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C. O. A. Ugwumba
Department of Agricultural Economics, Anambra State University, Igbariam Campus

Examining the efficiency of fresh maize marketing and effects of socio-economic and demographic factors on marketing income in Anambra State, this study utilized descriptive statistic, Sherpherd-futrel model of determining marketing efficiency and multiple regression in data analyses. Data were obtained through pre-tested observation instruments administered to 90 respondents. Fresh maize marketing was adjudged a profitable enterprise and was dominated by women (97.8%). The overall marketing efficiency coefficient was 51.16%. Marketing income was significantly influenced by age, gender, marketing experience, marketing cost and savings. Women empowerment could be enhanced by adopting measures that would reduce marketing cost, improve saving and thus marketing efficiency. Such measures should include the provision of soft loans and cheap means of transportation.

Keywords:  Marketing; profitability; efficiency; Sherpherd-Futrel model

Marketing entails all processes involved from the production of a commodity until it gets to the final consumer (Crammer, Jensen and Southgate, 2000). Thses processes ensure that the right product (form utility) is available at the right place (place utility), at the right price (possession utility), and at the right time (time utility) to fully satisfy the consumer ( Beierlein and Woolverton, 1991; Okoh, Ugwumba and Elue, 2008 ). Itenables producers such as farmers as well as middlemen to earn income with which they purchase other useful goods and services ( Ebe, 2007).

After wheat and rice, maize is the most important cereal in the world (Fakorede, Fajemisin, Kin and Iken, 1993). In Nigeria, maize has now rison to a commercial crop providing rawmaterials to agro-based industries. Its consumption accounts for about 64% of the total daily calorie intake of rural dwellers especially during the hunger time. It can be boiled or roasted or dried. Its paste is used in making porridge and pap popularly used by the Easterners in the country as weaning food for children. There is no class distinction in maize consumption and there is no apparent taboos or religious sentiment associated with its production, preservation and utilization (Okafor, 1994).

In the study area, fresh maize marketing is popular in the rainy season ( i.e. between the months of April and November of every year). Marketing agents travel long distances to local maize farms and the only daily fresh maize wholesale market at Onitsha to buy their product for sale from outlets located in different parts of the State. Moreso, maize being an agricultural product is bulky and perishable. It therefore exerts various pressures on handling, packaging, transport and sales with adverse antecedent effect on market prices. In addition, poor storage facilities coupled with improper handling and transportation stress lower quantity and quality and cause losses leading to reduced market margins and poor returns. Thus, the better the market situation of a product, the more the desire for higher production among the farmers.

 This paper seeks to examine the efficiency of fresh maize marketing and the effect of socio-economic variables on income from the marketing process in Anambra state. Specifically, the study examines the marketing channels of fresh maize ;the efficiency of fresh maize marketing ; and the effects of socio-economic and demographic factors on income from fresh maize marketing.

The study was undertaken in Anambra state of Nigeria .The state is situated on a fairly flat land with tropical vegetation. The climate is humid with substantial rainfall and a mean temperature of 87of. It has a weak soil that is easily eroded,

thus accounting for 500 erosion sites of varying dept and length (Anambra State Economic Development Strategy, 2006). Farming is the predominant occupation .It is carried out at the family level and it is mainly for subsistence .The little surplus production that may be generated is sold for money used to purchase non-farm commodities. Over the years , women are found to be heavily involved in petty trading attributed to lack of capital and access to loanable funds or credits (SEEDS, 2006).

Random sampling technique was used to select 90 respondents at Onitsha, Awka and Nnewi metropolitan cities of the state for the study. Data was collected through primary sources. Primary sources of data, which were cross-sectional, involved the use of structured questionnaire items administered   to the farmers , observations and memory recall .The complements of secondary data in fine tuning the work were also explored. Information obtained included  socio-economic and demographic factors such as age,
marital status, marketing experience , educational level, access to credit and family size and saving .The prices of product and input were also identified.

Descriptive statistics  such as frequency ,mean and percentages were used in describing socio-economic and demographic variables , while  Shepherd –Futrel technique, net profit analysis and multiple regression were respectively employed to determine marketing efficiency, profitability and effects of socio-economic and demographic factors on income realized from fresh maize marketing business. To determine the efficiency of fresh maize marketing the Sherpherd-Futrel model was employed. This model propounded by Sherpherd  and Futrel (1982) considers as an accurate measure of marketing efficiency the coefficient of total cost of marketing to total revenue expressed in percentage term. The model is specified as:

                       ME = TC X 100        or     TR- TC  X  100
                                  TR       1                      TC             1
                       ME = Coefficient of marketing efficiency.
                       TC  = Total cost incurred.
                       TR  =  Total value of products sold.
Net profit analysis was deployed for profitability assessment for the agents (producers, wholesalers and retailers). The analytical technique used is given as
                       NP = TR-TC
      Where: NP = Net profit.
                  TR = Total revenue.
                   TC = Total cost.

Multiple regression analysis following Lucey (2004) was adopted to analyze the effects of socio-economic and demographic factors on marketing income, and is implicitly specified as:
                  MI = f (AGE, MST, EDU, ACC, GEN, MKE, MKC, SAV ).
                  MI = Marketing income ( N ).
                  AGE = Age of marketer (years)
                  MST = Marital status (Dummy: married=1, single=0)
                  EDU = educational level (years)
                  ACC = Access to credit (Dummy: accessed credit=1, otherwise=0)
                  GEN = Gender of marketer (Dummy: male=1, female=0)
                  MKE = Marketing experience (years)
                  MKC = Marketing cost ( N )
                  SAV = Savings (N )
                    U = Stochastic or error term

Results and discussions

Table 1 below profiles the socio-economic and demographic characteristics of fresh maize marketers in the study area. Majority of them (72.2%) fell within the active, strong and productive age range of 31-50 years. This is an

indication that fresh maize marketing especially in roasted form requires youths who are active, strong and can therefore withstand the stress associated with purchasing, roasting and marketing of roasted maize cobs.


Table 2: Estimated profitability and efficiency of fresh maize marketing

Item                              Agent/Amount (N)                                       Total Amount ( N )
                                   Producer       Wholesaler         Retailer
Annual sales               80,000           106,000            150,000
Total revenue                                                                                        336,000
Variable costs:
Cost price                   40,000              42,600              65,000
Transportation                -                    18,600              11,200
Labour charges             2,240                 1,800                2,000
Market charges               -                       1,200                1,400
Other charges                    -                      1,000                    400
Fixed costs:
Annual rent                        -                        500                     -
Depreciation on barrow    200                       -                       -
Depreciation on Burner      -                          -                       100
Depr. On equipments          140                       -                       200
Total Cost                       42,600              65,000                81,100             188,700
Net profit                         37,400             41,000                68,900             147,500
Marketing efficiency
    ( TC/TR X 100) =       53.25%            61.32%               54.06%              56.16%

Source: Field survey 2008.                                                                          

N37,400.00 or 25.39 was scored by the retailers .

Results of analysis of coefficient of marketing efficiency are as shown in Table 2. An overall coefficient of marketing efficiency of 0.56 or 56.16% was recorded by the agents. This implies that 51.6% of sales revenue of the agents is taken up by costs. Efficiency of fresh maize marketing could be increased by adopting those measures that will increase revenue, reduce marketing cost and thus reduce coefficient of marketing efficiency. This is because, the lower the coefficient of marketing efficiency, the higher the level of efficiency. Thus, in the study area the producers were more efficient (0.53 or 53.25%), than the retailers (0.54 or 54.06%), and then the wholesalers (0.61 or 61.32%).

Effect of social economic and demographic factors on marketing income
The multiple regression analysis involved running three models of the equation, linear, semi-log, and double-log and choosing the one with the best signs and magnitude and highest coefficient of determination (R2) and F-ratio as the lead equation. The double-log equation model was chosen and the result for the marketing income function is presented below.

-1.349 – 0.149log * + 0.176logMST – 0.022logEDU + 0.197logACC
 (-0.048)    (-2.614)               ( 0.816)                (-0.007)             (0.192)

 -0.678logGEN* + 0.526logMKE* - 0.211logMKC* + 0.467logSAV*                                            

 (6.124)                    (2.389)                (-0.2.014)              (3.867)

  R2 = 0.78

  F = 56.17

  • = significant at 5% probability level.

   Values in parenthesis represent corresponding t-values.

 The coefficient of determination (R2) value of 0.78 implies that 78% of the variation in fresh maize marketing income is explained by age, marital status, education, access to credit, gender, marketing experience, marketing cost and savings. The F-ratio is statistically significant at 5% level of probability, further confirming the overall significance of the parameter estimates in the relationship.

Age of the marketer is negatively correlated with marketing income but significant at 5% level of probability. Marital status affects fresh maize marketing positively and significantly too. This suggests that married people are more likely to earn income from the business than individuals who are single. The reason could be that married marketers would have accumulated experience and resources to enable them excel in the business. Moreso, results of the regression analysis also show that marketing experience has positive relationship with marketing income and significantly determined it. Access to credit and savings are positively correlated with marketing income implying that marketers who have large resources will sell more fresh maize and realize more income than those with small capital. However, results of the regression analysis show that access to credit is not a significant determinant of marketing income but savings is.
Level of education is negatively signed and not statistically significant at 5% level of probability. Thus, marketing income was not influenced by the number of years spent in formal education. This implies that the act of fresh maize marketing could be acquired informally. Again the higher one’s level of education, the more he engages in lucrative businesses other than fresh maize marketing which is assumed to be more tedious.

The coefficient of gender is negatively correlated with marketing income and is significant. Given that this is a dummy variable (male = 1, female = 0 ), the reason could be that men looked down on fresh maize marketing business as petty trading meant for the women. This is also evidenced by the 97.8% of female participants in the business (Table 1). Marketing cost is negatively correlated with marketing income, implying that higher marketing cost is more likely to result in lower marketing income than lower marketing cost. Results of the regression analysis show that marketing cost is a significant determinant of marketing income.

Conclusion and recommendation
This study estimated the efficiency of fresh maize marketing and the effects of socio-economic and demographic factors on marketing income. Fresh maize marketing business was dominated by women, majority of whom attained basic education, were married, young and experienced. Results of data analysis also revealed the business as a profitable one with the producers, wholesalers and retailers realizing net profits of N37,400.00,  N41,000.00, and N68,900.00  respecAtedly. The overall coefficient of marketing efficiency was 0.56 or 56.16%. However, the producers were more efficient in marketing (53.25%) than the retailers (54.06%), and lastly the wholesalers (61.32%).
Marketing income was positively influenced by marital status, access to credit, marketing experience and savings. It was however, negatively affected by age, educational level, gender and marketing cost. Fresh maize marketing, though profitable, was dominated by women (97.8%), majority of whom are regarded as poor and less privilaged in the society. Policy must be geared towards those measures that will empower them, increase their participation and efficiency in order to better their lives. Such measures should include the provision of soft loans, infrastructural facilities, especially cheap mass transport system, and enlightenment campaigns.

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