Analysis the Factors Affecting Satisfaction of the Quality of Seafood Logistics in Vietnam45311

Analysis the Factors Affecting Satisfaction of the Quality of Seafood Logistics in Vietnam Hong Van Dao 1,2 , Van Quang Do 3,* , Thi Minh Ngoc Vu 2 , The Kien Nguyen 4 1 Hanoi Universi

Khan K., Manzoor, H.M (2012) The testing of Hall’s Permanent Income Hypothesis: a case study of Pakistan Asian Economic and Financial Review 2(4), 518-522

Perron, P (1989) The great crash, the oil price shock, and the unit root hypothesis Econometrica: Journal of the Econometric Society, 361-1401

Analysis the Factors Affecting Satisfaction of the

Quality of Seafood Logistics in Vietnam

Hong Van Dao 1,2 , Van Quang Do 3,* , Thi Minh Ngoc Vu 2 , The Kien Nguyen 4

1 Hanoi University of Natural Resources and Environment, Hanoi, Vietnam

2 Foreign Trade University, Hanoi, Vietnam

3 Thuyloi University, Hanoi, Vietnam

4 VNU University of Economics and Business, Vietnam National University, Hanoi, Vietnam

* Correspondence: quang61qs@gmail.com

Abstract: The paper analyzes the factors affecting customer satisfaction with the quality when using

Vietnam's seafood logistics service through SEM model From the result of this model, the authors found five groups of factors affecting satisfaction with seafood quality, including human resources

in logistics, technology, delivery and product packaging, shipping capacity, and reputation of enterprises All of these factors have a positive impact on this service The meaning of this study is to give the useful references in planning policies for seafood logistics in Vietnam

Keywords: Structural Equation Modelling (SEM); seafood; logistics; quality of service

1 Introduction

Vietnam is a rich natural resources country, especially water and marine resources This explains why the seafood industry is strongly developed and plays a vital role in the export sector of Vietnam In fact, the seafood industry accounts for a large share of GDP In order to push the seafood industry, it is required to develop a modern seafood logistics system Although many researchers have studied about logistics and seafood industry, the works that combine these two areas in the same topic and delve into the research on how to develop logistics in seafood industry is not popular yet

Nguyen (2012) studied the development of a maritime transportation planning support system for car carriers based on genetic algorithm Shipping plays a vital role in an integrated economy, evidence that shipping volumes have increased over the years and are expected to continue to increase in the near future For this reason, logistics providers are forced to enhance their competitiveness in terms of both price and quality by providing efficient services Based on this reason, many researchers have studied how to handle global logistics issues, and in the case of shipping, many studies have compared it to other transport industries because of its importance This research has developed an algorithm

and has succeeded in developing an algorithm for transport planning with algorithms, thus being able to prepare various options, evaluate them and thus support decision makers

Megan (2014) explored shipping issues at that time, particularly on how and how much seafood was shipped to the western federal markets of North Carolina The study also identified challenges as well as opportunities in improving the east-to-west supply chain

The three biggest challenges for shipping seafood from the east to the west were related to the availability of logistics, products, marketing and education The main reason for the big problem of logistics was lack of centralized distribution facility for seafood in the western part of North Carolina Logistics could be improved by establishing a domestic distribution center with a capacity of cold storage to facilitate road transport The study explored shipping issues in the seafood industry, namely how and how much seafood was shipped to in-state markets in the western part of North Carolina The thesis also identified challenges as well as opportunities in improving the east-to-west supply chain The author identified five major coastal-based seafood wholesale distributors and two inland-based distributors with routes established to serve goods, groceries, retail markets, and food distributors in all major metropolitan areas, including west areas of North Carolina and neighboring states

The study identified and strengthened alternative or complementary supply chains and domestic markets along the corridor from North Carolina to Baltimore, Philadelphia, New York and New Bedford North Carolina seafood supplied more to local locations would contribute to brand recognition and avoid price losses

2 Methodology

2.1 Model Building Base

On the basis of preliminary research results, research overview, and base on relevant arguments on customer satisfaction with the quality of logistics services, from the bridge angle (customers), due to seafood logistics characteristics , through the customer's need and feel research, to apply 5 angles of view of the SERVQUAL model, the authors have built a set of criteria to evaluate the quality of seafood logistics services, including 7 components: (1) Company's reputation , (2) Manpower Logistics, (3) Factor shipping capability, (4) Delivery and packaging factors, (5) Technological factors, (6) Satisfaction factor, and (7) Loyalty factor

To verify the relationship between the studied impacts, the linear structure model (Structural Equation Modelling-SEM) is the most suitable model proposed The SEM model specifies the relationship between the underlying variables (which are not direct measurements) and the variables that can be observed, while clearly pointing out the relationship between the underlying variables together

2.2 Data collection

According to Hair and Associates (1998), for the implementation of the EFA factor analysis, the size of the sample applied in the study must be at least 5 times the total number

of observed variables The study has 33 observation variables, so the minimum sample

number is 33 * 5 = 165; for multi-variable regression analysis: The minimum sample size to

be achieved by the formula is 50 + 8 * m (m: Independent variable number) (Tabachnick and Fidell, 1996) The study has 6 independent variables, so the minimum sample size is: 50 + 8

* 6 = 98 observations As such, to determine the factors that affect the level of satisfaction of seafood logistics service, research has conducted in-depth interviews and survey with structural inquiry for aquaculture enterprises, exploiting and processing seafood on the whole country The number of votes obtained is 500 votes, of which 492 are enough information to be used for analysis (98.4% ratio)

The interview card is designed with closed questions to ask businesses to evaluate, compare conditions, current status of seafood logistics services with their expectations, about the aspects related to the credibility of the company's logistics responsibilities, logistics manpower, transportation capacity, forwarding and packaging, technology, satisfaction, and loyalty Reviews using Likert scale with 5 levels: 1 = strongly disagree/very dissatisfied, 2 = disagree/dissatisfied, 3 = neutral, 4 = agree/satisfied and 5 = strongly agree/very dissatisfied

2.3 Data processing

In this study the authors applied the method of analyzing the model equation structure (Structural Equation Model – SEM), which uses the SPSS 22.0 and AMOS software version 20.0, which consists of 4 steps: The analysis of the reliability coefficient Cronbach's Alpha, Exploratory Factor analysis (EFA); The Affirmation analysis (Confirmatory Factor Analysis – CFA), analyzing the structural equation model (Structural Equation Model – SEM), specifically as follows:

Step 1: Evaluate the reliability of the scale

Cronbach's ALPHA (CA) coefficient is used to assess the reliability of the ladder for each observation variable belonging to the factor groups Peterson (1994) said that any factor with a CA less than 0.6 should be excluded from the research model According to Bernstein and Nunnally (1994), observation variables with a total correlation coefficient of less than 0.3 are considered garbage variations, which lead to a conclusion of rejecting the model

Step 2: Analyze the discovery factor (EFA)

EFA allows to describe the correlation between impact variables, known as

"factors" EFA is used in cases where the relationship between the observed variables and the underlying variable is unclear or uncertain EFA analysis is conducted in an explored manner to determine the scope, level of the relation between observation variables and the base factors, as the basis for a set of measurements to shorten or reduce the number of observations which are uploaded to the base factor Meyers and Associates (2016) said that,

in EFA, the method of extraction of Principal Component Analysis in conjunction with Varimax rotation is the most commonly used method A condition for EFA analysis is the following requirements: factor loading > 0.3; 0.5 ≤ KMO ≤ 1; Bartlett test having statistical significance (Sig <0.05); total variance percentage > 50%

Step 3: Analyzing the assertions factor (CFA)

CFA is used appropriately when researchers have information about underlying variable structures CFA may be the next step of EFA to test whether there is a theoretical model that is the basis of a set of observations Indicators for measuring the suitability of the model with the data of a limb (CMIN); The genus (CMIN/DF); Comparative relevance index (CFI); Tucker & Lewis Index (TLI); An estimate of the original average median (RMSEA) According to Hair and Associates (1998), if 1 <CMIN / df <3, the model is considered to be a good fit Nguyen (2011) stated that if the model receives CFI values, TLI

≥ 0.9; RMSEA ≤ 0.08, and P> 0.5, the model is relevant to the data

Step 4: Modeling equation structure (SEM)

The structural equation Model (SEM) is the following step of EFA and CFA, which defines a set of regression equations at the same time In this study, the SEM model was carried out with the aim to identify the factors of influence and the degree of influence of each factor to "customer satisfaction of seafood logistics services"

3 Results

3.1 Assessment of the quality factors for seafood logistics services

3.1.1 The prestigious group responsible for Logistics companies

The result of the analysis of the "corporate credibility" factor suggests that the observation variables have low average values, and the differences are not much, namely: the observation of "Companies always report the progress of services UNT1" with the lowest price among the 3.1024 factors, the smallest value is 1, the largest is 4 Level 3 is the neutral level, showing the level of interest of the seafood logistics businesses on the reporting of progress in the process of performing the services, this in accordance with the fact that multi-segment customers using the service do not capture the information in the logistics cycle, until the products are consumed by customers In contrast, the observation variable

"the company has a guarantee of delivery time-UTN2" has the highest average rating value (3.6424) However, this value is not high, which indicates that although the companies always strive to ensure the delivery time, due to issues of poor transport connections and synchronized infrastructure, traffic congestion and incidents often occur

Table 1: Assessment of reputation and responsibility of the companies

The companies always report on the progress of

services (UTN1)

492 1.00 4.00 3.1024 0.83702

The companies have guaranteed delivery time

(UTN2)

492 2.00 5.00 3.6424 0.69840

When there is a problem, the companies can show

their sincerity and readiness in problem solving

(UTN3)

492 1.00 5.00 3.2710 0.76457

Is the sum insured and compensation properly

paid according to the contract (UTN4)

492 1.00 5.00 3.4201 0.92031

Declare accurate customs procedures (UTN5) 492 1.00 5.00 3.3617 0.74183

Source: Analysis from the results of the investigation 3.1.2 The factor of Human resources in Logistics

The results of the "logistics’ human resource" factor analysis show that the observation of "service speed of company employees is on time and meet the requirements

of customers – NL4" has an average value of the lowest price among the 3.3192 factors , the smallest value is 1, the largest is 5 In fact, the current human resources in seafood logistics are mainly apprenticeships, who learn through the process of working The proportion of employees through formal training is very limited, thus leading to the low skills of processing the businesses Therefore, improving the quality of human resources working in seafood logistics would become a special concern in developing logistics development strategies in the future However, the group of factors "the service attitude of employees of the company has the passion and dedication – NL2", which reaches 4.2796, is well-appreciated by customers This figure shows the dedication and love of seafood logistics’ staff

Table 2: Logistics’ Human Resource Assessment

The service style of company employees is

professional ( NL1 )

492 3.00 5.00 3.6129 0.61569

The service attitude of company employees is

warm and dedicated ( NL2 )

492 2.00 5.00 4.2796 0.86200

Professional qualifications and skills of

employees ( NL3 )

492 2.00 5.00 3.4043 0.86260

The service speed of company employees on

time and meet the requirements of customers

( NL4 )

492 1.00 5.00 3.3192 0.72931

Source: Analysis from the results of the investigation 3.1.3 The factor of Transportation capacity

The results of the "transportation capability" factor analysis show that the observation of "Company's warehouses meet the recipient's standards-NLVC2" has the lowest average value price among the factors, at 3.9892 Reality shows that currently the level of concentration of the warehouses is not high, the quality is also not high, which leads

to the need to build a centralized seafood logistics system, thereby planning and building quality assurance warehouses In terms of the variable observation "the company can transport goods by air, waterway if requested", the authors found that air freight of Vietnam

is relatively developed currently Although not all of the seafood logistics companies have the service of aviation and waterway transportation, if seafood companies need to use these types of transport, logistics companies are ready to look for air freight and waterway services to meet the needs of customers Besides, the "means of transportation of the company is equipped with optimum equipment suitable for seafood items such as cold container, cold storage, " and the "cold supply chain of the company that meets the

requirements of seafood quality standard" has a low average value rating, this shows that the equipment needs to meet the specific needs of the standard of seafood logistics is limited, because investing in these equipment requires a relatively large investment This is a large void that needs to be filled in the future

Table 3: Transportation Capacity Assessment

The company's transportation vehicles are equipped with

optimal equipment suitable for seafood products such as:

Refrigerated containers, cold storage ( NLVC1 )

492 1.00 5.00 3.2619 0.99253

Does the company's warehouse meet the recipient 's

standards ( NLVC2 )

492 1.00 5.00 3.0082 0.79719

The company can transport the goods by air or by water if

required by customers ( NLVC3 )

492 2.00 5.00 3.8753 0.86447

Does the company's cold supply chain meet the seafood

quality standard ( NLVC4 ) requirements

492 1.00 5.00 3.2936 0.69274

Source: Analysis from the results of the investigation 3.1.4 The factor of Delivery and packaging products

The results of the "delivery and packaging product" factor analysis show that the observation of "delivery speed and packaging of the company to meet the requirements of our party" has the lowest average price level in the 3.3183 factors, the smallest value is 1, and the largest is 5 This shows that logistics companies cannot meet the need of urgent logistics services, due to the limitation in many stages, including human resources and equipment In contrast, the observation margin "The packaging of products are durable and includes all important steps to ensure the quality of seafood" has the highest average value,

at 3.5437, which shows that seafood logistics businesses have paid attention to the packaging process and fully implemented the steps of the packaging process However, the average level is still not very high, so businesses need to pay more attention to guarantee the quality

of seafood products

Table 4: Evaluation of Delivery and Packaging Products

Delivery speed and packaging of the company's products

can meet your requirements (GDG1)

492 1.00 5.00 3.3183 0.84437

Packaging is sure and full of important steps to ensure the

quality of Seafood (GDG2)

492 2.00 5.00 3.5437 0.61715

The company pays attention to the quality of seafood when

shipping and delivery (GDG3)

492 1.00 1.00 3.3867 0.76524

The company supports loading and unloading and

transporting goods from the port to the place of receipt and

warehousing (GDG4)

492 1.00 5.00 3,400 0.56831

(Source: Analysis from the results of the investigation)

3.1.5 Technology factor

The results of the technology factor analysis show that the observed variable

"Technology has a great impact on the price and quality of logistics services - CN1" has the lowest average value of 3.2573, which shows that when applying technology into seafood logistics chain, the service values do not change much In contrast, the observed variable

"Customers easily track the status of goods after sending via software - CN3" has the highest average value, at 3.7295, which shows that when seafood logistics enterprises use software, checking and monitoring the status of goods circulating will be more easily Furthermore, using software also helps to combine trips in order to avoid one way delivery, which is very wasteful However, the number of enterprises applying software in monitoring the process

of circulation and cold storage is not high

Table 5: Technology evaluation

Technology that affects the price and quality of logistics

services (CN1)

492 1.00 5.00 3.2473 0.77245

Information technology companies exploiting good

logistics services (CN2)

492 1.00 5.00 3.6645 0.62914

Customers easily track the status of goods after sending

via software (CN3)

492 1.00 5.00 3.7295 0.80136

Can the company's service chains meet

the robotization factor (CN4)?

492 1.00 5.00 3.4271 0.50136

Source: Analysis from survey results

3.2 Application of SEM model in analyzing factors affecting customer satisfaction with the quality of seafood logistics services

3.2.1 Analyze the reliability of the scales by Cronbach's Alpha

The results of a scale reliability assessment are carried out through the calculation of Cronbach's Alpha for 7 factor groups across certain loops The results obtained (table 6) indicate that the SHIFTS of the factor groups are greater than 0.6 and the total correlation coefficient is greater than 0.3 If one of the basic factors in the group is eliminated, a smaller

CA will occur Cronbach's Alpha results for "company credibility factor" suggest the variables UTN2, UTN3, UTN4 are satisfactory and retained to analyze the discovery factor

in the next round Cronbach's Alpha results for "Company reputation responsibilities" through 3 loops show the variables UTN2, UTN3, UTN4 are satisfactory and retained for analysis of the discovery factor in the next round Cronbach's Alpha results for "logistics manpower factor" through two loops indicate the NL1 variable, NL3, NL4 are satisfactory, Cronbach's Alpha results for "Shipping capacity elements" show through two loops that the variables NLVC1, NLVC2, NLVC4 are satisfactory Cronbach's Alpha results for "shipping and packaging elements" show up through two loops, the variables GDG1, GDG3, GDG4 are satisfactory Cronbach's Alpha results for "technological elements" show two loops, the variables CN1, CN2, CN3 are satisfactory Cronbach's Alpha Results for "element satisfaction" show through two loops, the variables HL1, HL3, HL4 are satisfactory The

result of Cronbach's Alpha "brand loyalty factor" shows that the TT1, TT2, TT3 MYDINH variables are both satisfactory and retained to analyse the discovery factor in the next round

As such, the resulting obtained 21 observed variables were introduced in EFA analysis

Table 6: Reliability Assessment Results Measurement

coefficients

Cronbach's Alpha if variable type

1 Reputable Responsibility Cronbach's Alpha = 0.689

1 UTN2 The company has a guarantee of delivery time 0.551 0.559

2 UTN3 When problems arise, the company can show

sincerity and readiness in problem solving

0.561 0.613

3 UTN4 The sum insured and compensation made strictly

according to the contract

0.505 0.650

2.Human resource of logistics Cronbach's Alpha = 0.851

4 NL1 Service style of company employees have an

engineer's career

0.739 0.808

5 NL3 Professional qualifications and skills of employees 0.756 0.762

6 NL4 The service speed of company employees on time

and meet the requirements of customers

0.720 0.800

3.Capacity of transport Cronbach's Alpha = 0.837

7 NLVC1 Transportation of the company is equipped with

the optimal equipment suitable for seafood items such as cold containers, cold storage ,

0.703 0.771

8 NLVC2 The company's warehouse meets the standards of

the recipient

0.704 0.770

9 NLVC4 The company's cold supply chain meets the

seafood quality standard requirements

0.692 0.782

4.Delivery and packaging Cronbach's Alpha = 0.862

10 GDG1 Speed of delivery and packaging of the company's

products can meet your requirements

0.721 0.822

11 GDG3 The company pays attention to the quality of

seafood when shipping and delivery

0.805 0.746

12 GDG4 The company supports loading and unloading

and transporting goods from the port into the

receiving and warehousing

0.694 0.849

5.Technology Cronbach's Alpha = 0.862

13 CN1 Technology affects the price and quality of

logistics services

0.671 0.866

14 CN2 Information technology companies exploiting

good logistics services

0.695 0.849

15 CN3 Customers easily track the status of goods after

sending via the software

0.861 0.687

6.Brand loyalty Cronbach's Alpha = 0.879

16 TT1 You have a problem when you have to change the

company about the logistics services are

cooperating

0.794 0.803

17 TT2 Are you ready to use their Logistics service again? 0.762 0.833

18 TT3 Are you willing to recommend another company

to use Logistics with them?

0.745 0.848

7.Satisfaction Cronbach's Alpha = 0.872

19 HL1 Are you satisfied with the quality of logistics they

have provided?

0.732 0.840

21 HL4 Satisfaction about the payment method 0.770 0.807

(Source: Analysis from the results of the investigation)

3.2.2 Exploratory Factor Analysis (EFA)

In this step, the authors bring all 21 variables obtained through inspection Cronbach's Alpha into EFA analysis, the results of the exploratory factor analysis (EFA) undergo several qualifying rounds, obtained: Table result 7 shows 0.5 < KMO = 0.689 < 1, conclusion: The factor analysis is appropriate for the actual data

- Test the correlation between measurement variables (Bartlett's Test)

+ Testing H0 hypothesis: the level of correlation of zero variables;

+ The results of a Bartlett's Test with a value of Sig = 0.000 < 0.05, conclusion: measurement variables correlated together in each factor group;

- Inspection of the variance of factors (% Cumulative variance):

In the Analysis results table, total Variance explained in the Component Line No 7 and the Cumulative % column has the variance value accrual factor of 77,533% > 50% meets the standard Conclusion: 77,533% of the changes of the factors are explained by the variables that measure the composition of the Factor

3.2.3 Confirmation factor Analysis (CFA)

After performing EFA analysis, the scales are inspected again, by the factor analysis method of the CFA affirmation The aim is to ensure more certainty about the reliability and value of the scale based on a number of predefined factors to limit mistakes in determining factors (Hair and Associates 1998) The CFA results show that the indicators assessing the relevance of the theoretical model create results of (GFI = 0,907; TLI = 0,960; CFI = 0,968; RMSEA = 0.020) Therefore this model fits into the actual data It is possible to conclude that the measurement components "satisfaction of the quality of Vietnam Seafood Logistics" with the independent factors achieved the value of discrimination (Nguyen et al 2003)

Figure 1: CFA model of the study

3.2.4 Modeling structural equations

In this study, the SEM model was carried out with the aim to determine the factors

of influence and the degree of influence of each factor to "satisfaction in the quality of seafood logistics services" The SEM model was conducted in analysis starting from the initial proposed research model, then conducting calibration of the model to better model

The results of the CFA test by AMOS Software follow the principle of correction of relations with mi > 4 (Mi-Indice Modification, which is a correction factor with the change

of χ2 on a degree of freedom), but this adjustment must ensure the appropriate theoretical and implied meanings of practical terms After making adjustments, the CFA results showed that indicators of theoretical model conformity were significantly improved (χ2/df = 1.115; GFI = 0,902; TLI = 0,939; CFI = 0,950; RMSEA = 0.025) Therefore, this model fits into the actual data Moreover, the regression factor between the satisfaction factors with the impact factor is the "prestige responsibility of the company",