物聯網下變革型領導對信賴、組織文化、知識共享、創新及組織績效之影響

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(1)The Effect of Transformational Leadership on Trust, Organizational Culture, Knowledge Sharing, Innovation and Organizational Performance in Internet of Things. by Hsiu-Wen Fan. A Thesis Draft Submitted to the Graduate Faculty in Partial Fulfilment of the Requirement for the Degree of. MASTER OF BUSINESS ADMINISTRATION Major: International Human Resource Development. Advisor: Cheng-Ping Shih, Ph. D.. National Taiwan Normal University Taipei, Taiwan June 6th, 2016.

(2) ACKNOWLEDGEMENT It is my honor to show my appreciation to people during the past two years who provided help with generosity and patience, which gave me a big hand during the struggling time for completing this thesis. I want to thank my advisor, Dr. Cheng-Ping Shih, to provide a myriad of help with my work from the very beginning to the end. You are the person who always stands by my side, give me helpful advices, and encourage me whenever I feel frustrated. In addition, I would like to show my deep respect and appreciation to my committees of thesis proposal and defense, Dr. Chih-Chien Lai and Dr. Pai-Po Lee, who are willing to attend to of the most important days in my school life and endeavor to share your knowledge and experience kindly. You are the light of wisdom leading me to adapt this thesis and make it even more completed. I would also like to express my gratitude to my friends and classmates. With your physical and mental help, I experienced the progress with less desperation and more confidence. Moreover, without the respondents’ help to fill out my questionnaires, I am not able to accomplish the grand work. Last but not least, I want to thank my family for the whole support in my life. You are the most indispensable ones fulfilling what I am and leading to what I have accomplished..

(3) ABSTRACT Considering global recession and the dropping market share of Taiwan industries nowadays, the concept of Internet of Things (IoT) has been provided. Internet of Things (IoT) shares the idea as a network of physical objects, thus establishes an integrated service system or platform to offer better services, attract customers and reduce costs. To achieve the goal of developing blue market and linking services with things by big data and cloud computing, innovation is an important element to change the present condition and improve the performance. To encourage people developing innovation in an organization, a successful leadership is indispensable, which influences trust and culture representing teamwork, and the efficiency of knowledge sharing and innovation. In this study, an integrated model was created and analyzed to understand how transformational leadership affects trust and organizational culture and how knowledge sharing and innovation are influenced and influence organizational performance as well by using Partial Least Squares (PLS) method. Distribution of questionnaires to 350 practitioners was completed with a response rate of 56 percent, and the data were investigated by three divisions: main study, information and communication (ICT) industry, and financial technology (FinTech) industry. The findings indicated that transformational leadership has a positive significant effect towards trust and organizational culture; trust has a positive significant effect towards knowledge sharing and innovation; organizational culture has a positive significant effect towards knowledge sharing and innovation; knowledge sharing and innovation have a positive significant effect towards organizational performance. The consequence discovered the characteristics of Taiwan industries and pointed out opportunities for improvement. Recommendations for further study were provided as well. Keywords: Transformational leadership, knowledge sharing, innovation, organizational performance. I.

(4) TABLE OF CONTENTS. ABSTRACT .......................................................................................................... I TABLE OF CONTENTS .....................................................................................II LIST OF TABLES ..............................................................................................IV LIST OF FIGURES ............................................................................................VI CHAPTER I INTRODUCTION .......................................................................... 1 Background of the Study ...................................................................................................1 Purposes of the Study.........................................................................................................7 Research Questions of the Study .......................................................................................7 Significance of the Study ...................................................................................................8 Delimitations and Limitations............................................................................................9 Definition of Terms ............................................................................................................9. CHAPTER II LITERATURE REVIEW ............................................................ 12 Transformational Leadership ...........................................................................................12 Trust .................................................................................................................................14 Organizational Culture .....................................................................................................16 Knowledge Sharing ..........................................................................................................18 Innovation ........................................................................................................................19 Organizational Performance ............................................................................................21. CHAPTER III METHODOLOGY .....................................................................23 Research Framework .....................................................................................................23 Research Hypotheses .......................................................................................................25 Research Procedure ..........................................................................................................26 Data Collection ................................................................................................................27 Measurement Instrument .................................................................................................28 II.

(5) Data Analysis ...................................................................................................................34. CHAPTER IV DESCRIPTIVE STATISTICS .................................................... 37 Sample Characteristics .....................................................................................................37 Descriptive Statistics Analysis .........................................................................................39. CHAPTER V MAIN STUDY ANALYSES AND PLS FINDINGS .................. 50 Correlations Analysis .......................................................................................................50 Validity and Reliability Analysis .....................................................................................53 Partial Least Square (PLS) Analysis ................................................................................54 Comparison Study among Main Study, ICT and FinTech Industries ..............................61. CHAPTER VI CONCLUSION AND RECOMMENDATIONS ....................... 72 Research Conclusion ........................................................................................................72 Recommendations for Taiwan ICT and FinTech Industries ............................................75 Recommendations for Further Research ..........................................................................76. REFERENCES.................................................................................................... 77 APPENDIX A: QUESTIONNAIRE ................................................................... 85 APPENDIX B: PILOT STUDY RESULTS...................................................... 100 Validity Test................................................................................................... 100 Reliability Test ............................................................................................... 105 Dropped Items ............................................................................................... 107 PLS Result for Pilot Study ............................................................................... 107. III.

(6) LIST OF TABLES Table 2.1. Leading Moral Components of Transactional and Transformational Leadership...13 Table 2.2. Definition of Trust ...................................................................................................14 Table 2.3. Definition of Innovation..........................................................................................20 Table 3.1. Summary of Instrument Used in This Study ...........................................................29 Table 3.2. Reliability of Instrument .........................................................................................30 Table 3.3. Validity of Instrument .............................................................................................31 Table 4.1. Sample Characteristics Based on Demographic Variables (N=196) .......................38 Table 4.2. Transformational Leadership - Mean and Standard Deviation ...............................40 Table 4.3. Trust - Mean and Standard Deviation .....................................................................42 Table 4.4. Organizational Culture - Mean and Standard Deviation .........................................43 Table 4.5. Knowledge Sharing - Mean and Standard Deviation ..............................................46 Table 4.6. Innovation - Mean and Standard Deviation ............................................................47 Table 4.7. Organizational Performance - Mean and Standard Deviation ................................49 Table 5.1. Correlation Analysis by PLS Algorithm (Main Study, N=196) ..............................51 Table 5.2. KMO and Bartlett’s Test of Sphericity Values (Main Study N=196) .....................53 Table 5.3. Reliability Test (Main Study, N=196) .....................................................................54 Table 5.4. Internal Consistency Reliability Analysis by PLS (Main Study, N=196) ..............55 Table 5.5. PLS Loadings (Main Study, N=196) ......................................................................55 Table 5.6. PLS Path Analysis Results (Main Study, N=196) ..................................................58 Table 5.7. Research Hypotheses Results..................................................................................58 Table 5.8. Summary of Model Direct and Indirect Effects by PLS (Main Study, N=196) .....60 Table 5.9. Total Effects According to Research Framework by PLS (Main Study, N=196) ..61 Table 5.10. PLS Loadings (ICT Industry, N=134) ..................................................................62 Table 5.11. PLS Path Analysis Result (ICT Industry, N=134) ................................................63 Table 5.12. Summary of Model Direct and Indirect Effects by PLS (ICT Industry, N=134) .65 IV.

(7) Table 5.13. Total Effects According to Research Framework by PLS (ICT Industry, N=134) ..................................................................................................................................................65 Table 5.14. PLS Loadings (FinTech Industry, N=62) .............................................................66 Table 5.15. PLS Path Analysis Result (FinTech Industry, N=62) ...........................................67 Table 5.16. Summary of Model Direct and Indirect Effects by PLS (FinTech Industry, N=62) ..................................................................................................................................................69 Table 5.17. Total Effects According to Research Framework by PLS (FinTech Industry, N=62) .......................................................................................................................................69 Table B.1. KMO and Bartlett’s Test of Sphericity Values (Pilot Test-Before Dropping Items) ................................................................................................................................................101 Table B.2. KMO and Bartlett’s Test of Sphericity Values (Pilot Test-After Dropping Items) ................................................................................................................................................101 Table B.3. EFA: Factor Loadings (Pilot Test, N=41) .............................................................103 Table B.4. Reliability Test (Pilot Test, N=41) ........................................................................105 Table B.5. Reasons for Dropping Items .................................................................................107 Table B.6. PLS Hypotheses Testing Results (Pilot Study, N=41) ..........................................108 Table B.7. PLS Loadings (Pilot Study, N=41) .......................................................................109. V.

(8) LIST OF FIGURES Figure 1.1. Nine Technologies Transforming Industrial Production .......................................3 Figure 1.2. Six Functions of Financial Services and Eleven Clusters of Innovation...............5 Figure 2.1. Model of Trust .......................................................................................................16 Figure 2.2. The Competing Values Framework .......................................................................17 Figure 2.3. The MOA Model ...................................................................................................19 Figure 3.1. Conceptualized LTCKIP model ............................................................................24 Figure 3.2. Simplified LTCKIP model ....................................................................................24 Figure 3.3. Research Procedures ..............................................................................................26 Figure 5.1. PLS Structural Model (Main study, N=196) .........................................................59 Figure 5.2. PLS Structural Model (ICT Industry, N=134) .......................................................64 Figure 5.3. PLS Structural Model (FinTech Industry, N=62) ..................................................68 Figure B.1. PLS Structural Model (Pilot study, N=41) .........................................................110. VI.

(9) CHAPTER I INTRODUCTION The chapter provides an overview of the research. To make the entire research more comprehensive, this chapter is established with background, purposes, questions, research significances; it is then followed by explanation of delimitations and limitations, along with definitions of those key terms in the framework.. Background of the Study In consideration of global recession and extremely competitive market nowadays, to initiate a new market becomes an inevitable issue. That is to say, for industries at the present time, searching for blue market became an indispensible challenge all over the world. To achieve the goal, considering things, process, or services that did not appear before has been turning into a crucial task, especially for Taiwan, which owns industries as information and communication technology (ICT) and financial technology (FinTech) to support its economy. Taiwanese also stood out in the first place as spending the longest time using the Internet by smart phones these years, proving it has already been an information-based society. Therefore, the concept of Internet of Things (IoT), which is one of the most well-known terms creating a prodigious sensation, is introduced in the next paragraph.. Internet of Things (IoT) Internet of Things (IoT) shares the idea as a network of physical objects, for instance, vehicles, manufacturing devices, buildings, and so on. The other side of the network is constructed with electronics, sensors, software, and network connectivity to confirm the hardware is in good condition and control its quality within network infrastructure remotely, transforming the physical world into data-based society with computer systems pursuing for efficiency, accuracy and economic benefit. In the company of the Internet, computers had. 1.

(10) changed into web, smart phones had changed into mobile internet, and people had changed into social network for now. In fact, since the transformation of future became unpredictable, people believe that the existence of the Internet will transform “things” into another “things” in the next decade. Intelligence service which can be developed and combined with hardware is the main point, meaning services are being more flexible, customized and unique that reduces costs at the same time tend to be the trend in the near future.. Industry 4.0 Industry 4.0 (German: Industrie 4.0) is defined as German vision of manufacturing in the future. It believes that with Smart Factories applying information and communications technologies (ICT) by Siemens, it can solve obstacles and challenges and reach goals of higher efficiency, lower costs, and better quality. Since Industry 1.0 that developed the water and steam water; Industry 2.0 represented the initiation of electricity; Industry 3.0 raised computing capabilities to Industry 4.0 which emphasized the importance of inter-connectivity of machines, processes and products, there is obviously a vital link among technologies and manufacturers in various industries. Industry 4.0 also provides the concept of cyber-physical system (CPS), including contemporary automation, data exchange and manufacturing technologies. A metaphor of this concept is an octopus, which indicates that Industry 4.0 is willing to connect the experts in each area and encourage them to cooperate with each other, with six design principles as implementation of this idea: interoperability, virtualization, decentralization, real-time capability, service orientation, and modularity. The concept has set up the goal as “Mass Customization”, by applying communication and connection among experts in each fields of manufacturing, factories in Germany are able to link the manufacturing process as a smooth and clear procedure with high quality products, which can be regarded as the ultimate goal for manufacturing industry. 2.

(11) Being in the fourth wave of technological advancement and the development of new digital industrial technology, there are nine technologies transforming industrial production in Industry 4.0 representing the connection among innovative technology and manufacturers. According to the figure below, Industry 4.0 is willing to apply the idea of machine-to-machine communication, which connects the movement and controls the situation of machines by machines in digital methods. For instance, automatic robots receive commands and react at the same time in a very complicated but flexible way; or when a machine with its concrete life cycle indicates the time of maintenance or reports its condition simultaneously to its manufacturer, it shortens huge time for people to contact and await each other, and successfully reduces cost due to less time on fixing the machines.. Figure 1.1. Nine Technologies Transforming Industrial Production. Adapted from “Industry 4.0: The Future of Productivity and Growth in Manufacturing Industries” by Rüßmann et al., 2015. Copyright 2015 by Boston Consulting Group [BCG].. 3.

(12) Taiwan’s Productivity 4.0 & Made in China 2025. Productivity 4.0 proposed by Taiwan, being a response to Industry 4.0, aims to achieve the goals of industrial transformation and value-added industries to construct a new generation of competitive products for the global market. Owning lots of contract manufacturing organizations (CMO), Taiwan could only earn meager profits and be unable to promote their own brands effectively, thus it determines to put Productivity 4.0 into practice. To elevate Taiwan's position in the global supply chain, Taiwan government has been planning to spend NT$36 billion (US$1.12 billion) over the next nine years as part of its Productivity 4.0 project since August, 2015. Productivity 4.0 involves getting hold of key and core technologies that allows Taiwan to achieve industrial transformation and enhance international competitiveness. Suggesting A-Team model as a standard of Productivity 4.0 and emphasize the importance of talent, which enhances the practicability and comprehensiveness of courses in universities and vocational schools. Made in China 2025 (MiC2025, previously called China Manufacturing 2025), is determined to be regarded as a new era for Chinese manufacturing industries. Having factories that produce large amount of components and products of vehicles and machines, China faces notions and concern of cheap and low-value manufacturing only as well. MiC2025 intends to solve China’s manufacturing problems with a comprehensive upgrading of fields based on Industry 4.0. In addition, as the first step in their three-stage plan, China aims to go beyond rival manufacturing hubs, for instance, Germany, the US and Japan by 2049.. Bank 3.0 and Digital Bank According to the aspect of Bank 3.0, banking will no longer be a physical location for business and services, but turn into a behavior based on its functions. The main idea is always banking but never at a bank, which indicates that banks should cooperate with technology 4.

(13) and pay attention to big data; interactive, personalized service will become more important, also the convenience and speed of trading system (King, 2012). In regard of Digital Bank, since the lifestyle had changed, services of banks should be completely renovated from aiming money to human. Social banking should emphasize the significance of convenience, society, big data, and cloud computing to link and calculate the customers’ needs and create valuable services (Skinner, 2014). As for financial technology (FinTech), World Economic Forum (WEF) had assembled experts around the world and concluded six functions of financial services and eleven clusters of innovation as Figure 1.2 presents, which claimed that the business innovation of platform based, data intensive, and capital light will create huge impact on the present financial industry. In accordance with the latest news, several banks in Taiwan are launching new services by the influence of FinTech, showing transformation in financial industries is turning its wheel.. Figure 1.2. Six Functions of Financial Services and Eleven Clusters of Innovation. Adapted from “The Future of Financial Services: How disruptive innovations are reshaping the way financial services are structured, provisioned and consumed” by Deloitte et al., 2015. Copyright 2015 by World Economic Forum [WEF]. 5.

(14) The combination of informatization and industrialization constructed an internet that connects people and people, machines and machines, people and machines, also services and services to accomplish comprehensive service, and the financial technology is improving itself by establishing networks. To enhance business innovation influencing the present appearance of process, technology and organization, a successful leadership is essential to motivate people to work together. Organizations nowadays begin to pay attention to more flexible and adaptive leadership to inspire members and encourage them to improve themselves. According to Bass, Avolio, Jung, and Berson (2003), leaders who are more flexible tend to confront and solve challenges with followers more efficiently, and it is essential for them to listen to people’s need and concern, also coach, train, inspire, support, and care for others as leadership behaviors (Bass &Riggio, 2005), which can be regarded as elements of transformational leadership being different from transactional leadership that emphasizes material influence as rewards or penalties. Since trust can be conceptualized as the loyalty to a leader (Podsakoff, MacKenzie, Moorman, & Fetter, 1990), previous studies have constructed models between leadership and trust; organizational culture is measured with indicators with leadership included as well (Cameron & Quinn, 2006), the two concepts related to human in an organization became obvious and noticed by people gradually. Knowledge management, especially knowledge sharing, is a new term among these decades, but with the synergy effect of innovation, it is given prominence and presents that to improve competitiveness of an organization nowadays, the perception to combine them is indispensible. In addition, innovation is proved to own highly correlation with organizational and business performance, which is a main point to investigate as well (Calantone, Cavusgil, & Zhao, 2002; Hult & Ketchen, 2001).. 6.

(15) Purposes of the Study Since the foremost purpose is to construct an integrated model, the study is willing to investigate the relationship between each two dimensions according to the framework. Hence, the purposes of this research are listed as follows: 1.. To explore the connections between transformational leadership, trust, organizational culture, knowledge sharing, innovation, organizational performance, which is efficient and reliable to Taiwan industries, an integrated model called LTCKIP model was developed by Cheng-Ping Shih and Hsiu-Wen Fan in this study.. 2.. To investigate Taiwan ICT and FinTech industries in need of improvement, and to provide suggestions for stakeholders on how to utilize and enhance transformational leadership and the other characteristics for the benefits of their institutions.. Research Questions of the Study Obtained from purposes of the research, the questions below were put forward to construct the framework in this study: 1.. Does transformational leadership have significant influence on trust or organizational culture?. 2.. Does trust have significant influence on knowledge sharing or innovation?. 3.. Does organizational culture have significant influence on knowledge sharing or innovation?. 4.. Does knowledge sharing or innovation have significant influence on organizational performance?. 5.. What can the stakeholders of Taiwan industries do to enhance innovation by transformational leadership for future development?. 7.

(16) Significance of the Study The present study is significant for both academics and practitioners. There are several main points of significance. First, considering globalization, rapid development of technology, and the high competitiveness nowadays, it is important to construct intimate relationship between people working together in order to enhance the possibility of innovation. Since human resource is the most important and primary resource of a company to expand its products and services, this study provides a view of the connection between the condition of supervisors leading their subordinates, trust and culture in the firm to display the condition of knowledge sharing and innovation which affects performance in Taiwan industries. Second, in view of the hyper-competitive and rapidly transforming situation of Taiwan industries mentioned above, knowledge management and creative development are becoming essential. The study provides the most difficult process of knowledge management, which is knowledge sharing and innovation as two main dimensions in the framework to measure the importance that effect performance of Taiwan industries, and observe the correlation among trust and culture inside. Third, although there are previous researches of each dimensions with either high correlation or negative results, this study proposed an integrated model of an overview investigating the complete relationships of leadership influencing attitudes of teamwork and creativity in Taiwan industries. Last but not least, regarding to the issue of manpower shortage and aging of population, it is necessary to emphasize the significance of cultivating and encouraging talented people, also avoiding brain drain simultaneously to achieve a new aspect to balance each other in the close future.. 8.

(17) Delimitations and Limitations Delimitations There are several delimitations in this study. It will be delimited in Taiwan industries, especially information and communication technology (ICT) and financial technology (FinTech) industry. In addition, the study focused on relationships among dimensions of transformational leadership, trust, organizational culture, knowledge sharing, innovation, and organizational performance according to the model constructed in this research.. Limitations The sample only consists of employees in ICT and FinTech industries in Taiwan, which indicates that the results might not represent all of the organizations, or even the entire industries in Taiwan. Nonetheless, this study in Taiwan ICT and FinTech industries may provide new and constructive concepts for those who are interested and tend to learn about the topic. The research was analyzed by quantitative study, which might not be able to know the opinion of respondents in more details, but enabled to observe the results with a macro perspective.. Definition of Key Terms Transformational Leadership (TFL) Theoretical Definition: Transformational leadership is a sort of leadership, which is apart from transactional leadership which emphasizes rewards and penalties. Leaders who lead with transformational leadership tends to encourage and inspire followers, coach and train people to solve challenging questions, also share the vision and goals to support people to pursue larger achievement, and develop the potential and capability of both leaders themselves and followers(Bass, 1991; Bass & Riggio, 2006). Operational Definition: Transformational leadership will be measured by a 20-item scale 9.

(18) adapted from Bass, Avolio, Jung, & Berson’s research in 2003, and the items are divided into five categories: individualized consideration (IC), intellectual stimulation (IS), inspirational motivation (IM), and idealized influence (attributes (IIA)/ behaviors (IIB)).. Trust (T) Theoretical Definition: The eagerness of people being vulnerable and show their helpless attitude and exception, which forces others to control them or provide solution to facilitate the target work or challenge as an important reaction to express the willingness of taking risks (Mayer, Davis, Schoorman, 1995). Operational Definition: Trust in this study will be examined by competence (C), openness and honesty (OH), concern for employee (CE), reliability (R), and identification (ID), which are 18 items in total (Shockley-Zalabak, Ellis, & Cesaria, 2003).. Organizational Culture (OC) Theoretical Definition: When defining an aspect to conduct business, there will be a complicated set of core values, assumption, beliefs, symbols and interpretations of an organization, which is regarded as organizational culture (Barney, 1986; Cameron & Quinn, 2006). Operational Definition: In this study, organizational culture will be measured by four categories of culture: clan culture (CC), adhocracy culture (AC), market culture (MC), and hierarchy culture (HC) with a 24-item scale from Cameron and Quinn (2006).. Knowledge Sharing (KS) Theoretical Definition: Knowledge sharing is regarded as the condition or receipt of task information, know-how, and feedback on the topic of a product or procedure (Hansen, 1999). Knowledge sharing can only be done smoothly and successfully when it is from one’s own 10.

(19) will in a practical case, which takes efforts and time (Gibbert & Krause, 2002), but presents a sort of interaction between people, also a behavior of process of knowledge management (Liu & Phillips, 2011). Operational Definition: Knowledge sharing will be measured with a 11-item scale, separated into three categories: motivation (M), opportunity (O), and ability (A) adapted from researches of Siemsen, Roth, and Balasubramanian (2008) as well as SohailandDaud (2009).. Innovation (I) Theoretical Definition: Innovation is regarded as an adoption of new ideas and actions (Jiménez-Jiménez & Sanz-Valle, 2011; Zaltman, Duncan, Holbek, 1973), which transforms not only products or process radically but value as well (Sher & Yang, 2005). According to Hult and Ketchen (2011), it helps organization to enhance its strengths and innovation itself becomes an organization’s competitive advantage at times. Operational Definition: There are 12 items examining innovation, and the items are divided into process innovation (PI), technical innovation (TI), and organizational innovation (OI) (Van der Panne, Van Beers, & Kleinknecht, 2003).. Organizational Performance (OP) Theoretical Definition: Organizational performance can be considered as the outcome of a procedure (Sawhney & Prandelli, 2000), which stakeholders and investors are paying close attention to the consequence (Emden, Yaprak, & Cavusgil, 2005). There are a variety of different aspects to measure organizational performance, for instance, organizational effectiveness, competiveness, development, innovation and so on (Lee & Choi, 2003). Operational Definition: Organizational performance is determined by 9 items separate into three categories of innovativeness (IN), financial performance (FP), and customer satisfaction (CS) according to Yang, Marlow, and Lu (2009). 11.

(20) Chapter II LITERATURE REVIEW In this chapter, main definitions and originals of each dimension in the research are presented.. Transformational Leadership Leadership is mainly seen as a material to effect employees, how a supervisor manages one’s subordinates, and trains people to improve their abilities or skills. Successful leadership carries out a satisfying result, which is important when it comes to project management, that is, being as a manager, selecting an appropriate leadership style may accelerate the process and efficiency of a project or goal, also solve problems appropriately as well (Gharehbaghi & McManus, 2003; Limsila & Ogunlana, 2007). Considering all of the various categories of leadership proposed by researchers nowadays, the most well-known two sorts of leadership could be regarded as transactional and transformational leadership. To be effective, the two different ways of leading employees are required to be decided by the circumstances, technology, and workforce (Bass, 1991). Transactional and transformational leadership leads to a variety of consequences according to its situation at the moment, sometimes transactional leadership satisfies followers in a direct way and constructs a highly identification of an organization (Epitropaki & Martin, 2005; Riaz & Hussain Haider, 2010; Wu, 2009), while transformational leadership encourages the development of followers themselves, making people more competent when encountering their tasks. The term of transformational leadership was first mentioned by Burns in 1978, that Bass and Avolio (1995) explained and developed the theory, which made the definition more completed. According to Bass (1991), leaders increase awareness and broaden the acceptance of subordinates’ attitude when facing their mission, also direct followers to perceive their self-interest and competencies to make progress of the group and themselves, it could be. 12.

(21) regarded as transformational leadership. Transformational leadership guides followers to the direction of what a leader or an organization anticipates, and inspires them to achieve higher goal than expected. (Bass, 1999; Pieterse, Van Knippenberg, Schippers, & Stam, 2010; Yukl, 1999). In this study, transformational leadership is set in the structural model as a main dimension. The table below according to Bass and Steidlmeier (1999) explains the factors and concerns of transformational leadership. Besides, in the questionnaire of this study, “Idealized Influence” will be separated into two parts: “Idealized Influence Attitude” and “Idealized Influence Behavior” in order to separate the words and action in this factor.. Table 2.1. Leading Moral Components of Transactional and Transformational Leadership Leadership Dynamic. Ethical Concern. Individualized Consideration. To confirm that whether followers are treated as ends or means, considering whether their unique dignity and interests are respected or not.. Intellectual Stimulation. To confirm that whether the leader’s program is accessible to dynamic transcendence and spirituality or is blocked as propaganda and rules to follow.. Inspirational Motivation. To confirm that whether the leader provides for true empowerment and self-actualization of followers or not.. Idealized Influence. To confirm that whether flattering and egoism on part of the leader dominates the situation and whether s/he is manipulative or not.. 13.

(22) Trust Concern for trust as a topic to discuss is increasing recently, which combines concepts from different areas and leads to new integrated consequences in each research fields. Although definition of trust has been developed and discussed as a variety of shapes, according to Mayer, Davis, and Schoorman’s (1995) concept, they presented their definition of trust as “the willingness of a party to be vulnerable to the actions of another party based on the expectation that the other will perform a particular action important to the trustor, irrespective of the ability to monitor or control that other party” (Mayer et al., 1995, p. 712).. Table 2.2. Definition of Trust Author. Year. Definition. Moorman, Deshpande, Zaltman. 1993. A willingness that one depends on an exchange partner who has high confidence in mind.. 1995. A willingness of a party to be vulnerable to the actions of another party based on the expectation that the party will do the particular behavior without the monitor or the control.. & 1995. Regarded as positive expectations to another person’s behavior.. Ellis & 2001 Shockley-Zalabak. Positive expectations that others’ actions will be based on experiences, roles, interdependencies and relationships.. Currall & Inkpen. The decision which is willing to depend on a. Hosmer. Mayer, Davis, Schoorman. &. 2002. partner with the anticipation that the partner will take action as the common agreement both sides agreed.. 14.

(23) Trust requires positive attitude for another team, which is regarded as a vital context to show confidence in one another, and is positively related to communication among team members (Palvia, 2009; Pinjani & Palvia, 2013). There is an important and specific point of trust to notice: it is not only the relationship when people are willing to solve problems and receive or give help, but an action that takes risks; in other words, it requires trustors (people who trust others) to devote the element of trust in the relationship with trustees (people who are trusted) to taking actions, receiving advices or suggestions, following the directions, and so on. Being willing to show their vulnerability and take risks of getting wrong information by mistake or being betrayed is one of the characteristics of trust as well. (Bachmann, 2001; Bachmann & Inkpen, 2011; Johnson-George & Swap, 1982; Mayer et al., 1995). Trust is a common integrated concept that impacts on the personal psychological history and institutional structure for entire groups, which acts as a major driving force for collaborative team behavior (Mayer et al., 1995; Rousseau, Sitkin, Burt, & Camerer, 1998). To confirm the factors of trustworthiness that effects how employees cooperate with each other in an organization, competence, integrity and benevolence emphasized by researchers that observe the relationship of trustees and trustors became indispensible in this research, which are vital to knowledge sharing as well (Alavi & Tiwana, 2002; Hall, 2001; Ipe, 2003; Mayer et al., 1995). According to Shockley-Zalabak, Ellis, & Cesaria’s theory (2003), five dimensions of trust will be used in this study to validate the existence of relationship between trust and knowledge sharing as well as trust and innovation: (1) concern for employees, to check if supervisors care about their employees and understand employee welfare; (2) openness and honesty, which allows employees to evaluate their own competency and whether they have courage to express opinion in front of supervisors; (3) identification, the consistency of connections and similar value with colleagues and supervisors; (4) reliability, to observe if supervisors keep their commitments and standards of work to employees; (5) competence, the 15.

(24) ability of colleagues and the efficiency of firm reaching goals, also the quality of organization’s products and services.. Concern for Employees. Openness and Honesty. Trust. Identification. Reliability. Competence Figure 2.1. Model of Trust. Adapted from “Measuring organizational trust: Cross-cultural survey and index,” by Shockley-Zalabak, Ellis, & Cesaria, 2003. Copyright 2003 by IABC Research Foundation.. Organizational Culture Organizational culture has been perceived in 1980s as one of the core values of managerial components, which influences innovativeness and flexibility, even financial performance in an organization, and firms with strong cultures lead to impressive performance (Deal & Kennedy, 1982; Peters & Waterman, 1982; Tichy, 1983). It varies with different definitions, and is one of the main reasons to determinate the result when a firm is changing its managerial structure and action (Linnenluecke & Griffiths, 2010). An organization should face its culture squarely, since culture not only correlated with its stakeholders (including employees, customers, suppliers, and competitors), but involves in. 16.

(25) values, beliefs, representations, symbols that defines how it engage business and the interaction among stakeholders. (Barney, 1986; Hofstede, 1997). Organizational culture is considered as an essential aspect in managerial transformation on the whole (Jung et al., 2009), including when determining the characteristics of the relationships of stakeholders and firms with high performance (Latham, 2008). Cameron and Quinn (2006) proposed a model of organization culture as Figure 2.2 presents, which indicates that there are four sorts of core values, which their criteria specify an organization with different characteristics.. Figure 2.2. The Competing Values Framework. Adopted from Diagnosing and changing organizational culture: Based on the competing values framework (p.46), by K.S. Cameron and R. E .Quinn, 2006, San Francisco, CA: Jossey-Bass. Copyright 2006 by Wiley. 17.

(26) In this study, the four core values are adopted to be indicators in the questionnaire and measure which culture the respondents are working in. Clan culture emphasizes doing works together and mentoring people, also the family-like, intimate interaction in the working circumstances; adhocracy culture focuses on being positive and aggressive, taking risk, doing works rapidly, and innovation; hierarchy culture owns its law in the organization, doing works right, keeping the process steadily and under control is the leader’s strategy and goal; market culture pays attention to results, achievements and consequences, thus makes the value of competition important in this sort of culture.. Knowledge Sharing Of all the process of knowledge management, knowledge sharing is regarded as the most difficult and challenging (Quinn et al., 1998) that takes lots of time and endeavors (Gibbert & Krause, 2002), which is especially crucial when providing information to clients or contribute to the results and advice of a project (Cummings, 2004). Past research has indicated that knowledge sharing has great effect on organizational performance (Argote & Ingram, 2000; Cummings, 2004; Gardner, Gino & Staats, 2012; Hansen, 2002). In addition, how people apply shared knowledge might affect the outcomes of knowledge capital that influences the efficiency of work, being claimed that sharing and applying knowledge should be regarded as entirely different concepts (Alavi & Tiwana, 2002; Dennis, 1996; Grant, 1996; Majchrzak et al., 2004). Based. on. the. behavioral. aspect. of. Lin. (2007). and. the. MOA. (Motivation-Opportunity-Ability) framework recommended by Blumberg and Pringle (1982), it has been a well-established model to test work performance and also knowledge sharing behavior now, thus the study will use the dimensions of MOA model to measure knowledge sharing in the goal organization. Motivation (Willingness) acquires the individual’s willingness to act, and if there is any reason for them to share knowledge (e.g. incentives, 18.

(27) promotions, recognition, appreciation, trust among people, and so on). Opportunity corresponds to the environmental or background systems and devices that influence actions, by confirming that are the structure, training programs and events effective to encourage knowledge sharing behavior. Ability determines that whether the skills or knowledge can be transferred and expressed successfully or not, which also affects consequence of knowledge sharing.. Capacity (Ability). Knowledge Sharing Willingness Opportunity (Motivation) Figure 2.3. The MOA Model. Adapted from “The missing opportunity in organizational research: some implications for a theory of work performance” by Blumberg & Pringle, 1982, Academy of Management Review, 7(4), 565. Copyright 1982 by the Academy of Management.. Innovation Discussions about innovation are increasing nowadays, especially for scientific fields and enterprises when creating objects new and thus attracts people’s interest. Innovation is regarded as the adoption of a new idea or behavior (Jiménez-Jiménez & Sanz-Valle, 2011; Zaltman & Duncan, 1973), which influences procedures and/or strategies leading to commercial success and possible market leadership, and renovates the definition and meaning of a product, service, and even value to an organization (Katz, 2007). Innovation is also defined as an application of new knowledge which provides a new product or service that 19.

(28) customers are willing to obtain (Porter, 2011). The following table has listed several definitions of innovation by researchers in the past decades.. Table 2.3. Definition of Innovation Author. Year. Definition. Thompson. 1965. The generation, acceptance, and implementation of new ideas, processes, products, or services, which is also the successful implementation of creative ideas within an organization.. Urabe et al.. 1988. Consisting of the generation of a new idea and its implementation into a new product, process or service. Moreover, it leads to the dynamic growth of the national economy and amplifies employment as well as to an establishment of profit for the innovative business enterprise.. Amabile et al.. 1996. The successful implementation of creative ideas within an organization.. Sher & Yang. 2005. Innovation is changing the product or process radically or incrementally, and the value as well.. Katz. 2007. Innovation is the successful generation, development and achievements of new and original ideas, which introduces new products, processes and/or strategies to a company or enhance current products.. Essmann. 2009. Innovation capability is the organizational means with which innovative outputs are generated.. Jiménez-Jiménez Sanz-Valle. & 2011. The adoption of a new idea and behavior.. 20.

(29) According to past researchers, innovation can not only create new concepts and objects, but lead to pure profit and high financial performance (Barney, 1991; Calantone et al., 2002; Deshpandé & Farley, 2004; Zahra, Ireland, & Hitt, 2000). Furthermore, when facing obstacles and the fast-changing market nowadays, innovation helps managers to solve problems (Hult, Hurley, and Knight, 2004) and enhances the competitiveness of an organization and makes it more powerful to economic growth (Hult & Ketchen, 2001; Tushman, Anderson, & O’Reilly, 1997). A variety of tools and factors were used to examine innovation in the past, while most of them adopted process innovation, organizational innovation and technological innovation into their studies. Progress innovation refers to putting new ideas and materials into procedure or service in an organization, which produces entirely new products and services that may also solve potential or present problems and conquer challenges (Damanpour & Gopalakrishnan, 2001). Organizational innovation, being different as the former, creates and constructs its original device, system, process, service, policy or program in order to adapt to the competitive circumstances outside the organization (Damanpour, 1991); technological innovation creates new products or services to customers by technology or market knowledge (Afuah, 2003).. Organizational Performance Most of the investors and stakeholders are concerned with the performance of an organization. To consider the definition of organization performance for especially business purpose, it presents the outcome of the previous achievement by the organization’s own interior standard (Emden, Yaprak, & Cavusgil, 2005). Elements from Balanced Scorecard (BSC) are applied as the factors to measure organizational performance, that the factors are adapted as indicators of innovativeness, financial performance, and customer satisfaction. 21.

(30) Innovativeness Due to the rapidly changing circumstances, especially for industries related to technology nowadays, to face challenges of increasing obstacles and this highly-competitive market, the organizational performance of a firm’s innovativeness becomes essential and indispensable. In addition, the items of this indicator correlate with knowledge sharing, which are able to show the relationship between knowledge sharing and organizational performance, thus prove whether the two dimensions are connected or not.. Financial performance In terms of reducing operational costs, sales growth rate, and profit rate, financial performance is measured in an organization that is in consider of its profit. In this study, the situation of financial flexibility, internal costs, and resources acquisition from respondents will be observed.. Customer Satisfaction People who accept the services and products from an organization are considered as customers in this study, which their satisfaction including service quality and the speed to response their need will be answered by employees’ perspectives.. 22.

(31) CHAPTER III METHODOLOGY In this study, quantitative approach is applied to observe the connection between each dimension and the outcomes of independent variables towards dependent variables. This chapter focuses on methodology with sections including conceptual framework, hypothesis, research procedure, data collection, measurement instrument, also data analysis methods, which will introduce the framework and hypothesis by presenting the correlations, make clear of the process when collecting data, and explain the reliability and validity of measurement instruments and methods to analyze data as well. The results of pilot test are presented to give an idea of further study and investigation, which were shown in Appendix B.. Research Framework Figure 3.1 and 3.2 presented the framework, regarded as LTCKIP model, in this study. Measurement instruments had explained the origins of the factors of each dimension, and most of the factors were adopted from former researchers’ study. The exception was transformational leadership, which was divided into five parts in multifactor leadership questionnaire (MLQ) after the proposal of Bass and Avolio in 1993 that claimed four factors. Idealized influence was separated into two parts: idealized influence attributes (IIA) and idealized influence behavior (IIB). Idealized influence attributes represents the attribution of charisma because of the positive characteristics of leaders, for instance, power perceived, focusing on higher-order ideals and values, and so on. These make followers gain more trust and confidence, which build a strong emotional link to their leaders. Idealized influence behavior prefers to act upon the values which leaders emphasize that are usually collective sense of mission and aspects.. 23.

(32) Trust (T) Knowledge Sharing (KS) Competence (C). H3. Motivation (M). Openness and Honesty (OH). Opportunity (O). Concern for Employee (CE). Ability (A). Reliability (R). H4. Identification (ID). H7. H1 Transformational Leadership (TFL). Organizational Performance. Individualized Consideration (IC). (OP). Intellectual Stimulation (IS) Inspirational Motivation (IM). Innovativeness (IN). Idealized Influence Attributes (IIA). Financial Performance (FP). Idealized Influence Behavior (IIB). Customer Satisfaction (CS). H2. H5. H8. Organizational Culture (OC) Innovation (I). Clan Culture (CC). Process Innovation (PI). Adhocracy Culture (AC) Market Culture (MC). H6. Technical Innovation (TI) Organizational Innovation (OI). Hierarchy Culture (HC). Figure 3.1. Conceptualized LTCKIP model.. H3 H1. T. H7 KS. H4. TFL. OP H5 H2 OC. I H6. Figure 3.2. Simplified LTCKIP model.. 24. H8.

(33) Research Hypotheses According to the research questions, literature review and framework, the research null-hypotheses are conducted as follows: H1: Transformational Leadership (TFL) has no effect on Trust (T). H2: Transformational Leadership (TFL) has no effect on Organizational Culture (OC). H3: Trust (T) has no effect on Knowledge Sharing (KS). H4: Trust (T) has no effect on Innovation (I). H5: Organizational Culture (OC) has no effect on Knowledge Sharing (KS). H6: Organizational Culture (OC) has no effect on Innovation (I). H7: Knowledge Sharing (KS) has no effect on Organizational Performance (OP). H8: Innovation (I) has no effect on Organizational Performance (OP).. 25.

(34) Research Procedure. Research Motivation. Review of Instrument. Review of Literature. Proposal Meeting. Identify Problems. Data Collection. Identify Research Questions and Hypotheses. Data Coding. Data Analysis Develop Theoretical Framework Conclusion and Suggestions Develop Research Method Report Completion Develop Instruments. Final Defense Translation and Expert Review of Instruments Revision Conduct Pilot Study Thesis Submission. Figure 3.3. Research Procedure.. 26.

(35) The pace of this study is structured in subsequent process as Figure 3.3 shown above. First, literature review and theoretical framework were achieved, and then research method and questionnaires were developed, which led to the following step of pilot study before thesis proposal. After proposal meeting for suggestions, data collection and analysis of main study were achieved, revision of former chapters, conclusion and suggestions for further study and research purposes were constructed into final thesis. Last, more revisions were finished after final defense of this thesis.. Data Collection The target samples of the study were aimed to be employees in Taiwan. The respondents who stood in ICT and FinTech industry were mainly considered to be chosen, and requirements for the employees in order to ensure this study are listed below: 1. The working experience of the respondent in present company should be more than 6 months. In order to make sure the competence of respondents, it was considered that the standard of six months includes the time period of three-month probation period to go through and another three months to fully understand his or her work. 2. The respondents are working in Taiwan currently. Moreover, for the privacy and security of the respondents, confidential information of each individual was for academic use in this research only.. Sampling Method In terms of sampling method, the study applied a non-experimental quantitative method to observe and implement the data. The synonym of non-experiment was regarded as correlation survey, which had less effect on samples and merely measured dependent variables of revelation to independent variable (Punch, 2014). Questionnaires were distributed online and by hard copies to respondents from ICT and FinTech industries. 27.

(36) Measurement Instrument The questionnaires were collected in English version and translated by the researcher into Traditional Chinese version. By using quantitative approach, this study examined those responses to the correlation between each dimension in the conceptual framework. The instrument was composed of 6 variables with a total amount of 99 questions, which was examined in pilot test with possibility to be reduced according to the outcome. The questionnaire consisted of seven parts as follows as Table 3.1 shows: part 1) transformational leadership; part 2) trust; part 3) organizational culture; part 4) knowledge sharing; part 5) innovation; part 6) organizational performance; and part 7) demographics. For part 1 to part 6, the questions must be answered completely by the respondents, and each item rated with a 5-point Likert Scale ranging from 1) Strongly Disagree to 5) Strongly Agree. Respondents answered part 7 by selecting one from the multiple options for each question as well. The validity and reliability of each item were recognized in the authors’ original work suitably and achieved various validations from prior studies. Part 1) transformational leadership, which was measured by multifactor leadership questionnaire (MLQ) and 20 questions were proposed by Bass and Avolio (1993); part 2) trust had 18 items from Shockley-Zalabak, Ellis, & Cesaria (2003); part 3) organizational culture owned 24 questions adopted from Cameron & Quinn (2006); part 4) knowledge sharing possessed questions adopted from Siemsen, Roth, & Balasubramanian (2008) and Sohail & Daud (2009); part 5) innovation had items from Van der Panne, Van Beers, & Kleinknecht (2003); part 6) organizational performance owned questions from Yang, Marlow, & Lu (2009). The validity and reliability of the entire items were tested in the pilot test. Moreover, peer reviews and expert review were utilized to preserve the validity of the instrument as well. Pilot test was also conducted initially to ensure the validity of each item before gathering the complete data for the study.. 28.

(37) Table 3.1. Summary of Instrument Used in This Study Part Variable. Items Reference. 1. Transformational Leadership (TFL). 20. 2. Trust (T). 18. 3 4. Organizational Culture (OC) Knowledge Sharing (KS). 24 11. Bass, Avolio, Jung, Berson (2003) Shockley-Zalabak, Ellis, & Cesaria (2003) Cameron & Quinn (2006) Siemsen, Roth, & Balasubramanian (2008);. 5. Innovation (I). 12. Sohail & Daud (2009) Van der Panne, Van Beers, & Kleinknecht (2003). 6 7. Organizational Performance (OP) Demographics. 9 5. Yang, Marlow, & Lu (2009) Designed by the author. Note. TFL= Transformational Leadership; T= Organizational Trust; OC= Organizational Culture; KS= Knowledge Sharing; I= Innovation; OP= Organizational Performance.. 29.

(38) Reliability and Validity Reliability Reliability of instrument corresponds to the external and internal consistency of measurement, while validity of instrument represents the scales measured in order to prove and make clear of what researchers have evaluated essentially (Williams & Monge, 2001). In this study, Cronbach’s Alpha and Average variance extracted (AVE) were measured in this study to test reliability according to Table 3.2.. Table 3.2. Reliability of Instrument Reliability Theoretical Meaning Type. How Reliability was Achieved. Reliability The steadiness or consistency It is considered acceptable that of the measure of a variable Cronbach’s Alpha value being above .70 Analysis (Neuman, 2011). when calculating each variable (Nunnally, 1978). Average variance extracted (AVE) is also taken into account. A cut-off value above or equal to .50 or higher is considered acceptable (Chin, 1998).. 30.

(39) Validity Four aspects for examining validity were presented in Table 3.3, not only the content of the questionnaires were adapted and tried to fit the respondents’ need to understand the questions, but Kaiser-Meyer-Olkin (KMO) and Bartlett’s test for Sphericity and factor analysis were measured as well.. Table 3.3. Validity of Instrument Validity Type. Theoretical Meaning. How Validity was Achieved. Face Validity. A type of validity measurement, which an indicator being reasonable as a measure of a construct when judging others, especially in the. The questionnaire is translated into Traditional Chinese by the researcher.. scientific area (Neuman, 2011). Content Validity. A type of validity measurement which requires a measure that represents all aspects of conceptual definition of a construct (Neuman, 2011).. Each item of the questionnaire refers to the definition of its variable, and is examined by two peer and expert reviews as well.. Criterion Validity. A type of validity measurement which relies on some independent, outside verification (Neuman, 2011).. The items of questionnaires are adopted from previous validated measures, and had been undergone pilot test initially.. (Continued) 31.

(40) Table 3.3. (Continued) Validity Type. Theoretical Meaning. How Validity was Achieved. Construct Validity. A type of validity measurement that applies multiple indicators with two subtypes, including how well the indicators of one construct converge or how well the. Construct validity in the study is established by applying convergent and divergent validity methods.. indicators of different construct diverge (Neuman, 2011).. Kaiser-Meyer-Olkin (KMO) and. Bartlett’s test for Sphericity are for the confirmation to the items that can be conducted after the former measure. By using Explanatory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA), convergent and divergent validity will be established obviously.. Face Validity Face validity is a type of validity measurement, which an indicator being reasonable as a measure of a construct when judging others, especially in the scientific area (Neuman, 2011). Considering the languages that the respondents use, the questionnaire is in English originally and translated into Mandarin.. Content Validity Content validity is a type of validity measurement which requires a measure that represents all aspects of conceptual definition of a construct (Neuman, 2011). In this study, every items of the questionnaire refers to a definition, and the measures represent their variables as well as dimensions.. Criterion Validity Criterion validity is a type of validity measurement which relies on some independent, 32.

(41) outside verification (Neuman, 2011). The entire questionnaire is adopted from previous validated instruments, and is examined by pilot test as well.. Construct Validity Construct validity is a type of validity measurement that applies multiple indicators with two subtypes, including how well the indicators of one construct converge or how well the indicators of different construct diverge (Neuman, 2011). Construct validity will be tested and. confirmed. by Explanatory Factor. Analysis. (EFA).. Before. applying EFA,. Kaiser-Meyer-Olkin (KMO) and Bartlett’s test for Sphericity will be accomplished, indicating the necessity and appropriateness of using EFA. Kaiser-Meyer-Olkin (KMO) Measure of Sampling Adequacy value specifies the appropriateness of applying factor analysis on data, that factor analysis will be considered as useful for those variables and items if KMO value is higher than .80 with an excellent result, since factors extracted from data account for the variance is better when being closer to 1.00 (Friel, 2010). A corrective action might be required if KMO is lower than .50, either to add other factors or items to the variables or to get rid of those that are not essential. In addition, as a remedy of low KMO value, reverse-coding of the negatively-worded items may also be a solution. Bartlett’s test for Sphericity clarifies the factuality of correlations between variables; by observing Bartlett's test statistic, chi-square value, and p-value (p-value must be larger than .05). Factor analysis can be conducted if the tests are proved with statistics going after the requirements of those values. Convergent and divergent validity can be explained by using Explanatory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). Explanatory Factor Analysis (EFA), applied to verify convergent validity, is responsible to be evidence for correlation between each item’s score and compare the consistency with total score of variables. To be consistent with previous study, the score of one item is expected to be larger than .40 (Kerlinger, 1986). 33.

(42) Furthermore, in order to make clear of divergent validity, Confirmatory Factor Analysis (CFA) is responsible for ensuring the statistics fit the entire threshold well.. Data Analysis Statistical Analysis The study uses SPSS 22 and SmartPLS software to analyze data, and presents descriptive statistics to express an overview concept of the consequence of the research.. Descriptive Statistics Without a probabilistic formulation, descriptive statistics are applied to portray the main features of a compilation of data quantitatively (Mann, 1995). It provides a better view to understand the data and where it comes from. To compare the population and sample, categorical variables, for instance, age, gender, educational background and length of employment, etc., frequencies and percentages will be used in this study. Descriptive statistics helps to clarify the considerable sample that represents the case study and identify the influential variable in this investigation. In this study, mean and standard deviation will be used in both pilot and main study.. Correlation Analysis A correlation analysis is used to explore the direction and strength of linear relationship between variables. The relationships between each variable and independent variable, which might be positive or negative, can be proved by correlation analysis. Nevertheless, it is important to emphasize that a high correlation coefficient may not imply absolutely that multicollinearity existed between the variables. As data being confirmed by CFA, it is also determined as distinct constructs; therefore, if the correlation coefficient value is high but owns verification by CFA, it can be considered as the variables are highly related, also the 34.

(43) value of regression can still be accepted.. Regression/Coefficient of Determination (R2) Coefficient of determination, or called as regression, will be applied to explain the endogenous latent variables to the total variance. Showing the percentage that how much data gathered can present the real situation of the variables. The higher the percentage is, the closer the data can explain and predict the variables in reality for the study. The structural model will be established by measuring the value of R2 of the latent variables, path coefficients and goodness of fit.. Structural Equation Modeling (SEM) Also called multivariate or multi-equation method, Structural Equation Modeling (SEM) is a statistical method confirming the relationships between interconnected variables of a research. SEM is usually applied to determine the competency and effectiveness of a model that explains its dimensions appropriately. Two core SEM techniques are relevant in the study: to perform CFA; and to perform causal modeling, or path analysis, that hypothesizes causal relationships among variables and measures the causal models with a linear equation system. Path coefficients are taken into consider to make clear of the relationship between variables and to determine the direction of the relationships and significance. SEM will be applied to get evidence to support or reject the hypothesis proposed in the beginning.. 35.

(44) Partial Least Square (PLS) PLS path-modeling algorithm is a sort of SEM technique developed by Herman Wold in 1975. Using a combination of principal component analysis, path analysis and a set of regressions, it also estimates path models by latent variable. PLS is an effective tool to predictions and theories, and is supportive for small sample analyses and complicated models. That is to say, PLS is helpful with exploratory analysis investigating whether relationships might exist among variables (Yu, Kim, & Kim, 2007) and is efficient for estimating causal models in myriad model and data situations.. 36.

(45) CHAPTER IV DESCRIPTIVE STATISTICS In this chapter, sample characteristics will be presented initially. In addition, it also presents descriptive statistics of the result which consists of the mean and standard deviation of every item in this study.. Sample Characteristics A total of 350 questionnaires were distributed online and by hard copy, while 196 questionnaires were collected and validated, leading the overall response rate as 56%. The survey was completed confidentially and anonymously by employees in either ICT or FinTech industries in Taiwan. The characteristics of the respondents are provided in Table 4.1, which is divided into categories of gender, age, highest level of education completed, working experience in present company, and working industry. Considering of gender, the percentage of respondents of male and female is close, each of the gender accounts for around 50%, showing the survey fairer in view of workforce in Taiwan. In addition, there is higher percentage for people whose age is among 31 to 40 years old (43.4%), following by 20-30 years old (26.0%), 41-50 years old (22.5%), and above 60 years old (1.0%); most of the participants attained a bachelor degree (62.8%), and population of master degree is not low (28.1%), which might represent the distribution of age and education of employees in ICT industry and FinTech industry (especially banking and service industries). In terms of working experience in present company, it is considered that the standard of six months includes the time period of three-month probation period to go through and another three months to fully understand his or her work, which formed the selections of range from half an year to over 10 years. Employment service over 10 years was the larger part of the responses in this survey (28.1%), followed by 1-3 years (21.9%), 3-6 years (17.9%), 6-10 years (17.3%), and half to 1 year (14.8%) respectively. Last but not least,. 37.

(46) this study focused mainly on ICT industry (68.4%), with a comparison of FinTech industry (31.6%).. Table 4.1. Sample Characteristics Based on Demographic Variables (N=196) Variable. Entries. Percentage. Gender. Male Female. 86 110. 43.9% 56.1%. Age. 20-30 years old 31-40 years old 41-50 years old. 51 85 44. 26.0% 43.4% 22.5%. 51-60 Above 60. 14 2. 7.1% 1.0%. Senior High Bachelor Master. 16 123 55. 8.2% 62.8% 28.1%. Ph. D.. 2. 1.0%. Experience (In present company). Half to 1 year 1-3 years 3-6 years 6-10 years Over 10 years. 29 43 35 34 55. 14.8% 21.9% 17.9% 17.3% 28.1%. Working Industry. ICT Industry FinTech Industry. 134 62. 68.4% 31.6%. Education. After a brief description of sample characteristics, descriptive statistics of the questionnaire items are proceeded to be presented in order to identify how the participants responded to the questions under study.. 38.

(47) Descriptive Statistics Analysis The following section offers a summary of the responses gathered for further research. The tables reflect perceptions of mean and standard deviation of each item in the questionnaire, ranging from “strongly disagree” (1) to “strongly agree” (5) by 5-point Likert scale measurement. However, only those items that were not dropped from analysis would be further elaborated.. Transformational Leadership Table 4.2 represents the mean and standard deviation of transformational leadership. It was measured by a 20-item scale, while two of them from inspirational motivation (TFL-IM1) and idealized influence attributes (TFL-IIA2) individually were dropped in pilot study. In regard to the construct of transformational leadership, the respondents showed high agreement in TFL-IC3 (M=3.64), which corresponds to “My direct supervisor considers an individual as having different needs, abilities and aspirations from others”, indicating that the participants tend to choose “agree” in regard to this item. The lowest score is one of the dropped items TFL-IIA2 (M=3.05) that claims “My direct supervisor goes beyond self-interest for the good of the group”, and the second lowest score is TFL-IM3 (M=3.07) representing “My direct supervisor articulates a compelling vision of the future” that the respondents answered fairly “neutral” on this item. The standard deviation of TFL-IC1 (SD=1.08) and TFL-IIA2 (SD=1.08) obtain the highest score, explaining that situation might be rather different in different industries or companies. The result implies that some of the supervisors of the employees might give them fully respect independently, but they might not possess enough concepts of common good or abundant vision in this competitive global world.. 39.

(48) Table 4.2. Transformational Leadership - Mean and Standard Deviation Code. Items. Mean. SD. TFL-IC1 TFL-IC2. My direct supervisor spends time teaching and coaching me. My direct supervisor treats others as an individual rather than just as a member of a group. My direct supervisor considers an individual as having different needs, abilities and aspirations from others. My direct supervisor helps others to develop their strengths. Average of Mean. 3.22 3.56. 1.08 .98. 3.64. .93. 3.40 3.45. 1.04. My direct supervisor re-examines critical assumptions to question whether they are appropriate. My direct supervisor seeks differing perspectives when solving problems. My direct supervisor gets others to look at problems from many different angles. My direct supervisor suggests new ways of looking at how to complete assignments. Average of Mean. 3.46. .92. 3.59. .88. 3.38. .89. 3.46. .92. My direct supervisor talks optimistically about the future. My direct supervisor talks enthusiastically about what needs to be accomplished. My direct supervisor articulates a compelling vision of the future. My direct supervisor expresses confidence that goals will be achieved. Average of Mean. 3.49 3.47. .98 .88. 3.07. 1.07. 3.54. .79. TFL-IIA1. My direct supervisor instills pride in me for being associated with him/her.. 3.30. 1.04. TFL-IIA2*. My direct supervisor goes beyond self-interest for the good of the group. My direct supervisor acts in ways that builds her/his respect. My direct supervisor displays a sense of power and confidence. Average of Mean. 3.05. 1.08. 3.28 3.57. 1.00 .96. TFL-IC3 TFL-IC4 TFL-IS1 TFL-IS2 TFL-IS3 TFL-IS4. TFL-IM1* TFL-IM2 TFL-IM3 TFL-IM4. TFL-IIA3 TFL-IIA4. 3.47. 3.39. 3.30 (Continued). 40.