Munich Personal RePEc Archive

The Effect of Logistics Services Quality

on Consumer Satisfaction in Fresh Food
E-Commerce: Evidence from the South
of Vietnam

Phan, The Vinh and Huynh, Cong Minh

Becamex Business School, Eastern International University, Binh

Duong Province, Vietnam

5 May 2023

Online at https://mpra.ub.uni-muenchen.de/117627/
MPRA Paper No. 117627, posted 15 Jun 2023 08:25 UTC
 The Effect of Logistics Services Quality on Consumer Satisfaction in
Fresh Food E-Commerce: Evidence from the South of Vietnam

The Vinh Phan

Becamex Business School, Eastern International University, Binh Duong Province, Vietnam
Email: vinh.phan.bbs20@eiu.edu.vn

Cong Minh Huynh

Becamex Business School, Eastern International University, Binh Duong Province, Vietnam
Email: minh.huynh@eiu.edu.vn
ORCID ID: 0000-0001-8169-5665

Abstract
This study aims to explore the impact of five aspects of Logistics service quality on Consumer
satisfaction for the fresh food e-commerce in three provinces of the Southern Vietnam, including
Ho Chi Minh City, Binh Duong, and Dong Nai. Results show that Personnel contact quality,
Delivery quality, and Empathy quality have significantly positive impacts on consumer
satisfaction. However, the impact of Information quality and Timeliness quality are not strong
significant. Remarkable, Personnel contact quality has the strongest impact on consumer
satisfaction in the logistics service quality of fresh food e-commerce. The findings provide: i)
logistics firms in the field of fresh food e-commerce with important managerial implications, and
ii) researchers with empirical evidence in the research context of an emerging economy.

Key words: Logistics service quality, Personnel contact quality, Delivery quality, Information
quality, Timeliness quality, Empathy quality, Fresh food, E-commerce, Consumer satisfaction.
JEL Classification: L81; M31; Q02

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1. Introduction
Logistics services have been considered as a technique to achieve a competitive edge in the market
because of their role in enhancing customer satisfaction (Bowersox et al., 2008; Novack et al.,
1995). Consumers increasingly want greater levels of service excellence in addition to better
quality products, which is strongly tied to the idea of behavioral intents and customer happiness
(Bowersox et al., 2002; Parasuraman et al., 1985). Especially, the role of e-commerce logistics has
become more and more important in the era of touchless economy due to pandemics.
The COVID-19 epidemic has changed how people live and how the economy functions,
which has led to a significant increase in online food shopping among customers. E-commerce is
a new method of doing business, and appears in all nations, including Vietnam – an emerging
economy. Also, possibilities have emerged for the top logistics industries, including e-commerce
and third-party logistics providers (Mazlan, 2021). Consumers used to purchase "a bunch of
veggies and fish" in the conventional market, but in order to assure their safety, they now purchase
fresh food online from online retailers via smartphone apps like e-wallets and VinID or e-
commerce websites like Lazada and Shopee... Fresh food supply is a major driver for e-commerce
sites and supermarkets because of the rising demand for goods including vegetables, fruits, meat,
seafood, and fish (Boxme, 2021). While the market for fresh foods is growing quickly, it also faces
to one of the most challenging issues: its supply chain management. Food is perishable items;
therefore, its logistics service quality is a challenge to satisfy customers through various stages
such as storage, transportation, and final delivery.
In an emerging market like Vietnam with a strong economic growth, there is a dramatic
increase in demand for fresh food. Consumers continue to purchase vegetables, fruits, milk, fish
and meat from e-commerce platforms, such as Tiki, Lazada, and Shopee... They also make use of
fast delivery services on these platforms. Vietnam's fresh food market is estimated to be worth $27
billion per year, continuing its expanding. Fresh food sales are expected to grow at a 4.3% annual
rate. Fresh food and fast-moving consumer goods (FMCG) account for roughly one-third of
Vietnamese income. Fresh food spending is three times that of FMCG, with an estimated weekly
expenditure of VND 1.1 million. According to Nielsen's research, consumers are more willing to
shop for fresh food online when they have a variety of purchasing options and a certain level of
quality assurance. Therefore, it is a potential market for logistics firms in the fresh food e-
commerce in Vietnam. Logistics firms need to know which dimensions of logistics service quality

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they should focus on to better their consumer satisfaction. To meet this need, we examine the
impact of five aspects of logistics service quality on consumer satisfaction for the fresh food e-
commerce in three provinces of the Southern Vietnam, including Ho Chi Minh City, Binh Duong,
and Dong Nai. This region has also attracted great attention from scholars in business management
(Dam and Huynh, 2022; Ho and Huynh, 2022; Nguyen and Huynh, 2022).
This study contributes to the literature in two ways. Firstly, it provides an evidence on the
research issue in the context of an emerging economy like Vietnam for scholars. Secondly,
findings will provide logistics enterprises managerial implications for enhancing their services to
satisfy their customers in the most efficient manner.

2. Literature review

2.1. Theories

2.1.1. Logistics services quality

Logistics have seen significant changes as a consequence of the usage of information and
communication technologies. The use of information technology to logistics has been genuinely
innovative, especially in terms of raising the caliber of clients' logistical services (Gil et al., 2008).
The ordering procedure, which is made easier and faster by the Internet, has a big influence on
brick-and-mortar retailers' business models as well. The e-commerce sector now has a ton of new
business prospects thanks to the Internet (Chen & Chen, 2014). With the rapid growth of e-
commerce, client demand for variety and punctuality increases; in fact, B2C e-commerce
enterprises increase the demand for logistical services (Wang, 2015).
Parasuraman et al. (1988) introduced a comprehensive service quality evaluation system,
widely acknowledged in the academic community of the service industry, based on the principles
of total quality management (TQM). The system consists of five dimensions: tangibles,
responsiveness, reliability, assurance, and empathy. However, while the SERVQUAL model
primarily emphasizes the functional and process aspects of service quality, logistics services
primarily focus on the technological and outcome-related aspects. Thus, research on the factors
influencing logistics service quality continues to evolve. For example, Bienstock et al. (1996)
developed and validated a 15-item scale derived from the literature on physical distribution and
logistics service quality. This scale encompassed three dimensions: timeliness, availability, and

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condition. Subsequently, Mentzer et al. (1999, 2001) further expanded the structure to incorporate
timeliness, availability, conditions, and additional dimensions related to function/process
attributes. In this study, we use the concept of logistics services quality developed by Jiang et al.
(2021) with five components, comprising: Personnel contact quality, Information quality,
Timeliness quality, Delivery quality, and Empathy quality.

2.1.2. Fresh food e-commerce logistics services

Companies are continually pushed to make city freight logistics economical and dependable
(Dablanc, 2007), but variables such as a large number of orders and a time pressure for order
fulfillment have an impact on the flow of products (Quak, 2008). As a result, last-mile logistics is
one of the supply chain's most inefficient and expensive' components (Fernie, Sparks, &
McKinnon, 2010). The last mile is estimated to account for 28% of total transportation costs
(Arvidsson, 2013) and is expected to contribute up to 35% of total e-commerce logistics costs due
to rising logistics congestions and insufficient planning resulting in longer distances to customer
locations (Kin, Verlinde, & Macharis, 2017).
Digital merchants are delivering increasingly responsive last-mile delivery services to their
clients in order to grow sales and gain market share from competitors, but the outcome is
sometimes insufficient to offset these operating expenses. The answer to this challenge is to
increase the focus on company efficiency by developing techniques that promote 'leaner' supply
chains that can lower costs and support faster and more effective delivery. As a result, the emphasis
should be on time and cost-effective solutions that may also enable efficient resource usage
(Prajapati, et.al, 2023).
This study focuses on the last-mile distribution component of fresh food e-commerce
logistics in certain southern Vietnamese regions. The procedure entails distributing packaged
goods to the consumer while ensuring that the order is fulfilled in the shortest amount of time
possible. Consumer satisfaction and corporate profitability are often influenced by service quality
and reaction time. The e-commerce website in fresh food e-commerce dynamically refreshes the
database on the details of orders to be fulfilled at any point in time. This provides them with an
estimate of the inventory to be kept in their warehouse. For efficient distribution planning, the
number of items to be kept at each local distribution center must be decided.

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2.1.3. Satisfaction

The phrase "customer satisfaction" is widely used in the business and commerce sectors. When
comparing performance to expectations, a person's sense of pleasure or discontent is called
customer satisfaction (Lasserre, 2017). In order to satisfy client expectations, a company's product
and service offerings are measured using this word. The company's Key Performance Indicator is
another name for this (KPI). In today's cutthroat market, a key component of corporate strategy is
focusing on customer happiness (Cheng, Gan, Imrie, & Mansori, 2019; Tomic & Spasojevic Brkic,
2019).
Customer satisfaction is a subject of interest to companies and many academics because
consumers are the most significant factor connected with firms and because ensuring their
happiness is a top goal for the creation of sustainable growth in organizations (Afework, 2013).

2.2. Previous studies and hypothesis development

Uvet (2020) conducted a study to examine the link between customer satisfaction and the quality
of logistics services. The findings demonstrated that five aspects of logistics service quality,
including personnel quality contact, order condition, timeliness, order discrepancy management,
and operational information sharing, could be used to explain customer happiness.
Also, in a case study of the Saigon New Port Logistics Company, Tran (2019) found that
elements of logistics service quality influencing satisfaction are staff quality, information quality,
order quality, and timeliness. The findings demonstrated that every element included in the study
model complied with the specifications. It confirmed that there was a relationship between the
caliber of the logistical service and customer satisfaction
In addition, Ho et al. (2012) looked at how logistic service quality factors including
punctuality, order condition/accuracy, information quality, and availability/quality of staff affected
customer satisfaction in Malaysia's logistic service market. With the exception of the variable of
human availability/quality, the outcomes of this study generally corroborated prior research, with
three out of four aspects impacting customer satisfaction.
Most updated, Nguyen and Huynh (2023) found that the service quality factors of the e-
commerce logistics that affect customer satisfaction are customer service, the quality of the order,
the quality of the information, the quality of the delivery, and the price of delivery.

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2.2.1 Personnel contact quality and Satisfaction

The "Personnel Contact Quality" component is characterized as staff making an effort to

comprehend the issue, maintaining courteous conduct, maintaining confidentiality, being
conveniently accessible, successfully handling enquiries and complaints, and having enough
product knowledge and expertise. Customer satisfaction with logistics services influences the
conduct and attention of logistics service providers' workforce (Gupta, et. al., 2022). In order to
raise customer expectations, communication between the customer and the contact person is
crucial in the service delivery process (Parasuraman et al., 1985). Customers evaluate service
quality using interaction quality as one of three dimensions. Interoperability is defined as the
interaction of customers, liaisons, and other customers, which is an important aspect of service
quality (Lehtinen & Lehtinen, 1991). The service staff must possess the following qualities:
experience, attitude, timeliness, ability to empathize with the customer's situation, desire to solve
problems during the delivery process, and knowledge of how to approach the customer. approach
their interactions with customers (Bitner et al., 1994; Mentzer et al., 2001). Due to the complexities
of fresh produce distribution, high-quality personnel will be required. These employees will have
direct contact with consumers, particularly during the last-mile delivery process, which will have
a direct impact on the overall evaluation of logistics services.
H1: Personnel contact quality positively affects consumer satisfaction.

2.2.2 Delivery quality and Satisfaction

Delivery service is defined as the delivery to the customer of carefully packed goods in accordance
with the order, at the agreed-upon time and location. If the customer received the correct goods
and there is no damage, the trouble of contacting service personnel to return the goods is
unnecessary (Hua & Jing, 2015). Transportation requirements for fresh products will be higher
than for other general industrial goods. Customers must receive goods at the appropriate time and
location, and product freshness must be ensured throughout the logistics process (Jiang, Lai,
Chang, Yuen, & Wang, 2021). Moreover, the higher the quality of the delivery service, the happier
the customer.
H2: Delivery quality has a positive impact on consumer satisfaction.

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2.2.3 Information quality and Satisfaction

According to Lin and Lee (2006), the quality of information determines the output of online
communities. DeLone and McLean (2014) define information quality as an e-commerce content
license. The "Information Quality" component specifies that the information supplied to clients by
logistics service providers must be comprehensive, timely, accurate, sufficient, and reliable. The
consumer wishes to be kept up to date on each transaction involving their shipments, including
their actual position and the time of delivery or delay, if any. The quality of information given,
whether offline or online, aids in meeting the customer's urgent needs (Gupta, et. al., 2022). Online
sellers and prospective customers need content that is individualized, comprehensive, reliable,
secure, and addresses the official community (Azemi, Zaidi, & Hussin, 2017). When it comes to
logistics, fresh food e-commerce companies give customers access to timely, accurate tracking
information, letting them know exactly when and where their orders will be delivered. By easily
laying out these details and educating guests, they also serve as a conduit for client feedback and
complaints (Tam & Oliveira, 2017). Therefore, it fosters comprehensive logistics service
evaluation and increases service satisfaction.
H3: Information quality positively affects consumer satisfaction.

2.2.4 Timeliness quality and Satisfaction

Timeliness is one of the three aspects of physical delivery service quality conceptualization
(Bienstock et al., 1996). Hult et al. (2000) defines that the time cycle begins with placing an order
and ends with delivery. This cycle time includes re-ordering time if the product does not meet
expectations (Hult et al., 2000; Mentzer et al., 2001; Mentzer et al., 1999). Moreover, tt refers to a
product being shipped in order for it to arrive on time. It must be completed within the time frame
specified (Rahmat & Faisol, 2016). In general, the time characteristic is the most traditional and
important factor of logistics service quality (Mentzer et al., 1999). To improve overall consumer
reviews use, and satisfaction with logistics services, fresh food e-commerce businesses can shorten
logistics service cycles, improve service speeds, and respond quickly to customer service requests.
H4: Timeliness quality positively affects consumer satisfaction.

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2.2.5 Empathy quality and Satisfaction
Empathy is defined as the concern and care that each customer receives from a company's
employees. Furthermore, empathy refers to the organization's offering of care and personalised
attention to its clients. Approachability, a sense of security, and an effort to understand the
customer's needs all contribute to empathy (Olatokun & Ojo, 2016). Empathy for customers,
according to Asperen, Pieter, and Dijkmans (2018), will increase customer satisfaction.
Customers will be satisfied with the service and may even return if they feel their needs are
understood and met (Aryee, Walumbwa, Seidu & Otaye, 2012). Fresh food e-commerce
platforms must provide careful care and advice for fresh products. In order to improve customer
satisfaction, businesses must ensure food safety for fresh products, good return service,
transaction safety, and customer privacy.
H5: Empathy quality has a positive impact on consumer satisfaction.

2.3. Research framework

Based on the above hypotheses and Jiang et al. (2021), we propose the research framework as
follows:

Personnel contact quality

Delivery quality

Information quality Consumer Satisfaction

Timeliness quality

Empathy quality

Figure 1: Research framework (Adapted from Jiang et al., 2021)

3. Data and research methodology

The quantitative method is used in this study, which is based on a questionnaire survey and then
analyzes to determine the effect of various dimensions of logistics service quality factors such as

8
Personnel contact quality, Delivery quality, Information quality, Timeliness quality, and Empathy
quality on customer satisfaction in three major provinces in the South of Vietnam, consisting of
Ho Chi Minh, Dong Nai and Binh Duong.
We use the convenience sampling method due to the easy accessibility and vicinity.
Furthermore, this form of sampling approach has many advantages such as being simple,
inexpensive, and straightforward, and frequently available.
We collect data from 187 people from Ho Chi Minh, Binh Duong, and Dong Nai. They are
customers who have utilized e-commerce sites to purchase green food. We do the survey to collect
data via both online Google Forms and offline face-to-face survey.
The survey questionnaire is divided into two main parts. The first part includes four
demographic questions about gender, age, marital status and education level. The second part
includes 27 questions to measure dependent and independent variables. The level of agreement
and disagreement is also evaluated using a five-point Likert scale, with 1 denoting strongly
disagreeing and 5 denoting strongly agreeing. Tables 1, 2, and 3 show the survey questionnaire for
demographic variables, dependent variable, and independent variables.

Table 1. Demographic variables

Variable Code Items Measurement scales

1= Male
Gender GEN Your gender
2= Female
1= Under 20 years old
2= 21 – 30 years old
Age AGE Your age 3= 31 – 40 years old
4= 41 – 50 years old
5= Over 50 years old
1= Single
Marital status MS Your marital status
2= Married
Educational 1= Elementary school or below
EDU Your educational level
level 2= Secondary school

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 3= High school
4= College/ University
5= Above University

Table 1. Dependent variable

Items Code Citation

Satisfaction SA
1. How do you rate the fresh food e-commerce
SA1
logistics service as a whole?
2. What are your thoughts on the service experience of (Thai, 2013; Kassim
SA2
fresh food e-commerce logistics? & Asiah Abdullah,
3. What are your thoughts on the customer service of 2010; Jiang et al.,
SA3
fresh food e-commerce logistics? 2021)
4. What are your thoughts on fresh food e-commerce
SA4
logistics' last-mile logistics service?
5. What are your thoughts on fresh food e-commerce
SA5
logistics delivery information providing service?

Table 3 Independent variables

Items Code Citation

Personnel contact quality PCQ
1. Fresh food e-commerce logistics courier
PCQ1 (Thai, 2013; Jiang et
demonstrates excellent service attitude and behavior.
al, 2021)
2. Fresh food e-commerce logistics courier will respond
PCQ2
to the customer's request calmly and graciously.

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3. Fresh food e-commerce logistics couriers are aware
PCQ3
of my service requirements.
4. Fresh food e-commerce logistics couriers are
responsible, think about their consumers, and have PCQ4
strong business skills.
5. Fresh food e-commerce logistics courier service
PCQ5
attitude is not outstanding.
Delivery Quality DLQ
1. Cold chain logistics distributes the fresh things I
purchase (such as refrigerated trucks and cold chain DLQ1
trucks.).
2. The fresh items I purchase will be delivered on time (Hong et al., 2019;
DLQ2
and correctly to the customer's selected location. Jiang et al., 2021)
3. The fresh items I purchase ensure product freshness
DLQ3
and quality during the shipping procedure.
4. The fresh things I buy arrive in their original
DLQ4
packaging and are clean.
Information Quality IMQ
1. I can quickly and precisely query the logistics
IMQ1
distribution information after purchasing fresh items.
2. I may quickly access the logistics distribution (Jiang et al, 2021;
IMQ2
information after purchasing fresh items. Huang et al., 2009;
3. I may obtain thorough and adequate feedback on Thai, 2013; Rafiq &
logistics distribution details after purchasing fresh IMQ3 Jaafar, 2007)
items.
4. I may obtain thorough and adequate feedback on
logistics distribution details after purchasing fresh IMQ4
items.
Timeliness Quality TLQ

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1. The logistics service provider took a short time from
the shipment to the final delivery of the goods after I TLQ1
ordered fresh supplies. (Jiang et al, 2021;
2. When I acquire new things, the logistics provider can Huang et al, 2009;
TLQ2
deliver them swiftly. Mentzer et al., 2001;
3. The period for pending orders at the logistics level is Thai, 2013; Xing et al.,
TLQ3
short after I buy fresh items. 2010)
4. If fresh items are not delivered on time after I order
them, the logistics service provider will swiftly arrange TLQ4
delivery.
Empathy Quality EPQ
1. When I utilize new logistical services, I have a
EPQ1
satisfying feeling of security.
2. When I had issues with the new logistics service, the
logistics service providers were kind and comforting, EPQ2
and they offered good return service when necessary.
3. When I encounter issues while utilizing the new (Jiang et al, 2021;
logistics service, logistics service providers will put EPQ3 Parasuraman et al.,
themselves in a position to assist me. 1988).
4. They offered extra attention when I encountered
EPQ4
issues with the new logistical service.
5. When I have issues with the new logistics service, I
will receive full assistance and support; they will respect EPQ5
the privacy of my personal information.

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4. Results and discussions

4.1. Descriptive statistics

Out of the total respondents (187), 43.32% (81 individuals) were males, while females accounted
for 56.68% (106 individuals). The majority of the respondents, numbering 181, fell within the
age range of 21 to 30 years old, representing 96.79% of the sample; only 6 individuals were
under 20 years old, making up 3.21% of the respondents. Regarding marital status, 97% of the
respondents were single, while 3% were married. When it comes to education, the highest
proportion of respondents, 97.3% (182 individuals) had attended university or above; while
college students constituted a mere 2.7% (5 individuals) of the sample. In terms of geographical
distribution, 57.75% (108 individuals) of the respondents resided in Binh Duong, while 23.53%
(44 individuals) lived in Dong Nai, and 18.72% (35 individuals) resided in Ho Chi Minh City.

4.2. Reliability test

To evaluate the measurement of dimensions and ensure consistency among the independent and
dependent variables, a reliability test using Cronbach's alpha will be employed. The range of
0.60 to 0.95 for alpha indicates a desirable correlation between measurements and variables. Any
measurement with an alpha value below 0.60 will be deemed unreliable and subsequently
discarded (Tavakol & Dennick, 2011). The reliability tests for all variables are shown in Tables
4a-b, 5a-b, 6a-b, 7a-b, 8a-b, 9a-b, 10a-b, and 11a-b.

4.2.1. Satisfaction

Table 4a. Reliability Statistics for Satisfaction

Cronbach's N of Items
Alpha

.791 4

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 Table 4b. Item-Total Statistics for Satisfaction

Scale Mean Scale Corrected Cronbach's

if Item Variance if Item-Total Alpha if Item
Deleted Item Deleted Correlation Deleted

SA1 12.20 4.012 .628 .726

SA2 12.15 4.139 .714 .683

SA3 12.14 4.630 .549 .764

SA4 12.08 4.623 .522 .777

As shown in Tables 4a and 4b, Cronbach’s Alpha is 0.791 which is higher than 0.6 and
Corrected Item-Total Correlation of 4 items SA1, SA2, SA3, and SA4 are higher than 0.3 so all
the item can be used for factor analysis.

4.2.2. Personnel contact quality

Table 5a. Reliability Statistics for Personnel contact quality

Cronbach's N of
Alpha Items

.856 5

Table 5b. Item-Total Statistics for Personnel contact quality

Corrected Item- Cronbach's

Scale Mean if Scale Variance
Total Alpha if Item
Item Deleted if Item Deleted
Correlation Deleted

14
 PCQ1 16.03 9.015 .701 .818

PCQ2 16.02 9.424 .663 .828

PCQ3 15.96 9.456 .689 .821

PCQ4 16.03 8.805 .747 .805

PCQ5 16.43 10.204 .551 .854

The Cronbach’s Alpha of Personnel contact quality is 0.856, higher than 0.6 and all the
five items have the Corrected Item-Total Correlation bigger than 0.3. Therefore, the PCQ variables
can be used in factor analysis.

4.2.3. Delivery quality

Table 6a. Reliability Statistics-Delivery quality

Cronbach's N of
Alpha Items

.784 4

Table 6b. Item-Total Statistics for Delivery quality

Scale Mean Scale Corrected Cronbach's

if Item Variance if Item-Total Alpha if Item
Deleted Item Deleted Correlation Deleted

DL1 11.23 6.092 .645 .702

15
 DL2 11.33 6.599 .589 .732

DL3 11.54 6.282 .574 .739

DL4 11.38 6.280 .556 .749

The Cronbach’ Alpha of Delivery quality is 0.784, being higher than 0.6; and all the item
DL1, DL2, DL3 and DL4 have the Corrected Item-Total Correlation bigger than 0.3. Therefore,
the DL variables will be used in factor analysis.

4.2.4. Information quality

Table 7a. Reliability Statistics for Information quality

Cronbach's N of
Alpha Items

.728 3

Table 7b. Item-Total Statistics for Information quality

Corrected Item- Cronbach's

Scale Mean if Scale Variance
Total Alpha if Item
Item Deleted if Item Deleted
Correlation Deleted

IMQ1 7.74 3.022 .568 .618

IMQ2 7.70 3.308 .531 .663

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 IMQ3 7.67 3.199 .551 .639

The Cronbach’s Alpha of Information quality is 0.728, being bigger than 0.6. Moreover,
the Corrected Item-Total Correlation of 3 items IMQ1, IMQ2, IMQ3 all bigger than 0.3 so all the
items will be analyzed in EFA analysis.

4.2.5. Timeliness quality

Table 8a. Reliability Statistics for Timeliness quality

Cronbach's N of
Alpha Items

.756 4

Table 8b: Item-Total Statistics for Timeliness quality

Scale Mean Scale Corrected Cronbach's

if Item Variance if Item-Total Alpha if Item
Deleted Item Deleted Correlation Deleted

TL1 11.36 5.941 .551 .699

TL2 11.26 5.969 .534 .709

TL3 11.36 6.134 .543 .703

TL4 11.42 5.761 .581 .682

The Cronbach’s Alpha of Timeliness quality is 0.756 and bigger than 0.6. As well as all
the four items have bigger than 0.3, so all the items can be used in factor analysis.

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4.2.6. Empathy quality

Table 9a. 2Reliability Statistics for Empathy quality

Cronbach's N of
Alpha Items

.752 5

Table 9b. Item-Total Statistics for Empathy quality

Scale Mean if Scale Variance if Corrected Item- Cronbach's Alpha

Item Deleted Item Deleted Total Correlation if Item Deleted

EPQ1 15.18 8.214 .571 .687

EPQ2 15.13 8.848 .477 .723

EPQ3 15.21 8.908 .534 .702

EPQ4 15.12 8.936 .506 .712

EPQ5 15.12 8.771 .500 .714

The Cronbach’s Alpha of Empathy quality is 0.752, bigger than 0.6 and all the Empathy
quality items are bigger than 0.3. Thus, all the items can be used to factor analysis.

4.3. Exploratory Factor Analysis (EFA)

Exploratory Factor Analysis (EFA) is a statistical technique to analyze the

interrelationships between items across various factors to identify observed items that load heavily
18
on multiple factors or items that do not align properly within a factor. EFA ensures the convergence
of items that measure the same variable, causing them to cluster together within a single factor.
Conversely, items that measure distinct variables will be separated into different factors,
promoting their segregation and distinct representation. Two key indicators are considered for
determining the suitability of EFA: i) the Kaiser-Meyer-Olkin (KMO) index, ranging from 0 to 1,
where a value of 0.50 or higher is deemed appropriate for factor analysis; ii) the significance of
Bartlett's Test of Sphericity, with a p-value less than 0.05 indicating the suitability of factor
analysis (Henson & Roberts, 2006).

4.3.1. Dependent variable (Satisfaction)

Table 3a. KMO and Bartlett's Test for the dependent variable

Kaiser-Meyer-Olkin Measure of Sampling .765

Adequacy.

Bartlett's Test of Approx. Chi-Square 224.539

Sphericity
df 6

Sig. .000

It is illustrated that KMO measure of Sampling Adequacy is 0.765 > 0.5. This means the
sample is adequate for EFA. In addition, Sig. of Barlett’s test of Sphericity is 0.000< 0.05. It means
that there is a correlation between items within a factor and that data is suitable for EFA.

Table 10b4. Total Variance Explained for the dependent variable

Component Initial Eigenvalues Extraction Sums of Squared Loadings

Total % of Cumulative % Total % of Cumulative %

Variance Variance

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 1 2.473 61.833 61.833 2.473 61.833 61.833

2 .652 16.307 78.140

3 .529 13.223 91.363

4 .345 8.637 100.000

Extraction Method: Principal Component Analysis.

As given in Table 10b, the Total Variance Explained which first component has
Eigenvalues higher than 1 at 2.473. Besides, The Total Variance Explained is 61.833% which is
higher than the requirement (>50%) which means four components can explain 61.833% of the
total variance.

Table 10c. Component Matrixa for the dependent variable

Component

SA2 .864

SA1 .808

SA3 .747

SA4 .718

Extraction Method: Principal Component

Analysis. a. 1 components extracted.

In Table 10c, 4 items are collected into 1 component, all the observed variables have Factor
Loading coefficient greater than 0.5. Therefore, all items above used for measuring satisfaction
are accepted and can be used for next steps.

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 4.3.2. Independent variables (PCQ, DLQ, IMQ, TLQ, EPQ)

Table 11a. KMO and Bartlett's Test for Independent variables.

Kaiser-Meyer-Olkin Measure of Sampling .872

Adequacy.

Bartlett's Test of Approx. Chi-Square 1412.161

Sphericity
df 210

Sig. .000

It can be seen in Table 11a that the KMO value of independent variables is 0.872. In
addition, the Sig value of Bartlett’s test of Sphericity is 0.000 which is smaller than 0.05.
Therefore, this outcome of the independent variables in appropriate for conducting EFA

Table 11b. Total Variance Explained Independent variables.

Component Initial Eigenvalues Extraction Sums of Squared Rotation Sums of Squared Loadings
Loadings

Total % of Cumula Total % of Cumulative Total % of Cumulative

Varianc tive % Varianc % Variance %
e e

1 6.328 30.134 30.134 6.328 30.134 30.134 3.274 15.591 15.591

2 2.335 11.118 41.252 2.335 11.118 41.252 2.627 12.509 28.100

3 1.591 7.577 48.829 1.591 7.577 48.829 2.476 11.793 39.892

4 1.410 6.713 55.542 1.410 6.713 55.542 2.372 11.297 51.189

21
5 1.128 5.373 60.915 1.128 5.373 60.915 2.042 9.726 60.915

6 .856 4.076 64.991

7 .739 3.518 68.509

8 .698 3.326 71.835

9 .682 3.249 75.084

10 .645 3.073 78.157

11 .571 2.719 80.877

12 .520 2.475 83.352

13 .488 2.326 85.678

14 .467 2.222 87.900

15 .459 2.186 90.086

16 .427 2.035 92.121

17 .397 1.888 94.009

18 .370 1.762 95.771

19 .330 1.569 97.340

20 .304 1.447 98.787

21 .255 1.213 100.000

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Extraction Method: Principal Component Analysis.

As shown in Table 11b, Component 1, 2, 3, 4, and 5 acquired their Initial Eigenvalues are
6.328, 2.335, 1.591, 1.410, and 1.128 respectively, which are higher than 1, indicating these
components are substantial. Moreover, the cumulative of Extraction Sums of Squares Loading is
60.915% (> 50%), showing that five factors explain 60.915% of the data variation.

Table 11c. Rotated Component Matrixa for Independent variables

Items Components

1 2 3 4 5

PCQ4 .837

PCQ1 .752

PCQ3 .736

PCQ2 .707

PCQ5 .706

EPQ1 .746

EPQ4 .688

EPQ5 .688

23
EPQ3 .633

EPQ2 .602

DL2 .761

DL1 .752

DL4 .708

DL3 .698

TL2 .749

TL4 .747

TL1 .676

TL3 .666

IMQ2 .748

IMQ1 .728

IMQ3 .652

Extraction Method: Principal Component Analysis.

Rotation Method: Varimax with Kaiser Normalization.
a.
Rotation converged in 5 iterations.

24
 Table 11c shows that the loadings of all 21 items distributed across five components are
greater than 0.5 (ranking from 0.652 to 0.837). PCQ4, EPQ1, DL2, TL2, and IMQ2 have the
strongest contribution to PCQ, EPQ, DL, TL, and IMQ, respectively.

4.4. Regression

We estimate the impact of five independent variables (Personnel contact quality, Delivery
quality, Information quality, Timeliness quality, Empathy quality) on the dependent variable
(Consumer Satisfaction) by employing the Multiple linear regression. Results are presented in
Tables 12, 13, and 14.

Table 12. Model Summaryb

Model R R Square Adjusted R Std. Error of Durbin-

Square the Estimate Watson

1 .790a .624 .613 .41809 1.923

a. Predictors: (Constant), EPQ, DL, TL, PCQ, IMQ

b. Dependent Variable: SA

Regression model is created by five factors: personnel contact quality (PCQ), delivery
quality (DL), information quality (IMQ), timeliness quality (TL), and empathy quality (EPQ). The
Adjusted R Square is 0.613 meaning that there is 61.3 percent of the change of the dependent
variable (customer satisfaction) is explained by the independent variables personnel contact quality
(PCQ), delivery quality (DL), information quality (IMQ), timeliness quality (TL), and empathy
quality (EPQ). The value of Durbin – Watson equals 1.923, in the range of 1.5 to 2.5, which means
there is no auto-correlated problem in this statistical model.

Table 13. ANOVAa

Model Sum of df Mean F Sig.

Squares Square

25
 1 Regression 52.427 5 10.485 59.985 .000b

Residual 31.639 181 .175

Total 84.067 186

a. Dependent Variable: SA
b. Predictors: (Constant), EPQ, DL, TL, PCQ, IMQ

In Table 13, the Sig value from the F-test indicates the sequence of independent variables
significantly anticipates towards the dependent variable, in which, the Sig. must be less than 0.05
(Leech et al., 2005). As the table shown above, The ANOVA acquires an F-test value of 59.985
and is significant (p<0.001). The results of this outcome demonstrate that the combination of the
predictors dramatically predicts customer satisfaction.

Table 14. Coefficientsa

Model Unstandardized Standardized t Sig. Collinearity

Coefficients Coefficients Statistics

B Std. Beta Tolerance VIF

Error

1 (Constant) .457 .220 2.081 .039

PCQ .430 .050 .482 8.669 .000 .674 1.484

DL .137 .045 .165 3.052 .003 .708 1.412

IMQ .112 .046 .139 2.413 .017 .624 1.603

TL .095 .046 .111 2.080 .039 .730 1.370

26
 EPQ .144 .050 .154 2.878 .004 .728 1.373

a. Dependent Variable: SA

Table 14 shows that the value of VIF of independent variables is smaller than 2 so there
is no multicollinearity in the multiple linear regression model. As given in Table 14, the t value
and the Sig. (p) of each independent variable indicates whether that variable is significantly
contributing to the equation for predicting dependent variable from the whole set of predictors
(Leech, Barrett, & Morgan, 2005). According to Field (2009), when Sig. of one predictor is equal
or less than 0.05, this predictor has a significant impact on the dependent variable. There are five
independent variables have Sig. values satisfying the condition of less than 0.05 including
personnel contact quality (PCQ) (Sig. = .000), delivery quality (DL), (Sig. = .003), information
quality (IMQ) (Sig. = .017), timeliness quality (TL) (Sig. = .039), and empathy quality (EPQ)
(Sig. = .004). Therefore, these factors have significant influence on customer satisfaction (SA).
However, the impacts of IMQ and TL on SA are not strongly significant as other factors.
Thus, we have the sufficient evidence to conclude that:
H1 is supported: Personnel contact quality positively affects satisfaction (β = 0.482, t =
8.669, p < 0.05)
H2 is supported: Delivery quality has a positive impact on satisfaction (β = 0.165, t = 3.052,
p < 0.05)
H3 is supported: Information quality positively affects satisfaction (β = 0.139, t = 2.413, p
< 0.05)
H4 is supported: Timeliness quality positively affects satisfaction (β = 0.111, t = 2.080, p
< 0.05)
H5 is supported: Empathy quality has a positive impact on satisfaction (β = 0.154, t =
2.878, p < 0.05)

Additionally, personnel contact quality has the highest standardized coefficients Beta
(0.482), which indicates that this predictor has the strongest impact on customer satisfaction. Next,
delivery quality ranks second with β = 0.165. Following that are Empathy quality (third) and

27
information quality (fourth) with β = 0.154 and β = 0.139 respectively, while timeliness quality
has lowest impact on customer satisfaction with β = 0.111. Details are given in Table 15.

Table 15. Summary

Hypothesis Significant Hypothesis Standardized Impact

Coefficient β Ranking
value result

H1: Personnel contact .000 Supported 0.482 First

quality positively impacts
on satisfaction.

H2: Delivery quality has a .003 Supported 0.165 Second

positive impact on
satisfaction.

H3: Information quality .017 Supported 0.139 Fourth

positively impacts on
satisfaction.

H4: Timeliness quality .039 Supported 0.111 Fifth

positively impacts on
satisfaction.

H5: Empathy quality has a .004 Supported 0.154 Third

positive impact on
satisfaction.

28
4.5. Discussion

Our results provide interesting findings as follows:

Firstly, Personnel contact quality (PCQ) is the most influential dimension of logistics
service quality that affects customer satisfaction. Because Sig. (0.000) is lower than 0.01 and Beta
(0.482), there is a positive relationship between Personnel contact quality and customer
satisfaction. This implies that higher Personnel contact quality leads to higher customer
satisfaction. The result of this finding is identical to that of Bitner et al., (1994) and Mentzer et al.,
(2001). Consumers will be more satisfied when they feel the professionalism, attitude, ability to
empathize and interact with customers.
Secondly, the second factor is Delivery quality (DL). In this study, Delivery quality is
statistically significant due to Beta = 0.165; Sig. = 0.003 < 0.01. When customers receive the items
they buy on time, carefully packed and preserved, customers will feel even more satisfied with the
service. Hua and Jing (2015)’s and Jiang, Lai, Chang, Yuen, and Wang (2021)’s finding are
comparable to this one.
Thirdly, the third logistics service quality factor is Empathy quality (EPQ). Due to Sig.
(0.004) lower than 0.01 and Beta (0.154), there is a positive relationship between Empathy quality
and customer satisfaction. The findings indicate that Customer satisfaction will be increased if
they receive care from the company's staff. The conclusion of the research is comparable to that
of Asperen, Pieter, and Dijkmans (2018).
Fourthly, the least significant impacts of logistics service quality’s dimensions on
consumer satisfaction are Information quality and Timeliness quality. Information quality, which
also improves customer satisfaction, is another aspect of logistics service quality factors. The
Pearson correlation between Information quality and customer satisfaction is 0.550; the beta
coefficient is 0.139 and Sig. (0.017) < 0.05. According to the findings of this study, Information
quality is one of the factors driving service satisfaction as they are given access to timely, accurate
tracking information about their orders. The finding for the Information quality dimension is
consistent to Tam and Oliveira (2007).
Whereas, Timeliness quality has a positive effect on customer satisfaction. Due to the Beta
coefficient is of 0.111 and the significance is 0.039 < 0.05. According to the findings of this study,
if customers can receive their goods quickly, as expected, or get instant feedback when they need

29
it, they will feel satisfied with the logistics service. The result for this Timeliness quality dimension
is similar to Mentzer et al., (1999).

5. Conclusion and implication

This study aims at exploring the impact of five aspects of Logistics service quality on Consumer
satisfaction for the fresh food e-commerce in three provinces of the Southern Vietnam, including
Ho Chi Minh City, Binh Duong, and Dong Nai. Results show that Personnel contact quality,
Delivery quality, and Empathy quality have significantly positive impacts on consumer
satisfaction. However, the impact of Information quality and Timeliness quality are not strong
significant. Remarkable, Personnel contact quality has the strongest impact on consumer
satisfaction in the logistics service quality of fresh food e-commerce.

The findings provide significant implications for researchers and practitioners. Firstly, the
findings add its academic significance to the topics of e-commerce logistics research with a better
knowledge of the key elements driving client satisfaction in main provinces in the South of
Vietnam – an emerging economy. Furthermore, unlike prior research that just show a correlation
between consumer perceived importance and customer satisfaction, this study shows that
consumer perceived importance has a strong positive causal link with consumer satisfaction.
Secondly, this study provides a helpful reference for fresh food e-commerce enterprises, online
retailers, and offline users of fresh food e-commerce. The findings will help fresh food e-commerce
enterprises evaluate which grade of service would increase consumer happiness and maybe
increase their likelihood to repurchase. Besides, fresh food e-commerce enterprises can gain a
better understanding of the quality goods they should seek for in their last mile logistics. Following
that, e-commerce enterprises will devise appropriate tactics to improve the quality of logistics
services, allowing consumers to experience higher-quality logistics while earning more profits
indirectly.

30
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