The impact of service quality and Cost on logistics service Outsourcing by vietnamese Manufacturing enterprises

This paper pointed out that the decision to use the service from LSP is generally different from the decision of choosing the alternative providers as the carrier, shipping[r]

VIETNAM NATIONAL UNIVERSITY, HANOI VIETNAM JAPAN UNIVERSITY

NGUYEN THI HUONG GIANG

THE IMPACT OF SERVICE QUALITY AND COST ON LOGISTICS SERVICE

OUTSOURCING BY VIETNAMESE MANUFACTURING ENTERPRISES

MASTER'S THESIS

VIETNAM NATIONAL UNIVERSITY, HANOI VIETNAM JAPAN UNIVERSITY

NGUYEN THI HUONG GIANG

THE IMPACT OF SERVICE QUALITY AND COST ON LOGISTICS SERVICE

OUTSOURCING BY VIETNAMESE MANUFACTURING ENTERPRISES

MAJOR: BUSINESS ADMINISTRATION CODE: 8340101.1

RESEARCH SUPERVISORS: Prof YOSHIKI MATSUI Assoc Prof VU ANH DUNG

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TABLE OF CONTENT

CHAPTER 1: INTRODUCTION

1.1 Research motivation

1.2 Research objectives

1.3 Research scope

1.4 The structure of research

CHAPTER 2: LITERATURE REVIEW

2.1 Definition and theories

2.1.1 Manufacturing enterprise

2.1.2 Logistics services and Logistics service provider

2.1.3 Business Buyer Behavior

2.1.4 Process of business decisions making

2.2 Outsourcing logistics service performance dimensions

2.3 Outsourcing logistics service process 11

2.4 Link the studies with reality in large scale Vietnamese manufacturing enterprise 18

2.5 Outcomes of outsourcing logistics service performance 18

2.6 Conceptual model and research hypotheses 19

2.7 Research model 23

CHAPTER 3: RESEARCH METHODOLOGY 24

3.1 Research scope 24

3.2 Measurement scale 24

3.3 Questionnaire design 27

3.3.1 Demographic information 27

3.3.2 Questionnaire 28

3.4 Sampling method 28

3.5 Sample size 29

3.6 Data analysis procedure 29

3.6.1 Testing reliability – Validity of scale measurement 29

3.6.2 Exploratory Factor Analysis (EFA) 30

3.6.3 Regression analysis 31

CHAPTER DATA ANALYSIS 32

4.1 Data collection and demographic results 32

4.2 Reliability test 33

4.3 Exploratory Factor Analysis (EFA) 35

4.3.1 Independent variable factor analysis 35

4.3.2 Dependent variable factor analysis 36

4.4 Analyzing the influence of demographic factors on Intention to continue using the same LSP 36

4.5 Correlation coefficient and linear regression analysis 42

4.5.1 Correlations Analysis 45

4.5.2 Regression analysis 45

4.5.3 Searching violation of regression assumptions 47

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5.1 Result discussion 49

5.2 Contributions 53

5.3 Managerial implications 54

5.4 Limitations 55

APPENDIXES 69

Appendix Survey form in English 69

Appendix Survey form in Vietnamese 76

Appendix Result of frequencies test 83

Appendix Result of reliability test 86

Appendix Result of factor analysis 93

Appendix Result of correlations and regression test 97

III

LIST OF TABLES

Table 2.1: SERVQUAL dimensions (Parasuraman et al., 1988) 20

Table 3.1: Measurement scale 24

Table 4.1: Manufacturing sectors .40

Table 4.2: Correlation matrix between variables 45

Table 4.3: Evaluation of the suitability of the model 46

IV

LIST OF FIGURES

Figure 2.1: Business Buyer Behavior model (Philip Kotler, 1980)

Figure 2.2: The business decision-making process (Philip Kotler, 1980)

Figure 2.3: Conceptual model 23

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ACKNOWLEDGEMENT

During the period of thesis writing, I received plenty of enthusiastic help and support that guide and encourage me to overcome all difficulties and finish this hard but meaningful time

I would like to express the warmest thanks to Prof Yoshiki Matsui and Assoc.Prof Vu Anh Dung who gave me useful advice that helps me to finish my thesis successfully Their advice gave me professional guidance and insightful comments that considerably help me gain a lot of experience in improving my skills in synthesizing the literature, data analysis Especially, I would like to express my endless thanks and gratefulness to my respectful teacher Prof Yoshiki Matsui His devoutness inspired me to complete this dissertation Without his motivation and instructions, the thesis would have been impossible to be done effectively

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CHAPTER 1: INTRODUCTION

1.1 Research motivation

In recent years, outsourcing has become a key element in the success of organizations and can no longer be overlooked in recent years (Tomas, 2010) The businesses have been involved in how they can use their competitive advantage to boost their sales and income since the Industrial Revolution (Handfield, 2006) Companies have tried to boost efficiency by outsourcing tasks that are not considered a core business competency Outsourcing a variety of resources, spanning from sanitation, distribution, and compound management among others, has been an influential factor in global pattern outsourcing services, but there are several concerns how often outsourcing results in a successful outcome and the circumstances that enable it While several businesses outsource to save costs, they frequently struggle to so and can even increase costs unless properly managed (Meixell and Norbis, 2008) Outsourcing management plays an important role in revolutionizing enhanced efficiency in businesses (Juettner et al., 2003) Organizations have been repetitively reviewing a variety of cost-cutting strategies while also enhancing their operating efficiency At the industry's foremost hand, there is often a trend to redefine core businesses away from certain conventional roles (Agrell et al, 2004) The strong growth of the service providers contributes to changes in the power structure, and the market sense and clock speed among the market participants This guiding force contributed to a large consolidation of core competences and to the outsourcing of certain roles in an attempt to achieve multiple performances and effective service delivery

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decisions can lead to rising cost, failure operation, disrupted services, and even entire business failure In an organization, a full understanding of a corporate strategy, core competencies, potential risks, and total costs, as well as a thorough justification of possible outsourcing arrangements for meeting business objectives were required to have efficient and effective outsourcing decision making (Sanders et al., 2007, McIvor et al., 2009)

One of the most concerning outsourcing service in the companies is logistics Logistics play a greatly important role in businesses especially in manufacturing enterprises According to Russell and Taylor, 2003, transportation costs account for about 20 percent of total production costs in manufacturing enterprises A survey was conducted by Pedersen and Gray (1998) showed that on average 50 percent of the total logistics cost could be attributed to transportation Transportation is not only an incurred cost, but also can be instrumental in achieving competitive advantage as distribution (Reimann, 1989) The performance of the logistics service provider may affect the efficiency of the total logistics function of an enterprise It follows that an appropriate logistics service provider (LSP) choosing process is important to the firm’s success As the global market develops with technological advances, especially the opening of markets in developing and underdeveloped countries, logistics is considered by managers as a tool, a means to connect the fields Due to the importance of logistics, using logistics service outsourcing at manufacturing enterprises is always carefully considered by managers LSPs must adapt themselves and provide more value-added in order to respond effectively to meet the ever-changing need of customers’ logistics requirements

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meaningful work, so that the author can find out the important factors that influence the decision of the manufacturing company to LSPs, from which the author put forward research hypotheses to conduct testing with the Vietnamese data

With the current status of the Vietnam economy that most manufacturing enterprises are foreign-invested enterprises The Selection criteria for LSP sometimes based on the decision of the headquarters outside Vietnam Is there any difference between the actual situation of Vietnam and other countries around the world? The next chapters will explain it carefully

1.2 Research objectives

The research objectives of this study are two-fold One objective is for manufacturers, another is for logistics service providers

- Manufacturing Enterprise: this study identifies how the service quality and

cost impact on logistics service outsourcing by Vietnamese manufacturing enterprises

- Logistics Service provider: Logistics service providers can sort information

and services that are considered as significantly important to the customers who are manufacturing enterprises from the knowledge of the key decision factors of the customers

1.3 Research scope

Because of limitations in terms of survey scale, only large-scale manufacturing enterprises that have more than 200 employees who are insured and have a total annual revenue of over VND 200 billion or have a total capital of over VND 100 billion are researched

1.4 The structure of research

 Chapter 1: Introduction

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 Chapter 2: Literature review

This chapter will firstly introduce the relevant definitions Next is a summary of related studies from which the research questions, hypotheses and initial research models will be developed

 Chapter 3: Research methodology

This chapter discusses the research design, the method used, and the data collection procedure

 Chapter 4: Data analysis

This chapter describes the analysis of the data collected and interpreted and then verifies the hypothesizes in Chapter

 Chapter 5: Results and discussions

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CHAPTER 2: LITERATURE REVIEW

2.1 Definition and theories

2.1.1 Manufacturing enterprise

According to the definition of the North American industry classification system that the manufacturing sector includes the establishment engaged using resources in combination with the application of science and technology to produce commodities to meet market demands Manufacturing enterprises are generally characterized as factories, plants, or mills and commonly use power-driven machines and materials-handling equipment

Each country has their own criteria to determine the scale of the business In Vietnam, there has not been any official decree on large-scale enterprises, but small and medium-sized enterprises definitions are stipulated in decree No 39/2018/ ND-CP dated March 11, 2018, of the Vietnam government In which:

Microenterprises in the industrial manufacturing sector have the average number of employees that have insured not exceeding 10 people per year and the total revenue does not exceed billion VND or the total capital source does not exceed billion VND

Small-sized enterprise's industrial manufacturing sector has an average number of employees that have insured no more than 100 people and the total revenue of the year does not exceed VND 50 billion or the total capital source is not over VND 20 billion

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an annual turnover of over VND 200 billion or total capital of over VND 100 billion for making selection criteria

2.1.2 Logistics services and Logistics service provider

FIATA, 2004 defined “logistics services” is kind of services relating to the carriage (carry out by multimodal transport means or single-mode), in relation to consolidating, transporting, managed, packaging, or distributing of goods or supplementary and consulting services, including but not limited to customs and fiscal matters, officially declared the goods, Provision of goods insurance and processing or acquisition of payment or goods documentations

The logistics service providers (LSP) provide logistic services to their customers Vietnamese LSPs have been supporting the local enterprises for more than 30 years, especially the manufacturing enterprise since they perform as trade facilitators such as in handling import-export shipments, connect the customs and import-exporters, negotiate with the shipping lines, or other transportation services, and finally coordinate with all related parties

2.1.3 Business Buyer Behavior

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Figure 2.1: Business Buyer Behavior model (Philip Kotler, 1980)

The buying behavior model of business shows that marketing and other factors influence the organization and create buyer responses These marketing factors include 4P (product, price, place, and promotion), other factors include important environmental forces of the organization, such as economy, technology, politics, and culture All of these factors influence the business and create its responses, such as goods or service selection, supplier selection, order quantity, delivery time and payment terms In order to design effective marketing modalities, marketers must find out what happens inside the organization in turning the stimulus into the buying organization's response Based on this model, we will examine the various factors of institutional customer buying behavior

2.1.4 Process of business decisions making

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Figure 2.2: The business decision-making process (Philip Kotler, 1980)

The process of LSP selection by large manufacturing enterprises is a series of thinking, evaluation and selection decisions (Plomaritou et al., 2011), but also includes behavioral modeling steps by Philip Kotler, specifically including the following basic stages:

Problem recognition: identify the need to use LSP(s), logistics services when a sales contract is signed and the goods need to be shipped to the destination specified by the buyer

General need description: the service buyer determines the feature and quantity of the goods to be handled

Product specification: based on the characteristics and quantity of goods required to handle the service buyer will search for all relevant information about shipping services, import, and export customs procedures in accordance with the requirements of the goods The customers can get this information based on their own experience or can be found in maritime magazines, on the internet, or through recommendations from colleagues

Supplier search: based on the characteristics of the need to use, the service buyer tries to find the most suitable vendors

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Supplier selection: the service buyer assesses the proposals After the assessment, the Service buyer decided to choose the most optimal plan as the LSP meet the most evaluation criteria, proceeding to sign a service provision contract with freight forwarders However, there are also cases where buying decisions are made by habit, which does not require any evaluation (repeat purchases or loyal purchases regardless of other information)

Order-routine specification: the service buyer gives the order to the chosen LSP(s), listing the technical specifications of the cargo, quantity, expected delivery time, and warranties

Performance review: performance of the LSP(s) is assessed and decided to continue, modify, or drop the arrangement by the service buyer

2.2 Outsourcing logistics service performance dimensions

Outsourcing logistics service performance was supported by the service quality dimensions originally defined by Parasuraman et al in 1985 and 1988 The research identified five specific dimensions of service quality: reliability (the ability to carry out reliably and accurately the advertised service); responsiveness (able to provide timely service to customers); assurance (understanding and courtesy employee, and the capacity to express faith and confidence); empathy (providing attention, individualized customer experience); and tangibles (physical facilities, equipment, resources, and communications materials) These dimensions were characterized in a measurement scale named SERVQUAL, which measured the quality of service as the difference between the quality requirements of pre-transaction customers and their expectations of service quality after being used

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Empirical data shows that the current delineation of five elements is contradictory as measured in various forms of service industries (Cronin and Taylor (1992); Babakus and Boller (1992); Carman (1990); and Finn and Lamb (1991) In fact, researchers have had difficulties simulating SERVQUAL dimensions in the context of services (Bienstock et al (1997)) One potential reason for the inconsistent findings is that the measurements of service quality differ from one sector to another It is particularly relevant for industrial services such as logistics, which rely on concrete activities directed at actual items and intangible behavior directed at thoughts and attitudes (Lovelock, 1983) Brown et al (1993) therefore encourage researchers carefully determine the important problems for the service quality in the different contexts and change the SERVQUAL scale accordingly Another logical reason is that a more general conceptual framework has not been defined yet

Stank et al (1999) used SERVQUAL measurements for creating a more generalized conceptualization of outsourcing logistics service performance, a specific illustration of a service sector They conceptualized two main aspects of logistic outsourcing: operational performance and relational performance Operational performance comprises of two main factors: reliability (which captured the reliability and accuracy of the service provider (Parasuraman et al., 1985) referred to the quality consistency factor of operational performance) and price The responsiveness, assurance, and empathy attributes of Parasuraman et al were included in the relational performance, the second dimension of service performance in their research

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Krajewski et al (1987); Hill (1989); Wood et al (1990); Cleveland et al (1989); Roth et al (1990); Ferdows et al (1990)) Further evidence for this approach is offered by Porter's generic strategies scheme, in which cost leadership (as opposed to the quality distinction) tends to be a straightforward, but feasible, the road to competitive advantage (Porter 1980; 1985)

2.3 Outsourcing logistics service process

Some researchers have studied the processes of outsourcing and how it flows in organizations that outsource logistics service Zoran et al (2007) concluded that although many studies were conducted about the outsourcing process issues, there are only a few frameworks that represent the actual stages and structure of the entire outsourcing process The study describe the main stages as: preparation, vendor(s) choosing, transition, managing relationship and reconsideration

The questions such as how, where, why, when, whether or not, among others were answered in the preparation phase The issues of whom to pick and not to pick from an identified and qualifying pool of potential service providers were addressed in the vendor selection stage The next stage discusses the transition stage of manage relationship issues in the approved service providers The outcome of the entire process was examined in the final stage

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researchers have developed research frameworks that organize selection criteria into a hierarchical structure (Hwang and Shen, 2015) Apart from the importance of the above criteria, this study focuses on their relationship elements on organizational strategy The majority of published research has focused on their operational aspects thus ignoring the strategic importance of outsourcing as well as the significance of a collaborative partnership to deliver competitive outcomes Landry (2011) believes that setting the goal is not the primary task, achieving the identified goals, and staying with the plan that matters Thus, achieving identified objectives is critical and aligning them with choosing logistics service provider is paramount It is believed that outsourcing relationships fail due to service provider promises to meet organizational strategic goals that have not been fully defined, communicated, and understood in the form of strategy (Lynch, 2004)

The LSP research classification framework proposed by Selviaridis and Spring (2007) is based on a comprehensive review of literature that focuses on peer-reviewed journal papers published during the period 1990 to 2005 A total of 114 academic sources were retrieved and analyzed This paper pointed out that the decision to use the service from LSP is generally different from the decision of choosing the alternative providers as the carrier, shipping lines, logistics service providers, etc but the criteria used to evaluate alternative providers are similar –cost, service quality, reliability, flexibility, and responsiveness

The selection process of the appropriate international containership carrier is dependent upon a variety of service quality attributes (Kent & Parker, 1998) 18 factors that affect the international containership carrier selection were used, and the results indicated that the factors that influence the international containership carriers choosing are different among the three groups: exporter; importer; and containerized transportation companies

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academic research on this topic, and the research concepts developed were still in its infancy Brooks identified 15 factors that influence carrier selection, of which freight rate is assessed by customers as the most important, followed by the frequency of trains departing during the week and reputation and transit time

Kokkinis, G et al (2006) argued that LSP consider that their customers’ main requirements are reliability on delivery time and information accuracy, together with personal treatment followed by the safety of transport, all related to the quality of service Low prices are an important criterion but less important than the main criteria of quality In a while, Swathy, S (2016) highlighted that the customers always look forward the LSPs have warehouse, good infrastructure, material handling, packaging, customs clearance, and documentation

Pedersen and Gray (1998) carried out a study on shipping line selection criteria of Norwegian exporters, according to which the criteria are divided into four main groups:

- Group of price factors: low freight rates, discount programs, the relationship between actual cost and estimated cost

- Group of time factors: short transit time, reliability of delivery time, many trains departing during the week

- Group of factors of safety: low loss and damage of goods, the ability to coordinate goods in transshipment ports, control delivery time, knowledge about wharves

- Group of service factors: cooperation with shipping lines, the ability to meet the transport of special shipments, ready to meet the urgent delivery

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domestic competition Second, Norway's main exports are raw materials, which are price sensitive This has led to a group of price factors being considered the most important when exporters choose shipping lines

In the Turkish market, Kofteci et al (2010) conducted a survey of cement trading enterprises on the choice of transportation method with four main factors: transportation cost, shipping time, reliability of transport time and safety of goods The results also show that "reliability" is considered to be the most important factor when customers choose the mode of transportation, and the factor "transportation cost" is equally important as "reliability" Meanwhile, customers not care much about "Safety" (the level of goods lost) due to the nature of the cargo being cement

Research by Tuna (2002) in Turkey shows that freight rates are not an important factor when customers choose this market carrier, while the factors of service value are important customers concerning The study was conducted with 24 observed variables, and the group of factors of "reliability and competitiveness" was rated as the most important when choosing a shipping line, including variables: respond to complaints of customers quickly, delivery on time agreed, meet requirements quickly, send accurate quotes, issue documents accurately and quickly, no goods damaged on delivery In which the criteria "respond quickly to complaints" is the first choice from customers Besides, the topic also mentioned the influence of many other factors when choosing shipping lines such as "support activities", "Value-added services", "Transport equipment"

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schedule, the ability to receive goods and response to complaints quickly This difference requires transportation service providers to consider and change business strategies to suit the needs of customers, because from the marketing point of view, "sell what customers need, not sell what you have available.”

Premeaux (2007) also investigates the difference between shippers and shipping lines when assessing the importance of shipping service selection criteria in the US market With 36 evaluation criteria, there are nine different criteria, of which five criteria are evaluated by customers more important and the remaining four criteria are more appreciated by shipping lines While customers pay much attention to the carrier's response factors to emergencies or unexpected situations, electronic data, flexible rates, the information provided to customers, translation in case of searching information via the internet The shipping line highly appreciates the reputation factors of the shipping line, the cooperation between shipping lines and customers, the knowledge of sales staff about customer needs and the results of shipping carrier's past operations When there are differences in the selection criteria, there is a gap in the level of satisfaction between the service provided by the carrier and the customer's expectations for that service (Wong, 2007)

Wong, P C C (2007) conducted research in the southern provinces of China on the factors affecting the mean of transportation and carrier selection This doctoral thesis of Wong was conducted for years from 2002 to 2007 Analytical data was collected through the survey questionnaire with 82 questions and the number of samples size up to 1100 After analyzing the EFA factor to eliminate nonconforming variables and grouping the variables into common factor groups, Wong used the AHP (Analytical Hierarchy Process) pair method to identify the influential factors The EFA analysis results identify seven groups of factors as follows:

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- Service response: availability of transport equipment, shipment information, service reliability, and low freight

- Customer service: the quality of service provided by the staff, the service provided at the loading port, the service quality of the customs declaration unit, past information on customer satisfaction, etc

- The ability to transport goods: including freight services, transport equipment - Location of the goods to be transported

- The reputation of the customer: this factor shows the reputation of the customer from the perspective of the customs office, such as whether the business is reliable or not, whether or not its goods are regularly inspected, etc

- Relationship with customs

The results of the AHP analysis show that for time-sensitive items, customers prefer to choose the mode of transport by truck As for the mode of transportation by barges, the factor of the frequency of departures during the week is of primary concern to customers Finally, heavy or bulk cargoes are more often transported by rail

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Another study conducted in Taiwan, Wen, C L and Gin, S L (2011) is related to the topic of this thesis From the reference of previous studies, Wen and Gin selected 22 observation variables that affect the choice of shipping lines to be included in the survey After analyzing the factors, these 22 variables were grouped into four groups of factors, namely: operational convenience, service completion, good cargo performance, and freight Next, FZOT (Fuzzy Zone of Tolerance) is used to assess the importance of these factors The results show that there are six criteria that customers consider to be the most important, including containers provided in good condition, on-time delivery, sales staff with good knowledge, and quick response to complaints, electronic data and tracking service over the internet This requires shipping businesses to pay attention to improve the quality of service to meet the needs and maintain customer satisfaction

Most recently, Rotaris et al (2012) conducted a survey of small and medium-sized manufacturing enterprises in Italy to assess the impact of transport cost factors, transit time, potential loss of cargo, and punctuality in choosing shipping lines The results show that these factors are important because they affect logistics costs and profitability of the business

The process of selecting LSP is a relatively complex process involving many parties interacting with one another to make decisions based on attitudes, perceptions, and information gathering and analysis (Barthel et al., 2010) Participants include the shipper, the consignee, the carrier, the logistics/forwarder service provider, and other intermediaries if any

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2.4 Link the studies with reality in large scale Vietnamese manufacturing enterprise

Vietnam's economy currently has been integrated period and the wave of foreign investment has been strongly entered Along with the strong development of manufacturing industries, LSPs also mushroomed which made the supply of logistics service saturated Businesses wishing to use outsourcing logistics service have more choices, making the criteria for choosing LSPs are stricter and stricter In realistics, a large-scale manufacturing business cannot use only one LSPs due to the financial limitations of the LSPs Besides, they are also using multiple LSPs at the same time to take advantage of the LSPs, it is a strategy that is fully utilized by manufacturing enterprises How are manufacturing enterprises choosing logistics service providers? In the scope of this article, the author will answer two questions:

- How are service quality and cost impacting on the selection of LSPs by

Vietnamese manufacturing enterprises?

- How are the logistics service providers adapting themselves to the demand of

the customers who are manufacturing enterprises?

2.5 Outcomes of outsourcing logistics service performance

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al (1995); Crosby et al (1990); and Reichheld et al (1990))

A large number of studies strongly support the idea that improving the quality of logistics services will enhance customer satisfaction (Innis and LaLonde (1994); Daugherty, Stank, and Ellinger (1998); and Leuthesser and Kohli (1995) Logistics service operational elements associated with product availability, product condition, delivery dependability and timely delivery as well as related elements such as communication and responsiveness have been demonstrated to have a positive impact on customer satisfaction (Innis and LaLonde 1994; Daugherty, Stank, and Ellinger 1998; and Stank, Goldsby, and Vickery 1999) In terms of loyalty and positive word of mouth, Parasuraman, Zeithaml , and Berry (1994) investigated the impacts of each service quality dimension on overall service satisfaction and behavioral intentions Primary data from 656 senior final year undergraduate students at one public university were collected based on a quantitative correlational design The findings indicate that the dimensions of service quality performance (tangibility, reliability, responsiveness, empathy, and assurance) are each significantly related to the overall satisfaction of customers, which in turn affects behavioral intentions

2.6 Conceptual model and research hypotheses

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performance Hence, instead of measuring both expectation and perception of service, only perception of service is evaluated However, SERVPERF is only recognized as a transformation of SERVQUAL because it applies the same scale and dimensions In reality, both SERVQUAL and SERVPERF are the most popular service quality model in logistics industry (Gulc, 2017)

Table 2.1: SERVQUAL dimensions (Parasuraman et al., 1988)

Some researchers considered the SERVQUAL dimensions in the service quality approach can also be used in determining the critical factors that may affect the purchasing logistics service decision (Kong & Mayo (1993); Bienstock, et al (1997))

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questioning; and approach, accuracy, support and price for the policy-capturing approach This study largely addressed the best approach for developing an instrument for measuring customer requirements and the associated measurement of logistics service quality, the selection of criteria is helpful in developing a picture of traditional attributes for use in carrier selection This paper included equipment as a service attribute, and as a result does address the capacity dimension

Based on the above discussion, the author concludes the hypothesis:

H1: Service quality of a logistics service provider has a positive impact on the intention to continue using the same logistics service provider

The LSP research classification framework proposed by Selviaridis and Spring (2007) is based on a comprehensive review of literature that focuses on peer-reviewed journal papers published during the period 1990 to 2005 A total of 114 academic sources were retrieved and analyzed This paper pointed out that the decision to use the service from LSP is generally different from the decision of choosing the alternative providers as the carrier, shipping lines, logistics service providers, etc but the some criteria including cost factor used to evaluate alternative providers are similar

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requirements such as punctual delivery, degree of control damage, etc., most selection decisions are made based on freight rates

Based on the above discussion, the aurthor concludes the hypothesis:

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2.7 Research model

Based on the above discussion, the author concludes the research model as the following:

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CHAPTER 3: RESEARCH METHODOLOGY

3.1 Research scope

The research scope (or target of data collection) of this survey is all manufacturing companies in Vietnam that meet the following characteristics:

- Having a manufacturing factory operating in Vietnam, meeting the conditions that the number of employees who participate in insurance is over 200 and the total annual turnover is over VND 200 billion or the total capital is over VND 100 billion

- Frequently use outsourced freight forwarding service (forwarder, shipping line, garage, etc.)

3.2 Measurement scale

Hair et al (2006b) recommends that literature can be applied to 25 to establish the development of the instrument, if the literature has provided a reliable sufficient study on the related research topic The application of the measurements scale supported by previous literature may be accepted as the valid scale (Hair, et al., 2006b) The table illustrates the development of the scale applied in this current study

Based on the previous researches, 36 question items were synthesized The author has developed customized items that fit the actual service context and processes:

Table 3.1: Measurement scale

Variables Coding Items

Tangibility (T)

T1 LSP X offers customers e-tracking shipment and electronic data transmission EDI

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T4 LSP X has a lot of offices that can handle our shipments in many different locations

T5 LSP X has sufficient infrastructure to handle a consignment of goods to be transported

Reliability (RL)

RL1 LSP X delivers on time

RL2 When a complaint or problem arises, the LSP X usually solves quickly

RL3 LSP X has the ability to control shipments very well in the transportation process

RL4 LSP X always issues correct documents with information we provide

RL5 I feel secure when using services from LSP X

Responsiveness (RS)

RS1 LSP X can afford to provide many services to our company

RS2 LSP X can handle the specify goods

RS3 LSP X has a shorter total transit time than other forwarders for our shipment

RS4 LSP X has an extensive worldwide agent network RS5 LSP X has the ability to consolidate cargoes RS6 LSP X frequently updates rates for us

26 Assurance (A)

A1 LSP X is a well-known name in its industry

A2 LSP X has a better reputation than other forwarders in its industry

A3 During transport, LSP X is less likely to cause damage or loss of goods

A4 LSP X always update information in the shipments handling process for us

A5 We are always consulted on laws and rules promptly from LSP X

A6 Goods are guaranteed when using services from LSP X

Empathy (E)

E1 We often receive gifts from LSP X on holidays E2 In previous collaborations with my company, LSP X

served very well

E3 Leaders of our company have close relationship with LSP X

E4 Forwarder X's sales staff regularly contacts us E5 We feel empathy from the staff of LSP X

Cost reduction (C)

C1 LSP X has a lower total cost than other forwarders for our shipments

C2 LSP X has a better credit term than other forwarders for our company

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C4 We save more money when using LSP X

Intention to continue (I)

I1A I will propose to stop using LSP X as soon as possible I1B I will propose to continue using LSP X as long as

possible

I2A I will propose to outsource more activities to LSP X in the future

I2B I will propose to outsource more activities to other logistic service providers instead of LSP X in the future

The 5-point likert scale was used to measure the extent of each measurement scale in this study

3.3 Questionnaire design

3.3.1 Demographic information

- The question of identifying the target respondents including:

 Field: 24 manufacturing field are specified (Food products, Beverages, Textiles, etc)

 Amount of employees: there are more than 200 employees who are insured?  Annual revenue: Is the total annual revenue of over VND 200 billion?  Total capital: Is the total capital of over VND 100 billion?

 Interaction with LSP: Do the respondents interact with Logistics service providers?

- Respondent’s infographic information including:

28  Gender: Male/ female

 Age: 24 years old or less /from 25 to 29/from 30 to 34/from 35 to 39/from 40 to 44 /from 45 to 49/ from 50 to 54/55 years old or more

 Working time: Less than year/ From to less than years/ From to less than years/ years or more

 Interaction frequency with LSP: Weekly/ Monthly/ Quarterly/Yearly/ Others

3.3.2 Questionnaire

The survey was conducted including 46 questions:

Google form was used for designing the questionnaire which is a popular online survey tool in Vietnam The questions relating to the research was arranged randomly to avoid the bias when the respondent answered Three sections (identify target respondents, demographic questions, the main question was pressed separately in pages to reduce the feeling that the survey was long when it was first seen and to increase the patience of the respondents The questionnaire is designed with a simple, clear and unbiased wording to help each person respond without confusion The questionnaire was designed in English and then translated into Vietnamese for Vietnamese respondents The translation version is based on a reference to people who are fluent in either English or Vietnamese, as well as a deep understanding of Vietnamese thinking and reading culture

3.4 Sampling method

Random sampling methods are used to conduct research on this topic The reason for choosing this sampling method is because respondents are easily accessible, they are willing to answer the research questionnaire as well as less time-consuming

29 Google Form service

3.5 Sample size

The reliability of the information will depend on the sample size selected The larger sample leads to the greater the accuracy of the research results, but the larger the sample size needs more time, resources and cost are increased Conversely, if the sample size is small, it is beneficial in terms of cost and time, but the information is poorly reliable

The choice of sample size, which is large enough to ensure processing reliability, is currently not clearly defined Moreover, the sample size depends on the estimation method used in the particular study

According to experience, there is a researcher who thinks that the minimum sample size must be from 100 to 150 There is also a researcher who thinks that the critical sample size must be 200 There are also researchers who believe that the minimum sample size is samples for a parameter to be estimated (Bollen, 1989)

In this research topic, the author chooses a sample of size 80 + 5n (Tabachnick and Fidell, 1996) with n = 30 (number of observed variables) Therefore, the sample size is expected to be 230 people

3.6 Data analysis procedure

The data collected was processed on the basis of SPSS 20 application

3.6.1 Testing reliability – Validity of scale measurement

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correlation among items is also an important indicator (Nunnally & Bernstein, 1994) This value indicates the correlation between one item and the other in the same measurement scale The accepted level is more than 0.3 for the item-total correlation, and if it is less than 0.3, this item will be deleted

3.6.2 Exploratory Factor Analysis (EFA)

EFA is used to investigate which factors influence the variables and to gather the analytical variables (DeCoster, 1998) EFA is a method for identifying factors for analyzing data input, which is intended to shorten the list of common factors that will appear in the correlations (McDonald, 1985) EFA is a method to reduce the number of variables into smaller variables while maintaining significance in the original list (Hair et al., 2006b) EFA helps to conduct a study consisting of some to hundred observed variables that can be grouped into smaller number of variables to achieve and clarify the hidden concept (Rummel, 1970) To carry out EFA, there are certain requirements:

- The sample size should be 300 at least and each variable to explore the latent

element should have between and 10 items observed (Comrey & Lee, 1992) The greater number of samples size will reduce the error in the collected data to a minimum However, the researcher usually relies on the previous measurement and literature and is generally acceptable for validity of the measurement scale

- Furthermore, if the data contains the high loading factor score (> 0.8),

Guadagnoli & Velicer (1988) discussed that 150 observation may be appropriate for the creation of a valuable research

- Hair et al (2006b) proposed that the sample size minimum should be more

than 50 and that 100 should be better

- Factor loading > 0.5 can be accepted

- Sample adequacy Kaiser – Meyer – Olkin (KMO) exceeds 0.5 It means that

there is strong correlation among variables where the KMO is less than 0.5

- Bartlett sphericity test, significant p<0.05 level to make sure that the relations

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3.6.3 Regression analysis

Regression analysis is a tool for predicting the results of one dependent variable based on one or more separate variables' interaction The most common type of regression analysis is linear regression, which shows an almost relation between dependent and independent variables based on the data collected

The regression model's function is usually represented:

Y: Dependent variable X: Predictor variables

𝛽1: The co-efficient vector of predict or variables 𝛽𝑜: Intercept

e: Error term

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CHAPTER DATA ANALYSIS

4.1 Data collection and demographic results

The writer start to conduct the survey from April 10, 2020 to May 05, 2020, 339 responses were recorded by Google form However, after removing inappropriate responses with the same points for all the questions or not to be the target objective, there are only 318 valid responses left This sample size (n = 318) corresponds to the expected sample size set in Chapter 3, section 3.2

Among respondents, 249 people are female and only 69 people are male It means that over three fourth of respondents are female The women are certainly interact with LSP more than the men

The group from 25 to 29 years old accounts for the most with 137 people (43.1%), the next group is from 30 to 34 years old with 84 people (26.4%), followed by the group under 24 years old with 40 people (12.5%), the group from 40 to 44 years of age only 20 people (6.3%) (Appendix 3)

Out of the 318 survey participants, only 45 respondents have a working time at the current enterprise of less than year, accounting for 14.2% These could be fresh graduates or new positions at the current company The highest proportion of 49.1% is the respondents who have working time from 1-3 years 23.3% is the proportion of people with 3-5 years of working time, and finally, those who have worked more than years accounted for 0.9% (Appendix 3)

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The majority of respondents often interact with LSPs weekly or monthly Only a few respondents interact with LSPs quarterly or yearly (Appendix 3)

Among 318 responses, 49 answers were from the Wearing apparel industry, accounting for the highest percentage of all responses, 15.4% Ranked second is Computer, electronic and optical products with 44 answers, accounting for 13.8% Textiles and Electrical equipment received 33 responses, accounting for 10.4% Next is the paper products group with 30 answers, accounting for 9.4% Fabricated metal products, except machinery and equipment 8.8%, Machinery and equipment 7.5%, Chemicals and chemical products 6.6%, Rubber and plastics products 6.3%, Printing and reproduction of recorded media 5.7%, Other transport equipment 2.8%, Furniture 1.6%, Other manufacturing 0.6%, Wood and cork products except for furniture; articles of straw and plaiting materials 0.6% (Appendix 3)

The group often using outsourcing logistics service is the Wearing apparel industry, fiber, electronics, Computer, electronic and optical products This is consistent with the situation of foreign investment in Vietnam when most foreign-invested enterprises are these industries Moreover, with the characteristics of foreign businesses often importing and exporting, the frequent using LSP's services is inevitable

4.2 Reliability test

Cronbach’s alpha value is used to test the reliability of the scale and eliminate variables (if any) The variables and observed item are considered appropriately will be used in the next step

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Reliability analysis of Tangibility (T) According to the testing results, the scale of

responsible behavior has good reliability with Cronbach’s α equal 0.660 But observed variable T1 and T5 has corrected item-total correlation less than 0.03, It could lead to considerable increase of Cronbach’s α if deleting T1 and T5 Therefore, reliability is re-tested (Appendix 4)

After removing T1 and T5, we have the result of Cronbach’s α equal 0.841, the scale tangibility has good reliability with three observed variable T2, T3, T4

Reliability analysis of Reliability (RL): The reliability factor has a Cronbach's alpha

coefficient of 0.730, which is eligible to be kept as a variable, but recognizing that the observed variable RL1 if removed will make Cronbach's coefficient alpha increase Cronbach's α from 0.730 to 0.849 (Appendix 4)

Reliability analysis of Responsiveness (RS): According to the realiability testing

results, the scale of Responsiveness has good reliability with Cronbach’s α equal 0.774 However, observed variable RS3 and RS6 has corrected item-total correlation less then 0.03, It could lead to considerable increase of Cronbach’s α if deleting RS3 and RS6 Therefore, reliability is re-tested, Cronbach's α increase Cronbach's α from 0.774 to 0.867 (Appendix 4)

Reliability analysis of Assurance (A): Assurance factor has good reliability with

Cronbach’s α equal 0.817 and But observed variable A1 has corrected item-total correlation less then 0.03, It could lead to considerable increase of Cronbach’s α if deleting A1 Therefore, reliability is re-tested After removingA1, the result of Cronbach’s α equal 0.871, the scale tangibility has good reliability (Appendix 4)

Reliability analysis of Empathy (E): E1 should be deleted to increase cronbach alpha

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Reliability analysis of Cost (C): C3 should be deleted to increase cronbach alpha from

0.714 to 0.794 (Appendix 4)

Reliability analysis of Intention of Continue using the same LSP (I): Intention of

Continue using the same LSP factor has good reliability with Cronbach’s α equal 0.847 and all observed variables remain in the scale with corrected item-total correlations are higher than 0.3

In brief, after the scale has been refined, the measurement scale comprises of 28 items which will be taken into the step of exploratory factor analysis

4.3 Exploratory Factor Analysis (EFA)

After eliminating the uncertainty variables, the retained variables will be considered for conformity through EFA factor analysis If cronbach’s alpha is used to evaluate the reliability of the scale, EFA factor analysis is used to evaluate the convergence and discriminant value of the scale

In this research, factor analysis will help to consider the possibility of reducing the 28 observed variables to a few factors used to measure intention to continue using the same LSP factors It also helps to re-test the observed variables in each factor to be truly reliable and have the cohesion as they showed in the determination of Cronbach's alpha coefficient

4.3.1 Independent variable factor analysis

The value of KMO is reached 0.758 and the Sig index from Bartlett’s Test is less than 1/1000 This number indicates that the observed variables are correlated that the correlation is large enough and factor analysis can be used (Appendix 5)

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satisfies the requirement of factor analysis that the total variance extracted is greater than 50% (Appendix 5)

Looking at the Component matrix, it is hard to see which variables explain which factor, so we need to rotate the component The rotation used in this study is Varimax, which rotates the angle of the component to minimize the number of variables with large coefficients at the same factor, thus enhancing the ability to interpret the factors After rotation, we will also remove variables with factor load factor less than 0.5 Only variables with a load factor greater than 0.5 is used to explain a factor (Appendix 5)

Thus, the final result after factor analysis, we have 28 observed variables and are divided into factors with names corresponding to independent variables in the research model we built initially Therefore, the original proposed research model will be preserved for subsequent regression analysis (Appendix 5)

4.3.2 Dependent variable factor analysis

EFA analysis results show that the load factors of the four observed variables are 0.778 greater than 0.5, the significance level of Bartlett test is 1/1000, the total variance extracted is 68.471% (Appendix 5)

Thus, the four observed variables of the scale were grouped into one factor as expected, no observed variables were excluded after factor analysis The scale meets the requirements for differentiation and convergence

4.4 Analyzing the influence of demographic factors on Intention to continue using the same LSP

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Gender

The Independent-sample T-test will tell us is there a difference in Intention to continue using the same LSP (IC) between men and women

Hypothesis Ho: There is no difference in the Intention to continue using the same LSP between groups of male and female respondents

According to the results of the Levene's test, Sig > 0.05 (0.799) so the variance between men and women does not differ statistically T-test for Equality of Means > 0.05(0.974) (Appendix 7) So it can be concluded that there is no difference between the two groups of male and female respondents in Intention to continue using the same LSP Therefore, Ho is accepted

Conclusion: Gender does not affect the Intention to continue using the same LSP

Age

Using ANOVA (Analysis of variance) to consider the difference in the Intention to continue using the same LSP among different age groups

Hypothesis Ho: There is no difference in the Intention to continue using the same LSP among different age groups

The result of the variance test in the Test of Homogeneity of Variances table shows that the significance of sig <0.05 (0.00) (Appendix 7) The variance between age groups is not equal Therefore, ANOVA table can not be used Welch test result is used to identify the difference in the Intention to continue using the same LSP among different age groups of respondents

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According to ANOVA's in-depth analysis, the result in multiple comparison table of Post hoc test shows that:

- There is no difference in Intention to continue using the same LSP among different age groups: from 30 to 34, from 35 to 39, from 40 to 44 of the respondents (Sig >0.05)

- Mean value in the descriptive table shows that the older respondents will impact stronger on the intention to continue using the same LSP

Conclusion: Age group of respondents affects intention to continue using the same

LSP Older respondents will impact stronger on the intention to continue using the same LSP

Working time

Using ANOVA (Analysis of variance) to consider the difference in the Intention to continue using the same LSP among different working times

Hypothesis Ho: There is no difference in the Intention to continue using the same LSP among different working times

The result of the variance test in the Test of Homogeneity of Variances table shows that the significance of sig <0.05 (0.00) (Appendix 7) The variance among different working times is not equal Therefore, ANOVA table can not be used Welch test result is used to identify the difference in the Intention to continue using the same LSP among different working times

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According to ANOVA's in-depth analysis, the results in multiple comparison table of Post hoc test shows that:

There is no difference in Intention to continue using the same LSP among the groups have working time: from years to less than years and the group of more than years (Sig >0.05) (Appendix 7)

Mean value in descriptives table show that the respondents have longer working times will impact stronger on intention to continue using the same LSP

Conclusion: working time affects intention to continue using the same LSP The

people have longer working times will impact stronger on intention to continue using the same LSP

Interaction frequency

Using ANOVA (Analysis of variance) to consider the difference in the Intention to continue using the same LSP among the groups have different interaction frequency

Hypothesis Ho: There is no difference in the Intention to continue using the same LSP among the groups have different interaction frequency

According to the results of the Levene's test, Sig > 0.05 (0.629) (Appendix 7) So the variance among the groups have different interaction frequency not differ statistically Thus, ANOVA analysis results are good According to ANOVA analysis, with significance level sig.> 0.05 (sig = 0.388), it can be concluded that there is no statistically difference in Intention to continue using the same LSP among the groups have different interaction frequency Therefore, Ho is accepted

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Position

The Independent-sample T-test will tell us is there a difference in Intention to continue using the same LSP between the employees and managers

Hypothesis Ho: There is no difference in the Intention to continue using the same LSP between the employee and manager

According to the results of the Levene's test, Sig > 0.05 (0.593) (Appendix 7) so the variance between the employee or manager does not differ statistically T-test for Equality of Means > 0.05(0.156) So it can be concluded that there is no difference between the two groups of employees or managers in Intention to continue using the same LSP Therefore, Ho is accepted

Conclusion: Position does not affect the Intention to continue using the same LSP

Manufacturing sectors

To make easy in the analysis process, the author encodes the following Manufacturing sectors:

Table 4.1: Manufacturing sectors

CODE Manufacturing sectors

1 Food products Beverages

3 Tobacco products Textiles

41 Leather and related products

7 Wood and cork products except furniture; articles of straw and plaiting materials

8 Paper and paper products

9 Printing and reproduction of recorded media 10 Coke and refined petroleum products

11 Chemicals and chemical products

12 Basic pharmaceutical products and pharmaceutical preparations 13 Rubber and plastics products

14 Other non-metallic mineral products 15 Basic metals

16 Fabricated metal products, except machinery and equipment 17 Computer, electronic and optical products

18 Electrical equipment 19 Machinery and equipment

20 Motor vehicles, trailers and semi-trailers 21 Other transport equipment

22 Furniture

42 24 Other manufacturing

Using ANOVA (Analysis of variance) to consider the difference in the Intention to continue using the same LSP among the different Manufacturing sectors

Hypothesis Ho: There is no difference in the Intention to continue using the same LSP among the different Manufacturing sectors

The result of the variance test in the Test of Homogeneity of Variances table shows that the significance of sig <0.05 (0.01) (Appendix 7) The variance among different product fields is not equal Therefore, ANOVA table can not be used Welch test result is used to identify the difference in the Intention to continue using the same LSP among the different Manufacturing sectors

Welch test shows that Sig < 0.05 (0.000) (Appendix 7), it means there is a statistically significant difference in Intention to continue using the same LSP among the different Manufacturing sectors Therefore, Ho is rejected

Conclusion: Manufacturing sectors affects intention to continue using the same LSP

Whereby, sectors 17 (Computer, electronic and optical products), 11 (Chemicals and chemical products) seems to consider RL factor more important than other industries Sector 17 (Computer, electronic and optical products), (Paper and paper products) and 11 (Chemicals and chemical products) consider RS factor more important than other industries The 22 (Furniture), (Textiles), (Wearing apparel) industries consider C factor is the most important factor in Intention to continue using the same LSP

4.5 Correlation coefficient and linear regression analysis

This study has two research hypotheses as follows:

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H2: Cost reduction of a logistics service provider has a positive impact on the intention to continue using the same logistics service provider.

The hypotheses from H1 and H2 will be tested by linear regression analysis

After going through factor analysis, factors were included in the model The factor value is the average of the variables observing the component of that factor Pearson correlation analysis is used to consider the suitability of introducing components into the regression model

Based on the result of EFA, the author creates representative variables with the following computing values:

 I (representing dependent variable of Intention to continue using the same LSP) = Mean (I1A, I1B, I2A, I2B)

 T (representing independent variable of Tangibility) = Mean (T2, T3, T4)

 RL (representing independent variable of Relibility) = Mean (RL2, RL3, RL4, RL5)

 RS (representing independent variable of Responsiveness) = Mean (RS1, RS2, RS4, RS5, RS7)

 A (representing independent variable of Assurance) = Mean (A2, A3, A4, A5, A6)  E (representing independent variable of Empathy) = Mean (E2, E3, E4, E5)

 C (representing independent variable of Empathy) = Mean (C1, C2, C4)

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First of all, the correlation coefficient between the dependent variable and the independent variables will be considered Next, the MLR multiple regression is used to test the impact of independent variables (T, RL, RE, A, E, C) on dependent variables (IC)

The regression model has the following form:

IC = βo + β1*T+ β2*RL + β3*RS + β4*A + β5*E + β6*C + e (In which: βo: constant, βi: regression coefficient, e: error)

With the goal is to test hypotheses, the ENTER method is used in regression analysis to consider the impact of the independent variable on the dependent variable The ordinary least squares method (OLS) is used to estimate regression weights β and the Adjustment coefficient to assess model suitability

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4.5.1 Correlations Analysis

Pearson correlation coefficient test is used to check the linear relationship between the independent and dependent variables If the variables are closely correlated, the multi-collinearity problem must be considered when regression analysis

Table 4.2: Correlation matrix between variables

T RL RS A E C I

T

RL -.007

RS -.010 439** 1

A -.036 010 127* 1

E -.001 030 067 -.012

C -.028 141* .295** .078 -.022 1

I 090 534** .729** .382** .272** .308** 1

According to the correlation matrix, the variables are correlated and significant at the 0.00 level The correlation coefficient between the dependent variable (I) and the independent variables is relatively, in which the Reliability of RS with I (0.729) Therefore, we can conclude that these independent variables can be included in the model to explain the I variable

4.5.2 Regression analysis

Regression analysis was performed with independent quantitative variables including T, RL, RS, A, E, C, with dependent variable I

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Table 4.3: Evaluation of the suitability of the model

Model Summaryb

Model R R Square Adjusted R

Square Std Error of the Estimate Durbin-Watson

1 869a .755 .750 .42096 1.944

a Predictors: (Constant), C, E, T, A, RL, RS b Dependent Variable: I

With R Square of 0.755, the independent variables could explain 75.5% of dependent variable of dependent variable I (Intention to continue using the same logistics service provider) The rest of 24.5% Intention to continue using the same logistics service provider was decided by other factors

In the ANOVA analysis table (Appendix 6), we see the value of sig is very small (sig = 0.000), so the regression model is suitable for the data set and can be used

Test the hypothesis of the model is overall fit, value F = 159,415 with sig equal 0.000 less than 5% prove that R squared of the population is different from zero, so the regression model fits the data and can be used

Table 4.4: Factors affecting the Intention to continue using the same LSP

Model

Unstandardized Coefficients

Standardized Coefficients

t Sig

Collinearity Statistics

B Std Error Beta Tolerance VIF

1 (Constant) -2.176 228 -9.538 000

T 122 031 111 3.939 000 998 1.002

RL 285 032 282 8.994 000 805 1.242

RS 565 035 523 15.976 000 738 1.356

A 327 030 312 10.991 000 978 1.023

E 247 030 235 8.326 000 993 1.007

C 094 028 098 3.323 001 909 1.100

a Dependent Variable: I

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Looking at Table testing the hypothesis of the overall fit the model show that with sig.<5%, T, RL, RS, A, E, C are significant to determine I Hypothesis H1, H2 are supported

Regression coefficients are expressed in two forms: (1) Unstandardized and (2) Standardized (beta, β), Standardized (beta, β) is used to compare the impact of independent variable-dependent variables An independent variable with a greater weight means that it has a strong impact on the dependent variable

Based on Table above, we have the results of regression analysis as follows:

Figure 4.1: Results of regression analysis 4.5.3 Searching violation of regression assumptions

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guaranteed Therefore, to ensure the reliability of the model, we must conduct a series of searching the violation assumptions in linear regression

The first assumes a linear relationship between the dependent variable and the independent variables as well as the variance change phenomenon Test this assumption by plotting the distribution of residuals and the predicted values given by the linear regression model The Scatterplot graph (Appendix 6) shows that the residual is scattered randomly in an area around the line passing zero degrees, not forming any shapes Thus, the predicted value and the residual are independent and the variance of the residuals does not change Regression model is appropriate

The assumption of the normal distribution of residuals is checked by using the frequency chart of the Histogram standardized residuals Looking at the graph, we can see that the residuals have an approximately normal distribution with mean = 0.00 and the standard deviation of Std.Dev = 0.990 which is almost equal to Therefore, it can be concluded that the normal distribution assumption of residuals is not violated (Appendix 6)

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CHAPTER RESULT AND DISCUSSION

5.1 Result discussion

The purpose of current research is to identify how are service quality and cost impacting on outsourcing logistics service by Vietnamese manufacturing enterprises? And how are the Logistics service providers adapting themselves to the demand of the customers who are manufacturing enterprises?

- The first, research demonstrates the Impact of Service quality dimension and Cost

reduction on intention to continue using the same LSP by Vietnamese manufacturing enterprise

- The second, linking the research result with the realistic to identify how Logistics

service providers adapting themselves to the demand of the customers who are manufacturing enterprises

 Service quality and cost reduction of a logistics service provider have a

positive impact on the intention to continue using the same logistics service provider

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situation of LSPs, only a few LSPs are able to provide sufficient infrastructure, but they can fully rent from other vendors to provide services to their customers Observation variables RL1 (LSP X delivers on time.), RS3 (LSP X has a shorter total transit time than other forwarders for our shipment.), RS6 (LSP X frequently updates rates for us.), A1 (LSP X is a well-known name in its industry), E1 (We often receive gifts from LSP X on holidays.) has been examined by Lu (2003), Premeaux (2007), Pedersen & Gray (1998), Tuna (2002) In the US, Turkey and China markets, but not suitable for the circumstances of manufacturing enterprises and were eliminated after the analysis of Cronbach's alpha

The results of the EFA analysis draw six factors that influence the intention to continue using the same LSP by Vietnamese manufacturing enterprise with the original construction theory

The research results show that intention to continue using the same LSP by Vietnamese Manufacturing enterprise is strongly impacted by the factors responsiveness, reliability, assurance, in which responsiveness factors strongly influence In particular, the Responsiveness factor is considered the most powerful factor, followed by Assurance, reliability, and Empathy

To ensure the significance of the regression analysis results, a series of searching the violated regressions were also performed These are assumptions about the linear relationship between the dependent and independent variables, on the variance of the constant residuals, the assumption of the normal distribution of residuals, the independence of residuals, and the assumption of multi-collinear phenomena The results show that the regression model built does not violate the necessary assumptions in linear regression

 How Logistics service providers adapting themselves to the demand of the

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LSP's responsiveness is shown to be able to provide a wide range of services to its customers, besides the Global agent network will help customers' shipments to be processed around the world It is suitable for the characteristics of foreign-registering manufacturing enterprises that mainly use materials from imported and then export finished products Responsiveness is also the handling of special goods, the ability to provide consolidation According to the analysis results in chapter 4, Manufacturing sector 17 (Computer, electronic and optical products), (Paper and paper products), 11 (Chemicals and chemical products) consider the Responsiveness factor more important than other industries This is consistent with the characteristics of goods Accordingly, sector 17 with the characteristics of high-value goods but small size should often be transported by air freight or by sea but should be combined with the goods of the other companies This requires LSPs to be able to consolidate goods from different shippers It is not easy when LSPs not have enough customers who want to consolidate If LSP does not have a strategy of focusing on goods consolidation, it will be more difficult to get the customers in this sector In some cases, LSPs not have the ability to consolidate, they can still supply this service to the customer by using the service of other LSP that able to consolidate goods However, using intermediary vendors will make costs higher, unable to take the initiative in controlling goods during transportation

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about both Vietnam's environmental law and the Import and Export Law, understands the process of handling goods that need to be transported, understands the legal documents, and experienced staff Otherwise, LSP's customers will suffer greatly For example, if there are not enough testing certificates, the goods will immediately be re-exported to the port of loading Group 11 (Chemicals and chemical products) is considered a sensitive group when this group is frequently classified as dangerous goods Depending on the danger level of the goods, there will be different shipping rules and customs procedures Knowledge of dangerous goods and understanding the handling process is required Misrepresentation of dangerous cargoes sometimes results in LSP being deprived of a freight permit

Reliability representing elements of document accuracy or the ability to quickly solve problems that also significantly affects the Intention to continue using the same LSP The accuracy of documents was important since those documents are used as formal evidence especially in the international payment of goods procedure Any errors or discrepancies may cause delays and other charges such as the fee for L / C correction and so on Computer, electronic and optical products (17), Chemicals and chemical products (11) sectors are also consider RL factor more important than other industries Industry groups (17) with the characteristics of goods are a lot of different types, it is difficult to identify the identification code of each type and accurately manage on the system Issuing documents correctly is sometimes a little difficult for the person doing it directly The group of goods (11) is frequently classified as dangerous goods and is often rejected by the Shipping lines or airline since they fear fire or conflict with other goods being transported When handling these shipments, LSPs must always be in a position to handle arising problems At the same time must be knowledgeable about handling dangerous goods to be able to handle problems quickly

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of heavy goods and the regular container shipping method The transportation costs of these groups are very large Therefore, it is understandable to consider the Cost factor the most important LSPs with limited financial capacity may find it difficult to reach these customers, as transportation costs such as container wagering for import and export shipments or trucking fees are often high and LSPs always have to prepay for their customers The total credit amount is big along with the large manufacturing scale Spending a large amount of money to prepay for the customers while the low-profit margin makes businesses can be in a state of financial difficulties LSPs with limited financial capacity can access to other logistics service needs such as customs declarations and international freight sales instead of trucking in this industry

Besides answering research questions, the result of interaction frequency does not affect the Intention to continue using the same LSP in chapter is also an interesting result to discuss In fact, costs arising from logistics account for a high proportion of costs for businesses, affects the efficient operation of the businesses as mentioned on the previous chapters Therefore, the selecting freight forwarders are often considered very carefully and must be considered through the top management of the company, who are not usually communicate with the LSP However, in order to decide whether or not to continue using a LSP, the company's leaders will often consult with their employees, who are usually communicate with the LSPs, from which to make decisions In fact, almost companies consider LSPs selection is a serious decision in their company, especially in large manufacturing They usually decide whether or not to continue using a LSP based on their employee's evaluation, almost them it every month

5.2 Contributions

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objectives, thus creating an advantageous win-win situation Like most other global manufacturers, Vietnamese manufacturing companies outsource their logistics function to LSP to concentrate on their core competency The manufacturing industry sets a very high standard for LSP vendor selection, thanks to the high level of complexity in its logistics operations, and aims to maintain long-term partnerships with the selected LSP Most of the criteria that have been identified in recent literature, regardless of business characteristics or special requirements, apply to all the buying conditions of LSPs with regard to the selection criteria of the LSPs The research presented here focuses on the large-scale Vietnamese manufacturing business that focuses heavily on close and regular collaboration with its strategic LSP partners in order to gain a competitive advantage in a global supply chain complex Quantitative and qualitative approaches were adopted in the current study The total results of a multi-method approach can give an enhanced explanation of the quantitative results of the research Qualitative data are used in one regard for quantitative methods as a critical counterpoint In other respects, the quantitative analysis benefits from the perceptions of personal experiences and observations This study provides a consistent insight into the criteria for selection in academia, which are important for selecting LSP Besides the determining selection criteria, the study provides insight into why these determinants are important to large-scale manufacturing companies Moreover, certain emerging subcriteria, including document accuracy, problem-solving ability, and cost reduction, enhance the body of LSP selection knowledge as precedent studies mostly point to the key factors of delivery time and price Practical terms, the results of this study are widely responsive and detailed information for Vietnamese manufacturers that help them to concentrate on selection criteria in planning outsourcing logistics In addition, LSP offers valuable insights in assessing its ability and position in order to meet the needs of its clients

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Although the selection criteria themselves are common, the study provides a clearer overview of the LSP collection within the large scale manufacturing enterprise with a ranking of their relative significance and explanation of the deciding criteria defined by this research The analysis offers businesses an outline of provider selection requirements that are relevant for outsourcing activities in terms of their functional consequences From a management point of view, this analysis gives guidance for both decision-makers from manufacturing businesses and LSPs The research results should be viewed as guidance when preparing logistics outsourcing activities for large-scale industrial firms that have regional supply chain requirements to create effective LSP collaborations In fact, organizations can use the objectives defined by this research to decide which fields should be the priority of strategic LSPs This research also offers useful information to LSP businesses who wish to stay profitable and bring value to their consumers Typically speaking, the LSP that provides a quality service, meets the needs of consumers, and ensures rigorous cost management is the most desirable in large scale manufacturing companies In particular, the document accuracy, completeness, and consistency are prerequisites for reliable logistical results In addition, the LSP problem-solving ability to solve specific logistical challenges and emergency situations, as well as the value-added services that meet the customer's strategic supply chain demands, or serve as a source of business insight, are essential to consumers.Lastly, since this study is focused on the background of large-scale manufacturing enterprise, the LSP selection experience of these participants may be a reasonable guide for other fields with related characteristics of heavy capital investment, competitive market demands and working in a global supply chain network

5.4 Limitations

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Due to time constraints and accessibility to Respondent, the sample size of the topic is not large Therefore, there is a need for studies with a larger number of samples for this topic because the larger the sample size, the greater the accuracy of the study Besides, if the sample is selected by probability sampling method instead of convenient sampling, the representativeness and the ability to generalize will be higher

With an R2 coefficient of approximately 75.5% which means that there is about 75.5% variance explained by the independent variables in the research model, there are still other factors that influence intention to continue using the same LSP but not found in this study Therefore, the author suggested that the next research direction should refer to many other research models and the scale should continue to be completed in order to achieve high reliability

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APPENDIXES

Appendix Survey form in English

Survey about logistics service providers Dear friends and Colleagues,

My name is Giang I am studying the Master of Business Administration program at Vietnam Japan University - Vietnam National University, Hanoi

I am currently doing research on logistics service providers I would like to thank you for your support today, and I hope you may feel comfortable, happy, and spirited to share your views on this topic

Your opinions will help me in understanding the topic that I am studying I assure that your response be kept confidential and that the results of this survey are for scientific research purpose only after statistical analysis, never for any commercial purposes

Thank you once again for taking the time and wish you all the great success in your work and life

It takes you around ten minutes to complete answering this questionnaire What is the main product of your enterprise? Please select only one  Food products

 Beverages

 Tobacco products  Textiles

 Wearing apparel

 Leather and related products

70  Paper and paper products

 Printing and reproduction of recorded media  Coke and refined petroleum products

 Chemicals and chemical products

 Basic pharmaceutical products and pharmaceutical preparations  Rubber and plastics products

 Other non-metallic mineral products  Basic metals

 Fabricated metal products, except machinery and equipment  Computer, electronic and optical products

 Electrical equipment  Machinery and equipment

 Motor vehicles, trailers and semi-trailers  Other transport equipment

 Furniture

 Repair and installation of machinery and equipment

 Other manufacturing: (Please specify the product: ……… ……) Does your business have more than 200 employees who are insured?

Yes No

3 Does your business have a total annual revenue of over VND 200 billion? Yes No

4 Does your business have a total capital of over VND 100 billion? Yes No

71

Yes No What is your position in your company?

Employee Manager

7 Please assess the logistics service provider (LSP X) that you most frequently interact among the logistics service providers that your company is using by indicating your level of consent for the following statements on a scale of to 5, with convention:

1: Strongly disagree 3: Neutral 5: Strongly agree (Please choose only one number per statement)

No Description Consent level

1 LSP X has a lot of offices that can handle our

shipments in many different locations LSP X delivers on time During transport, LSP X is less likely to cause damage

or loss of goods When a complaint or problem arises, the LSP X

usually solves quickly 5 I will propose to outsource more activities to LSP X

in the future

6 LSP X has an extensive worldwide agent network LSP X has the ability to control shipments very well

72

8 LSP X always has enough equipment that we need LSP X has the ability to consolidate cargoes

10

I will propose to outsource more activities to other logistic service providers instead of LSP X in the future

1

11 LSP X has their own warehouse 12 LSP X can afford to provide many services to our

company

13 LSP X has a better reputation than other forwarders in

its industry

14 LSP X has sufficient infrastructure to handle a

consignment of goods to be transported 15 LSP X always issues correct documents

with information we provide 16 LSP X can handle specific goods 17 I feel secure when using services from LSP X 19 LSP X offers customers e-tracking shipment and

electronic data transmission EDI 19 Forwarder X's sales staff regularly contacts us 20 LSP X has a shorter total transit time than other

73

21 In previous collaborations with my company, LSP X

served very well 22 We save more money when using LSP X 23 LSP X always update information in the shipments

handling process for us 24 LSP X frequently updates rates for us 25 I will propose to stop using LSP X as soon as possible 26 Leaders of our company have close relationship with

LSP X

27 LSP X is a well-known name in its industry 28 LSP X meets our basic requirements for handling a

shipment

29 LSP X has a lower total cost than other forwarders for

our shipments

30 We are always consulted on laws and rules promptly

from LSP X

31 We often receive gifts from LSP X on holidays 32 LSP X has discount programs for our shipments 33 Goods are guaranteed when using services from LSP

74

34 I will propose to continue using LSP X as long as

possible

35 We feel empathy from the staff of LSP X 36 LSP X has a better credit term than other forwarders

for our company

8 Please indicate your gender:

Male Female Age:

24 years old or less

from 25 to 29

from 30 to 34 from 35 to 39 from 40 to 44 from 45 to 49 from 50 to 54 55 years old or

more 10 How long have you been working with LSP X?

Less than year From to less than years From to less than years years or more

11 How often to work with LSP X?

76

Appendix Survey form in Vietnamese

Khảo sát nhà cung cấp dịch vụ Logistics

Kính gửi bạn, anh chị đồng nghiệp,

Tơi Giang, học viên chương trình Thạc sĩ Quản trị kinh doanh Đại học Việt Nhật – Đại học quốc gia Hà Nội

Tôi làm nghiên cứu nhà cung cấp dịch vụ giao nhận vận tải, logistics Việt Nam muốn thu thập ý kiến bạn nhà cung cấp dịch vụ Cảm ơn bạn hỗ trợ ngày hôm nay, hy vọng bạn cảm thấy thoải mái để chia sẻ quan điểm thân chủ đề Ý kiến bạn giúp hiểu chủ đề mà nghiên cứu Tôi đảm bảo phản hồi bạn giữ bí mật kết khảo sát nhằm mục đích nghiên cứu khoa học sau phân tích thống kê, hồn tồn khơng cho mục đích thương mại

Cảm ơn bạn lần dành thời gian cho khảo sát chúc bạn thành công công việc sống

Bạn khoảng mười phút để hoàn thành việc trả lời câu hỏi

1 Doanh nghiệp bạn có sản phẩm gì? Vui lịng chọn  Thực phẩm

 Đồ uống  Thuốc  Xơ sợi

 Hàng may mặc

 Da sản phẩm liên quan tới da

77  Giấy sản phẩm từ giấy

 in ấn phương tiện dùng để chép (bang đĩa nhạc, máy quay phim, chụp hình, )

 than cốc sản phẩm tinh chế từ dầu mỏ  hóa chất sản phẩm hóa học

 sản phẩm dược phẩm chế phẩm dược phẩm (nguyên liệu bào chế thuốc, )

 Các sản phẩm cao su nhựa

 Các sản phẩm khoáng sản phi kim loại khác  Kim loại

 Các sản phẩm kim loại chế tạo, gia cơng, trừ máy móc thiết bị  Máy tính, sản phẩm điện tử quang học

 Thiết bị điện

 Máy móc thiết bị

 Xe giới, rơ moóc sơ mi rơ moóc  Thiết bị vận tải khác

 Đồ nội thất

 Sửa chữa, lắp đặt máy móc thiết bị

 Sản xuất khác : (Vui lòng ghi rõ sản phẩm: .)

2 Cơng ty bạn có 200 nhân viên đóng bảo hiểm? Có Khơng

78

4 Cơng ty bạn có tổng vốn đầu tư 100 tỷ đồng? Có Khơng

5 Bạn có thường xuyên tương tác với nhà cung cấp dịch vụ giao nhận vận tải logistics (forwarder) không?

Có Khơng Vị trí bạn cơng ty bạn ?

Nhân Viên Quản Lý

7 Hãy đánh giá nhà cung cấp dịch vụ giao nhân vận tải, logistics (Forwarder X) mà bạn thường xuyên tương tác nhà cung cấp dịch vụ vận tải, logistics mà công ty bạn sử dụng cách mức độ đồng ý bạn nhận định sau thang điểm từ đến 5, với quy ước:

1: Rất không đồng ý 2: không đồng ý 3: trung lập 4: đồng ý 5: Hoàn tồn đồng ý

(Vui lịng chọn đánh giá cho mỗinhận định)

STT Mô tả Mức độ đồng ý

1

Forwarder X có nhiều văn phịng đại diện, xử lý lơ hàng nhiều địa điểm khác

1

2 Forwarder X giao hàng thời gian yêu cầu Trong trình vận chuyển, Forwarder X gây hư

79

4 Khi có khiếu nại vấn đề phát sinh, Forwarder X

thường giải nhanh chóng 5 Tôi đề xuất sử dụng dịch vụ Forwarder X nhiều

hơn tương lai Forwarder X có mạng lưới đại lý rộng khắp toàn

thế giới

7 Forwarder X kiểm sốt lơ hàng tốt q

trình vận chuyển Forwarder X ln có đủ thiết bị cần thiết mà chúng

tôi cần để xử lý lô hàng cần vận chuyển Forwarder X có khả gom hàng lẻ 10 Tôi đề xuất sử dụng dịch vụ Forwarder khác

nhiều thay forwarder X tương lai 11 Forwarder X có kho riêng họ 12 Forwarder X có khả cung cấp nhiều dịch vụ cho

công ty 13 Forwarder X có danh tiếng tốt forwarder

khác

14 Forwarder X có đủ sở vật chất để xử lý lô hàng

80

15 Forwarder X phát hành chứng từ xác

với thơng tin chúng tơi cung cấp

16

Forwarder X có khả cung cấp dịch vụ cho hàng hóa đặc thù (hàng chịu kiểm tra chuyên ngành, hàng nguy hiểm,…)

1

17 Tơi cảm thấy an tồn sử dụng dịch vụ từ

Forwarder X

18

Forwarder X cung cấp cho khách hàng hệ thống theo dõi lịch trình hàng hóa online Trao đổi liệu điện tử (EDI)

1

19 Nhân viên kinh doanh Forwarder X thường xuyên

liên lạc với chúng tơi 20 Forwarder X có tổng thời gian vận chuyển ngắn

so với Forwarder khác cho lô hàng 21 Trong lần hợp tác trước với công ty tôi,

Forwarder X phục vụ tốt 22 Chúng tơi tiết kiệm chi phí sử dụng

Forwarder X

23 Forwarder X cập nhật thông tin trình

xử lý lơ hàng cho chúng tơi 24 Forwarder X thường xuyên cập nhật giá cho chúng

81

25 Tôi đề xuất ngừng sử dụng Forwarder X sớm

càng tốt

26 Lãnh đạo công ty có mối quan hệ thân

thiết với Forwarder X 27 Forwarder X tên tiếng ngành giao

nhận vận tải

28 Forwarder X đáp ứng yêu cầu chúng

tôi xử lý lô hàng 29 Forwarder X có tổng chi phí thấp forwarder

khác cho lô hàng 30 Chúng tư vấn điều luật

quy tắc kịp thời từ Forwarder X 31 Chúng thường nhận quà tặng từ Forwarder

X vào ngày lễ 32 Forwarder X có chương trình giảm giá cho lơ

hàng chúng tơi 33 Hàng hóa đảm bảo sử dụng dịch vụ từ

Forwarder X

34 Tôi đề xuất tiếp tục sử dụng Forwarder X lâu

càng tốt

35 Chúng cảm thấy đồng cảm từ nhân viên

82

36 Forwarder X có sách cơng nợ tốt so với

forwarder khác cho công ty Vui lòng cho biết giới tính bạn :

Nam Nữ

9 Vui long cho biết độ tuổi bạn:

từ 24 tuổi trở xuống từ 25 đấn 29

từ 30 đến 34 từ 35 đến 39 từ 40 đến 44 từ 45 đến 49 từ 50 đến 54 55 tuổi trở lên 10 Bạn làm việc với Forwarder X rồi?

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83

Appendix Result of frequencies test

Manufacturing Sector

Frequency Percent Valid Percent Cumulative Percent

Valid

4.00 33 10.4 10.4 10.4

5.00 49 15.4 15.4 25.8

7.00 6 26.4

8.00 30 9.4 9.4 35.8

9.00 18 5.7 5.7 41.5

11.00 21 6.6 6.6 48.1

13.00 20 6.3 6.3 54.4

16.00 28 8.8 8.8 63.2

17.00 44 13.8 13.8 77.0

18.00 33 10.4 10.4 87.4

19.00 24 7.5 7.5 95.0

21.00 2.8 2.8 97.8

22.00 1.6 1.6 99.4

24.00 6 100.0

Total 318 100.0 100.0

Position

Frequency Percent Valid Percent Cumulative Percent

Valid

Manager 77 24.2 24.2 24.2

84 Gender

Frequency Percent Valid Percent Cumulative Percent

Valid

Male 69 21.7 21.7 21.7

Female 249 78.3 78.3 100.0 Total 318 100.0 100.0

Age

Frequency Percent Valid Percent Cumulative Percent

Valid

24 years old or less 40 12.6 12.6 12.6 from 25 to 29 137 43.1 43.1 55.7

from 30 to 34 84 26.4 26.4 82.1

from 35 to 39 37 11.6 11.6 93.7

from 40 to 44 20 6.3 6.3 100.0

Total 318 100.0 100.0

Working_time

Frequency Percent Valid Percent Cumulative Percent

Valid

Less than year 45 14.2 14.2 14.2

From to less than years 156 49.1 49.1 63.2 From to less than years 74 23.3 23.3 86.5

5 years or more 40 12.6 12.6 99.1

5.00 9 100.0

85 Interaction Frequency

Frequency Percent Valid Percent Cumulative Percent

Valid

Weekly 239 75.2 75.2 75.2

Monthly 54 17.0 17.0 92.1

Quarterly 9 93.1

Yearly 22 6.9 6.9 100.0

86

Appendix Result of reliability test

 Testing reliability of Tangibility Reliability Statistics

Cronbach's Alpha

N of Items

.660

Item-Total Statistics Scale Mean if Item Deleted

Scale Variance if Item Deleted

Corrected Item-Total

Correlation

Cronbach's Alpha if Item Deleted

T1 11.3082 6.864 145 729

T2 11.2987 5.516 570 539

T3 11.1604 4.905 683 472

T4 11.2893 5.178 608 513

T5 11.1698 6.854 166 716

 Retesting reliability of Tangibility Reliability Statistics Cronbach's

Alpha

N of Items

.841

Item-Total Statistics Scale Mean if

Item Deleted

Scale Variance if Item Deleted

Corrected Item-Total Correlation

Cronbach's Alpha if Item

Deleted

T2 5.6635 2.741 656 825

T3 5.5252 2.326 767 717

87  Testing reliability of Reliability

Reliability Statistics Cronbach's

Alpha

N of Items

.730

Item-Total Statistics Scale Mean if

Item Deleted

Scale Variance if Item Deleted

Corrected Item-Total Correlation

Cronbach's Alpha if Item

Deleted

RL1 14.6352 11.027 -.036 849

RL2 14.8176 7.815 490 685

RL3 14.8648 6.963 672 607

RL4 14.7201 7.224 679 609

RL5 14.7987 6.742 751 574

 Retesting reliability of Reliability Reliability Statistics Cronbach's

Alpha

N of Items

.849

Item-Total Statistics Scale Mean if

Item Deleted

Scale Variance if Item Deleted

Corrected Item-Total Correlation

Cronbach's Alpha if Item

Deleted

RL2 10.9937 7.230 503 884

RL3 11.0409 6.241 730 789

RL4 10.8962 6.548 726 792

RL5 10.9748 6.044 810 754

88 Reliability Statistics

Cronbach's Alpha

N of Items

.774

Item-Total Statistics Scale Mean if

Item Deleted

Scale Variance if Item Deleted

Corrected Item-Total Correlation

Cronbach's Alpha if Item

Deleted

RS1 22.8553 12.730 607 720

RS2 22.9025 13.350 571 729

RS3 23.2421 16.771 197 794

RS4 22.7516 13.329 635 716

RS5 22.7453 13.093 635 715

RS6 23.0314 16.277 168 812

89  Retesting reliability of Responsiveness

Reliability Statistics Cronbach's

Alpha

N of Items

.867

Item-Total Statistics Scale Mean if Item Deleted

Scale Variance if Item Deleted

Corrected Item-Total

Correlation

Cronbach's Alpha if Item Deleted

RS1 15.6572 9.343 689 841

RS2 15.7044 9.792 672 844

RS4 15.5535 9.787 744 825

RS5 15.5472 9.618 733 827

RS7 15.6887 11.540 651 854

 Testing reliability of Assurance Reliability Statistics

Cronbach's Alpha

N of Items

.817

Item-Total Statistics Scale Mean if Item Deleted

Scale Variance if Item Deleted

Corrected Item-Total

Correlation

Cronbach's Alpha if Item Deleted

A1 19.5535 16.109 169 871

A2 19.5346 12.060 784 742

A3 19.5252 12.837 629 777

A4 19.4748 13.026 636 776

A5 19.5818 13.014 587 787

90  Retesting reliability of Assurance

Reliability Statistics Cronbach's

Alpha

N of Items

.871

Item-Total Statistics Scale Mean if Item Deleted

Scale Variance if Item Deleted

Corrected Item-Total

Correlation

Cronbach's Alpha if Item Deleted

A2 15.6447 10.003 812 814

A3 15.6352 10.775 641 857

A4 15.5849 10.893 659 852

A5 15.6918 10.883 608 866

A6 15.6572 10.661 779 825

 Testing reliability of Empathy Reliability Statistics Cronbach's

Alpha

N of Items

.726

Item-Total Statistics Scale Mean if Item Deleted

Scale Variance if Item Deleted

Corrected Item-Total

Correlation

Cronbach's Alpha if Item Deleted

E1 14.2201 10.216 225 785

E2 13.4119 10.022 482 687

E3 14.2547 7.900 559 650

E4 13.7516 8.263 530 662

91  Retesting reliability of Empathy

Reliability Statistics Cronbach's

Alpha

N of Items

.785

Item-Total Statistics Scale Mean if Item Deleted

Scale Variance if Item Deleted

Corrected Item-Total

Correlation

Cronbach's Alpha if Item Deleted

E2 10.2704 7.264 516 771

E3 11.1132 5.501 568 757

E4 10.6101 5.500 610 727

E5 10.6667 6.368 759 671

 Testing reliability of Cost

Reliability Statistics Cronbach's

Alpha

N of Items

.714

Item-Total Statistics Scale Mean if Item Deleted

Scale Variance if Item Deleted

Corrected Item-Total

Correlation

Cronbach's Alpha if Item Deleted

C1 10.2390 5.798 566 612

C2 10.1289 6.113 444 688

C3 11.1698 6.962 263 794

92  Retesting reliability of Cost

Reliability Statistics Cronbach's

Alpha

N of Items

.794

Item-Total Statistics Scale Mean if Item Deleted

Scale Variance if Item Deleted

Corrected Item-Total

Correlation

Cronbach's Alpha if Item Deleted

C1 7.3899 3.400 630 726

C2 7.2799 3.363 580 784

C4 7.6698 3.477 709 651

 Testing reliability of dependent variable Reliability Statistics

Cronbach's Alpha

N of Items

.844

Item-Total Statistics Scale Mean if Item Deleted

Scale Variance if Item Deleted

Corrected Item-Total

Correlation

Cronbach's Alpha if Item Deleted

I1B 11.7925 6.626 747 773

I1A 11.7642 6.679 722 784

I2B 11.8365 6.768 628 824

93

Appendix Result of factor analysis

 EFA of independent variable KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy .758

Bartlett's Test of Sphericity

Approx Chi-Square 3936.144

df 276

Sig .000

Total Variance Explained Comp

onent

Initial Eigenvalues Extraction Sums of Squared Loadings

Rotation Sums of Squared Loadings

Total % of Variance

Cumulativ e %

Total % of Variance

Cumulativ e %

Total % of Variance

Cumulativ e % 4.819 20.080 20.080 4.819 20.080 20.080 3.420 14.251 14.251 3.358 13.991 34.071 3.358 13.991 34.071 3.398 14.160 28.411 2.541 10.586 44.657 2.541 10.586 44.657 2.785 11.605 40.016 2.288 9.535 54.192 2.288 9.535 54.192 2.544 10.600 50.617 2.025 8.439 62.631 2.025 8.439 62.631 2.295 9.562 60.179 1.570 6.542 69.173 1.570 6.542 69.173 2.159 8.995 69.173 873 3.639 72.812

94 16 334 1.393 92.613

17 305 1.270 93.883 18 269 1.120 95.003 19 249 1.037 96.040 20 235 979 97.019 21 231 964 97.983 22 192 799 98.782 23 163 679 99.461 24 129 539 100.000

Extraction Method: Principal Component Analysis

Rotated Component Matrixa Component

1

A2 892 A6 869 A4 775 A3 762 A5 753

RS5 821

RS4 821

RS1 779

RS7 771

RS2 736

RL5 912

RL3 878

RL4 796

95

E5 883

E4 799

E3 770

E2 710

T3 902

T4 862

T2 845

C4 868

C1 832

C2 781

Extraction Method: Principal Component Analysis Rotation Method: Varimax with Kaiser Normalization a Rotation converged in iterations

 EFA of dependent variable KMO and Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy .778

Bartlett's Test of Sphericity

Approx Chi-Square 547.545

df

96 Component Matrixa

Component

I1B 875 I1A 860 I2B 786 I2A 785 Extraction Method: Principal Component Analysis

97

Appendix Result of correlations and regression test

Correlations

T RL RS A E C I

T

Pearson

Correlation -.007 -.010 -.036 -.001 -.028 090 Sig (2-tailed) 900 865 521 991 625 111

N 318 318 318 318 318 318 318

RL

Pearson

Correlation -.007 439** 010 030 141* 534** Sig (2-tailed) 900 000 853 596 012 000

N 318 318 318 318 318 318 318

RS

Pearson

Correlation -.010 439** 127* 067 295** 729** Sig (2-tailed) 865 000 024 231 000 000

N 318 318 318 318 318 318 318

A

Pearson

Correlation -.036 010 127* -.012 078 382** Sig (2-tailed) 521 853 024 828 163 000

N 318 318 318 318 318 318 318

E

Pearson

Correlation -.001 030 067 -.012 -.022 272** Sig (2-tailed) 991 596 231 828 691 000

N 318 318 318 318 318 318 318

C

Pearson

Correlation -.028 141* 295** 078 -.022 308** Sig (2-tailed) 625 012 000 163 691 000

N 318 318 318 318 318 318 318

I

Pearson

98

N 318 318 318 318 318 318 318

** Correlation is significant at the 0.01 level (2-tailed) * Correlation is significant at the 0.05 level (2-tailed)

Variables Entered/Removeda Model Variables

Entered

Variables Removed

Method

1 C, E, T, A, RL,

RSb Enter

a Dependent Variable: I

b All requested variables entered Model Summaryb

Model R R Square Adjusted R Square

Std Error of the Estimate

Durbin-Watson

1 869a 755 750 42096 1.944

a Predictors: (Constant), C, E, T, A, RL, RS b Dependent Variable: I

ANOVAa

Model Sum of Squares df Mean Square F Sig

1

Regression 169.500 28.250 159.415 000b Residual 55.112 311 177

Total 224.613 317 a Dependent Variable: I

99 Coefficientsa

Model Unstandardized Coefficients

Standardized Coefficients

t Sig Collinearity Statistics

B Std Error Beta Tolerance VIF

1

(Constant) -2.176 228 -9.538 000

T 122 031 111 3.939 000 998 1.002

RL 285 032 282 8.994 000 805 1.242

RS 565 035 523 15.976 000 738 1.356

A 327 030 312 10.991 000 978 1.023

E 247 030 235 8.326 000 993 1.007

C 094 028 098 3.323 001 909 1.100

a Dependent Variable: I

Residuals Statisticsa

103

Appendix Result of T-test and ANOVA

 Gender

Group Statistics

Gender N Mean Std Deviation Std Error Mean

I Male 69 3.9239 84920 10223 Female 249 3.9277 84140 05332 Independent Samples Test

Levene's Test for Equality of Variances

t-test for Equality of Means

F Sig t df Sig (2-tailed) Mean Differen ce Std Error Differen ce 95% Confidence Interval of the Difference Lower Upper

I

Equal variances assumed

.065 799 -.033 316 974 -.00380 11470 -.22947 22187

Equal variances not assumed

-.033 107.8

42 974 -.00380 11530 -.23235 22476

 Age

Test of Homogeneity of Variances I

Levene Statistic df1 df2 Sig

104 Robust Tests of Equality of Means

I

Statistica df1 df2 Sig Welch 4.828 13 25.292 000 a Asymptotically F distributed

Multiple Comparisons Dependent Variable: I LSD

(I) Age (J) Age Mean

Difference (I-J)

Std Error Sig 95% Confidence Interval Lower

Bound

Upper Bound

24 years old or less

from 25 to 29 -.47505* 14141 001 -.7533 -.1968 from 30 to 34 -.85387* 15115 000 -1.1513 -.5565 from 35 to 39 -.95828* 17947 000 -1.3114 -.6052 from 40 to 44 -1.05625* 21548 000 -1.4802 -.6323

from 25 to 29

24 years old or

less 47505* 14141 001 1968 7533 from 30 to 34 -.37882* 10903 001 -.5934 -.1643 from 35 to 39 -.48323* 14577 001 -.7701 -.1964 from 40 to 44 -.58120* 18834 002 -.9518 -.2106

from 30 to 34

24 years old or

less 85387* 15115 000 5565 1.1513 from 25 to 29 37882* 10903 001 1643 5934 from 35 to 39 -.10441 15525 502 -.4099 2011 from 40 to 44 -.20238 19576 302 -.5876 1828

from 35 to 39

24 years old or

105

from 40 to 44 -.09797 21837 654 -.5276 3317

from 40 to 44

24 years old or

less 1.05625* 21548 000 6323 1.4802 from 25 to 29 58120* 18834 002 2106 9518 from 30 to 34 20238 19576 302 -.1828 5876 from 35 to 39 09797 21837 654 -.3317 5276 * The mean difference is significant at the 0.05 level

 Working time

Test of Homogeneity of Variances I

Levene Statistic df1 df2 Sig

5.238 313 000

Robust Tests of Equality of Means I

Statistica df1 df2 Sig Welch 30.563 22.345 000 a Asymptotically F distributed

Multiple Comparisons Dependent Variable: I LSD

(I) working_time (J) working_time Mean Difference (I-J)

Std Error

Sig 95% Confidence Interval

Lower Bound

Upper Bound

Less than year

From to less than

years -.41207* 13540 003 -.6785 -.1457 From to less than

106

5 years or more -.90486* 17388 000 -1.2470 -.5627

From to less than years

Less than year 41207* 13540 003 1457 6785 From to less than

years -.26728* 11294 019 -.4895 -.0451 years or more -.49279* 14181 001 -.7718 -.2138

From to less than years

Less than year 67935* 15126 000 3817 9770 From to less than

years 26728* 11294 019 0451 4895 years or more -.22551 15703 152 -.5345 0835

5 years or more

Less than year 90486* 17388 000 5627 1.2470 From to less than

years 49279* 14181 001 2138 7718 From to less than

years 22551 15703 152 -.0835 5345 * The mean difference is significant at the 0.05 level

 Interaction frequency

Test of Homogeneity of Variances I

Levene Statistic df1 df2 Sig

.580 314 629

ANOVA I

Sum of Squares df Mean Square F Sig Between Groups 2.409 803 1.135 335 Within Groups 222.204 314 708

107  Manufacturing sectors

Test of Homogeneity of Variances I

Levene Statistic df1 df2 Sig

2.195 13 304 010

Robust Tests of Equality of Means I

Statistica df1 df2 Sig Welch 4.828 13 25.292 000 a Asymptotically F distributed

Multiple Comparisons Dependent Variable: I LSD

(I) nganh1 (J) nganh1 Mean

Difference (I-J)

Std Error Sig 95% Confidence Interval Lower Bound Upper Bound

4.00

108

21.00 03788 30587 902 -.5640 6398 22.00 -.34545 39033 377 -1.1136 4226 24.00 1.45455* 59231 015 2890 2.6201

5.00

4.00 10158 18316 580 -.2589 4620 7.00 1.05612 58676 073 -.0985 2.2107 8.00 08946 18856 636 -.2816 4605 9.00 29223 22418 193 -.1489 7334 11.00 -.06293 21214 767 -.4804 3545 13.00 33112 21582 126 -.0936 7558 16.00 35969 19269 063 -.0195 7389 17.00 -.30751 16893 070 -.6399 0249 18.00 37430* 18316 042 0139 7347 19.00 43112* 20265 034 0324 8299 21.00 13946 29497 637 -.4410 7199 22.00 -.24388 38186 524 -.9953 5075 24.00 1.55612* 58676 008 4015 2.7107

7.00

109

24.00 50000 81337 539 -1.1005 2.1005

8.00

4.00 01212 20518 953 -.3916 4159 5.00 -.08946 18856 636 -.4605 2816 7.00 96667 59400 105 -.2022 2.1355 9.00 20278 24250 404 -.2744 6800 11.00 -.15238 23142 511 -.6078 3030 13.00 24167 23480 304 -.2204 7037 16.00 27024 21373 207 -.1503 6908 17.00 -.39697* 19258 040 -.7759 -.0180 18.00 28485 20518 166 -.1189 6886 19.00 34167 22275 126 -.0967 7800 21.00 05000 30913 872 -.5583 6583 22.00 -.33333 39289 397 -1.1065 4398 24.00 1.46667* 59400 014 2978 2.6355

9.00

110

5.00 06293 21214 767 -.3545 4804 7.00 1.11905 60190 064 -.0654 2.3035 8.00 15238 23142 511 -.3030 6078 9.00 35516 26126 175 -.1589 8693 13.00 39405 25413 122 -.1060 8941 16.00 42262 23480 073 -.0394 8847 17.00 -.24459 21573 258 -.6691 1799 18.00 43723 22705 055 -.0096 8840 19.00 49405* 24304 043 0158 9723 21.00 20238 32405 533 -.4353 8401 22.00 -.18095 40474 655 -.9774 6155 24.00 1.61905* 60190 008 4346 2.8035

13.00

4.00 -.22955 23049 320 -.6831 2240 5.00 -.33112 21582 126 -.7558 0936 7.00 72500 60321 230 -.4620 1.9120 8.00 -.24167 23480 304 -.7037 2204 9.00 -.03889 26426 883 -.5589 4811 11.00 -.39405 25413 122 -.8941 1060 16.00 02857 23813 905 -.4400 4972 17.00 -.63864* 21935 004 -1.0703 -.2070 18.00 04318 23049 852 -.4104 4967 19.00 10000 24626 685 -.3846 5846 21.00 -.19167 32647 558 -.8341 4508 22.00 -.57500 40668 158 -1.3753 2253 24.00 1.22500* 60321 043 0380 2.4120

16.00

111

8.00 -.27024 21373 207 -.6908 1503 9.00 -.06746 24573 784 -.5510 4161 11.00 -.42262 23480 073 -.8847 0394 13.00 -.02857 23813 905 -.4972 4400 17.00 -.66721* 19663 001 -1.0541 -.2803 18.00 01461 20899 944 -.3966 4259 19.00 07143 22626 752 -.3738 5167 21.00 -.22024 31166 480 -.8335 3931 22.00 -.60357 39489 127 -1.3806 1735 24.00 1.19643* 59532 045 0250 2.3679

17.00

4.00 40909* 18730 030 0405 7777 5.00 30751 16893 070 -.0249 6399 7.00 1.36364* 58806 021 2064 2.5208 8.00 39697* 19258 040 0180 7759 9.00 59975* 22757 009 1519 1.0476 11.00 24459 21573 258 -.1799 6691 13.00 63864* 21935 004 2070 1.0703 16.00 66721* 19663 001 2803 1.0541 18.00 68182* 18730 000 3132 1.0504 19.00 73864* 20640 000 3325 1.1448 21.00 44697 29756 134 -.1386 1.0325 22.00 06364 38386 868 -.6917 8190 24.00 1.86364* 58806 002 7064 3.0208

18.00

112

11.00 -.43723 22705 055 -.8840 0096 13.00 -.04318 23049 852 -.4967 4104 16.00 -.01461 20899 944 -.4259 3966 17.00 -.68182* 18730 000 -1.0504 -.3132 19.00 05682 21820 795 -.3726 4862 21.00 -.23485 30587 443 -.8367 3670 22.00 -.61818 39033 114 -1.3863 1499 24.00 1.18182* 59231 047 0163 2.3474

19.00

4.00 -.32955 21820 132 -.7589 0998 5.00 -.43112* 20265 034 -.8299 -.0324 7.00 62500 59862 297 -.5530 1.8030 8.00 -.34167 22275 126 -.7800 0967 9.00 -.13889 25361 584 -.6379 3602 11.00 -.49405* 24304 043 -.9723 -.0158 13.00 -.10000 24626 685 -.5846 3846 16.00 -.07143 22626 752 -.5167 3738 17.00 -.73864* 20640 000 -1.1448 -.3325 18.00 -.05682 21820 795 -.4862 3726 21.00 -.29167 31792 360 -.9173 3339 22.00 -.67500 39985 092 -1.4618 1118 24.00 1.12500 59862 061 -.0530 2.3030

21.00

113

16.00 22024 31166 480 -.3931 8335 17.00 -.44697 29756 134 -1.0325 1386 18.00 23485 30587 443 -.3670 8367 19.00 29167 31792 360 -.3339 9173 22.00 -.38333 45367 399 -1.2761 5094 24.00 1.41667* 63584 027 1655 2.6679

22.00

4.00 34545 39033 377 -.4226 1.1136 5.00 24388 38186 524 -.5075 9953 7.00 1.30000 68051 057 -.0391 2.6391 8.00 33333 39289 397 -.4398 1.1065 9.00 53611 41118 193 -.2730 1.3452 11.00 18095 40474 655 -.6155 9774 13.00 57500 40668 158 -.2253 1.3753 16.00 60357 39489 127 -.1735 1.3806 17.00 -.06364 38386 868 -.8190 6917 18.00 61818 39033 114 -.1499 1.3863 19.00 67500 39985 092 -.1118 1.4618 21.00 38333 45367 399 -.5094 1.2761 24.00 1.80000* 68051 009 4609 3.1391

24.00

114

17.00 -1.86364* 58806 002 -3.0208 -.7064 18.00 -1.18182* 59231 047 -2.3474 -.0163 19.00 -1.12500 59862 061 -2.3030 0530 21.00 -1.41667* 63584 027 -2.6679 -.1655 22.00 -1.80000* 68051 009 -3.1391 -.4609 * The mean difference is significant at the 0.05 level

Descriptives

N Mean Std Deviation

Std Error 95% Confidence Interval for Mean

Minimu m

Maxi mum Lower Bound Upper Bound

T

115

19.00 24 2.9861 67730 13825 2.7001 3.2721 1.00 4.00 21.00 2.8148 68943 22981 2.2849 3.3448 2.00 4.00 22.00 2.5333 73030 32660 1.6266 3.4401 2.00 3.33 24.00 2.0000 00000 00000 2.0000 2.0000 2.00 2.00 Total 318 2.8071 76360 04282 2.7229 2.8914 1.00 5.00

RL

4.00 33 3.5530 92862 16165 3.2238 3.8823 2.00 5.00 5.00 49 3.7704 85974 12282 3.5235 4.0174 2.00 5.00 7.00 2.0000 00000 00000 2.0000 2.0000 2.00 2.00 8.00 30 3.6500 65192 11902 3.4066 3.8934 2.00 4.50 9.00 18 3.0694 74659 17597 2.6982 3.4407 2.00 4.00 11.00 21 4.3810 46515 10151 4.1692 4.5927 3.25 4.75 13.00 20 3.3625 75861 16963 3.0075 3.7175 2.00 4.25 16.00 28 3.4107 71107 13438 3.1350 3.6864 2.00 4.25 17.00 44 4.3409 32836 04950 4.2411 4.4407 3.75 5.00 18.00 33 3.3712 81519 14191 3.0822 3.6603 2.00 4.50 19.00 24 3.2708 80053 16341 2.9328 3.6089 2.00 4.25 21.00 3.3056 70465 23488 2.7639 3.8472 2.00 4.25 22.00 4.3000 11180 05000 4.1612 4.4388 4.25 4.50 24.00 3.0000 1.41421 1.00000 -9.7062 15.7062 2.00 4.00 Total 318 3.6588 83019 04655 3.5672 3.7504 2.00 5.00

RS

116

17.00 44 4.1773 53738 08101 4.0139 4.3407 2.20 4.80 18.00 33 3.7333 90646 15779 3.4119 4.0547 2.20 4.80 19.00 24 3.5833 94899 19371 3.1826 3.9841 2.00 4.80 21.00 4.0889 67905 22635 3.5669 4.6109 2.80 4.80 22.00 4.2000 44721 20000 3.6447 4.7553 3.60 4.80 24.00 2.5000 42426 30000 -1.3119 6.3119 2.20 2.80 Total 318 3.9075 77834 04365 3.8217 3.9934 2.00 5.00

A

4.00 33 4.0061 81775 14235 3.7161 4.2960 2.00 5.00 5.00 49 4.0286 84163 12023 3.7868 4.2703 2.00 5.00 7.00 3.3000 70711 50000 -3.0531 9.6531 2.80 3.80 8.00 30 3.6800 84298 15391 3.3652 3.9948 2.00 4.80 9.00 18 4.0556 78157 18422 3.6669 4.4442 2.20 4.80 11.00 21 3.8857 77607 16935 3.5325 4.2390 2.00 5.00 13.00 20 4.1000 66014 14761 3.7910 4.4090 2.80 5.00 16.00 28 3.7571 93865 17739 3.3932 4.1211 2.00 5.00 17.00 44 4.0364 60428 09110 3.8526 4.2201 2.00 5.00 18.00 33 3.7939 88950 15484 3.4785 4.1093 2.00 5.00 19.00 24 3.6750 81254 16586 3.3319 4.0181 2.00 4.80 21.00 3.8444 86474 28825 3.1797 4.5091 2.20 5.00 22.00 4.3200 75631 33823 3.3809 5.2591 3.00 4.80 24.00 4.0000 56569 40000 -1.0825 9.0825 3.60 4.40 Total 318 3.9107 80272 04501 3.8221 3.9993 2.00 5.00

E

117

13.00 20 3.4250 87772 19626 3.0142 3.8358 2.25 4.75 16.00 28 3.6607 88771 16776 3.3165 4.0049 2.25 5.00 17.00 44 3.7159 83977 12660 3.4606 3.9712 2.25 5.00 18.00 33 3.3636 71011 12361 3.1118 3.6154 2.00 4.50 19.00 24 3.6875 77407 15801 3.3606 4.0144 2.25 5.00 21.00 3.8889 97717 32572 3.1378 4.6400 2.25 5.00 22.00 3.6500 91173 40774 2.5179 4.7821 2.50 5.00 24.00 3.7500 70711 50000 -2.6031 10.1031 3.25 4.25 Total 318 3.5550 79908 04481 3.4669 3.6432 2.00 5.00

C

With the current status of the Vietnam economy that most manufacturing enterprises are foreign-invested enterprises.