Where: R ST = Rent paid by Satellite tenant α = 0.17 β AS = AS = Area of Shop β PDC = editor@iaeme.com

7 Dr. Omolade A. Akinjare, Mrs. Victoria A. Akinjare, Dr. Caleb A. Ayedun, Dr. Afolasade O. Oluwatobi, PDC = potential to draw customers β SMSM = SMSM = size of market being serviced by the mall β LoM = LoM = Location of the Mall β LSwM = LSwM = Location of shops within the mall β PDT = PDT = potential to draw tenants 5.4. Rent Determinants for Satellite Tenants The Mall Managers Perspective As earlier achieved for determinants of rents for anchor tenants, the responses of the mall managers for rent determination for satellite tenants were analysed using the arithmetic mean and Relative Importance index. The analysis is as tabulated in Table 5. Table 5 Analysis of Determinants of Satellite Tenants Rent - Mall Managers Perspective Impact Scale (IS) Mean Ranking Factors Score freq. x IS Potential to draw tenants - - 3(3) 5(4) 2(5) th Potential to draw customers - - 2(3) 5(4) 3(5) rd Design functionality - 2(2) 4(3) 2(4) 2(5) th Location of the mall - - 3(3) 2(4) 5(5) nd Location of shop within the mall - - 2(3) 5(4) 3(5) rd Size of market being serviced by the mall - - 5(3) 2(4) 3(5) th Area of each shop (4) 9(5) st Vacancy ratio of mall 8(1) 2(2) th Gross turnover of sales 7(1) 2(2) 1(3) th Population of customers - - 7(3) 3(4) th Retail mix - 1(2) 6(3) 2(4) 1(5) th Based on the analysis of responses of mall managers, area of each shop was ranked first amongst the eleven variables in determining rents paid by satellite tenants as it had a mean score of This was followed by location of the mall with a mean score of The potential to draw customers and location of shop within the mall were ranked third in order of importance as both had a mean score of Potential to draw more tenants (2.60) to the mall was considered fourth while size of market being serviced by the mall (2.53) were individually considered fifth and sixth in order of influence on rents paid by satellite tenants. Others were the duo of population of customers (2.2) and retail mix (2.2) ranking seventh while gross turnover of sales (0.93) and vacancy ratio of mall (0.93) individually ranked eighth and ninth position. 6. FINDINGS Sequel to the analysis, the rents of anchor tenants were found to be determined mainly by four factors as revealed by both mall managers and anchor tenants. These four factors were: Projected financial turnover of the anchor tenant (business), anchor tenant s potential customer pull (business), location and physical characteristics of the mall (physical) and type editor@iaeme.com

8 Rent Determinants for Retail Shopping Malls in Southern Nigeria and market weight of anchor tenants (business). Beyond the aforementioned four factors, anchor tenants also signified the influence of number of anchor tenants present in the mall (business) in determining the rents they paid. This was unlike the findings from the mall managers who signified the additional factors of occupancy ratio (business) and anchor tenant s bargaining power (lease) in ascertaining anchor tenant rents. Furthermore, the rent of satellite tenants with mall were found to be determined by six factors namely: area of the shop (physical), potential to draw customers (business), size of market being serviced by the mall (business), location of the mall (physical), location of shop within the mall (business) and potential to draw tenants (business). This was established by both the satellite tenants and mall managers. 7. CONCLUSION AND RECOMMENDATION Based on the findings of this study, the average anchor tenant s rent is a function of four factors principally asides three other -number of anchor tenants present in the mall, occupancy ratio and anchor tenant s bargaining power. Thus, the average rent of the anchor tenant can mathematically be stated as: R at =f (Projected financial turnover of the anchor tenant, anchor tenant s potential customer pull, location and physical characteristics of the mall and type and market weight of anchor tenants or better still, can be paraphrased as: R AT = f (PTAT, ATPCP, LPCM, TMWAT). Similarly, the average satellite tenant s being a function of six factors can mathematically be stated as: R ST = f (area of the shop, potential to draw customers, size of market being serviced by the mall, location of the mall, location of shop within the mall and potential to draw tenants) or better still, can be summarized as: R ST = f (AS, PDC, SMSM, LoM, LSwM, PDT). Overall, rents for both anchor and satellite tenants were categorized into three major factors namely: physical, business and lease factors. In consonance with Tay, Lau and Leung (1996), the overall equation can be stated mathematically as: R AT/ST = f (physical, business and lease). The study recommends the creation of smaller shops in the malls in order to increase affordability to prospective mall tenants of lower financial standing. This was envisaged to be in the best interest of mall owners as the loyalty of satellite tenants would translate to lease renewals and extended stay at the mall. ACKNOWLEDGEMENTS The authors appreciate Covenant University, Canaanland, Ota, Nigeria for defraying the publication cost of this research paper. REFERENCES [1] Awolesi, J.A.B., & Ayedun, C.A (2012). An assessment of the effect of renumeration on the conctruction performances of professionals in the Nigerian Building Industry. Mediterranean Journal of Social Sciences (MJSS), 3(1), [2] Bamisaye, O. M. (2017). Assessment of tenant turnover in Ikeja city mall (ICM). (Unpublished B.Sc. project), Covenant University, Nigeria. [3] Bello (2012). The determinants of shopping center rent in Akure, Nigeria. Presented at the FIG working week in Rome, Italy. Held between the 6 th and 10 th of May. [4] College of Estate Management (1975). Rent assessment and tenant mix in planning shopping centers: CALUS research report, Whiteknights, Reading College of Estate Management editor@iaeme.com

9 Dr. Omolade A. Akinjare, Mrs. Victoria A. Akinjare, Dr. Caleb A. Ayedun, Dr. Afolasade O. Oluwatobi, [5] Fraser, W. D. (1988). Valuation Techniques: A matter of Evidence and Motive in French editorial Paper. Journal of Property Investment and Finance, 19 (4), [6] Ibhahulu, O.O. (2017). Determinants of rental value for shopping malls in Lagos metropolis. (Unpublished B.Sc. project), Covenant University, Nigeria. [7] ICSC, (1999). ICSC shopping center definitions: Basic configurations and types. Manual of the International Council of Shopping Centers. New York, US: Runstad Centre. [8] Karytinos, A. & Vlachostergiou, V. (2001). Estimating Commercial Property rentals in the Greek Market using Multiple regression analysis (No. eres2001_196). European Real Estate Society (ERES). [9] Kihore, R. (1996). Discounted cash flow analysis in property investment valuations. Journal of Property Valuation and Investment, 14 (3), [10] Orlu-Makele, T.O. (2016). Assessment of anchor tenant loss and shopping mall rent. Case study: Port Harcourt shopping mall. (Unpublished B.Sc. project), Covenant University, Nigeria. [11] Sirmans, G. S. & Guidry, K. A. (1992) The Determinants of Shopping Centre Rents, The Journal of Real Estate Research, 8(1), [12] Tay, R. S., Lau, C. K., & Leung, M. S. (1996). Rent determination for differentiated retail space in shopping centres. Lincoln University. Commerce Division. [13] Nigeria Real Estate Guide (2015). A publication of Detail Commercial Solicitors, Lagos Nigeria. Retrieved on the 15th of June, 2017 from: media /archive2/real_estate_guide/realestate Guide2015.pdf. [14] Troth, A. (1980). Property Valuation Methods: Interim Report, Polytechnic of the South Bank. Royal Institution of Chartered Surveyors, London. [15] Wickramanayake, W. S., & Weerakoon, K. G. P. K. (2014). Model for Determining Rental Values of Commercial Properties: Case Study in Boralesgamuwa Urban Council Area editor@iaeme.com