min m ■ 11*» Li ANALYZING FACTORS AFFECTING LOGISTICS DEVELOPMENT IN VIETNAM'S SEAFOOD INDUSTRY BY USING STRUCTURAL EQUATION MODELLING • DAO HONG VAN ABSTRACT: ị This study proposes a model of the factors affecting the development of logistics in Vietnam’s seafood industry by using the PEST (political, economic, social and technological) analysis The structural equation modelling (SEM) is used to evaluate, adjust and draw conclusions about the impact of factors on the logistics development in Vietnam’s seafood industry This study is i expected to provide useful information for the process of making macro policies and ; management decisions of policymakers and logistics firms Keywords: logistics development, seafood industry, SEM model Introduction Logistics plays a significant role in the development of seafood industry In particular, a I good logistics system helps optimize the uses of warehouses and decrease the time for transportation, which in turn increases seafood quality With the SEM model, this study analyses the advantages and disadvantages of the seafood industrys logistics in Vietnam, and therefore policy makers could find theừ solutions to improve ogistics in the seafood industry Literature review Per Engelseth, Irina V Karlsen, Shulin Huang, and Arild Hoff (2016) published a study named *rThe Value Aspect of Reallocating Seafood Freight from Road to Sea Transport” The study c evelops a plan on organizing a project to promote transport mode change in the food chain from the perspective of value The value that lies within the context of this project is revealed as a complex intersubjective phenomenon Value is created by multiple actors located at different locations in the supply chain Customer value is one of the many positive value components of this study IA Soenandi and YJuan and MBudi (2017) published a study named “Optimization for routing vehicles of seafood product transportation” The study refers to the optimization of the routing facilities as a method to help reduce ttansit times and thus keep seafood fresh This study will solve a random vehicle routing (VRP) problem with time and power windows using a comparison of six methods and finding the best one to optimize In this situation, companies can choose the best method, suitable for their existing conditions In this study, the authors compared optimization with another method such as branching and dynamic programming, and Ant Colony Optimization (ACO) algorithm In the end, the author got the best results after running the ACO algorithm with existing So 18-Tháng 7/2021 255 TẠP CHÍ CƠNG THƯƠNG travel time data With the ACO algorithm, it was possible to reduce the travel time of the car to 3189.65 minutes, about 23% lower than the current one and based on considering the time constraints within days (including the rest periods for drivers) using a 28-ton truck capacity and two vehicle units for transportation Barbara Garrity-Blake and Megan Ware (2014) published a study titled “Keep It Moving: North Carolina Seafood Transportation Logistics with a Focus on East to West Routes” The purpose of this study was to determine how and how much North Carolina seafood is being distributed to western intrastate markets today, and to examine options where domestic distribution (inland distribution) can be improved to better serve suppliers, distributors, retailers and consumers Many factors are needed to strengthen the shipping routes that supply seafood from east to west in North Carolina Taking this initiative forward will require abundant human resources to carry out the necessary preparations: for example, bringing potential partners together to come to cooperation agreements, measuring the level of interest of the seafood industry in incubating more domestic enterprises Methodology The method of structural equation modelling (SEM) is applied with the use of SPSS 22.0 and AMOS version 20, including steps: Cronbach’s alpha analysis, exploratory factor analysis (EFA), confirmatory factor analysis (CFA) and structural equation model (SEM) analysis, specifically as follows: 3.1 Step 1: Assess the reliability ofthe scale The results are taken from the previous study of building a model of factors affecting the logistics development in Vietnam’s seafood industry 3.2 Step 2: Exploratoryfactor analysis (EFA) The correlation between the impact variables, called "factors" are described by the EFA Exploratory factor analysis is used effectively when the relationship between observed variables and the underlying variables is unclear or uncertain The EFA helps to determine the extent and degree of the relationship between observed variables and the underlying factors, which underlie a set of measurements to reduce the number of observed variables uploading base 256 So 18-Tháng 7/2021 factors Meyers et al (2016) reported that in the EFA, the Principal Component Analysis extraction method associated with the Varimax rotation is the most commonly used method [7] The EFA can only be used when these conditions are satisfied: Factor loading > 0.3; 0.5 < KMO < 1; Bartlett test has statistical significance (Sig 50% 3.3 Step 3: Confirmatoryfactor analysis (CFA) The CFA is applicable when researchers already have knowledge of underlying variable structure Researchers can apply the CFA as a next step of the EFA to test whether there is a theoretical model underlying a set of observations Indicators for measuring the suitability of the model with data are Chi square (CMIN); Chi square adjusted according to degrees of freedom (CMIN/df); Comparative Fit Index (CFI); The Tucker - Lewis Index (TLI); and The Root Mean Square Error of Approximation (RMSEA) According to Hair Jr et al., if < CMIN/df 0.9, TLI > 0.9; RMSEA < 0.08, and p > 0.5, the model is suitable for the data 3.4 Step 4: Structural equation model (SEM) The Structural equation model (SEM) is the following step of the EFA and the CFA, helping to test a set of regression equations at the same time In this study, the SEM model was implemented with the aim to identify the influencing factors and the degree of influence of each factor on the development of logistics in Vietnams seafood industry Results and discussion 4.1 Factors found in the previous study This study uses the results of the previous study named “Building a model of the factors affecting logistics development in Vietnam's seafood industry by PEST analysis ” of the author in 2021, which built a model of the factors affecting logistics development in Vietnams seafood industry There are 31 variables of factors including: (1) Policy envừonment factors; (2) Market capacity factors; (3) Logistics human resources; (4) Information technology factors; (5) Infrastructures and equipment factors; (6) Integration factors; and (7) Future perspective of logistics in the seafood industry factors The variables used in this study are as follows: Table QUẢN TRỊ-QUẢN LÝ Table Variables used in this study Symbol MTCS1 Variable The impact o^the government's policy on trade development and goods circulation management on logistics development in the seafood industry MTCS2 There are many preferential policies for investment and market access for logistics in the seafood industry MTCS3 Transparency of state management policies on logistics in the seafood industry MTCS6 The impact of credit policies and interest rates on the development of logistics in the seafood industry MTCS7 During the operation, the local government always supports logistics businesses in the seafood industry DLTT1 Your business always has a relatively large minimum number of orders during its operation DLTT2 The market is increasingly expanding due to international economic integration DLTT3 Enterprises also provide logistics services directly to foreign markets DLTT4 Your businesses must always operate to the fullest capacity to meet the requirements of the market DLTT5 The logistics capacity of your business has met the market demand NNL1 Whether the employee's professional qualifications or skills meet the customers' needs NNL2 Employees always have a professional and enthusiastic professional working attitude NNL3 Employees always have the opportunities to participate in joint training programs between domestic and foreign enterprises NNL5 Your enterprises can always recruit good logistics managers easily NNL6 Service speed of employees is on time and meets requirements of customers NNL7 Employees are always capable of acquiring and applying machinery technology CNTT1 Your enterprises apply information technology well in logistics services in the seafood industry CNTT2 Customers can easily track the status of goods after sending via software CNTT3 With the support of information technology software, your work is solved more quickly and more effectively CNTT4 Investment promotion activities help businesses to approach customers more easily CNTT5 Enterprises information about customers who use logistics services is accurate and updated HTTB4 The system of the road connecting to the fish seaports has not been properly invested HTTB5 The port locations ar convenient for cargo transportation HTTB6 Planning ground for logistics development like logistics center, warehousing, etc HN1 The trend of using outsourced logistics services of seafood processing enterprises is increasing HN2 HN3 The development of foreign logistics enterprises affects the development of domestic logistics enterprises in the seafood industry The participation of Vietnam in international trade agreements and organizations has affected the development of logistics in the seafood industry PT4 Your business is regionally and internationally competitive PT5 Activities of providing logistics services in the seafood industry on a national scale have developed PT6 Logistics supplying services in the seafood industry will thrive Source: Authors analysisfrom survey results So 18 - Tháng 7/2021 257 TẠP CHÍ CƠNG THƯ0NG 4.2 Analysis 4.2.1 Exploratoryfactor analysis (EFA) In this step, the author took all 31 variables obtained through Cronbach's alpha coefficient test run the EFA analysis The process of EFA underwent a number of qualifying variables The author obtained: The results of table 10 show that 0.5 0.5 and the factor created after factor analysis are factors with 30 measurement variables The result of table 11 shows that Factor loading coefficient of observed variables is greater than 0.5 Therefore, 258 So 18-Tháng 7/2021 the observed variables of the factors affecting Vietnam’s logistics development in the seafood industry are coưelated with the whole The results of allocating the number of variables with the following factors: "Policy envừonment” factors have measurement variables: MTCS1, MTCS2, MTCS3, MTCS6, MTCS7; “Market capacity” factors have measurement variables: DLTT1, DLTT2, DLTT3, DLTT4, DLTT5; "Logistics human resources” factors have measurement variables are NNL1, NNL2, NNL3, NNL5, NNL6, and NNL7; “Information technology” factors have measurement variables: CNTT1, CNTT2, CNTT3, CNTT4, CNTT5; The "Infrastructures and equipment" factors have measurement variables: HTTB4, HTTB5, HTTB6; Integration factors have measurement variables: HN1, HN2, HN3; The "Future perspective of logistics in the seafood industry” factors have measurement variables: PT4, PT5, andPT6 4.2.2 Confirmatoryfactor analysis (CFA) From the analysis results of the EFA, there are main factors with 30 observed variables are used in this model The AMOS 22 structural equation modeling software is used to analyze factors The CFA is carried out with the hypothesis HO that surely the factors have a correlation relationship The CFA is the next step to test whether the above conceptual model is satisfactory The suitability of the entire model is in fact assessed through the following criteria of relevance: Using Chi-square (CMIN); Chi-square adjusted degrees of freedom (CMIN/df); Comparative Fit Index (CFI) Tucker & Lewis Index (TLI - Tucker & Lewis Index) RMSA (Root Mean Square Error Approximation) index The model is considered suitable for the actual conditions when the Chisquare test has a P-value > 0.05 If a model receives GFI values, the CFI > 0.9 (Bentler and Bonett, 1980); CMIN/df < 2, in some cases CMIN/df can be < 3; (Carmines and McIver); SRMR < 0.08, RMSEA < 0.05 are considered very good (James H Steiger); then the model is considered to be consistent with the actual data, or compatible with the actual conditions Tho and Trang (2008) suggest that if the model receives the QUẢN TRỊ - QUẢN LÝ Picture The CFA model after correction values of TLI, CFI > 0.9, CMIN/df, 2, RMSEA < 0.08, then the model is suitable (compatible) with the actual data Picture The CFA’s results show that the relevant indicators of the theoretical model have results as follows: GFI = 0.837; TLI = 0.918; CFI = 0.928; RMSEA = 0.054 Therefore, this model fits the real data It can be concluded that the measurement "The components development in Vietnam’s seafood with industry" independent factors achieve discriminant value (Nguyen Dinh Thoetal.,2003) 4.2.3 Structural model analysis (SEM) Structural Equation Modeling (SEM) is the next step of factor analysis, which helps to test a set of regression equations at the same time The SEM model clearly shows the relationship between latent variables and Source: Authors analysisfrom survey results measured variables It also provides The CFA’s results are tested by the AMOS relationships between predictive latent variables of according to the principle of adjusting the relations interest to researchers In this study, the SEM with MI > (MI - Modification Indicies, which is the model is implemented with the objective to adjustment coefficient corresponding to the change determine the influencing factors and the degree of of per degree of freedom) This adjustment must influence of each factor on the "Socio-economic ensure that it is appropriate on the theoretical basis development" of the people under the survey The and has practical significance After making the SEM model was analyzed starting from the original adjustment, the CFA’s results show that the fit proposed research model, then calibrated the indicators of the theoretical model are significantly model to have a better model Picture So 18 - Tháng 7/2021 259 TẠP CHÍ CƠNG THIÍ0NG Picture Results of model accreditation Chi-square=592.931; df=382; P=.000 39 ;Chi-square/df=1.552 ;GFI=.837; TLI=.918; CFI=.928 NHL ;RMSEA=.O54 ocnggi DLTF5 ,1 PTC M @17 PTC M ~ , J x^ PT4 rt - Ế1Ì SBii 17 CHHX.K CNTT Source: Authors analysisfrom survey results improved with the following figures: 4-2/df =1,115; GH = 0.837; TLI= 0.918; CFI = 0.928; RMSEA = 0.054 Therefore, this model fits the real data Moreover, the regression coefficients between the development of seafood logistics and the influencing factors are: (1) Policy envừonment factors; (2) Market capacity factors; (3) Logistics human resources; (4) Information technology factors; (5) Infrastructures and equipment factors; (6) Integration factors are all less than and different from statistically significantly Therefore, it can be concluded that the components measuring the logistics development in Vietnam’s seafood industry with independent factors achieve discriminant value (Nguyen Dinh Tho et al., 2003) 260 So 18-Tháng 7/2021 Hypothesis testing includes: • H01: Policy environment does not affect the logistics development in Vietnam’s seafood industry • Hl 1: Policy environment affects the logistics development in Vietnam’s seafood industry • The significance is 0.011 (< 0.05) rejecting the hypothesis H01, and accepting Hll The variable MTCS (policy envừonment) has an influence on the logistics development in Vietnam’s seafood industty and has a positive relationship (coefficient a5 = 0.196) • H02: Logistics human resources not affect the logistics development in Vietnam’s seafood industry QUẢN TRỊ-QUẢN LÝ • HI2: Logistics human resources affect the logistics development in Vietnam’s seafood industry The significance is 0.004 (< 0.05) rejecting hypothesis H02, and accepting Hl2 The variable NNL (human resources) has an influence on the logistics development in Vietnam’s seafood industry and has a positive relationship (coefficient a5 = 0,187) • H03: Market capacity does not affect the logistics development in Vietnam’s seafood industry • H13: Market capacity affects the logistics development in Vietnam’s seafood industry The significance is 0.001 (< 0.05) rejecting hypothesis H03, and accepting H13 The variable tourism (market capacity) has an effect on the logistics development in Vietnam’s seafood industry and has a positive relationship (coefficient a5 = 0,214) • H04: Information technology does not affect the logistics development in Vietnam’s seafood industry • Hl3: Information technology affects the logistics development in Vietnam’s seafood industry The significance is 0.040 (< 0.05) rejecting hypothesis H04, and accepting Hl4 The variable IT (information technology) has an influence on the logistics development in Vietnam’s seafood industry and has a positive relationship (coefficient a5 = 0,169) • H05: Infrastructure and equipment not affect the logistics development in Vietnam’s seafood industry • Hl5: Infrastructure and equipment impact the logistics development in Vietnam’s seafood industry The significance is 0.043 (< 0.05) rejecting hypothesis H05, and accepting Hl5 The variable HTTB (equipment infrastructure) has an influence on the development of seafood logistics and has a positive relationship (coefficient 0.5 = 0,182) • H06: Integration does not affect the logistics development in Vietnam’s seafood industry • Hl 6: Integration affects the logistics development in Vietnam’s seafood industry The significance is 0.000 (< 0.01) rejecting hypothesis H06, and accepting Hl6 The variable HN (integration) affects the logistics development in Vietnam’s seafood industry and has a positive relationship (coefficient a5 = 0,163) Conclusions Policy environment, market capacity, logistics human resources, information technology, infrastructure and equipment, integration, have the same impact on the logistics development in Vietnam’s seafood industry In other words, the development of the above factors will promote the logistics development in Vietnam’s seafood industry The biggest impact factor is the market capacity factor, the research results once again confirm the role of the market factor in the development of an industry in general and of the logistics development in Vietnam’s seafood industry in particular In order to have a good market, it is necessary to have seafood products that meet quality standards and meet the strict requirements of international customers At the same time, participating in trade agreements with the policies of international integration brought Vietnamese seafood the opportunity to penetrate into international markets In addition, it is necessary to have the most optimal infrastructure and warehouse connection plans, have policies to support loans, promote logistics in seafood businesses to purchase appropriate transportation and warehousing equipment etc in accordance with the characteristics of seafood products and international standard technical standards ■ REFERENCES: Barbara Garrity-Blake (2014) Keep it moving: North Caroline seafood transportation logistics with a focus on East to West routes Retrieved from: https://cefs.ncsu.edu/wp-content/uploads/keep-it-moving-nc-seafoodtransportation-logistics.pdf7x77888 Bender, p M and Bonett, D G (1980) Significance tests and goodness of fit in the analysis of covariance structures Psychological Bulletin, 88(3), 588-606 So 18 - Tháng 7/2021 261 TẠP CHÍ CƠNG THƯdNG Edward G Carmines and John p McIver (1983) An introduction to the analysis of models with unobserved variables Oxford Journals, 9(No 1), 51-102 James H Steiger (2010) Structural model evaluation and modification: an interval estimation approach Multivariate Behavioral Research, 25(2), 173-180 Joseph F Hair JR., William c Black, Barry J Babin et al (2018) Multivariate data analysis Boston, Massachusetts, United States: Cengage Nguyễn Đình Thọ (2003) Các thành phần lý thuyết khoa học tiêu chuẩn đánh giá Tạp chí Phát triển kinh tế, Năm thứ 13 (Tháng 4), 37-39 Nguyễn Đình Thọ (2013) Giáo trình Phương pháp nghiên cứu khoa học kinh doanh, Tái lần thứ hai Hà Nội: Nhà xuất Tài Per Engelseth, Irina V Karlsen, Shulin Huang et al (2017) The value aspect of reallocating seafood freight from road to sea ttansport Retrieved from: https ://www intechopen.com/chapters/55095 9.1A Soenandi, Y Juan, and M Budi (2017) Optimization for routing vehicles of seafood product transportation IOP Conference Series: Materials Science and Engineering, Indonesia Received date: June 15,2021 Reviewed date: July 5,2021 Accepted date: July 22,2021 Authors biology: MA DAO HONG VAN Lecturer, East Asia University of Technology PHÂN TÍCH CÁC NHÂN Tố ẢNH HƯỞNG ĐẾN PHÁT TRIỂN HOẠT ĐỘNG LOGISTICS CỦA NGÀNH HẢI SẢN VIỆT NAM BANG MƠ HÌNH SEM • Th.s ĐÀO HỒNG VÂN Giàng viên Trường Đại học Cơng nghệ Đơng Á TĨM TẮT: Nghiên cứu xây dựng mơ hình yếu tố ảnh hưởng đến phát triển hoạt động logistics ngành Hải sản Việt Nam thông qua phương pháp phân tích PEST (chính trị, kinh tế, xã hội cơng nghệ) Mơ hình phương trình cấu trúc (SEM) sử dụng để đánh giá, điều chỉnh đưa kết luận tác động yếu tố đến phát triển hoạt động logistics ngành Hải sản Việt Nam Nghiên cứu kỳ vọng cung cấp thơng tin hữu ích cho q trình hoạch định sách vĩ mơ định quản lý nhà hoạch định sách doanh nghiệp logistics Từkhoá: phát triển logistics, ngành Hải sản, mơ hình SEM 262 Số 18-Tháng 7/2021 ... Lecturer, East Asia University of Technology PHÂN TÍCH CÁC NHÂN Tố ẢNH HƯỞNG ĐẾN PHÁT TRIỂN HOẠT ĐỘNG LOGISTICS CỦA NGÀNH HẢI SẢN VIỆT NAM BANG MƠ HÌNH SEM • Th.s ĐÀO HỒNG VÂN Giàng viên Trường... mơ hình yếu tố ảnh hưởng đến phát triển hoạt động logistics ngành Hải sản Việt Nam thơng qua phương pháp phân tích PEST (chính trị, kinh tế, xã hội cơng nghệ) Mơ hình phương trình cấu trúc (SEM) ... chỉnh đưa kết luận tác động yếu tố đến phát triển hoạt động logistics ngành Hải sản Việt Nam Nghiên cứu kỳ vọng cung cấp thông tin hữu ích cho q trình hoạch định sách vĩ mô định quản lý nhà hoạch