This study investigates factors influencing stock-out occurrence in retail shops in Kumasi Metropolis in Ghana. The study sampled two hundred and forty four retail outlets located in the central business areas of Kumasi Metropolis. A well structured questionnaire was used to solicit information from the respondents. Both descriptive statistics and inferential statistics were used to analyse the data. The results of the study revealed that delay in supplier’s items, demand underestimation, and bad back-of-store practices were the main causes of stock-outs. Generally, the study reveals that most retailers are not equipped to use most of the sophisticated stock control techniques and only limit themselves to the use of stock books to control stock. Information and communication technology and collaboration with suppliers were considered by the retailers as the main stock control implementation barriers. The study concludes that, although retailers are aware of the occurrence and the causes of stock-outs, many of them had done little to put in place measures to control it; and even the few that have been able to put in place stock control measures were confronted with implementation challenges. It is therefore recommended that retailers should adopt effective and efficient stock control techniques to limit out-of-stock occurrence.
Retailing includes the business activities involved in selling goods and services to consumers for their personal, family, or household use. It includes every sale to the final consumer. Berman and Evans [
In a highly competitive retail industry, the occurrence of stock-out or out-of-stock (OOS) is an important issue confronting retailers. Its occurrence is a common phenomenon among frequently purchased product categories [
Many authors have stressed that the OOS phenomenon in retail stores is the direct symptom of the failure of some supply processes, such as incorrect estimation of demand, inefficient distribution of products between different stores, incorrect replacement criteria, etc. [
Empirical evidence suggest that stock-out in the retailing industry is common: Vasconcellos [
A rise in purchasing power and a shift towards formal retail space is helping to burnish a positive outlook for retailers in Ghana. Mall retailing is still in its infancy, particularly outside the capital, but international brands and developers are increasingly enthusiastic about the country [
The effects of stock-outs go beyond the lost sales of the item in question. According to Gruen and Corsten [
Despite innovations such as EDI (Electronic Data Interchange) and JIT (Just-in-time) systems that attempt to improve the supply chain between manufacturers and retailers, stock-outs situations still occur [
Even though the importance of this problem cannot be over emphasize, studies on stock-outs come in handy and are mainly focused on understanding consumer reactions to stock-outs, with little research looking into the causes and methods to mitigate it.
The purpose of this study is to investigate factors influencing stock-out in retail shops in Kumasi Metropolis in Ghana.
Inventory management is the “process of efficiently overseeing the constant flow of units into and out of an existing inventory” [
Thus, effective inventory management “is all about knowing what is on hand, where it is in use, and how much finished product results” [
As part of its logistics efforts, a retailer employs inventory management to acquire and maintain a proper merchandise assortment while ordering, shipping, handling, storing, displaying, and selling costs are kept in check. The scope of inventory management “also concerns the fine lines between replenishment lead time, carrying costs of inventory, asset management, inventory forecasting, inventory valuation, inventory visibility, future inventory price forecasting, physical inventory, available physical space for inventory, quality management, replenishment, returns and defective goods and demand forecasting and also by replenishment or can be defined as the left out stock of any item used in an organization” [
It has been argued that “balancing the various tasks of inventory management means paying attention to three key aspects of any inventory”. Generally, the first aspect primarily concerns time. “In terms of materials acquired for inclusion in the total inventory, this means understanding how long it takes for a supplier to process an order and execute a delivery”. Inventory management also demands that a “solid understanding of how long it will take for those materials to transfer out of the inventory be established” [
Calculating what is known as buffer stock is “also key to effective inventory management. Essentially, buffer stock is additional units above and beyond the minimum number required to maintain production levels” [
Inventory management “is not limited to documenting the delivery of raw materials and the movement of those materials into operational process” [
Finally, “inventory management has to do with keeping accurate records of finished goods that are ready for shipment” [
Corsten and Gruen [
Berman and Evans [
A stock-out event occurs where inventories get exhausted. “While out-of-stocks can occur along the entire supply chain, the most visible kind are retail out-of-stocks in the fast moving consumer goods industry (e.g., sweets, diapers, fruits)” [
Ehrenthal et al. [
Stock-out is also defined by Vasconcellos and Sampaio [
According to Berger, “retail stock-outs problems have been studied from two major perspectives: Measurement of stock-outs rates in stores and consumer response to stock-outs”. Zinn and Liu have suggested that “re- gardless of the perspective guiding the research, most studies suggest that managers deal with stock-outs by taking action to reduce the number of stock-outs as much as possible” [
Gruen and Corsten [
Corsten and Gruen [
There are two potential consequences of stock-outs: “subject to distribution inventory stock-outs or manufacturing inventory stock-out, the impact on the supplier and the customer is different in terms of extent and scale, i.e. the impact is greater and more serious for one party than the other one” [
Corsten and Gruen [
It has been argued that “when a supplier is unable to satisfy demand with available inventory, one of four events may occur: 1) The customer waits until the new replenishment arrives; 2) The customer back orders the product; 3) The sale is lost; 4) The customer is lost” [
Krafft and Mantrala [
Brand, item, and category should have no negative consequences for the retailer. In fact, a brand switch from a national brand to a private label may have positive profit consequences owing to higher private label margins. Of the “no-substitute” purchase reactions, store switch in particular has rather negative consequence for retailers. In the case of store switching, consumers visit another store to buy the product that is out of stock. In this competing store, consumers can also purchase products in other categories which they would normally have purchased in the store where the out-of-stock occurred.
According to Corsten and Gruen [
Consequently, Anderson et al. [
This implies that stock-out has consistently remained an important managerial problem.
Zinn and Liu [
According to Bhargava et al. [
The data for the study were predominantly primary data collected from traders who have registered with Kumasi Metropolitan Assembly (KMA) as businesses operating within the metropolis. In all the KMA offices have 1300 registered traders. The total sample size was estimated using an estimation method given by Yamane [
where
n is the sample size;
e = error level; e = 1 ? confidence level; and
N is the total population of registered traders.
Assuming 95% confidence level, e = 0.05 and there are an estimated 1300 registered traders within the study area as provided by KMA officers, a sample size of 300 registered traders were selected for the study However, with a large population, Frankfort-Nachmias and Nachmias [
where
The total sample of 244 respondents was randomly selected for the study.
Descriptive statistics such as frequency tables and percentages were used to present the socio-economic characteristics of respondents and the type of retail businesses they owned. A Logit regression model was used to examine the factors influencing stock-out in these retail shops. The phenomena of retail shops experiencing stock- out or not give a binary dependent variable which can be modeled using the above relationships:
where Yi is equal to one (1) when a respondent (shop owner) experience stock-out and zero (0) otherwise; this means: Equation (1) represents a binary choice model involving the estimation of the probability of respondents experiencing stock-out (Y) as a function of independent variables (X). Mathematically, this is represented as:
where Yi is the observed response for the ith observation of the response variable Y. This means that Yi = 1 for a shop owner who experiences stock-out and Yi = 0 for an owner who does not experience stock-out. Xi is a set of independent variables which are expected to influence stock-out such as literacy, monthly income, age, marital status, gender, etc. associated with the ith individual, which determine the probability of experiencing stock-out (P). The function F may take the form of a normal, logistic or probability function. In this study a logit model was employed to examine the factors influencing stock-out in retail shops. The logit model uses a logistic cu- mulative distributive function to estimate P as follows [
Taking log we have Equation (10) as follows
The empirical model is specified as:
Dependent variable:
Y = 1 if respondent experience stock-out, zero (0) otherwise.
Independent variable:
X1 = Age of shop owner in years;
X2 = Age of the business in years;
X3 = Knowledge of stock management dummy (1 = Has knowledge; 0 = Otherwise);
X4 = Daily sales of the trader;
X5 = Gender of the business operator, dummy (1 = Male; 0 = Otherwise);
X6 = Number of years spent schooling;
X7 = Distance to the nearest supplier office in kilometers;
X8 = Ability to use ICT to order goods (1 = If respondent has ability to use ICT; 0 = Otherwise);
X9 = Size of the business with net assets in Ghana Cedis;
X10 = Number of employees;
X11 = Take records of inflows and outflow of stock.
Kendall’s Coefficient of Concordance (W) analysis was used to rank the items identified as constraints to stock management by the respondents. The degree of agreement of the rankings by the respondents was then measured as W which ranges from 0 to 1. In deriving W, let T represents the sum of ranks for each constraint being ranked by the respondents. The variance of the sum of ranks is given by:
where
where
By simplifying Equation (3) above, the result in the computational formula for
The results of the study indicates that most of the respondents are within the 30 - 39 years age bracket (53%), this is followed by 18 - 29 (20%) while 16% of the respondents are within the age of 40 to 49 years. The rest are 5% and 6% respectively for ages between 50 and 59 years and 60 years above. Thus the majority of the shop owners in the retail sector are in their active ages. This might be due to the fact that the retail business is a very demanding job.
The results also indicate that all the respondents sampled for the study have some level of formal education. Forty-six percent of the respondents had completed Higher National Diploma (HND)/Diploma, 38.0% had Se- nior High School education certificates; while 15% of the respondent had first (Bachelor’s) Degree and only 1
Items | Description | Frequency | Percentages |
---|---|---|---|
Gender | Male | 142 | 58 |
Female | 102 | 42 | |
Total | 244 | 100 | |
Age | 18 - 29 | 49 | 20 |
30 - 39 | 129 | 53 | |
40 - 49 | 39 | 16 | |
50 - 59 | 12 | 5 | |
>60 | 15 | 6 | |
Total | 244 | 100 | |
Education | JHS | 2 | 1 |
SHS | 93 | 38 | |
HND | 112 | 46 | |
Bachelors’ | 37 | 15 | |
Masters | 0 | 0 | |
PhD | 0 | 0 | |
Total | 244 | 100 | |
Experience | 0 - 3 years | 163 | 67 |
4 - 6 years | 56 | 23 | |
7 - 10 years | 15 | 6 | |
>10 years | 10 | 4 | |
Total | 244 | 100 | |
Type of business | Auto parts/Accessories | 37 | 15 |
Office stationeries | 49 | 20 | |
Health and personal care | 61 | 25 | |
Electrical appliances | 20 | 8 | |
General merchants | 77 | 12 | |
Total | 244 | 100 |
Source: Field Survey Data 2014.
person had a master’s degree. The results means that the majority of the employees are SHS and Diploma/HND graduates: This can be attributed to the fact that most of the retail shops begin as family businesses.
Sixty-seven percent of the respondents had been operating their business for 0 - 3 years, 23% had been in the retail business for 4 - 6 years, while 6% had operated retail shops for 7 - 10 years, and only a few of them (representing 4%) had been with an outlet for more than 10 years. This result supports the study which revealed that most SMEs fails within the first 1 - 10 years of its formation [
Respondents were asked to indicate the type of sourcing their outlet uses to stock their shops. The results, as presented in
One of the major objectives of the study is to identify the factors that influence stock-out in retail shops in the Kumasi Metropolis. The estimated logit regression model (
The result shows that 5 out of the 9 independent variables are statistically significant. Age is negative and significantly different from zero at 1%. This means that the younger people have a greater probability of expe- riencing stock-out in their retail shop as compared with older people. However, the square of the age variable is positive and also significant at 1%. This means that as retail shop owner advances in age the probability of stock-out reduces up to a point in age. This is economically plausible since the younger retail shop owners might also be in other businesses and may not have enough time to consistently check their stocks which may lead to stock-out. The marginal effect revealed that an addition year in age would decrease stock-out by 0.014%.
The retail shop owner’s knowledge in stock management was also assessed using a dummy variable. The coefficient of this variable is negative and significant. This implies that those who have knowledge in stock management are less likely to experience stock-out. The marginal effect is 0.40 which implies that those retail shop owners who have knowledge in stock management are 40% less likely to experience stock-out.
Gender in the model was a dummy where one represents the male category. From the results, the variable is significant and positive. This means that the male has a greater probability of experiencing stock-out as com- pared to their female counterparts. This meets the research a priori expectation since the male appear to be involved with a lot of activities and do not have much time to be taking stock regularly as compared to female in the retail businesses. This is in line with the findings of Campo et al., [
Items | Description | Frequency | Percentage |
---|---|---|---|
Type of sourcing | Single | 62 | 25 |
Multiple | 182 | 75 | |
Total | 244 | 100 | |
Supply frequency | Monthly | 192 | 79 |
Weekly | 37 | 15 | |
Random | 15 | 6 | |
Total | 244 | 100 |
Source: Field Survey Data 2014.
Independent variables | Coefficient (St. error) | P-values | Marginal effect |
---|---|---|---|
Age of shop owner in years | −0.7610*** (0.2891) | 0.0001 | −0.0014 |
Age of the business in years | 0.0134*** (0.0050) | 0.0012 | 0.0024 |
Knowledge of stock management | −1.8992*** (0.7638) | 0.0034 | 0.4062 |
Daily sales of the trader | 1.0068 | ||
Gender of the business operator | 1.3489 (0.7897) | 1.8927 | 0.0127 |
Marital status | −1.2970** (0.639) | 0.0420 | 0.1501 |
Number of years spent schooling | 0.1015*** (0.0012) | 0.0015 | 0.2394 |
Distance to the nearest supplier office in kilometers | 0.0043 (0.0075) | 2.0581 | 0.2301 |
Ability to use ICT to order goods | 2.6781*** (0.9245) | 0.0021 | 0.5100 |
Size of the business with the net asset in Ghana Cedis | 0.5315 (0.8940) | 2.3698 | 0.1122 |
Number of employees | 0.2110 (0.4881) | 3.2587 | 0.0045 |
Take records of inflows and outflow of stock | 0.0032* (0.0013) | 0.0789 | 0.0572 |
Constant | −0.3544 (4.0258) | 1.2458 | − |
LR Chi-Square (X) | 193.96 | ||
Pron > Chi-Square | 0.00000 | ||
Log likelihood | −36.3134457 | ||
Pseudo R2 | 0.71028 |
***Significant at 1%; **Significant at 5%; *Significant at 10%; Source: Field Survey Data 2014.
the data revealed that most of the respondents who are married operate the business with their wives. Based on the result of the marginal effect married retail shop owners are 5% less likely to experience stock-out.
From the result, education is significant at 1% significant level and negative. The variable is measured as the total number of years a respondent spend in formal education. The negative coefficient value of the variable means that the more educated retailers are, the less likely they are to experience stock-out. With each additional year of formal education retail shop owners are 34% less likely to experience stock-out. Similar to this was the findings of Campo et al. [
Respondents who are able to use ICT to order goods have a lower chance of experiencing stock-out as this variable has a negative but significant coefficient with a marginal effect of 0.51012. This implies that retail shop owners who used ICT to order goods are 51% less likely to experience stock-out.
The study also revealed that those who keep proper records of their transactions, particularly stock books, are less likely to experience stock-out as the coefficient of this variable is negative and significant at 0%. The mar- ginal effect revealed that retail shop owners who keep stock records are 6% less likely to experience stock-out.
The study identified three main issues that respondent perceived as constraint to stock management. These are inability to forecast demand accurately; inability and lack of use of stock books; and irregular review of stock. The respondents were asked to rank these constraints, and the result of the ranking is presented in
The study revealed that the most important constraint faced by the respondents in management of stock is the
Influencing factors (Constraints) | Frequency* | Percentage | Rank |
---|---|---|---|
Inability to forecast demand accurately | 102 | 21.94 | 3 |
Inability to use stock books | 214 | 46.02 | 1 |
Irregular review of stock | 149 | 32.04 | 2 |
Total | 465 | 100 | |
Coefficient of concordance (W) | 0.6375 (63.75%) |
Source: Field Survey Data 2014. *Multiple response.
inability or lack of use of stock books followed by irregular review of stock while inability of the respondents to forecast demand accurately was ranked third.
The stock-out phenomenon is considered as one of the major problems confronting retailers; and retailers that manage it effectively and efficiently stand to gain a competitive advantage. The occurrence of stock-out reflects all the deficiencies in the supply chain which include incorrect demand forecasting, low replenishment rates, incorrect ordering of products and delays on the part of suppliers [
Beyond the findings from the retailers, the four key conclusions from the research are:
1. Retailers do not have clear insight into issues pertaining to retail logistics and supply systems that are dependent on the use of information technology.
2. Control of data and information coupled with robust logistic system remains the key to availability of products and services.
3. A stock-out situation in a retail shops would be reduced or avoided when retailers form partnerships with logistics providers.
4. Finally a holistic approach in tackling the stock out situations in respect of store forecasting and ordering, replenishment of goods through store stockings and warehousing management; as well as managerial planning would reduce stock out in retail shops.
It is recommended that retailers should take stock frequently and it should be consistent with the market potential and demand as this would not only help them to avoid stock-out but also support them in identifying pilferage of their stock.
Retailers should be educated on retail logistics and supply systems that are dependent on the use of information technology as well as how to keep proper stock books. This would assist them to get goods on time at a cheaper cost and also identify stock which is running out in time to be able to place an order. Retailers should be encouraged to partner logistics providers in areas of information sharing to reduce and possibly avoid stock-out situations. Furthermore, there is the need for a holistic approach in tackling the stock-out situations in respect of store forecasting and warehousing management.