This chapter introduces the research design and methodology. The research framework and the hypotheses to be tested in this study are presented. Besides, the research procedure for the researcher to follow is included. Details of data collection, the measurement instrument, validity and reliability, and the methods of data analysis are also explained.
Conceptual Framework
In order to conducting a valid and reliable study, the research framework for this study is constructed based on the background and purpose of the study described in chapter one, as well as literature review summarized in chapter two.
The TKICC Model (which stands for trust, knowledge sharing, customer relationship management and innovation capabilities) shown in figure 3.1 was developed based on the model of propensity to trust, interpersonal trust, and knowledge sharing of Mooradian et al.
(2006), the model of knowledge sharing, absorptive capacity, and innovation capability by Ho et al. (2012), and the model of customer focus, service process fit and customer relationship management profitability by Fan and Ku (2010).
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Figure 3.1.The TKICC Model of this study.
Research Hypotheses
The research hypotheses test the relationships among trust, knowledge sharing, customer relationship management, and innovation capabilities. Based on the literature review and research questions, the following null-hypotheses are developed for the purpose of testing the results:
H1: Trust has no effect on knowledge sharing.
H2: Knowledge sharing has no effect on customer relationship management.
H3: Knowledge sharing has no effect on innovation capabilities.
Trust
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Research Procedure
An orderly research procedure has been clearly outlined for the purpose of making an obvious steps for this study. The research was conducted following this research process:
Figure 3.2. Research procedure
Identify Research Questions and Hypothesis
Develop Theoretical Framework of the Study
Develop Research Method of the Study
Develop the Instrument
Translation and Expert Review of the Instrument
Conduct Pilot Study
Adjust Survey Instrument and Conduct Main Study
Data Analysis
Report Research Findings and Conclusions Review of Literature
Research Motivation
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Data Collection
The target population of this study are employees of Pan Asia, a human resources management and consulting corporation in Taiwan. The respondents must be fully employed within human resources management and consulting corporation. This means that volunteers and part-time employees are not included in the sample population. Besides, the researcher use on-line questionnaire to do the investigation.
There are 284 full-time employees in Pan Asia. The instrument was first tested on a group of 37 employees who participated in a pilot study in the target company. After refining the instrument through reliability and validity procedures, the main study was conducted by distributing 142 questionnaires within Pan Asia. Out of the 142 questionnaires 128 were received. The response rate was 90 percent. Namely, the sample size of the main study was 128 people.
Brief Introduction to Pan Asia
Pan Asia Human Resources Consulting Company was established in July, 1992. It is the first human resources company nationwide that obtained ISO 9000 Quality Management Systems Certification. By now, Pan Asia have already become multinational manpower resources organization serving as mediators for foreign laborers, mentors for short-time manpower dispatching, job bank, head-hunters for senior officers’ positions, and as service centers for executives’ business management educational programs. Pan Asia’s priorities are always taking in account their clients’ needs, being step ahead of their customers, and continuously providing the most comprehensive services.
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Pan Asia Human Resources Group is based in Taiwan, but operates also in mainland China, Philippines, and Thailand. Its group integrates eight institutions. By constant development and innovation, Pan Asia provides their customers with the most complete and effective services.
Departments of Pan Asia
Table 3.1.
Department Introduction
Department Name Introduction
Head-hunting department
Pan Asia head-hunting department HiHunter was established in the year 2000. After more than 10 years of consistent development, it has become a professional executive search firm for Taiwan and mainland China.
Dispatching Services department
Pan Asia manpower dispatching agencies provide customers with professional and customized dispatching services. The agencies are located in Taipei, Taoyuan, Xinzhu, Changhua, Taizhong, Jiayi, Tainan, Gaoxiong. This infrastructure allows the company to respond immediately to their customers' needs.
Education department
Pan Asia International Education Center provides educational courses that help companies to create the biggest value of their human resources. The center runs both short-term and long-term professional training courses and business management graduate degrees for corporate managers through the integration of world-class universities, professors and professional lecturer groups.
(continued)
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Table 3.1. (continued)
Department Name Introduction
Foreign Workers Services department
Foreign labor division was established in 1992, as the government allowed foreign manpower to Taiwan. The purpose of this department is to introduce foreign workers to domestic enterprises.
Pan Asia foreign workers department provide services such as planning, cost analysis and recommendations, agency assessment of the application procedures for the medium-term and high-quality workers, immigration-related procedures and testing, and even the introduction of foreign workers to work and life issues. This complete service allows customers not only to find effective solution for lack of manpower, but also to save costs on labor recruitment.
Corporate Training department
Department of training division provides professional corporate management consulting and training services. In the past few years, many cross-strait businesses profited from Pan Asia’s consulting guidance and internal training courses. Because of Pan Asia’s spirit of professionalism and enthusiasm, many of their previous customers return to seek their services again.
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Measurement Instrument
In this study, a quantitative approach was implemented since the research intend to collect numerical data, and analysis the statistical relationship between each variable. The research instrument consists of self-reported survey questionnaire. And the function of the research instrument is to collect the required data and to test the established hypotheses. A cover letter is used to briefly introduce the study, as well as its purposes is clearly stated. 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 related studies. The survey contains five parts: trust, knowledge sharing, customer relationship management, innovation capabilities, and respondent profile. The measurements are described in the following:
1. Trust (5 items): Adopted from Mooradian et al. (2006), the variables of trust consist of trust in peers (TiP) and trust in management (TiM).
2. Knowledge sharing (4 items): The measurement of knowledge sharing were adopted by Cummings’ (2004) scale and categorizing knowledge sharing into two types: intra-groups knowledge sharing, and inter-groups knowledge sharing.
3. Customer relationship management (22 items): Adopted from Ö ztaysi et al. (2011), the variables of customer relationship management (CRM) consist of win-back management (WbM), production/ service customization (P/SC), customer information management (CIM), referrals management (RefM), expansion management (EM), and termination management (TM).
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4. Innovation capabilities (15 items): Adopted fromLiao et al. (2007), the variables of innovation capabilities consist of product innovation (ProdI), process innovation (ProceI), and management innovation (MI)
5. The respondent profile: This section was added as a fourth section in order to provide a descriptive analysis of the survey respondents. This section contained demographic information such as participants’ age, gender, educational background, tenure, department, and job position.
Participants were asked to fill out the survey based on their experiences of working in their organization. The survey were presented with five-point Likert-type scales from ‘strong disapproval’ (1) to ‘strong approval’ (5).
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Construct Coding and Scales
The items used to measure the variables of this study are listed in Tables 3.2 to 3.6.
Each item was coded for later use in the statistical analysis of the data. Dummy variables were created to code part IV of the measurement instrument pertaining to demographics.
Table 3.2
Items Measuring Trust
Construct Code Questionnaire Item
Trust in peers (TiP; 3 items)
TiP1 If I got into difficulties at work I know my colleagues would try and help me out.
TiP2 I can Trust the people I work with to lend me a hand if I needed it.
TiP3 Most of my colleagues can be relied upon to do as they say they will do.
Trust in management
TiM1 Management at my firm is sincere in its attempts to meet the employees’ point of view.
(TiM; 2 items) TiM2 I feel quite confident that the firm will always try to treat me fairly.
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Table 3.3
Items Measuring Knowledge Sharing
Construct Code Questionnaire Items
Intra-groups (Intra; 2 items)
Intra1 I frequently share knowledge and information with my work teammates.
Intra2 I usually involve myself in discussions of various topics rather than specific topics with my teammates.
Inter-groups (Inter;
2 items)
Inter1 I frequently share knowledge with people even though he (or she) is not in my team.
Inter2 I usually involve myself in discussions of various topics rather than specific topics with colleagues from other work teams.
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Table 3.4.
Items Measuring Customer Relationship Management
Construct Code Questionnaire Items
Win-back management (WbM; 3 items)
WbM1 Our department has processes (or tools) to win-back valued lost customer.
WbM2 Our department has processes (or tools) to determine the value of lost customers.
WbM3 Our department has processes (or tools) to evaluate the cost of wining back the lost customers.
Production/ Service customization (P/SC; 3 items)
P/SC1 Our department has processes (or tools) to differentiate the customer acquiring efforts based on their value.
P/SC2 Our department has processes (or tools) to provide customized product/service to customers based on their value.
P/SC3 Our department has processes (or tools) to manage expectations of high valued customers.
Customer information
management (CIM;
6 items)
CIM1 Our department has processes (or tools) to get in connection with potential customers using various channels (e.g., e-mail, customer service center, phone, FAX, face-to-face, etc.).
CIM2 Our department has processes (or tools) to trace the status of our relationship with customers.
(continued)
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Table 3.4. (continued)
Construct Code Questionnaire Items
Customer information
management (CIM;
6 items)
CIM3 Our department has processes (or tools) to identify and affect different potential customers segments.
CIM4 Our department has processes (or tools) to identify non-profitable customers.
CIM5 Our department has processes (or tools) to evaluate the cost of retaining each customer.
CIM6 Our department has processes (or tools) to capture and integrate customer data from whole contact points (email, call-center, web site, FAX, face-to-face, etc.).
Referrals management (RefM; 4 items)
RefM1 Our department has processes (or tools) to manage customers’ referrals.
RefM2 Our department has processes (or tools) to trace customer referrals.
RefM3 Our department has processes (or tools) to motivate customers’ referrals.
RefM4 Our department has processes (or tools) to reward our customers based on their referrals.
(continued)
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Table 3.4. (continued)
Construct Code Questionnaire Items
Expansion
management (EM;
4 items)
EM1 Our department has processes (or tools) to maintain up-sell activities (providing higher level service, or more customized service) with customers.
EM2 Our department has processes (or tools) to maintain cross-sell activities (providing a variety of services) with customers.
EM3 Our department has processes (or tools) to increase the sales from potential customers with high value.
EM4 Our department has processes (or tools) to improve the relationship with potential customers with high value in order to provide cross-sell (providing a variety of services) and up-sell (providing higher level service, or more relationship with non-profitable customer (e.g. the cost of maintaining customer relationships is too high to have profit).
TM2 Our department has processes (or tools) to orientate the non-profitable customer to terminate their relationship with our company (e.g. delay in service).
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Table 3.5
Items Measuring Innovation Capabilities
Construct Code Questionnaire Items
Product innovation (ProdI; 5 items)
ProdI1 Our company often develops new services well accepted by the market.
ProdI2 A great majority of our company’s profits are generated by the new services developed.
ProdI3 The new services developed by our company always arouse imitation from competitors.
ProdI4 Our company can often launch new services faster than our competitors.
ProdI5 Our company has better capability in R&D of new services than our competitors.
Process innovation (ProceI; 5 items)
ProcI1 Our company often tries different operation procedures to hasten the realization of the company’s goals.
ProcI2 Our company always acquires new skills or equipment to improve the manufacturing operation process.
ProcI3 Our company can develop more efficient manufacturing process or operation procedure.
ProcI4 Our company can flexibly provide products and services according to the demands of the customers.
ProcI5 The new manufacturing process or operation procedure employed by our company always arouses imitation from competitors.
(continued)
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Table 3.5. (continued)
Construct Code Questionnaire Items
Management innovation (MI; 5 items)
MI1 Our company will change the division of work among different departments according to the needs of market management.
MI2 Our company’s department heads will adopt new leadership approaches to lead all staff towards task completion.
MI3 The new financial management system adopted by our company can effectively monitor the actual discrepancy between our performance and our goals.
MI4 Our company emphasizes innovative and creative capability when recruiting staff.
MI5 The new performance assessment method adopted by our company can enable department heads to gain a better picture of how far the staff has achieved the company goal.
Table 3.6.
Coding System for Demographics Variables
Variables Code Items
Age 1 20-25
2 26-30
3 31-35
4 36-40
5 Above 40
(continued)
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Table 3.6. (continued)
Variables Code Items
Gender 1 Female
2 Male
Educational background
1 High school
2 Bachelor
3 Master
4 Doctor/ Ph. D
Tenure 1 1 to 2 years
2 2 to 3 years
3 3 to 4 years
4 4 to 5 years
5 More than 5 years
Department 1 Head-hunting
2 Dispatching Services
3 Education
4 Foreign Workers Services
5 Corporate Training
6 Pan-Asia (headquarter)
Job Position 1 Manager
2 Administrative staff
3 Consultant/ Marketing staff
4 Assistant
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Translation and Face Validity
The questionnaire was translated from English to Chinese by the researcher. The translation was then revised by two bilingual experts. And then, a backwards translation of the questionnaire was implemented to double check the original meaning of the items was not lost through the translation process. Beside, for the convenience of respondents, the instrument stated each question in both English and Chinese.
Validity and Reliability
The validity and reliability is tested by internal consistency and stability. The Cronbach’s alpha is used for testing internal consistency. A common method for testing reliability is Cronbach’s assessment. Hair, Anderson, Tatham, and Black (1998) suggest that the generally accepted lower limit for Cronbach’s alpha is 0.70.The research instrument construct validity was examine through factor analysis. Explanatory factor analysis (EFA) will be chosen to test that the factors of each scale which are consist with studies.
Table 3.7.
Pilot Cronbach’s Alpha Results for all the Constrcts using SPSS
Constructs Number of items Cronbach’s Alpha
Trust 5 .867
Knowledge Sharing 4 .864
Customer Relationship Management 22 .957
Innovation Capabilities 15 .949
Note: n=37
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Through the reliability test using Statistical Package for the Social Science (SPSS) 20.0, the coefficient values of each construct show in Table 3.7. For trust (0.867), knowledge sharing (0.864), customer relationship management (0.957), and innovation capabilities (0.949). The Cronbach’s alpha of all the constructs in this study are higher than the acceptable level of 0.70 (Nunnally, 2010). As a result, the value indicates a high level of internal consistency and reliability.
Table 3.8. illustrates the Cronbach’s alpha reliability test coefficient value for each variable and detailed in this study. 0.897 for trust in peers of trust, and 0.846 for trust in management of trust. 0.790 for intra-groups of knowledge sharing, and 0.874 for inter-groups of knowledge sharing. 0.913 for win-back management of CRM, 0.832 for production/ service customization of CRM, 0.802 for customer information management of CRM, 0.870 for referrals management of CRM, 0.902 for expansion management of CRM, and 0.858 for termination management of CRM. 0.860 for product innovation of innovation capabilities, 0.893 for process innovation of innovation capabilities, and 0.874 for management innovation of innovation capabilities.
All the Cronbach’s alpha value of variables are higher than 0.70. Therefore, it can conclude that the scales for all the variables had a high level internal consistency as well as reliability.
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Table 3.8.
Pilot Cronbach’s Alpha Results for all the Variables using SPSS
Constructs Variables Number of items Cronbach’s Alpha
Trust Trust in Peers 3 .897
Win-back management 3 .913
Production/ Service
Referrals Management 4 .870
Expansion Management 4 .902
Termination Management 2 .858
Total 22 .957
Innovation Capabilities
Product Innovation 5 .860
Process innovation 5 .893
Management Innovation 5 .874
Total 15 .949
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Data Analysis Methods
Partial Least Squares (PLS) and multiple regression analysis are the two main data analysis methods in this study. PLS is used to analyze simultaneously the interrelationships among all the constructs. However, PLS is not able to evaluate each individual item’s impact on innovation capabilities. Therefore, multiple regression analysis is implemented to assess each item’s influence on the dependent variables. Partial Least Squares (PLS) and multiple regression analysis are complimentary to each other. The data for this research was analyzed using the software of SPSS 20.0 and Smart PLS. Before analysis, the data were coded using number sequence. The 46 trust, knowledge sharing, customer relationship management, and innovation capabilities questions were coded using a 5-point Likert scale.
Partial Least Squares (PLS) Structural Equation Modeling
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 (S.-Y. Lee, Kim, & Gupta, 2009).
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.
Bontis (1998) reports the benefits of using PLS for such studies:
The objective in PLS is to maximize the explanation variance. Thus, R² (r-squared) and the significance of relationships among constructs are measures indicative of how well a model is performing. The conceptual core of PLS is an iterative combination of principal components analysis relating measures to constructs, and path analysis
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permitting the construction of a system of constructs. The hypothesizing of relationships between measures and constructs, and constructs and other constructs is guided by theory.
The estimation of the parameters representing the measurement and path relationships is accomplished using ordinary least squares (OLS) techniques. The first step in PLS is for the researcher to explicitly specify both the structural model and the construct-to-measures relationships in the measurement model. The exogenous constructs are consistent with the idea of independent variables (antecedents). Similarly, the endogenous constructs are consistent with the idea of dependent variables (consequents). The constructs can be specified as “formative” indicators or “reflective” indicators. Formative indicators imply a construct that is expressed as a function of the items (the items form or cause the construct). Reflective indicators imply a construct where the observable items are expressed as a function of the construct (the items reflect or are manifestations of the construct). One looks to theory to decide on which type of epistemic or construct-to-measure relationship to specify. In this case, all constructs were “reflective” indicators.
Once specified, the measurement and structural parameters are estimated using a process of PLS, simple and multiple regressions. The process continues until the differences in the component scores converge within certain criteria (p. 69).
Data analysis is performed according to a two-stage methodology (Anderson & Gerbing, 1988) using Smart PLS. The first step in the data analysis was to establish the convergent and discriminant validity of constructs using the measurement model. The second step was to test the structural model.
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