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This chapter contains the research framework, research hypotheses, research procedure, data collection, measurement instrument and data analysis methods. It will explain the research framework to show how variables are tested. The details of measurement instrument are provided. However, it will present the method of data collection, and data analysis methods.

Research Framework

By following the logic of literature review, a model was proposed. The model was based on Organizational Trust Model by (Mooradian, Renzl and Matzler, 2006; Shockley-Zalabak Ellis and Cesaria, 2003), Knowledge Sharing Model by (Cummings, 2004; Van den Hooff and De Ridder, 2003), Organizational Learning Model by Jerez-Gomez, Céspedes-Lorente and Valle-Cabrera (2005), and Academic Satisfaction Model by Ahmed and Masud (2014).

In Figure 3.1, Cheng-Ping Shih and Hildeberto Seca developed LASS model. OT-LASS model served as the research framework for this study (see figure 3.1). The OT-OT-LASS model (stands for organizational trust, knowledge sharing, organizational learning and academic satisfaction).

Figure 3.1. OT-LASS model, developed by Shih and Seca.

H4

H6 H3

Knowledge Sharing -Intra-Groups

-Inter-Groups

-Knowledge Donating -Knowledge Collecting

Organizational Learning -Management Commitment -System Perspective

-Openness and Experimentation -Knowledge Transfer and Integrate Organizational Trust

-Trust in Peers

-Trust in Management -Openness and Honesty -Reliability

-Identification

Academic Satisfaction -Responsiveness Academic Staff -Assurance

-Academic Feedback -Empathy

-Tangibles

-Administrative Service -Academic Programs

H1

H2

H5

Research Hypotheses

The research hypotheses test the relationships among trust, knowledge sharing, organizational learning, and academic satisfaction. Based on the literature review and research questions, the following null-hypotheses are developed for testing the results:

H1: Organizational trust has no effect on knowledge sharing.

H2: Organizational trust has no effect on organizational learning.

H3: Organizational trust has no effect on academic satisfaction.

H4: Knowledge sharing has no effect on organizational learning.

H5: Knowledge sharing has no effect on academic satisfaction.

H6: Organizational learning has no effect on academic satisfaction.

Research Procedure

An systematic research procedure has been obviously charted for the purpose of making an understandable stages for this study. The research was conducted by following this research process:

.

Figure 3.2. Research process

Research Motivation

Develop Theoretical Framework of the Study

Report Research Findings and Conclusions

Review the study

Publish the study Review of Literature

Identify Research Questions and Hypothesis

Develop Research Method of the Study

Instrument Development and Expert Review of the Instrument

Conduct Pilot Study

Gather the Main Data for the Study

Data Analysis

Data Collection

This research used a quantitative approach that followed a self-reported survey methodology to gather the necessary data and to investigate the relationship among the variables of interest (organizational trust, knowledge sharing, organizational learning and academic satisfaction).

The participants of this research are international students studying in Taiwan. The respondents must be international students that are currently enrolled in any university in Taiwan. This means that students could be from any region from Africa, the Americas, Asia, Oceania, Europe, excepted local students from Taiwan. Besides, the researcher use on-line questionnaire to do the investigation. Participants had the privacy to fill in a questionnaire anonymously, so that can provide real answers. The convenient sampling procedure was employed to collected data. The instrument was first tested on a group of 49 international students who participated in a pilot study. After refining the instrument through reliability and validity procedures, the main study has successfully collected 225 valid sample out of 240, with a relatively high response rate of 94%, which only left out 6% of the non-response rate.

Measurement

In this research, a quantitative approach was applied since the research intend to gather numerical data and analysis the statistical relationship between each variable. The research instrument consists of self-reported survey questionnaire. Nevertheless, the function of the research instrument is to gather the required data and to test the established hypotheses. The questions were grouped into five sections on the basis of their relevance and relationship.

Simple instructions are provided at the beginning of the questionnaire and at each section. Most importantly, the questions are applicable and answerable by most participants. All constructs in the questionnaire were adapted from pre-validated measures in existing correlated researches.

The instrument consisted of 4 variables with total amount of 84 questions. A cover letter is used to briefly introduce the study, as well as its purposes is clearly stated. The survey contains two parts: organizational trust, knowledge sharing, organizational learning, academic satisfaction, and respondent demographic data. For part I, respondents were asked to rate each item with scale anchors ranging from “strongly agree” (5) to “strongly disagree” (1). For part II, respondents were asked to choose one of different available options. The measurements are described in the following:

1. Organizational Trust (18 items): Adopted from Mooradian, Renzl, and Matzler (2006).

the variables of trust consist of trust in peers (T_P) and trust in management (T_M) and by Shockley-Zalabak, Ellis, and Cesaria (2003) the variables of trust consist of openness and honest (O_H), reliability (RE), identification (IDE).

2. Knowledge Sharing (13 items): The measurement of knowledge sharing were adopted by Cummings’ (2004) scale and categorizing knowledge sharing into two types: intra-groups (I_G), and inter-intra-groups (INTER_G) and by Van den Hooff and De Ridder (2003) with the variables knowledge donating (K_D) and knowledge collecting (K_C).

3. Organizational Learning (15 items): Adopted from (Pilar Jerez-Gómez, José Céspedes-Lorente, Ramón Valle-Cabrera. 2005), the variables of management commitment (M_C), system perspective (S_P), openness and experimentation(O_E), knowledge transfer and integrate (KT_I).

4. Academic Satisfaction (30 items): Adopted Ahmed and Masud (2014), the variables of responsiveness academic staff (RAS), assurance (ASSU), academic feedback (A_F), empathy (EMPA), tangibles (TANG), administrative service (A_S), academic programs (A_P).

5. The Respondent Demographic Profile: This unit was added as a second section in order to provide a descriptive analysis of the survey respondents. This section contained demographic information such as participants’ program, university, years in Taiwan, region of origin, scholarship type, gender and language ability (Mandarin and English).

Participants were randomly asked to fill out the survey based on the requirement that they should be an international student that are currently studying in Taiwan. The survey were presented with five-point Likert-type scales from ‘strongly disagree’ (1) to ‘strongly agree’ (5).

Construct Coding and Scales

The items used to measure the variables of this study are listed in Tables 3.1 to 3.4.

Each item was coded for later use in the statistical analysis of the data by using PLS. Thus, Dummy variables were created to code part II of the measurement instrument relating to demographics.

Table 3.1.

Items Measuring Organizational Trust

Construct Code Questionnaire Item

Trust in Peers (T_P; 3 items)

T_P1 If I got into difficulties at university, I know my classmates would try and help me out.

T_P2 I can trust the people I study with to lend me a hand if I needed it.

T_P3 Most of my classmates can be relied upon to do as they say they will do.

Trust in Management (T_M; 3 items)

T_M1 Management at my university is sincere in its attempts to meet the students’ point of view.

T_M2 I feel quite confident that the university will always try to treat me fairly.

T_M3 Our academic staff (professors, lecturers, administrative, etc.) would be quite prepared to gain advantage by deceiving the students.

Openness and Honesty(O_H;

4 items)

O_H1 I can get enough evaluation of my studying abilities.

O_H2 I can have opinions to the decisions which is relevant to my studies.

O_H3 When something is wrong, I don’t afraid to tell my tutors.

O_H4 When I don’t agree with my tutor’s opinions, I don’t feel uncomfortable.

Reliability (RE; 4 items)

RE_1 My tutors does what he or she said.

RE_2 Top managers keep their commitments to students.

RE_3 My tutors keep commitments to all students.

R4_4 My tutors behaves in a consistent manner.

Identification (IDE;4 items)

IDE_1 I feel connected to my peers.

IDE_2 I feel connected to my tutors.

IDE_3 My value is similar to my classmate’s values.

IDE_4 My value is similar to my tutors values.

Table 3.2.

Items Measuring Knowledge Sharing

Construct Code Questionnaire Item

Intra-Groups (I_G; 3 items)

I_G1 I frequently share knowledge and information with my university classmates.

I_G2 I usually involve myself in discussions of various topics rather than specific topics with my classmates.

I_G3 I usually spend a lot of time conducting knowledge sharing activities within my classmate’s team.

Inter-Groups (INTER_G; 3 items

INTER_G1 I frequently share knowledge with classmates even though he (or she) is not in my team.

INTER_G2 I usually involve myself in discussions of various topics rather than specific topics with classmates from other classmate’s teams.

INTER_G3 I spend a considerate amount of time conducting knowledge sharing activities with other classmates teams in the university

Knowledge Donating(K_D;

3 items)

K_D1 When I have learned something new, I tell my classmates about it.

K_D2 When they have learned something new, my classmates tell me about it.

K_D3 Knowledge sharing among classmates is considered normal in my university.

K_C2 I share my skills with classmates when they ask for it.

K_C3 Classmates in my university share knowledge with me when I ask them to.

K_C4 Classmates in my university share their skills with me when I ask them to.

Table 3.3.

Items Measuring Organizational Learning

Construct Code Questionnaire Item

Management Commitment (M_C; 4 items)

M_C1 Student learning capability is considered a key factor in the university.

M_C2 Student learning is considered an investment rather than an expense.

M_C3 Innovative ideas that work are rewarded in the university.

M_C4 Top managers look favourably on carrying out changes in any area to adapt to and/or keep ahead of new environmental situations.

System Perspective (S_P; 3 items)

S_P1 I have generalized knowledge regarding university’s objectives.

S_P2 I always experience situation in university in which (departments, sections, school staff, etc.) were not able to solve my problems and tell me to look for another (departments, sections, school staff, etc.).

S_P3 I satisfied with my university (departments, sections, school staff, etc.) because they are well interconnected, working together and solve my problems.

Openness and Experimentati on (O_E; 4 items)

O_E1 My university promotes experimentation and innovation to improve the study processes.

O_E2 My university follows up what other universities in the sector are doing, adopting those practices and techniques it believes to be useful and interesting.

O_E3 Experiences and ideas provided by external sources (advisors, students, staff members, etc.) are considered a useful tool for my university’s learning.

O_E4 Part of my university’s culture is that students can express their opinions and suggestions regarding the procedures and methods in place for carrying out tasks (homework, assignments, etc.).

Knowledge Transfer and Integrate (KT_I; 4 items

KT_I1 Teamwork is the usual way to work in my university.

KT_I2 Errors and failures are always discussed and analyzed in my university’s every levels.

KT_I3 I have the chance to express new ideas, programs, and activities that might be of useful to my university.

KT_I4 My university has tools (manuals, databases, files, organizational routines, etc.) that allow what has been learned in past situations to remain valid, although the students are no longer the same.

Table 3.4.

Items Measuring Academic Satisfaction

Construct Code Questionnaire Item

Responsiveness Academic Staff (RAS; 3 items)

RAS_1 Academic staff (professors, lecturers) communicate well in the classroom.

RAS_2 Academic staff (professors, lecturers) show positive attitude towards students.

RAS_3 Academic staff (professors, lecturers) have the knowledge to answer my questions.

Assurance (ASSU; 4 items)

ASSU_1 The staff (professors, lecturers, administrative, etc.) respect my confidentiality.

ASSU_2 Students are given fair amount of freedom.

ASSU_3 Students are treated equally with respect by the staff (professors, lecturers, administrative, etc.).

ASSU_4 My university values feedback from students to improve performance.

Academic Feedback ( A_F; 3 items)

A_F1 Academic facilities are adequate.

A_F2 Academic staff (professors, lecturers, administrative, etc.) allocate convenient time for consultation.

A_F3 Academic staff (professors, lecturers, administrative, etc.) provide feedback about my progress.

Empathy ( EMPA; 3 items)

EMPA_1 When I have academic problems, academic staff (professors, lecturers, administrative, etc.) show sincere attitude/involvement.

EMPA_2 Academic staff (professors, lecturers, administrative, etc.) are never too busy to respond to my request.

EMPA_3 Academic staff (professors, lecturers, administrative, etc.) deal with me in a caring manner.

Tangibles (TANG; 5 items)

TANG_1 My university has standardized and simple service delivery procedures.

TANG_2 My university has an ideal location with excellent campus layout.

TANG_3 My university has professional appearance/image.

TANG_4 My university physical facilities are visually appealing.

TANG_5 My university has up-to-date equipment.

Administrative Service (A_S; 7 items)

A_S1 Administrative staff promise to do something by a certain time.

A_S2 When I have a problem, administrative staff show sincere interest.

A_S3 Administrative staff are never too busy to respond to request.

A_S4 Administrative staff show positive work attitude towards students.

A_S5 Administrative staff communicate well with students.

A_S6 Administrative staff have good knowledge of the systems.

A_S7 I feel secure in my dealings with my university.

Academic Programs (A_P; 5 items)

A_P1 My university offers programs with flexible timetabling.

A_P2 My university offers highly reputable programs.

A_P3 Academic staff provide students individual attention.

A_P4 Academic staff are highly educated.

A_P5 Complaints are dealt with efficiently.

Table 3.5.

Items Measuring Demographic Data Profile

Variables Code Items

Degree 1 Mandarin study

2 Exchange program

3 Bachelor

4 Master

5 Postgraduate

University of Study 1 Name of the university

Period of time in Taiwan 1 Less than one year

2 One year

3 Two years

4 Three years

4 Four years

6 More than four years

Region of Origin 1 Africa

2 The Americas

3 The Caribbean

4 Asia

5 Oceania

6 Europe

7 Others

Financial Sponsorship 1 ICDF

2 MOFA

3 MOE

4 University Scholarship

5 Self-Sponsored

6 Others

Gender 1 Male

2 Female

(Continued )

Table 3.5. (Continued)

Variables Code Items

English Ability 1 Listening

2 Speaking

3 Reading

4 Writing

Chinese Ability 1 Listening

2 Speaking

3 Reading

4 Writing

Validity and Reliability

The validity and reliability of this research is tested by internal consistency and stability.

The Cronbach’s alpha was used for testing internal consistency. A common method for testing reliability is Cronbach’s assessment. According to Arambewela, Hall and Zuhair (2006), advised that the commonly accepted lower limit for Cronbach’s alpha is 0.70. In the table 4.1, all Cronbach’s values meet the requirement. According to Nunnally and Bernstein (1994), the composite reliability should be equal or higher than 0.7, so the composite reliability values are accepted. The table 4.1 demonstrated that all composite reliability values are above 0.7. The average variance extracted (AVE) should be equal or higher than 0.5, thus it meet with minimum requirement (Hair, Tatham and Anderson, 2006). As demonstrated in the table 4.1, all data are greater than 0.5, which means all data can be accepted. Moreover, in order to test individual items reliabilities, the loadings were examined. If the loadings are greater than 0.5, thus the results are accepted (Chin, 1998). Table 4.4 exhibited that all loadings are higher than 0.5. According to outcomes from PLS tests, all data meet with the minimum obligation of reliability and validity.

Partial Least Square (PLS)

The empirical data collected from the sample population was evaluated through Partial Least Square. PLS estimates path models using latent variables. It allows the simultaneous modeling of relationships among multiple constructs, or that it allows the analysis of a system of constructs. The objective in PLS is to “maximize the explanation variance, thus R2 and the significance of relationships among constructs are measures indicative of how well a model is

performing” (Bontis, 1998, p. 69). A PLS model comprises of a structural part, which reflects the relationship between the variables and a measurement component, which displays how the variables are related. SmartPLS 2.0 software will be employed to perform a confirmatory factor analysis and a path analysis. The analysis of the structural model were made by evaluating the coefficient of determination (R2), path coefficients, t-value (t) and bootstrapping. R square is used to explain the endogenous latent variables to the total variance. Chin (1998) proposed R2 values of .67, .33 and .19 are considered substantial, moderate and weak respectively. Path coefficients are used to judge the relationship between variables, determine the direction of the relationships and its significance. In PLS this value can be determined by bootstrapping the data and examining the resulting t-value. Hair et. al., (2011) defines the critical values in a two-tailed test to be weak when they are less than 1.65, moderate when they are between 1.65 and 1.96 and strong when they are equal or greater than 2.58. Bootstrapping is “a nonparametric approach to statistical inference that does not make any distributional assumptions of the parameters like traditional methods. It draws conclusions of a population strictly from the sample at hand” (Sharma and Kim, 2012, p.2). Accordingly, Wong (2010) stated that, PLS converted into a good alternative software analysis, when the following situations are encountered: sample size is small, applications have little available theory, predictive accuracy is paramount and correct model specification cannot be ensured. PLS is ideal in this study for the following reasons:

1. PLS can test the psychometric properties of the indices and provide better evidence for the existence of relationships.

2. The investigation of this model is exploratory in nature rather than confirmatory.

3. PLS has less stringent standards regarding sample size, distribution parameters, and levels of correlation between variables.

CHAPTER IV STUDY FINDINGS, ANALYSIS AND DISCUSSIONS

Pilot Test

Pilot study was conducted before collecting entire sample for the main study. The pilot test was conducted in order to check if the instrument is valid and the measurement is valuable to the main study. In order to conduct the pilot test, forty-nine samples were collected.

Nevertheless, the pilot data were examined by using smart PLS and the result presented for this study.

Table 4.1.

Cronbach’s Alpha, Composite Reliability, R Square Results for all Dimension (n =49)

Constructs Number of

Note. AS= Academic Satisfaction; KS= Knowledge Sharing; OL=Organizational Learning;

OT= Organizational Trust.

Table 4.2.

Path Coefficients Results for all Dimension (Pilot Study, n =49)

Path Original Sample(O)

Sample Mean(M)

Standard

Error(STERR) T-Statistics P Values

KS-AS 0.091 0.116 0.175 0.520 0.604

KS-OL 0.350 0.342 0.126 2.773 0.006

OL-AS 0.700 0.699 0.154 4.558 0.000

OT-KS 0.719 0.746 0.063 11.464 0.000 OT-OL 0.500 0.514 0.140 3.572 0.000

Table 4.3.

PLS Loadings (Pilot Test, n= 49)

Items Loading Items Loading Items Loading Items Loading

T_P .765 Iter_G .801 M_C .683 RAS .682

T_M .713 Itra_G .799 S_P .526 ASSU .795

O_H .677 K_D .770 O_E .875 A_F .732

RE .757 K_C .660 KT_I .859 EMP .855

Iden .805 TAN .767

A_S .917

A_P .931

Note. T_P= Trust in peers. T_M=Trust in management. O_H= Openness & honesty.

RE=Reliability. Iden= Identification. Iter_G= Inter-groups. Itra_G=Intra-Groups.

K_D=Knowledge donating. K_C=Knowledge colleting. M_C=Management commitment.

S_P= System perspective. O_E= Openness and experimentation. KT_I=Knowledge transfer integrate. RAS=Responsiveness academic staff. ASSU=Assurance. A_F=Academic feedback.

EMP=Empathy. TAN=Tangibles. A_S=Administrative service. A_P=Academic Programs.

Table 4.4.

PLS Hypotheses Testing Results (Pilot Study n=49)

Path Hypothesis β-path Adj. t-value Sig. Direction Null Hypotheses

OT  KS H1 .611 7.463 *** + Rejected

OT  OL H2 .388 3.082 *** + Rejected

KS OL H3 .429 4.384 *** + Rejected

KS AS H4 .091 .507 + Accepted

OL AS H5 .633 4.073 *** + Rejected

Note. OT= Organizational Trust; OL=Organizational learning; KS= Knowledge sharing; AS=

Academic Satisfaction.

*** p < .001.

According to Hair, Ringle, and Sarstedt (2011), the t-values for two-tailed test are 1.65, 1.96 and 2.58, which presented weak, moderate, and strong significance. Consequently, the relationship between each variables can be examined and accessed. Table 4.4 presented that there is a positive and significant impact between organizational trust and knowledge sharing (β =0.611, t = 7.463, P < .001). Thus, the null hypothesis 1 was rejected. Organizational trust has a positive and significant impact to organizational learning (β =0.388, t = 3.082, P < .001).

Thus, the null hypothesis 2 was rejected. Knowledge sharing has a positive and strong significant impact to organizational learning β =0.429, t = 4.384, P < .001). Thus, the null hypothesis 3 was rejected. Knowledge sharing has a positive and weak significant impact on academic satisfaction (β =0.091, t = 0.507, P < .05). Thus, the null hypothesis 4 was accepted.

Although, hypotheses 4, knowledge sharing does not have a direct impact to academic satisfaction for international students studying in Taiwan, it has indirect impact to academic satisfaction. Organizational learning has a positive and significant impact to academic satisfaction (β = 0.633, t = 4.073, P < .001). Thus, the null hypothesis 5 was rejected.

The figure 4.1 showed the results of the structural model that can explain 37%, 54%

and 49% of the variance in organizational trust, knowledge sharing, organization learning and academic satisfaction. The result demonstrated that in the organizational trust, the most dominant factor for international students studying in Taiwan is identification and the least dominant factor is openness and honesty. Regarding the knowledge-sharing dimension, the most dominant factor is knowledge sharing inter groups and the least dominant factor is knowledge colleting. In the dimension of organizational learning, the most dominant factor is openness and experimentation and the least dominant factor is system perceptive. When it comes to academic satisfaction concerning the service quality delivered by the universities, the most dominant factor for international students studying in Taiwan is academic programs and the least dominant factor is responsiveness academic staff.

Figure 4.1. PLS structural model (Pilot study, n=49).

Organizational Learning R2 =54%

-Management Commitment .683*** (7.107) -System Perspective .526*** (2.832)

-Openness and Experimentation .875*** (35.308) -Knowledge Transfer and Integrate .751*** (8.827) Organizational Trust

-Trust in Peers .765*** (7.866)

-Trust in Management .713*** (7.494) -Openness and Honesty .677*** (5.116) -Reliability .757*** (7.840)

-Identification .805*** (13.846)

Academic Satisfaction R2 =49%

Academic Satisfaction R2 =49%

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