Conference PaperPDF Available

Consumer's Preference on Delivery Options: A study from Online Shoppers


Abstract and Figures

Last-mile delivery is an important aspect to ensure online shoppers in Malaysia experience excellent online shopping. Therefore, e-retailers are required to explore the difficulties faced during the delivery of the product, and the preferred delivery option chosen by the online shopper. From this study, it shows how the traditional delivery, time-slot delivery and the unattended delivery may influence the customer delivery options of online shopping. Questionnaires were distributed in order to collect the data needed for this study. Pearson's correlation, multiple regression analysis and chi-square analysis were used to analyse the result of the questionnaires. It is found that time slot delivery is the most preferred delivery option follow by unattended delivery and traditional delivery. This study is essential for online retailers to provide the preferred delivery option to their customers and improve their last-mile delivery services. This paper also includes the study of unattended delivery which is rarely applied in Malaysia context.
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(ICOSSH 2019)
8 9 October 2019
Parkcity Everly Hotel, Bintulu, Sarawak, Malaysia
Published 2019
Faculty of Agriculture and Food Sciences,
Universiti Putra Malaysia Bintulu Sarawak Campus
Perpustakaan Negara Malaysia Cataloguing-in-Publication-Date
eISBN 978-967-12140-6-0
The view and concepts presented are those of the authors. No responsibility is assumed by
the organizer for any injury and/or damage to persons or property as a matter of product’s
liability, due to negligence or otherwise, or from any use or operation of any methods,
products, instructions, or ideas contained in the material herein.
Copyright © Universiti Putra Malaysia Kampus Bintulu, 2019
Salini Devi Rajendran & Siti Norida Wahab
Department of Logistics Management, Faculty of Business and Information Science,
Kuala Lumpur, Wilayah Persekutuan Kuala Lumpur
Last-mile delivery is an important aspect to ensure online shoppers in Malaysia
experience excellent online shopping. Therefore, e-retailers are required to explore
the difficulties faced during the delivery of the product, and the preferred delivery
option chosen by the online shopper. From this study, it shows how the traditional
delivery, time-slot delivery and the unattended delivery may influence the customer
delivery options of online shopping. Questionnaires were distributed in order to collect
the data needed for this study. Pearson's correlation, multiple regression analysis and
chi-square analysis were used to analyse the result of the questionnaires. It is found
that time slot delivery is the most preferred delivery option follow by unattended
delivery and traditional delivery. This study is essential for online retailers to provide
the preferred delivery option to their customers and improve their last-mile delivery
services. This paper also includes the study of unattended delivery which is rarely
applied in Malaysia context.
Key terms: delivery options, last-mile delivery, online shopping, e-retailers
E-commerce's functioning on the B2C market depends upon product deliveries
because of its generic specificity. There are three main types of delivery methods or
models, namely traditional delivery, time-slot delivery, and unattended delivery. Same-
day, next-day and multi-day delivery are the traditional delivery choices that are right
now utilized by some of the e-retailers (Xu et al., 2008). Time slot delivery refers to a
time allocated and communicated to the recipient of a parcel from a courier or delivery
service to receive delivery of their parcel. Secure unattended delivery alternatives
including mobile reception box, home security access systems, fitted external box,
fitted integrated box, utilization of existing outlets, mechanised storage (collection
points), workplace collection, and retrieval devices. Recent studies by Morganosky
and Cude (2015) have demonstrated that the convenience and time-saving
advantages of online shopping cannot be achieved. Due to delays in delivery or the
issues of a failed delivery, some online shoppers even feel online shopping takes longer
than traditional shopping. 38% of home customers need to collect missed delivered
things from a post office or other warehouse in 2016 (Castle, 2016). 63% say delivery
speed is an important consideration when shopping online (Charlton 2018).
According to a 2017 statistics by Statista, customers demand delivery flexibility the
most from their last-mile delivery services, which occupies 65% followed by speed
of delivery (61%), real-time visibility (51%), delivery options (45%), and specific
delivery slot selection (41%). The objective of this paper is to identify the problems
faced by customers in last-mile delivery of online shopping, to identify the preferences
of customers in choosing delivery options for online shopping, and to investigate the
willingness of customers to pay higher for fast delivery. With 67% of Malaysians online,
Malaysia has the most astounding penetration of online shoppers, followed by 57%
contributed by Thailand and 52% by Singapore. It is also stated that by looking at the
development rate of our region in general, Malaysia is one of the speediest developing
markets, keeping pace with China at 25% development rate.
The remainder of the chapter is organized as follows. In section 2, we present
the literature review of our independent variables and dependent variable. In section
3, we discuss the methodology used to collect and analyse data. In section 4, we
discuss the resulting outcome of this paper. Finally, in section 5, we discuss the
conclusion of the paper and important areas of further research.
Theoretical background and research framework
With the growth of online shopping, the importance of last-mile deliveries to
customers has increased. However, issues are occurring in this service, and these
issues significantly result in customer dissatisfaction and low efficiency. The last mile
issues occur during the arrangement of distribution service from a transportation hub
to the final delivery destination of the consumer's house or workplace (Han et al.,
2017). Therefore, it is crucial to identify the issues existing in last-mile deliveries
because it influences how consumers perceive the organization's brand image. 45%
of users responded that they would never shop again with an e-retailer that provide a
negative delivery experience (Allen et al., 2018.). A recent study by Holdorf and Haasis
(2014) concluded different issues with last-mile deliveries. The main issues that are
faced by consumers are delayed delivery; not-at-home or forced to stay at home to
receive the products which leading in failure of first-time delivery (Visser et al., 2014).
Most product delivery services distributed products during office hours or the time not
at home, resulting in failed product deliveries (Huang, 2015). In such cases, courier
services will ask recipients to rearrange another time to redeliver the products or
require them to go to a nearest post oƥce branch to collect their items. Thus, the
shipping courier company or the customer might need to bear for the additional
charges for a failed delivery, and this consequently dissatisfied the customers.
Therefore, it is obvious to identify the delivery options preferred by most of the online
shoppers. The most common delivery options used by online retailers nowadays are
traditional delivery, time slot delivery and unattended delivery (Xu et al., 2008).
Customer preferences
As the consumers' expectations have expanded simultaneously due to the
growth of e-commerce, this leads to a challenge for the e-retailers to meet consumers'
requirements while sustaining the profits when developing their business (MetaPack,
2015). Several studies suggest that it is necessary to understand consumer
preferences for online delivery to obtain their satisfaction and loyalty as well as to
increase deliveries efficiency. The insufficient understanding of online shoppers'
preferences and needs for the logistics services leads to high costs and low efficiency
of logistics. According to European Commission (2012), each customer has different
preferences on the products or services. The previous survey indicated that online
shoppers would like to have more control over delivery, deep understanding of the
delivery process, convenient return processes, and delivery status acknowledgement
via new technologies. Furthermore, online shoppers prefer to have a say over when,
where, and how they want their consignments to be delivered.
Willingness of consumers to pay for fast delivery service
Other than the delivery options preferred by consumers, it is also crucial to
understand the willingness of a consumer to pay for the fast delivery services.
Although many consumers desire faster last-mile delivery, yet price-sensitive remain
most highly concern when choosing an e-retailer. Pallant (2016) has emphasized 56%
of e-shoppers mentioned that free shipping was a crucial factor when choosing an e-
retailer and 55% of consumers refuse to completed an order because the delivery
charges were too high. Several researchers argued that some consumers are willing
to pay for the express delivery because it is convenient to have their order delivered
to their house. However, they do not consider to pay too much for that convenience.
Online shoppers always expect the delivery charges to be relatively low as they think
they would instead purchase from a retail shop if they had to spend more on shipping
prices (Agatz et al. 2011). In addition, Peiling and Tingting (2018) claimed that
consumers would measure whether the shipping price is worth purchase those
products online. Likewise, E-Consultancy conducted a survey stated out 58% of 5,849
respondents will purchase more to take advantages of free shipping. Based on the
researcher’s findings,
means that regular delivery or called multi-day delivery,
which is essentially the low-cost delivery, will continue to play a significant role in last-
mile delivery.
Figure 1: Research framework
Traditional delivery
Traditional delivery emphasizes on same-day delivery, next-day delivery and
multi-day delivery (Xu et al., 2008). This delivery reception of the goods ordered at a
location chosen by the customer either in-home or workplace using delivery time
windows defined by the service provider. So, it needs the recipient to be available to
receive the goods and signature also required during the recipient of items. Based on
the studies investigate by Peiling and Tingting (2018), the three levels of different
values of the delivery speed factor had been compared. It can find that same-day
delivery has the highest value, which is 0.231, and it means the consumers are
acceptable to this method on the same day when they shop the products online.
Furthermore, a survey study by Brewster and An (2018) conclude that consumers are
willing to pay more for same-day or express delivery due to the exception of the price,
about 25% survey respondents mentioned fast delivery as the elements that customer
purchase from a particular retailer. Next, the values of the next-day delivery are lower
than the value on the same-day delivery, but the customer is still receivable for that.
From the results, it can judge that the consumers are perfectly acceptable for delivery
speed of fewer than two days. The survey also finds out the multi-day delivery or
weekly delivery speed has the lowest value compared to both of the delivery because
the value is -0.423. The changes in the utility value are massive from a positive value
to a negative value. This means that consumers unable to accept the multi-day of
groceries online.
Based on the study done by Ahn et al. (2014), the consumer may switch to
other competitor or physical shops if delivery speed is too late. In other words, timely
and reliable delivery will satisfy users so that they can continue to use the Internet to
purchase, and companies can also increase sales and market share through customer
loyalty. According to the survey done by Joerss et al. (2016), traditional delivery has
been ranked as the top delivery options that the consumer had chosen. Despite
increasing customer demand for same-day and express delivery, more than 50% of
consumers choose delivery options simply based on price, while another 20% prefer
the cheapest available option of home delivery. That means that regular parcel delivery
(delivery several days after the order), which is essentially the low-cost alternative to
same-day or express delivery, will continue to play a significant role. Furthermore,
Eurosender (n.d.) also noted that traditional delivery remains the most popular choice
among customer because there have some benefits for traditional delivery. For
example, it is saving time and effort as there is no need to go anywhere and carry the
shipment around since it will be taken from the stated address. However, Dimaria
(2014) argued that same-day delivery is not realistic for most online ordering since
the organization should have enough storage located in nearly every location within
the country, leading to an expensive operation. Thus, Dimaria (2014) prefer next day
or multi-day delivery in her/ his studies. Therefore, the following hypothesis has been
H1: There is a significant relationship between traditional delivery and customer
preferences on delivery options for online shopping in Malaysia.
Time slot delivery
Time slot delivery is providing an hourly delivery window when or after online
ordering was made, which has been widely used by many e-grocery retailers nowadays
(Xu et al., 2008). The goal is for all couriers and delivery services to provide their
customers with a delivery slot to ensure the efficient use of a driver's and customer's
time. According to de Vos (2016), 80% customers want a time slot of when to expect
their delivery to arrive. It is widely used in attended delivery services for the
organizations to offer the consumer a choice of narrow delivery time slots to ensure a
satisfactory service provided and to prevent delivery failures as much as possible.
Some authors have recognized the specific time slot offering impact the perceived
customer service and also the expected delivery efficiency (Agatz et al., 2011). Time
slot delivery (mean = 3.80) is the most likely delivery options to be favoured by online
retailers over the next three years since adopting the time slots delivery can be
resulting in significant savings by driving down total delivery costs (TDC) (Xu et al.
2008). Retailers can then use this experience to adjust their business operations
further to increase delivery and logistics efficiency. Wayne (2018) found that
businesses that offer 3-hour delivery services are now preferred by one in five (19%)
Aussie shoppers. It is appealing that almost a third (32%) of Aussie consumers are
willing to pay extra for the convenience.
Generally, time slots for attended delivery are pre-scheduled by online shoppers
during the time of ordering. Also, some time slots can be shorter and more popular,
which are mostly during late afternoons and weekends. Thus, the following time slots
will be offered at a higher delivery charge to balance the demand peaks season
(Ferguson 2015). There is an excellent advantage to the clients by providing a time
slot as they can better manage their time by picking an appropriate slot. Nonetheless,
this represents a challenge to the service and delivery organizations, a capacitated
Vehicle Routing Problem (cVRP), their original issue, turns into a capacitated Vehicle
Routing Problem with Time Windows (VRPTW) (Hungerländer et al., 2017). They also
mentioned the VRPTW is an extension of the well-known vehicle routing issue. We get
the VRPTW on the off chance that we add a time window to every client. A vehicle
presently needs to visit a client within a specific period in addition to the capacity
limitation. The client cannot be serviced until the point that the time windows open
although the vehicle may arrive before the time window opens yet. After the time
window has shut, it is not permitted to arrive. Therefore, the following hypothesis is
H2: There is a significant relationship between time-slot delivery and customer
preferences on delivery options for online shopping in Malaysia.
Unattended delivery
Unattended delivery refers to simply leaving an item on someone's doorstep, or
in their garden shed, but this brings many security concerns and implications for those
items (Xu et al., 2008). According to the studies of Temando (2016), unattended
reception depends on the courier reception boxes, shared reception boxes, or the
collection and delivery points (CDP). These options considered as an alternative to
home delivery to meet the busy lifestyle of consumers while still being profitable for
the company. Furthermore, unattended reception is the ideal service concept from the
viewpoint of cost-efficiency in-home delivery transportation. It allows for increased
operating efficiency without giving up the level of service; however, it needs
investment in reception solutions at the shopper end. According to Morganti et al.,
(2014), collection and delivery points (CDP) have become a crucial factor in effective
last-mile deliveries in Europe countries. Delivery to-door, although the recipient is not
present also applicable when the items are delivered or pass to the neighbours. Based
on Xu et al. (2008), unattended delivery (mean = 3.87) are the most preferred delivery
options to be preferred by online retailers over the next three years, whereas
consumers do not show a keen interest in this method. There are only two respondents
agree with unattended delivery due to the concerns of cost, safety, space, and
planning permission concerning the installation of receptive devices at consumers'
homes. By tradition, UK consumers are used to and prefer to have, items delivered to
neighbouring houses, rather than attempting to use safe boxes for unattended delivery.
Moreover, according to Huang (2015), this option would be successful in reducing the
problems of failure of attended delivery. The prior research has shown that 40% of
potential or active European e-grocery shoppers would be interested in unattended
deliveries (Metapack, 2015).
In contrast, (Morganosky et al., 2015) found out a slightly different statement
compared to by the above researcher. In his findings, attended home delivery method
is the first choice chosen by the consumers. Pickup from collection point came second,
followed by pickup from a delivery point, while unattended home delivery and pickup
from store mode were the least preferred choices, mainly due to the cost and security
concerns. Therefore, different countries or area resulting in different preferences of
delivery options. Hence, the following hypothesis is proposed:
H3: There is a significant relationship between unattended delivery and customer
preferences on delivery options for online shopping in Malaysia.
In this research, to evaluate the relationship between the independent variable
and the dependent variable, the quantitative methodology was conducted. The data
collection method used in this research is questionnaires. Purposive sampling is used
in this research as it saves time, money and effort. It also helps in reaching the
targeted sample quickly. In this research, the targeted sample is people who shop
online and uses the delivery options provided by online retailers. The targeted
population is 150 online shoppers in Malaysia with different age range and from
different categories. In factor analysis, a sample size of 100 or higher is advised (Hair
et al., 2010). A sample of 100 is sufficiently large enough to produce reliable factors.
If less than 100 subjects are used, then replication studies are required using other
samples for purposes of validity. The targeted area for the survey questionnaire is in
Malaysia, and the targeted samples for this research are the respondents that are in
the age range of 18 until 60 years old. The targeted age range is between 18 to 60
years old as the majority of Malaysians that uses the internet for online shopping are
range from age 18 to 60 years old (Digital Influence Lab, 2017).
Data analysis and discussion
Collected data would be analysed by descriptive analysis, normality test and
reliability test. Finally, developed hypothesis in this research will be tested by Pearson
product-moment correlation, multiple regression test and Chi-Square analysis.
Normality test is used to test whether the collected data is typically distributed
while the reliability test is used to test the reliability of the collected data. Descriptive
analysis is used to find out our first objective of the paper, which is the problem faced
by customers in last-mile delivery. Frequency distribution analysis will summarize the
information on the problems faced by customers in last-mile delivery. To meet the
second objective, correlation analysis and multiple regression analysis are used to find
out the most preferred delivery options among Malaysian.
Demographic profile of respondents
From Table 1, there are 63 male (42%) and 87 female (58%) who responded
to the questionnaire. Sixty-two of the respondents (41.3%) are in the age range of 18
to 29 years old; 43 respondents (28.7%) are in the age between 30 to 44 years old.
Lastly, 45 respondents (30.0%) are 45 to 60 years old. Most of the respondents are
single where there is 99 of them accumulating 66.0% of the total respondents. As this
research targets respondents in Malaysia, all 150 respondents (100%) are Malaysian.
There are 7 Malay respondents (4.7%), 131 Chinese respondents (87.3%), and 12
Indian respondents (8.0%) in this research. Most respondents are Bachelor degree
graduates which is 108 of them and complies of 72.0% of the total respondents. 85
respondents (56.7%) are employed; 46 respondents (30.7%) are unemployed; 19
respondents (12.7%) with other employment status are mostly part-timers. There are
65 respondents (43.3%) with a monthly income range from RM 0 RM 2,000. 41
respondents (27.3%) have a monthly income range from RM 2,001 RM 5,000.
Besides, 39 respondents (26.0%) received a monthly income range from RM 5,001
RM 8,000. Three respondents (2%) come from the monthly income range of RM 8,001
RM 10,000. The remaining questionnaires are completed by two respondents (1.3%)
whose incomes are more than RM 10,000.
Percentage (%)
18 to 29
30 to 44
45 to 60
Marital Status
Education Level
Bachelor Degree
Employment Status
Monthly Income
RM 0 RM 2,000
RM 2,001 RM 5,000
RM 5,001 RM 8,000
RM 8,001 RM 10,000
More than RM 10,000
Table 1: Demographic profile of respondents
Problem faced in last-mile delivery
According to Table 2, the delivery problems usually encountered by the
respondents is the parcel delivered too late, which accounted for 56.7% of the total
respondents. The second problem usually encountered by the 150 respondents is that
respondents had to wait around for the delivery. This problem is selected by 55
respondents which represent 36.7% of the total respondents. Our results are broadly
similar to every survey established that late deliveries and have to wait around for the
delivery are common problems that experience by consumers. Refers to Consumer
Dispute Resolution Ltd. (2016), nearly half of customers (46%) experienced late parcel
delivery. Another survey done by Metapack (2015) revealed that almost 40% of
customers stayed at home to receive a parcel, but it did not arrive on that day.
However, more reports of late parcels may help online retailers identify patterns of
overall parcel delays and method to figure out these problems or help a retailer
promise a more realistic delivery time. Besides, according to the study investigated by
marketing consultant Acquity group in the year 2015, it showed that more than half
of surveyed consumers (52 %) blamed the online retailer when a parcel arrived late,
whereas 49 % who said they would blame the delivery company. This means that
consumers will hold the online retailer’s responsibility and not the delivery company
when something goes wrong. This impact can be destructive to the online retailer
because the test also revealed that 63 % of consumers who had experienced a late
delivery would negatively influence their relationship with the online retailer and they
might not return to the online retailer. Besides that, problems such as the parcel did
not get delivered at all, respondents had to queue to collect the parcel, and it was not
possible to track the parcel with 9.3%, 8.7%, and 8.0% are also problems faced by
the respondents.
Delivery Problems Usually Encountered
Frequency (n)
Percentage (%)
The parcel got delivered too late
The parcel did not get delivered at all
I had to queue to collect the parcel
I had to wait around for the delivery
It was not possible to track the parcel
Table 2: Problem faced in last-mile delivery
Pearson’s correlation analysis
Pearson correlation is used to identify the degree of a linear relationship between two
or more variables. According to Table 3, it can be concluded that only time slot delivery
(0.362) has a moderate relationship with customer preferences. However, there are
two independent variables, which are traditional delivery (0.232) and unattended
delivery (0.270) have a weak relationship with customer preferences.
Table 3 Pearson Correlation
Pearson Correlation
Traditional Delivery
Time Slot Delivery
Unattended Delivery
From Table 3, we can conclude that time slot delivery is more preferable by the
customer in online shopping. The reason that online shoppers nowadays most
preferred time slot delivery because of their busy lifestyle needs. Besides, the common
problems of last-mile delivery, such as ‘not at home' issues can be avoided by online
shoppers by selecting the available time slot during their online purchases.
Furthermore, our result could be supported by Temando (2016), which reports
explored that almost 80 per cent of online shoppers prefer time slot deliver when shop
online. Therefore, online retailers have to take into consideration and try to improve
their delivery services by providing options for time slot delivery.
Multiple regression analysis
Multiple Regression Analysis is a test to identify the relationship between the
independent variables (traditional delivery, time slot delivery and unattended delivery)
and the dependent variable (customer preferences on delivery options). Besides that,
this test also identifies the significance of the relationship between the variables by
hypothesis testing. Table 4 shows the results of multiple regression analysis; R-value
is explained about the correlation coefficient relationship between the dependent
variable and the independent variables. The R-value of this analysis is 0.409 which is
showing a moderate degree of correlation between the independent variables
(traditional delivery, time slot delivery and unattended delivery) and a dependent
variable (customer preferences on delivery options). Furthermore, customer
preferences on delivery options were treated as a dependent variable, 16.7% of the
variation customer preferences on delivery options can be explained from the three
independents variables which adopted from the (Xu et al., 2008) model.
From Table 4 it shows that only time slot delivery has a significant relationship with
customer preferences on delivery options. The significant level of time slot delivery
(p=0.004) is significance at 5% of significance. This finding can be proven with the
survey: Metapack (2015) stated that 80% of respondent request a time slot of when
to expect their delivery to arrive. However, traditional delivery (p = 0.065) and
unattended delivery (p = 0.091) have no significant relationship with customer
preferences on delivery options. This finding is similar to Mckinnon and Tallam (2003)
research's result, which showed that only 6.8 % of respondent preferred traditional
delivery because of the ‘not at home' issues. Moreover, they also stated that only two
respondents out of 117 respondents agree with the unattended delivery method in
their study most online shoppers against to use unattended delivery method mainly
due to the cost and security concerns. Furthermore, one of the concerns is the time
available for collecting the parcel is limited, and it would increase the travel cost to the
collection point. Beta coefficient explained the relative importance of the factors in
terms of their contribution to the variance. In our test, time slot delivery (β = 0.256)
carried the heaviest weight in explaining customer preferences on delivery options.
Unstandardized Coefficients
Std. Error
1 (Constant)
Traditional Delivery
Time Slot Delivery
Unattended Delivery
R Square
Adjusted R Square
Std. Error of the
Table 4: Regression Analysis Results
Chi-Square Test
Willingness to pay for fast delivery is being tested using Chi-Square Test. The chi-
square independence test is a procedure for testing if two categorical variables are
related in some population Pallant (2016).
Asymp. Sig. (2-sided)
Pearson Chi-Square
Likelihood Ratio
Linear-by-Linear Association
N of Valid Cases
0 cells (0.0%) have expected count less than 5. The minimum expected count is 17.20.
Table 5. Chi-Square Test for Willingness to Pay for Fast Delivery (Age)
The Pearson Chi-Square value is 0.553, with an associated significance level of 0.758.
To be significant, the Sig. value needs to be 0.05 or smaller. The value of 0.758 is
larger than the alpha value of 0.05, so it is concluded that the result is not significant.
This means that there is no association between willingness to pay and age.
Asymp. Sig. (2-sided)
Pearson Chi-Square
Continuity Correction
Likelihood Ratio
Fisher's Exact Test
N of Valid Cases
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 25.20.
b. Computed only for a 2x2 table
Table 6: Chi-Square Test for Willingness to Pay for Fast Delivery (Gender)
The Pearson Chi-Square value is 19.869, with an associated significance level of 0.000.
To be significant, the Sig. value needs to be 0.05 or smaller. The value of 0.000 is
smaller than the alpha value of 0.05, so it is concluded that the result is significant.
This means that the proportion of males who are willing to pay for fast delivery is
significantly different from the proportion of females who are willing to pay for fast
Asymp. Sig. (2-sided)
Pearson Chi-Square
Likelihood Ratio
Linear-by-Linear Association
N of Valid Cases
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 7.60.
Table 7: Chi-Square Test for Willingness to Pay for Fast Delivery (Employment Status)
The Pearson Chi-Square value is 0.793, with an associated significance level of 0.673.
To be significant, the Sig. value needs to be 0.05 or smaller. The value of 0.673 is
higher than the alpha value of 0.05, so it is concluded that the result is not significant.
This means that there is no association between willingness to pay and employment
Research Implication
This research adds to the current literature by determining the importance of
last-mile delivery to customers' satisfaction. First, it attempts to confirm and extend
the delivery options, which is currently available in the existing literature. Second, it
will consider the implications of each role, including last-mile delivery providers and
online retailers to focus on the last mile performance and control over the last-mile
delivery. Our findings will help future literature to focus more on the time slot delivery,
which is highly preferable by most of the consumers. Besides, the study also
highlighted the issue of vehicle routing that becomes one of the challenges for service
and delivery organization.
This paper also includes implications for online retailers operating on the e-
commerce platform. Many companies are still struggling with the efficiency of the last-
mile process. Efficiency is a vital performance measure, yet customer satisfaction
becoming equally important in the e-commerce sector. This study provides information
to online retailers on the importance of time slot delivery where most online shoppers
are willing to pay more for the services. Secondly, offering delivery choices to
customers can make the last mile delivery process more efficient in the way of
providing customized delivery services to meet individual customers need. By
increasing efficiency of the delivery process, online retailers enable to create higher
satisfaction among their online shoppers.
Limitations and future studies
There are a few limitations in this study that should be noted and solved. The
conceptual framework adapted from Xu et al. (2008) only considered three delivery
options. However, there are a few other delivery options that may contribute but not
being discussed in the research. Therefore, future researchers can enhance their
research by including other delivery options such as crowdsourcing, in-store pickup,
change of delivery time on request and self-pickup possibility. Second, this research is
adopted from Xu et al., (2008) which is done previously in the United Kingdom, and
our research is done in Malaysia. Thus, it is recommended that future researchers can
use the same model and enhance it by including other secondary services of the
current last-mile delivery services. Third, in our research, we had explored the
willingness of the customer to pay more for fast delivery and the percentage to pay
extra for fast delivery. However, a customer's priority between cost and speed should
have been explored so that online retailers can keep on improving the delivery service
that they provide and also implement new delivery methods to improve customer
satisfaction. To further establish this, further research should find out whether cost or
speed more valuable to customers. Hence, customers' response to these two options
could be investigated to decide a practical way to improve customer value and
satisfaction in last-mile logistics. Fourth, this research only focusses on the online
shoppers' perspectives while the online retailers' views and concerns of the delivery
as mentioned earlier options are not gathered. Therefore, it is suggested that future
research includes online retailers as their targeted population to know how online
retailers positioned themselves in providing their customer's last-mile delivery.
This paper explores the most preferred delivery options in online shopping
among Malaysian. The results indicate that time slot delivery is the most preferred
delivery option, whereas Malaysian less prefers unattended delivery and traditional
delivery. Furthermore, most online shoppers ranked that the main problem they
usually faced is the parcel delivered too late. Some consumers make clear that the
last mile delivery problem would affect their purchase in the future. Thus, online
retailers need to solve the problems that happened in last miles delivery in order to
provide their customers with better service and hence improve customer satisfaction.
Lastly, in our findings, an additional cost of 10 20% higher than the standard delivery
cost is accepted by the population, and most of them are willing to pay for fast delivery.
This result is crucial to online retailers as well as last-mile delivery service provider to
improve the service and control the additional cost needed as well.
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... According to the previous study, challenges such as extended lead time and failure of door-to-door delivery are not the only issues with last-mile delivery in Malaysia (Ballare & Lin, 2020). Another challenge includes missing deliveries, delivery flexibility, real-time visibility, delivery options, specific delivery slot selection, and a few others (Rajendran & Wahab, 2019). These challenges trigger hindrances in the express industry's development, growth, and expansion. ...
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As technology develops and advances, last-mile delivery is deemed to be a crucial component of online trading. The use of automated parcel stations (APS) sustenance sustainable last-mile delivery among SMEs and e-commerce users. Thus, it is essential to ensure APS is able to increase efficiency, reduce shipping and labour costs as well as offer free, convenient delivery and return processes. This study aims to understand the challenges of APS usage and propose a mitigation strategy for better use of APS in Malaysia towards enhancing last-mile delivery services among SMEs and e-commerce users. Keywords: Automated parcel station, last-mile delivery, e-commerce, sustainable supply chain management eISSN: 2398-4287 © 2022. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BYNC-ND license ( Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians/Africans/Arabians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. DOI:
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The capacitated vehicle routing problem with time windows (cVRPTW) is concerned with finding optimal tours for vehicles that deliver goods to customers within a specific time slot (or time window), respecting the maximal capacity of each vehicle. The on-line variant of the cVRPTW arises for instance in online shopping services of supermarket chains: customers choose a delivery time slot for their order online, and the fleet’s tours are updated accordingly in real time, where the vehicles’ tours are incrementally filled with orders. In this paper, we consider a challenge arising in the on-line cVRPTW that has not been considered in detail in the literature so far. When placing a new order, the customer receives a selection of available time slots that depends on the customer’s address and the current (optimized) schedule. The customer chooses a preferred time slot, and the order is scheduled. The larger the selection, the more likely the customer finds a suitable time slot, leading to higher customer satisfaction and a higher overall number of orders placed. We denote the problem of determining the maximal number of feasible time slots for a new customer order as the Slot Optimization Problem (SOP). We formally define the SOP and propose an adaptive neighbourhood search heuristic for determining feasible slots for inserting a new customer orders based on a given delivery schedule in real time. Our approach is tailored to the SOP and combines local search techniques with strategies to overcome local minima. In an experimental evaluation, we demonstrate the efficiency of our approach on a variety of benchmark sets.
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Growth in e-commerce has led to increasing use of light goods vehicles for parcel deliveries in urban areas. This paper provides an insight into the reasons behind this growth and the resulting effort required to meet the exacting delivery services offered by e-retailers which often lead to poor vehicle utilisation in the last-mile operation, as well as the duplication of delivery services in urban centres as competitors vie for business. A case study investigating current parcel delivery operations in central London identified the scale of the challenge facing the last-mile parcel delivery driver, highlighting the importance of walking which can account for 62% of the total vehicle round time and 40% of the total round distance in the operations studied. The characteristics of these operations are in direct conflict with the urban infrastructure which is being increasingly redesigned in favour of walking, cycling and public transport, reducing the kerbside accessibility for last-mile operations. The paper highlights other pressures on last-mile operators associated with managing seasonal peaks in demand; reduced lead times between customers placing orders and deliveries being made; meeting delivery time windows; first-time delivery failure rates and the need to manage high levels of product returns. It concludes by describing a range of initiatives that retailers and parcel carriers, sometimes in conjunction with city authorities, can implement to reduce the costs associated with last-mile delivery, without negatively impacting on customer service levels.
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In Europe, shopping habits have changed fast during the last decade and a high percentage of consumers now shop online. E-commerce for physical goods generates a significant demand for dedicated delivery services, and results in increasingly difficult last mile logistics. In particular home delivery services, which are usually the preferred option by the online consumers, contribute to the atomization of parcel flows thus causing particular problems within the urban areas. However, alternative delivery solutions are growing fast, especially in metropolitan areas The purpose of this article is to compare the alternatives to home delivery that have been developed by French and German parcel delivery operators which developed pick-up points in stores and automated lockers networks. The paper includes an analysis of the key drivers of the development of the two emblematic delivery services (pick-up points and lockers), with reference to the strategies of service providers and e-commerce firms as well as consumer preferences.
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Many products ordered online need to be physically delivered to the consumers. The home delivery logistics in e-commerce, as it is so-called 'the last mile' of online shopping, has been one of the key factors leading to failures of pioneering dot coms, and is becoming a great challenge facing many eTailers. The convenience and time saving benefits of online shopping may not be realised due to the inefficiency or failure of the last mile delivery. This paper examines consumers' experience with the current delivery services, and the perceptions of unattended delivery from both consumers and eTailers' perspectives. It found that UK e-shoppers do not perceive unattended delivery as favourably as reported elsewhere in Europe, but have a great desire for picking up from local collection points. Differences exist on future delivery preferences between eTailers and consumers. The results have many implications for eTailers to develop their home delivery logistics strategy.
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In this paper we analyze consumer demand for and acceptance of online food retailing using longitudinal data collected in three studies (1998, 1999, and 2001). Information reported is from online food shoppers in ten US markets. Comparisons of results from each of the three studies is presented and change patterns identified. We conclude by recommending that researchers shift their attention toward addressing some of the more troublesome supply side issues of the online food retailing equation.
Attended home delivery(AHD) has been identified as a crucial delivery mode of the last mile problem.As the name implies, AHD involves delivery of needed goods at the customer's doorsteps or nearby via walking or short-distance vehicle. Considering no-show and random response time, this article presents an integrative approach that combines appointment scheduling and vehicle routing problem with soft time windows. We also propose an intuitive heuristic dynamic programming to tackle the appointment scheduling problem whose optimal decision is expected to be very complicated, embed it into tabu search and formulate a hybrid heuristic algorithmto solve this integrative model. Moreover, an extension to hard time windows has also been discussed. Our results indicate that the integrative approach could lead to high-quality solutions in a reasonable amount of runtimeas compared to the hierarchical approach.
Unlike much of the previous research on this topic, which assesses the economic consequences of failed deliveries to the home, this study examines the issue of failed delivery from a carbon-auditing perspective. It considers the potential environmental savings from the use of alternative forms of collection and delivery over traditional delivery methods for failed home deliveries. With a spreadsheet carbon audit model, carbon dioxide (CO2) emissions for a failed delivery are calculated on the basis of a typical van home delivery round of 120 drops and 50-mi (80-km) distance. Three first-time delivery failure rates (10%, 30%, and 50%) are assessed. The additional CO2 from a second delivery attempt increases the emissions per drop by 9% to 75% (depending on the delivery failure rate). The vast majority (85% to 95%) of emissions emanating from a traditional failed delivery arise not from the repeat van delivery but from the personal travel associated with the customer's collecting a missed redelivery from the carrier's local depot. A range of collection-delivery points (CDPs) (supermarkets, post offices, railway stations) were all found to reduce the environmental impact of this personal travel. Post offices (currently operating a CDP system through the U.K. Royal Mail's Local Collect service) yielded the greatest savings, creating just 13% of the CO 2 produced by a traditional collection by car from a local depot. Overall, the research suggests that the use of CDPs offers a convenient and more environmentally friendly alternative to redelivery and customer collection from a local parcel depot.
As the volume of retail sales distributed to the home rises, the proportion of deliveries made when there is no one at home (i.e. “unattended”) is also likely to increase. Traditionally unattended delivery involved leaving orders on the doorstep or with a neighbour. In recent years new systems of secured delivery have been developed, many of them employing reception boxes. This paper classifies the main types of unattended delivery and assesses their relative security. It identifies security problems common to most forms of unattended delivery and examines ways of overcoming them. It also advocates more rigorous analysis of the trade-offs between delivery cost, customer convenience and security, particularly by the new generation of “e-fulfilment’ companies.
Internet shopping mall has the dual nature of Web-based application system and traditional shopping mall. This paper explores online and offline features of Internet shopping malls and their relationships with the acceptance behaviors of customers. The results from a Web survey of 932 users show that the technology acceptance model (TAM) is valid in predicting the acceptance of the Internet shopping malls and that online and offline features have positive effects on the user acceptance. Both online and offline features have greater effects on the usefulness, attitude, and intention to use than either online or offline features separately. This study provides a domain-specific, integrative approach in evaluating the quality and antecedents of user acceptance for Internet shopping malls.