MUKUCHA, P., JARAVAZA, D.C., SARUCHERA, F. 

STRATEGIC POSTPONEMENT IN FAST FOOD OPERATIONS: ENHANCING ORDER FULFILMENT IN A FRONTIER 

EMERGING MARKET 

  

 

 

B
u

s
in

e
s

s
 E

x
c
e

ll
e
n

c
e
 a

n
d

 M
a
n

a
g

e
m

e
n

t 

V
o

lu
m

e
 1

5
 I
s

s
u

e
 2

 /
 J

u
n

e
 2

0
2

5
 

T
h
e
or

e
ti
ca

l 
a
nd

 E
m
pi
ri
ca

l 
R
e
se

a
rc

h
e
s 

in
 U

rb
a
n 

M
a
na

ge
m
e
nt

 

 

5 

 

STRATEGIC POSTPONEMENT IN FAST FOOD 

OPERATIONS: ENHANCING ORDER 

FULFILMENT IN A FRONTIER EMERGING 
MARKET 

 

Paul MUKUCHA 

Bindura University of Science Education, Bindura, Zimbabwe 
paulmukucha@gmail.com 

 

Divaries Cosmas JARAVAZA 

Bindura University of Science Education, Bindura, Zimbabwe 
djaravaza@buse.ac.zw 

 

Fanny SARUCHERA 

University of the Witwatersrand, Johannesburg, South Africa 
fanny.saruchera@wits.ac.za 

 
 

 

Abstract  
This research explores the effect of strategic postponement on order fulfilment performance within Zimbabwe's 
fast-food sector, a vital yet underexamined area in Sub-Saharan African market studies. This investigation is 
propelled by the notable lack of empirical scrutiny on postponement strategies in the region's fast-food industry, 
particularly within the challenging context of Zimbabwe's volatile economy. Such conditions offer limited 
managerial insights into the correlation between form postponement and order fulfilment efficiency, diverging from 
the trends observed in more developed and saturated markets. Utilising a causal research framework, the study 
gathered data from a survey of 100 fast food establishments in Harare, employing Multivariate Analysis of 
Variance (MANOVA) for data analysis, complemented by Bonferroni correction to mitigate type 1 error from 
multiple comparisons. Findings indicate that restaurants implementing a postponement strategy significantly 
outperform their counterparts in order fulfilment metrics. The study advocates for the adoption of postponement 
strategies by fast food operators to enhance order fill rates, accuracy, and cycle times, thereby navigating the 
complexities of emerging markets more effectively. Despite its insightful contributions, the study acknowledges its 
geographical limitation to Zimbabwe, attributed to budgetary restraints.  

Keywords: Postponement strategy, Order fill rate, Order fulfilment cycle time, Order fulfilment accuracy. 
DOI: https://doi.org/10.24818/beman/2025.15.2-01 
 
 
 
 
 
 

mailto:paulmukucha@gmail.com
mailto:djaravaza@buse.ac.zw
mailto:fanny.saruchera@wits.ac.za
https://doi.org/10.24818/beman/2025.15.2-01


 

 

 

 

 

 

MUKUCHA, P., JARAVAZA, D.C., SARUCHERA, F. 

STRATEGIC POSTPONEMENT IN FAST FOOD OPERATIONS: ENHANCING ORDER FULFILMENT IN A FRONTIER 

EMERGING MARKET  

 

  

 
 

B
u

s
in

e
s

s
 E

x
c
e

ll
e
n

c
e
 a

n
d

 M
a
n

a
g

e
m

e
n

t 

V
o

lu
m

e
 1

5
 I
s

s
u

e
 2

 /
 J

u
n

e
 2

0
2

5
 

T
h
e
or

e
ti
ca

l 
a
nd

 E
m
pi
ri
ca

l 
R
e
se

a
rc

h
e
s 

in
 U

rb
a
n 

M
a
na

ge
m
e
nt

 

 

6 

1. INTRODUCTION  

The concept of postponement was first coined by Alderson (1950) to refer to the delay in determining a 

product's form, identity, or placement until a customer's specific requirements are ascertained. 

Postponement is also a supply chain management concept where a generic product is produced using a 

make-to-stock strategy and later modified using a make-to-order strategy (Prataviera et al., 2024). It is a 

push strategy driven by an uncertainty in demand for the final product (Prataviera et al., 2020). Instead of 

producing a product to its finality, the postponement strategy advocates for stocking semi-finished goods 

until demand patterns are clearer (Prataviera et al., 2024). The completion of the production process upon 

receiving a definite customer order is motivated by the need to eliminate incorrect product deployment, 

eradicate higher inventory costs, and avoid stock obsolescence (Siiskonen et al., 2023). Thus, 

postponement involves a decoupling point where demand changes from being independent to a 

dependent status (Olhager & Van Donk, 2024). 

Businesses in general and restaurants in particular benefit through making shorter forecasting horizons 

(Fildes et al., 2022; Ma & Fildes, 2020) and customisation of generic products (Siiskonen et al., 2023; 

Lyons et al., 2020). Postponement generally applies to production processes involving a production 

system whose output at various nodes is modular (Becker et al., 2021). The modular product design has 

exchangeable components, is loosely coupled, and is scalable (Becker et al., 2021). There are generally 

three generic types of postponement: form, time, and place postponement (Zinn & Bowersox, 1988). In the 

fast-food restaurant industry, form postponement is the most common. Fried chicken and chips, the most 

common product line in the fast-food industry in Zimbabwe (Mukucha et al., 2024), are served through the 

form postponement strategy. Fried chicken and chips are prepared using the lean strategies under the 

assembly line method. However, differentiation is delayed until an ascertainment of customer orders, 

which differ due to varying flavours and pack sizes of menu items (Seo, 2020). 

The fast-food industry is associated with the provision of ready-made food in order to keep in line with its 

key distinctive features of easy accessibility and convenience (Abdollahnejad et al., 2025). The 

customisation aspect of the generic meal comes in when the restaurant caters to varied patrons' needs in 

terms of flavours, temperature, and pack sizes (Yoon et al., 2020). Therefore, this study seeks to 

determine the effects of postponement strategy on order processing metrics in the fast-food restaurant 

industry. 

This investigation is propelled by the notable lack of empirical scrutiny on postponement strategies in the 

region's fast-food industry, particularly within the challenging context of Zimbabwe's volatile economy. 

Thus, the objective of this article is to investigate the relationship between product postponement 

strategies and order fill rates. We intend to offer insights into the potential benefits of postponement for 



 

 

 

 

 

 

MUKUCHA, P., JARAVAZA, D.C., SARUCHERA, F. 

STRATEGIC POSTPONEMENT IN FAST FOOD OPERATIONS: ENHANCING ORDER FULFILMENT IN A FRONTIER 

EMERGING MARKET 

  

 

 

B
u

s
in

e
s

s
 E

x
c
e

ll
e
n

c
e
 a

n
d

 M
a
n

a
g

e
m

e
n

t 

V
o

lu
m

e
 1

5
 I
s

s
u

e
 2

 /
 J

u
n

e
 2

0
2

5
 

T
h
e
or

e
ti
ca

l 
a
nd

 E
m
pi
ri
ca

l 
R
e
se

a
rc

h
e
s 

in
 U

rb
a
n 

M
a
na

ge
m
e
nt

 

 

7 

improving order fulfilment performance since order fulfilment is crucial for enhancing customer outcomes 

such as customer satisfaction and loyalty. Eventually, our findings may provide some valuable implications 

for practitioners in search of operational strategies that enhance greater efficiency and higher order 

fulfilment levels. Henceforth, the rest of the study is organised as follows: a literature review related to how 

various dimensional aspects of order fulfilment metrics are impacted by the postponement strategy, 

operationalisation of the study variables, data collection procedures, data analysis, and lastly, a discussion 

of the results that culminates in the formulation of the recommendations and managerial implications of the 

study. 

 

 

2. LITERATURE REVIEW 

The concept of postponement refers to the delay in coming up with product-specific attributes to avoid a 

mismatch between customer orders and the inventory at hand (Jafari et al., 2021; Lysons & Farrington, 

2020). It can also be regarded as an order fulfilment strategy to ensure that firms supply what customers 

require (Mukucha & Chari, 2023). Postponement can be done as late as the order fulfilment phase 

(Christopher, 2020). Postponement is a combination of push strategies and pull strategies whereby the 

initial phase involves pushing a product along the supply chain up to a certain point where the pulling of a 

product takes over depending on the requirements of the customers (Chopra et al., 2018), thus deriving 

product differentiation at the later stages of the supply chain (Jafari et al., 2022). 

Postponement allows for differentiation at various production points, such as assembling, packaging, and 

labelling (Christopher, 2022). Kotler and Keller (2016) identified the levels of a product as core, actual, and 

augmented. The postponement assembling is at the actual production levels, where differentiation comes 

from the ingredients used in making the product. At the augmented level, postponement comes in the form 

of packaging. In this study, postponement is proposed to lead to an improvement in order fulfilment 

performance metrics. There are several order fulfilment performance metrics, and these include order 

fulfilment rate, order cycle fulfilment time, and order cycle fulfilment accuracy (Chopra et al., 2018).  

 

2.1 Form postponement and order fulfilment rate 

Order fill rate in supply chain management is a percentage of customer orders that a firm can deliver to 

customers without missing a sale or recording backorders (Chopra et al., 2018). It can also be explained 

as the fraction of orders placed and filled from the inventory at hand (Sanders, 2025). Backorders are 

orders that cannot be met with the available stock, leading to customers having to wait for some time 

before they receive their orders (Lysons & Farrington, 2020). The fill rate is determined by dividing the 



 

 

 

 

 

 

MUKUCHA, P., JARAVAZA, D.C., SARUCHERA, F. 

STRATEGIC POSTPONEMENT IN FAST FOOD OPERATIONS: ENHANCING ORDER FULFILMENT IN A FRONTIER 

EMERGING MARKET  

 

  

 
 

B
u

s
in

e
s

s
 E

x
c
e

ll
e
n

c
e
 a

n
d

 M
a
n

a
g

e
m

e
n

t 

V
o

lu
m

e
 1

5
 I
s

s
u

e
 2

 /
 J

u
n

e
 2

0
2

5
 

T
h
e
or

e
ti
ca

l 
a
nd

 E
m
pi
ri
ca

l 
R
e
se

a
rc

h
e
s 

in
 U

rb
a
n 

M
a
na

ge
m
e
nt

 

 

8 

number of orders fulfilled by the total number of orders received (Lysons & Farrington, 2020). Attaining a 

maximum order fill rate improves the relationship between a business and its customers (Coyle et al., 

2021), shows how well a business manages its inventory through logistics and supply visibility (Chopra et 

al., 2018), and alerts businesses to lost sales due to understocking (Christopher, 2022). 

Customers place orders with full confidence that the business they approach has what they want in stock 

(Kotler & Keller, 2016). They usually invest much time physically or electronically visiting business 

organisations, incurring monetary or time-wise expenses. These costs may be in the form of time away 

from their usual places of residence or financial in terms of the travelling costs or data costs if the visit is 

done online. Therefore, finding the needed item out of stock may lead to embarrassment and discomfort, 

resulting in unfavourable behavioural tendencies like customer defections and spreading negative word of 

mouth (Taylor, 1994). The prevalence of out-of-stock situations is common in industries where make-to-

stock production systems are practised (Christopher, 2022), yet the market needs are diverse. In such 

markets, customers may not be willing to accept the substitutes. This is common in the restaurant industry. 

One of the limited solutions open to businesses operating in markets with varied needs is to practice a 

form postponement strategy. The postponement has ample inventory kept in a semi-finished state and 

finalised upon receipt of definite customer orders (Christopher, 2022). That was, the order fill rate tended 

to improve to acceptable levels. Therefore, it is predicted that: 

H1: Form postponement has a statistically significant effect on order fill rate. 

 

2.2 Form postponement and order fulfilment time 

Order cycle fulfilment time is a supply chain metric that assesses the duration that lapses between the time 

a customer places an order and the time the receipt of an order is made (Lysons & Farrington, 2020). This 

metric provides insight into the internal efficiency of the order fulfilment process and the entire supply chain 

in general (Chopra et al., 2018). Making customers wait too long affects their satisfaction and repatronage 

behaviours (Wirtz & Lovelock, 2021). Worse, some customers may cancel orders if they are not received 

in time (Lysons & Farrington, 2020). Such a move may lead to immediate losses since businesses with 

cancelled orders may end up with products that may not be resold, especially in the case of restaurant 

orders.  

Generally, customers do not enjoy waiting (Wirtz & Lovelock, 2021). The sentiments of customers towards 

waiting have already been profiled by Maister (1988). He said the perceived waiting duration could be 

shorter if explained, in-process, fair, occupied, and inevitable if possible customers would prefer to get their 

orders upon placing an order (Al-Adwan et al., 2022). However, the prompt receipt of an order is possible 

in make-to-stock production systems where customer needs are known in advance, and the quantity 



 

 

 

 

 

 

MUKUCHA, P., JARAVAZA, D.C., SARUCHERA, F. 

STRATEGIC POSTPONEMENT IN FAST FOOD OPERATIONS: ENHANCING ORDER FULFILMENT IN A FRONTIER 

EMERGING MARKET 

  

 

 

B
u

s
in

e
s

s
 E

x
c
e

ll
e
n

c
e
 a

n
d

 M
a
n

a
g

e
m

e
n

t 

V
o

lu
m

e
 1

5
 I
s

s
u

e
 2

 /
 J

u
n

e
 2

0
2

5
 

T
h
e
or

e
ti
ca

l 
a
nd

 E
m
pi
ri
ca

l 
R
e
se

a
rc

h
e
s 

in
 U

rb
a
n 

M
a
na

ge
m
e
nt

 

 

9 

demanded can be forecasted accurately (Rau et al., 2021; Saruchera & Asante‐Darko, 2021). In some 

industries with higher customer needs variability, the only viable production system is the make-to-order 

strategy. The connotations of this strategy are that customers would be forced to wait while their orders are 

being prepared and processed (Wirtz & Lovelock, 2021). However, adopting the form postponement 

strategy suggests that a lean production of a generic product version can be done up to a decoupling point 

from which product variants can be made upon receiving a definite customer order. That way, the duration 

of an order fulfilment is reduced to acceptable levels. Based on this discussion, it is anticipated that: 

H2: Form postponement has a statistically significant effect on order cycle fulfilment time. 

 

2.3 Form postponement and order fulfilment accuracy 

Order fulfilment accuracy refers to the number of accurately processed orders as a proportion of the total 

number of orders processed (Chopra et al., 2018). Order fulfilment accuracy leads to accelerated 

profitability (Lysons & Farrington, 2020), reduces incorrect deliveries (Coyle et al., 2021), and improves 

customer retention (Kotler & Keller, 2016). Inaccurate order processing is associated with costly returns 

(Chopra et al., 2018) that can harm a business's reputation and negatively impact the customers' 

patronage behaviours and re-patronage intentions (Al-Adwan et al., 2022). 

Order fulfilment accuracy is one of the most important metrics businesses have to monitor religiously 

(Lysons & Farrington, 2020). Delivering wrong orders to customers is usually associated with negative 

consequences for the customers and the businesses (Mukucha & Chari, 2023). In critical industries such 

as medical businesses, giving a customer a wrong prescription may result in the customer losing his or her 

life. At the same time, the business that gave the wrong prescription may be sued or have its operating 

license withdrawn. The same happens in restaurants where giving customers wrong orders may cause 

patrons to consume food that may harm their health or lead to switched orders that may end up hurting all 

the customers involved in a service failure. Thus, ensuring accuracy in order fulfilment may prevent 

financial losses to the business and its customers (Chopra et al., 2018). Accuracy is attained if a business 

accurately captures customers' needs instead of delivering what it thinks are the needs of customers 

(Kotler & Keller, 2016). Therefore, it is thus suggested that form postponement can align the production 

system with the customers' requirements. This is because production is based on the customer's definite 

and precise order (Lysons & Farrington, 2020). Therefore, it is reasonable to suggest that: 

H3: Form postponement has a statistically significant effect on order cycle fulfilment accuracy. 

 

 

 



 

 

 

 

 

 

MUKUCHA, P., JARAVAZA, D.C., SARUCHERA, F. 

STRATEGIC POSTPONEMENT IN FAST FOOD OPERATIONS: ENHANCING ORDER FULFILMENT IN A FRONTIER 

EMERGING MARKET  

 

  

 
 

B
u

s
in

e
s

s
 E

x
c
e

ll
e
n

c
e
 a

n
d

 M
a
n

a
g

e
m

e
n

t 

V
o

lu
m

e
 1

5
 I
s

s
u

e
 2

 /
 J

u
n

e
 2

0
2

5
 

T
h
e
or

e
ti
ca

l 
a
nd

 E
m
pi
ri
ca

l 
R
e
se

a
rc

h
e
s 

in
 U

rb
a
n 

M
a
na

ge
m
e
nt

 

 

10 

3. METHODS 

 

3.1 Population and sampling  

The population of this study was all the fast-food restaurants in Harare. There are no official statistics on 

the population size of all the restaurants in Harare due to the shambolic administration systems in most 

third-world countries. Due to the unavailability of the sampling frame, the researchers used convenience 

sampling methods (Struwig & Stead, 2013). Convenience sampling is a non-probability sampling method 

(Saunders et al., 2024). That means the researchers had to rely on those restaurants that were easily 

accessible and willing to be part of this study. The sample size of 100 was therefore determined based on 

the statistical requirements of the statistical tools used for analysing the data. 

 

3.2 Data collection instrument 

The data collection instrument used to assess all the study variables of postponement strategy, order 

fulfilment rate, order cycle fulfilment time, and order fulfilment accuracy was a questionnaire. The 

postponement was operationalised as a binary construct with yes for the implementation of the strategy 

and no for non-implementation. The order fill rate was operationalised as the percentage of orders satisfied 

with the inventory (Larsen & Thorstenson, 2012). Order cycle fulfilment time was operationalised as the 

time a customer has to wait before he/she receives his/her order. Order fulfilment accuracy was 

operationalised as the percentage of orders correctly delivered to the customers. 

 

3.3 Data collection procedures 

Using a self-administered questionnaire, data were collected from chief operating officers or their 

equivalents at fast-food restaurants in Harare. These chief operating officers provided data on 

postponement strategies adopted, order fill rate, order cycle fill time, and order cycle fill accuracy. Given 

the busy schedules of respondents, the self-administered survey gave the respondents enough time to 

respond to the questions on their own time without feeling pressured by the presence of researchers. After 

a few days, the researchers would return to the respondents to collect the filled questionnaires. That way, 

the researcher managed to attain a 100% response rate. 

 

3.4 Data analysis procedures 

Hypotheses testing was conducted using One-way Multivariate Analysis of Variance (MANOVA) through 

the Statistical Package for Social Scientists (SPSS) version 26. One-way MANOVA is a multivariate 

statistical tool used for assessing the effects of a single independent variable on multiple dependent 



 

 

 

 

 

 

MUKUCHA, P., JARAVAZA, D.C., SARUCHERA, F. 

STRATEGIC POSTPONEMENT IN FAST FOOD OPERATIONS: ENHANCING ORDER FULFILMENT IN A FRONTIER 

EMERGING MARKET 

  

 

 

B
u

s
in

e
s

s
 E

x
c
e

ll
e
n

c
e
 a

n
d

 M
a
n

a
g

e
m

e
n

t 

V
o

lu
m

e
 1

5
 I
s

s
u

e
 2

 /
 J

u
n

e
 2

0
2

5
 

T
h
e
or

e
ti
ca

l 
a
nd

 E
m
pi
ri
ca

l 
R
e
se

a
rc

h
e
s 

in
 U

rb
a
n 

M
a
na

ge
m
e
nt

 

 

11 

variables (Field, 2024) and is an extension of the univariate Analysis of Variance (ANOVA) (Hair et al., 

2014). MANOVA reduces the inflation of Type 1 errors common in related post hoc tests, including 

ANOVA (Warne, 2014; Tabachnick & Fidell, 2013). The validity of results emanating from MANOVA tests 

depends on meeting MANOVA statistical assumptions (Field, 2024). The statistical assumptions were 

assessed, and the hypotheses were tested. The Bonferroni correction was done to cater for numerous 

comparisons (Hunt, 2022).  

 

 

4. RESULTS 

The results presented in this section relate to the studied firms' sample characteristics and hypotheses 

testing. 

 

4.1 Sample characteristics 

As shown in Table 1, the respondents in this study were top-level managers; 60% and 40% were male and 

female, respectively. 

TABLE 1. DEMOGRAPHIC PROFILE OF RESPONDENTS 

Attribute N % 
Buyer characteristics   

Gender   

Male 40 40 

Female 60 60 

Experience   

0-1 55 55 

2-4 30 30 

5 and above 15 15 

   

Firm characteristics   

Location   

Urban 63 63 

Resort Centre 30 30 

Along Highways 07 07 

Firms' structure   

Single entity restaurants 75 75 

Chain restaurants 25 25 

Source: authors’ research 

 

Their experience was largely above five years. Most of the restaurants surveyed were located in the CBD 

(58%), followed by the industrial areas (32%), and lastly, residential areas (10%). 23% of the surveyed 

restaurants were part of restaurant chains, while 77% were stand-alone. Table 2 shows the descriptive 

statistics regarding the number, mean and standard deviation of the OFR, OCFT and OCFA for the 

restaurants studied.  



 

 

 

 

 

 

MUKUCHA, P., JARAVAZA, D.C., SARUCHERA, F. 

STRATEGIC POSTPONEMENT IN FAST FOOD OPERATIONS: ENHANCING ORDER FULFILMENT IN A FRONTIER 

EMERGING MARKET  

 

  

 
 

B
u

s
in

e
s

s
 E

x
c
e

ll
e
n

c
e
 a

n
d

 M
a
n

a
g

e
m

e
n

t 

V
o

lu
m

e
 1

5
 I
s

s
u

e
 2

 /
 J

u
n

e
 2

0
2

5
 

T
h
e
or

e
ti
ca

l 
a
nd

 E
m
pi
ri
ca

l 
R
e
se

a
rc

h
e
s 

in
 U

rb
a
n 

M
a
na

ge
m
e
nt

 

 

12 

TABLE 2. DESCRIPTIVE STATISTICS 

 Postponement 
Strategy 

Mean Std Deviation N 

OFR Yes 95.82 2.118 49 

 No 90.49 2.679 51 

 Total 93.10 3.600 100 

OCFT Yes 97.02 3.626 49 

 No 90.75 2.521 51 

 Total 93.82 4.418 100 

OCFA Yes 97.71 2.160 49 

 No 90.53 3.331 51 

 Total 94.05 4.571 100 

Source: authors’ research 

 

4.2 Hypotheses testing 

The three study hypotheses suggested statistically significant differences between restaurants that follow 

the postponement strategy and those that do not pursue the same strategy regarding order fulfilment rate, 

order cycle fulfilment time and order fulfilment accuracy. These three hypotheses were tested using One-

way MANOVA. Prior to hypothesis testing, the assumption of correlation was assessed and was found to 

be statistically significant for all the pairs. MANOVA's power is affected by the correlations of the 

dependent variables and by the effect sizes associated with those variables (Saunders et al., 2024). For 

example, in the case of two groups and two dependent variables, MANOVA's power is weaker when the 

correlation equals the ratio of the smaller to the larger standardised effect size (Field, 2024). The other 

assumptions of MANOVA, such as multivariate normality and equality of covariance, were side-lined on 

the basis that the departures from multivariate normality are inconsequential when the sample sizes are 

larger (Hair et al., 2014), and there were equal cases in each group (Field, 2018) respectively. Therefore, 

Pillai's Trace, which is robust to all these violations of these assumptions, was used (Field, 2024). 

TABLE 3. MULTIVARIATE TESTS 
Effect Value F df Error 

df 
Sig. Partial Eta 

Squared 
Observed 

Power 

Intercept Pillai's Trace 1.000 130003.000b 3 96 .000 1.000 1.000 

 Wilk’s Lambda .000 130003.000b 3 96 .000 1.000 1.000 

 Hotelling's Trace 4062.594 130003.000b 3 96 .000 1.000 1.000 

 Roy's Largest Root 4062.594 130003.000b 3 96 .000 1.000 1.000 

Postponement 
Strategy 

Pillai's Trace .820 145.360b 3 96 .000 .820 1.000 

 Wilk’s Lambda .180 145.360b 3 96 .000 .820 1.000 

 Hotelling's Trace 4.543 145.360b 3 96 .000 .820 1.000 

 Roy's Largest Root 4.543 145.360b 3 96 .000 .820 1.000 

a. Design: Intercept + Postponement strategy 

b. Exact statistic 

c. Computed using alpha = .05 

Source: authors’ research 

 



 

 

 

 

 

 

MUKUCHA, P., JARAVAZA, D.C., SARUCHERA, F. 

STRATEGIC POSTPONEMENT IN FAST FOOD OPERATIONS: ENHANCING ORDER FULFILMENT IN A FRONTIER 

EMERGING MARKET 

  

 

 

B
u

s
in

e
s

s
 E

x
c
e

ll
e
n

c
e
 a

n
d

 M
a
n

a
g

e
m

e
n

t 

V
o

lu
m

e
 1

5
 I
s

s
u

e
 2

 /
 J

u
n

e
 2

0
2

5
 

T
h
e
or

e
ti
ca

l 
a
nd

 E
m
pi
ri
ca

l 
R
e
se

a
rc

h
e
s 

in
 U

rb
a
n 

M
a
na

ge
m
e
nt

 

 

13 

The results of MANOVA in Table 3 revealed that there was a statistically significant difference between the 

two production strategies, postponement and non-postponement, on the combined dependent variables, 

Pillai's T=.685, F (3,96) =145.360, p<.001, partial η2 =.820, observed power = 1.00. Based on these 

results, evidence was sufficient to reject the null hypothesis and conclude that order fulfilment metrics 

differed based on the form of the postponement strategy adopted. The effect size was large. The observed 

power was 1.00, indicating a 100% chance that the result could have been significant. Considering that the 

MANOVA results came out, significant separate univariate analyses were conducted and the results are 

shown in Table 4. The Bonferroni method was then used, and each ANOVA was tested at a .016(.05/3) 

alpha level.  

TABLE 4. IN-BETWEEN SUBJECTS TESTS 

Source Dependent 
Variable 

Df F Sig. Partial Eta 
Squared 

Noncent. 
Parameter 

Observed 
Power 

Postponement 
strategy 

OFR 1 121.014 .000 .553 121.014 1.000 

OCFT 1 101.660 .000 .509 101.660 1.000 

 OCFA 1 162.352 .000 .624 162.352 1.000 

Error OFR 98      

 OCFT 98      

 OCFA 98      

Source: authors’ research 

 

Results demonstrated that there was sufficient evidence to reject the order fulfilment rate, F (1, 98) = 

121.014, p<.001, partial η2 =.533, observed power = 1.000, the order cycle fulfilment accuracy rate, F (1, 

98) =101.660 p<.001, partial η2 =.509, observed power = 1.000, and the order fulfilment time adherence 

rate null hypotheses, F (1, 98) = 162.352 p<.001, partial η2 =.624, observed power = 1.000 (see Table 4). 

Therefore, all the research hypotheses were accepted. Thus, the OFR was higher under the post-

postponement strategy (M = 95.82, SD = 2.11) than under the non-postponement strategy (M = 90.49, SD 

= 2.68). The OCFT was also higher under the post-postponement strategy (M = 97.02, SD = 2.52) than the 

non-postponement strategy (M = 90.75, SD = 2.52). The OFR was higher under the post-postponement 

strategy (M = 97.71, SD = 2.16) than under the non-postponement strategy (M = 90.53, SD = 3.33) (see 

Table 2 for mean and standard deviations). The effect size was large for both ANOVAs. The observed 

power of 100 indicated a 100% chance that the results could have been significant for all the analyses.  

 

 

5. DISCUSSION 

The results demonstrated an improvement in the assessment of order fulfilment metrics of order fill rate, 

order cycle fulfilment time, and order fulfilment accuracy as a result of adopting the form postponement 

strategy. It is apparent that with form postponement, there is always enough inventory stocked due to the 



 

 

 

 

 

 

MUKUCHA, P., JARAVAZA, D.C., SARUCHERA, F. 

STRATEGIC POSTPONEMENT IN FAST FOOD OPERATIONS: ENHANCING ORDER FULFILMENT IN A FRONTIER 

EMERGING MARKET  

 

  

 
 

B
u

s
in

e
s

s
 E

x
c
e

ll
e
n

c
e
 a

n
d

 M
a
n

a
g

e
m

e
n

t 

V
o

lu
m

e
 1

5
 I
s

s
u

e
 2

 /
 J

u
n

e
 2

0
2

5
 

T
h
e
or

e
ti
ca

l 
a
nd

 E
m
pi
ri
ca

l 
R
e
se

a
rc

h
e
s 

in
 U

rb
a
n 

M
a
na

ge
m
e
nt

 

 

14 

demand forecasting strategies to meet the customers' orders. Forecasting ensures that possible future 

demand shifts are considered and relevant strategies are implemented to avoid supply disruptions (Lysons 

& Farrington, 2020). Usually, the first phase of form postponement leads to a build-up of adequate 

inventory, which in most cases leverages supply redundancy (Prataviera et al., 2020). The redundancy 

strategy advocates for the maintenance of spare stock to cater for demand shocks (Christopher, 2020). 

The postponement strategy has been successfully applied in several industries, such as the home 

appliances industry.  

The study has demonstrated that form postponement leads to an improved order fill rate. The attainment 

of a high order fill rate is attributed to the business's potential to produce according to customers' 

requirements (Larsen & Thorstenson, 2012). It is a common cause that patrons have varied needs 

concerning culinary services (Namkung & Jang, 2007). Demand forecasting may be a mammoth task in 

most restaurant businesses if the same patrons can vary their needs across different days. This makes 

lean production problematic when it comes to restaurant services. 

In most cases, a lean production system results in a narrow product line that may not cater for the varied 

needs of a diverse culinary customer base. As a result, most restaurants experience back or unfulfilled 

orders (Lysons & Farrington, 2020). In order to avoid unfulfilled orders, food preparation should be delayed 

until customers' orders are received. However, production can take place using the generic product 

version until product differentiation becomes necessary (Bech et al., 2018). That way, order fill rates may 

be achieved while at the same time achieving the acceptable order fulfilment duration.  

Usually, when patrons visit a restaurant, the objective is to deal with the immediate pangs of hunger. It 

therefore means that restaurateurs should strive to develop innovative ways of reducing the duration of 

order fulfilment. One such method is to practice lean management, where the production system is made-

to-stock (Jafari et al., 2021). This method relies mostly on strong forecasting techniques (Chopra et al., 

2018). However, with most restaurant services, this method needs to be modified to work well because the 

needs of the restaurant patrons vary widely. That is when the postponement strategy comes in. 

Postponement combines the best lean production system up to the decoupling point and then 

accomplishes the production process using the agile production system (Prataviera et al., 2020). Thus, the 

stock, which in the case of restaurant businesses is menus, is kept in a state of semi-finished goods. Then, 

the production process will be completed upon receipt of a definite customer order. 

Serving customers with inaccurate orders is a gravy practice in the restaurant industry. It does not only 

cost much money in terms of lost revenue through having to render the service again, but a wrongly 

delivered order may be thrown into a bin in full view of the other patrons. The other patrons who see a 

rejected order are likely not to be privy to the reasons for such an act but would not stop speculating. 



 

 

 

 

 

 

MUKUCHA, P., JARAVAZA, D.C., SARUCHERA, F. 

STRATEGIC POSTPONEMENT IN FAST FOOD OPERATIONS: ENHANCING ORDER FULFILMENT IN A FRONTIER 

EMERGING MARKET 

  

 

 

B
u

s
in

e
s

s
 E

x
c
e

ll
e
n

c
e
 a

n
d

 M
a
n

a
g

e
m

e
n

t 

V
o

lu
m

e
 1

5
 I
s

s
u

e
 2

 /
 J

u
n

e
 2

0
2

5
 

T
h
e
or

e
ti
ca

l 
a
nd

 E
m
pi
ri
ca

l 
R
e
se

a
rc

h
e
s 

in
 U

rb
a
n 

M
a
na

ge
m
e
nt

 

 

15 

Some of the speculations may be image tarnishing (Kotler & Keller, 2016), such as suggesting that the 

food was badly prepared, the restaurant used stale ingredients, failed to mix the ingredients properly, or 

used unhygienic food preparation methods. Moreover, supplying patrons with inaccurate orders may result 

in health consequences. There are certain foods that some patrons are not allowed to consume for health 

reasons. Consuming prohibited foods may end up causing serious health issues that may result in some 

patrons getting ill or suing the defaulting restaurant businesses (Fuster et al., 2021). The practice of form 

postponement reduces the incidences of serving inaccurate orders since food preparation is done in 

accordance with the confirmed orders from the individual patrons. 

Form postponement has proved to be a necessary strategy for attaining the key order fulfilment metrics of 

order fill rate, order fill time, and order fill accuracy. Logically, patrons are interested in attaining all these 

metrics within acceptable parameters. For instance, when the order fill rate is attained, it must be attained 

within the expected time frame and with high precision. It seems that postponement can achieve all three 

metrics. Thus, restaurateurs are advised to invest in appropriate equipment and systems that enable them 

to practice from postponement to the levels that match the needs of their customer bases. 

 

 

6. MANAGERIAL IMPLICATIONS 

The fact that form postponement is related to improved order fulfilment metrics makes it imperative for 

businesses to implement it with earnestness. The customers in the contemporary business environment 

are so diverse in terms of their needs and preferences that serving them with a standardised product or 

service churned from a lean production system is no longer feasible. The implications are that businesses 

must invest in versatile equipment to produce differentiated products. That way, the entire production 

system will be conditioned to be in a state of readiness to meet the varied needs of different customers 

without incurring extraordinary costs.  

Furthermore, the beneficial impact of postponement also necessitates a strategic reevaluation of supply 

chain operations and customer relationship management. Specifically, businesses should consider the 

integration of advanced technologies and data analytics to dynamically adjust their operations and supply 

chains in real-time, catering to fluctuating customer demands efficiently. This adaptation not only ensures 

higher satisfaction rates among a diverse customer base but also enhances competitive advantage in a 

rapidly evolving market landscape. Moreover, the emphasis on form postponement underscores the 

importance of fostering a culture of flexibility and responsiveness within organisations. Training programs 

aimed at developing skills in agile management and responsive decision-making should become a staple, 

ensuring that the workforce is well-equipped to implement these strategic shifts. Implementing these 



 

 

 

 

 

 

MUKUCHA, P., JARAVAZA, D.C., SARUCHERA, F. 

STRATEGIC POSTPONEMENT IN FAST FOOD OPERATIONS: ENHANCING ORDER FULFILMENT IN A FRONTIER 

EMERGING MARKET  

 

  

 
 

B
u

s
in

e
s

s
 E

x
c
e

ll
e
n

c
e
 a

n
d

 M
a
n

a
g

e
m

e
n

t 

V
o

lu
m

e
 1

5
 I
s

s
u

e
 2

 /
 J

u
n

e
 2

0
2

5
 

T
h
e
or

e
ti
ca

l 
a
nd

 E
m
pi
ri
ca

l 
R
e
se

a
rc

h
e
s 

in
 U

rb
a
n 

M
a
na

ge
m
e
nt

 

 

16 

strategies will allow businesses to navigate the complexities of modern consumer markets with greater 

agility and precision, thereby securing a robust position in the industry. 

 

 

7. LIMITATIONS AND FUTURE RESEARCH AGENDA 

The study was done using a convenience sample. A convenience sample produces results that may be 

difficult to generalise to a population but can still be generalised to a theory (Saunders et al., 2024). 

Therefore, the results of this study were useful in strengthening the idea that form postponement is a 

solution to meeting several order fulfilment metrics. However, at the moment, the results cannot be 

generalised to the population from which the sample was drawn. Thus, future researchers must strive to 

compile a complete sampling frame for the restaurant business in Harare or whatever intended population 

and then produce generalisable results. 

Order fulfilment metrics are also a function of variables such as vendor-managed inventory, internal 

marketing practices, and the business operating environment. Therefore, the fact that these variables were 

not assessed may mean that this study may lack higher levels of internal validity. Future researchers are 

therefore encouraged to assess all the potential variables that affect the attainment of excellent order 

fulfilment metrics. In future studies, the researchers may use factorial MANOVA or factorial MANCOVA, 

which are statistical tools designed to cater for multiple independent variables while eliminating the 

confounding effects of the other independent variables. 

 

 

REFERENCES 

Abdollahnejad, E., Karimzad, A., & Akbarbegloo, M. (2025). Determinants of Fast-Food Consumption 

Pattern and Causes of Tendency towards Ready-to-eat Food in Iranian Secondary School 

Students: A Cross-sectional Study. International Journal of School Health, 12(1), 3-13. 

Al-Adwan, A. S., Al-Debei, M. M., & Dwivedi, Y. K. (2022). E-commerce in high uncertainty avoidance 

cultures: The driving forces of repurchase and word-of-mouth intentions. Technology in Society, 71, 

102083. 

Alderson, W. (1950), Marketing efficiency and principle of postponement. Cost and Profit Outlook, 3(1), 15-18. 

Bech, S., Brunoe, T. D. & Larsen, J. K. (2018). Changeability of the manufacturing systems in the food 

industry- A case study. Procedia CIRP, 72(1), 641-646.  

Becker, T., Bruns, B., Lier, S., & Werners, B. (2021). Decentralized modular production to increase supply 

chain efficiency in chemical markets: an example of polymer production. Journal of Business 

Economics, 91, 867-895. 

Chopra, S., Meindl, P. & Kalra, D. (2018). Supply Chain Management. Strategy, Planning, and Operation. 

7th edition. New Delhi: Pearson Education. 



 

 

 

 

 

 

MUKUCHA, P., JARAVAZA, D.C., SARUCHERA, F. 

STRATEGIC POSTPONEMENT IN FAST FOOD OPERATIONS: ENHANCING ORDER FULFILMENT IN A FRONTIER 

EMERGING MARKET 

  

 

 

B
u

s
in

e
s

s
 E

x
c
e

ll
e
n

c
e
 a

n
d

 M
a
n

a
g

e
m

e
n

t 

V
o

lu
m

e
 1

5
 I
s

s
u

e
 2

 /
 J

u
n

e
 2

0
2

5
 

T
h
e
or

e
ti
ca

l 
a
nd

 E
m
pi
ri
ca

l 
R
e
se

a
rc

h
e
s 

in
 U

rb
a
n 

M
a
na

ge
m
e
nt

 

 

17 

Christopher, M. (2022). Logistics and Supply Chain Management. Creating Value-Adding Networks. 6th 

edition. London: Pearson education. 

Coyle, J. J., Langley Jr, C. J., Novack, R. A. & Gibson, B. J. (2021). Supply Chain Management: A 

Logistics Perspective (11th Ed.). South-Western Cengage Learning. 

Field, A. (2024). Discovering Statistics Using IBM SPSS Statistics. SAGE Publications Ltd: London. 

Field, A. (2024). Discovering statistics using IBM SPSS statistics. Sage publications limited. 

Fildes, R., Ma, S., & Kolassa, S. (2022). Retail forecasting: Research and practice. International Journal of 

Forecasting, 38(4), 1283-1318. 

Fuster, M., Handley, M. A., Alam, T., Fullington, L. A., Elbel, B., Ray, K. & Huang, T. T-K. (2021). 

Facilitating healthier eating at restaurants: a multidisciplinary scoping review comparing strategies, 

barriers, motivators, and outcomes by restaurant type and initiator. International Journal of 

Environmental Research and Public Health, 18:1-17.  

Hair, J. F., Black, W. C., Babin, J. B. & Anderson, R. E. (2014). Multivariate Data Analysis. 7th ed. Essex, 

England: Pearson. 

Hunt, I. (2022). In-sample tests of predictability are superior to pseudo-out-of-sample tests, even when 

data mining. International Journal of Forecasting, 38(3), 872-877.  

Ivanov, D., Tsipoulanidis, A. & Schonberger, J. (2019). Global supply chain and operations management. 

A decision-oriented introduction to the creation of value (2nd ed.). Switzerland: Springer Nature. 

Jafari, H., Eslami, M. H., & Paulraj, A. (2022). Postponement and logistics flexibility in retailing: The 

moderating role of logistics integration and demand uncertainty. International Journal of Production 

Economics, 243(1), 108319. 

Larsen, C. & Thorstenson, A. (2012). The order and volume fill rates in inventory control systems. 

International Journal of Production Economics,  

Lyons, A. C., Um, J., & Sharifi, H. (2020). Product variety, customisation and business process 

performance: A mixed-methods approach to understanding their relationships. International Journal 

of Production Economics, 221, 107469. 

Lysons, K. & Farrington, B. (2020). Procurement and Supply Chain Management. 9th edition. Pearson 

Education Ltd, London. 

Ma, S., & Fildes, R. (2020). Forecasting third-party mobile payments with implications for customer flow 

prediction. International Journal of Forecasting, 36(3), 739-760. 

Mukucha, P., & Chari, F. (2023). The moderating role of vendor managed inventory on the bullwhip effect 

in the COVID-19 pandemic. Cogent Business & Management, 10(1), 2158604. 

Mukucha, P., Tsekea, S., Jaravaza, D. C., & Jaravaza, N. (2024). Contract farming: a comparison of 

production and marketing contracts as sourcing strategies in the fast food restaurant industry. 

Journal of Foodservice Business Research, 1-18. 

Namkung, J. & Jang, S. (2007). Does food quality really matter in restaurants? Its impact on customer 

satisfaction and behavioural intentions. Journal of Hospitality and Tourism Research, 31(3):387-

409.  

Olhager, J., & Van Donk, D. P. (2024). Managing Customer Order Decoupling Points in Supply Chains. In 

The Palgrave Handbook of Supply Chain Management (pp. 1115-1137). Cham: Springer 

International Publishing. 

Pozzi, R., Strozzi, F., Rossi, T., & Noè, C. (2018). Quantifying the benefits of the lean thinking adoption by 

the beer game supply chain. International Journal of Operational Research, 32(3), 350-363. 



 

 

 

 

 

 

MUKUCHA, P., JARAVAZA, D.C., SARUCHERA, F. 

STRATEGIC POSTPONEMENT IN FAST FOOD OPERATIONS: ENHANCING ORDER FULFILMENT IN A FRONTIER 

EMERGING MARKET  

 

  

 
 

B
u

s
in

e
s

s
 E

x
c
e

ll
e
n

c
e
 a

n
d

 M
a
n

a
g

e
m

e
n

t 

V
o

lu
m

e
 1

5
 I
s

s
u

e
 2

 /
 J

u
n

e
 2

0
2

5
 

T
h
e
or

e
ti
ca

l 
a
nd

 E
m
pi
ri
ca

l 
R
e
se

a
rc

h
e
s 

in
 U

rb
a
n 

M
a
na

ge
m
e
nt

 

 

18 

Prataviera, L. B., Jazairy, A., & Abushaikha, I. (2024). Navigating the intersection between postponement 

strategies and additive manufacturing: insights and research agenda. International Journal of 

Production Research, 1-23. 

Prataviera, L. B., Perotti, S., Melacini, M. & Moretti, E. (2020). Postponement strategies for global 

downstream supply chain: a conceptual framework. Journal of Business Logistics, 41(1), 94-110. 

Rabinovich, E. & Evers, P. T. (2003). Postponement effects on inventory performance and impact of 

information systems. International Journal of Logistics Management, 14(1), 33-48. 

Rahman, M. H., Rahman, M. A. & Talapatra, S. (2020). The bullwhip effect: causes, intensity, and 

mitigation. Production & Manufacturing Research, 8(1), 406-426. 

Rau, H., Daniel Budman, S., & Monteiro, C. N, (2021. Improving the sustainability of a reverse supply 

chain system under demand uncertainty by using postponement strategies. Waste Management, 

13(1), 72-81. 

Sanders, N. R. (2025). Supply chain management: A global perspective. John Wiley & Sons. 

Saruchera, F., & Asante‐Darko, D. (2021). Reverse logistics, organisational culture and firm operational 

performance: Some empirical evidence. Business strategy & development, 4(3), 326-342. 

Saunders, M., Lewis, P. & Thornhill, A. (2024). Research Methods for Business Students. 9th edition. 

Pearson Education Limited, Essex: England. 

Seo, H. S. (2020). Sensory nudges: The influences of environmental contexts on consumers’ sensory 

perception, emotional responses, and behaviors toward foods and beverages. Foods, 9(4), 509. 

Siiskonen, M., Govender, R., Malmqvist, J., & Folestad, S. (2023). Modelling the cost-benefit impact of 

integrated product modularisation and postponement in the supply chain for pharmaceutical mass 

customisation. Journal of Engineering Design, 34(10), 865-896. 

Struwig, F. W. & Stead, G. B. (2013). Research: Planning, designing and reporting. Pearson, Cape Town. 

Tabachnick, B. G. & Fidell, L. S. (2013). Using Multivariate Statistics. 6th edition. Boston, MA: Allyn and 

Bacon. 

Warne, R. T. (2014). A primer on multivariate analysis of variance (MANOVA) for behavioural scientists. 

Practical Assessment & Evaluation, 19(17):1-10. 

Wirtz, J. & Lovelock, C. (2021). Services Marketing. People, Technology, Strategy. 9th edition.  

Yoon, B., Chung, Y. & Jun, K. (2020). Restaurant industry practices to promote healthy sustainable eating: 

A content analysis of restaurant websites using the value chain approach. Sustainability, 12(1), 

7127; doi:10.3390/su12177127. 

Zinn, W. & Bowersox, D. J. (1988). Planning physical distribution with the principle of postponement. 

Journal of Business Logistics, 9(2), 117-136.