Can E-Learning System Enhance Learning Culture in the Workplace? A Comparison among Companies in...

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Can E-Learning System Enhance Learning Culture in the

Workplace?

A Comparison among Companies in South Korea

Journal: British Journal of Educational Technology

Manuscript ID: BJET-0435-Oct-2013-OMS.R1

Manuscript Type: Original Manuscript

Date Submitted by the Author: 19-May-2014

Complete List of Authors: Yoo, Sun Joo; Samsung SDS, HR consulting part

Huang, Wenhao; University of Illinois, Human Resource Education; University of Illinois, Educational Psychology

Keywords: Empirical, Quantitative research, e-learning

British Journal of Educational Technology submitted article


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What is already known about this topic · Information technologies can support learning, performance development, and organizational development in the workplace. · E-Learning Systems support employees’ learning and performance in the workplace. · Technology will not be worthwhile if users do not accept them cognitively and affectively.

What this paper adds · Information technology does not guarantee workplace learning without utilization by employees. · E-Learning System in company A and C can promote the development of learning organization by supporting empirical data sets of South Korean companies. · E-Learning System in company B did not affect the development learning organization.

Implications for practice and/or policy · A holistic perspective is necessary to integrate technologies into the workplace for the creation and sustainability of a learning organization. · Adopting information technology can be a viable intervention for organizational development. · Adopting information technology is a complex process that is related to psychological, organizational, and systems variables.

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Can E-Learning System Enhance Learning Culture in the Workplace? A Comparison among Companies in South Korea

Abstract How organizations need to act in order to develop their learning capacities has always been a focal interest of research and practice in the workplace. In practice, E-Learning System is often utilized to foster professional development, as it is capable of delivering information and knowledge to individuals across organizations. However, the effect of E-Learning System on fostering the development of learning organizations in South Korean companies remains unsubstantiated in empirical research. Hence a total of 327 data sets from three Korean companies (A, B, and C) were analyzed in this study to investigate research question that utilizing E-Learning System can facilitate the process to become learning organizations. The results showed that only E-Learning System of company A and C, not of company B, facilitated the development of learning organizations. The study concluded that employees’ acceptance levels towards E-Learning System must be considered in order to effectively promote long-term implementation of E-Learning System leading to the development of learning organizations.

Key words: e-Learning, technology, learning culture, learning organization, workplace, South Korea

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Introduction

Technology makes it possible to create, save, and share knowledge in the workplace as knowledge is the key to an organization’s success (Mladkova, 2007). Furthermore, Adopting information technology is essential for organizations because it influences work performance, organizational culture, and organizational development (Daghfous, 2004). In South Korea, the E-Learning System represented technological solutions to support employees’ learning across various organizations in the workplace (Clark & Meyer, 2011; Lee & Suh, 2003) which might be described as the delivery of multiple stand-alone courses, which do not require an instructor’s physical presence, and learners control the learning process (Byun & Lee, 2007; Lee, Yoon, & Lee, 2009). Although E-learning has been a common intervention in developing learning organizations in the workplace of South Korea, few studies have investigated its effects on the development of learning organizations. Hence, many integration-related organizational issues remain unexplored. This study addresses this deficiency by investigating how employees’ perceptions of E-Learning System could influence the perceived dimensions of a learning organization.

Literature Review

Learning Organization A learning organization has predictable effects on job performance, job satisfaction, and the implementation of technology in the workplace. A learning organization is defined as an organization in which employees continually develop their competencies to achieve performance by learning with colleagues (Senge, 1990). Garvin (1993) also defined it as an organization that facilitates employees’ learning and transfers itself continually. King (2001) focused on developing and using an organization’s information and knowledge capabilities in order to create higher-valued information and knowledge. This was done in an effort to change employees’ behaviors and improve bottom-line results. Said another way, a learning organization focuses less on the present or short-term goals than on future ones, considering long-term strategies (Müller, 2011). The collective concept of learning organization entails sharing knowledge and enabling opportunities at individual and organizational levels. Presently, information technology (IT) provides a critical way to deliver information and knowledge within organizations as well as support employees’ learning opportunities overall. Some scholars explicitly referred to the potential of information technology for sharing knowledge and developing a mutual understanding (e.g., Pedler, Burgoyne, & Boydell, 1991). Chen and Hsiang (2007) argued that E-learning should help nurture a learning organization and foster an organizational culture based on knowledge sharing.

E-Learning systems in the Workplace According to Benson, Johnson, & Kuchinke (2002), information technologies in global organizations have been used to support learning, enhance performance development, and promote organizational development and growth. This advancement in technology also had a significant influence on recent training and learning experiences among employees in South Korean companies (Lim, 2007). For example, the rate of corporations in South Korea that implemented ELS was more than half (63%) in 2011 (National IT Industry Promotion Agency, 2011). Approximately 52.8 % of individuals in South Korean corporations participated in E-learning (NIPA, 2011). Moreover, E-Learning Systems are gaining in popularity in the workplace due to its many advantages. The E-Learning System provides employees with flexible access to learning contents regardless of the location of the workplace, gender, or cultural differences (Biech, 2008; Jia, Wang, Ran, Yang, Liao, & Chiu, 2011). Additionally, E-Learning Systems can support learning while creating, sharing, and transferring knowledge across organizations (Liebowitz & Frank, 2011). Further, E-Learning Systems enable organizations to update their capabilities worldwide and deliver a consistently high quality of learning materials in various formats. E-Learning Systems enable users to share their knowledge and experience, accumulate knowledge assets, and build knowledge communities for organizations and individual employees as well (Jia et al., 2011). These knowledge communities and the availability of knowledge, can contribute to greater organizational performance when E-Learning Systems are utilized properly (Gregg, 2007).

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The Utilization of E-Learning System Although organizations have developed advanced technology to support employees’ learning experiences and performance, it will not be worthwhile if users do not accept and use technology in the workplace (Venkatesh, Morris, Davis, & Davis, 2003). To maximize the use of technology, employees’ acceptance level is important Although technology is largely pervasive in the workplace, work productivity could remain unchanged due to a low level of acceptance regarding technology (Keil, 1995). This unfavorable outcome results from an organizational myth that employees would use technological systems once they were built (Lee et al., 2009; Rosenberg, 2006). Many organizations in South Korea fall victims to this myth since the implementation of information technology was not as straightforward as the organizations expected it to be. For example, Lee and colleagues (2009) conducted a study on learners’ acceptance of an E-Learning System in South Korea and revealed that the success of E-Learning System relied heavily on users’ perceptions of the usefulness, playfulness and perceived ease of use with the technology. The acceptance rate among technology system users can influence the implementation of information technology (Liaw, Huang, & Chen, 2007). Therefore, understanding an individual’s usage and acceptances or reservation toward information technology, such as E-Learning System, is important in the workplace. This study adopted the Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh, et al., 2003) to understand E-Learning System users’ acceptance level.

UTAUT explains employees’ intention to use technology. It is validated by Venkatesh and colleagues (2003) and consists of eight constructs: performance expectancy, effort expectancy, social influence, facilitating conditions, self-efficacy, anxiety, behavioral intention to use, and attitude toward using technology. The framework was designed to examine information technology integration opportunities and barriers in both academic and workplace settings. For example, it has been used to evaluate the acceptance of E-Learning Systems (Borotis, Poulymenakou, 2009; Lee et al., 2009; Lee, Hsieh, & Ma, 2010; Park, 2009) and it was validated in cross-cultural settings (Oshlyansky, Cairns, & Thimbleby, 2007). However, UTAUT studies that focus on the development of a learning organization derived from workplace settings remains scarce. Purpose of the Study It is crucial for organizations to enhance their capabilities for effective learning by using information and communications technology (Wang, Moormann, & Yang, 2011). Thus, employees’ use and perceptions of E-Learning System should influence the perceived dimensions of a learning organization (Ungaretti & Tillberg-Webb, 2011). While earlier research offered some support in this regard (e.g., Marchi, 1999; Vongchavalitkul et al., 2005), there is a paucity of research on learning organizations’ characteristics in relation to the use of technology systems (e.g., the Internet). Thus, this study responds to the following research question: How does the utilization of an E-Learning System in the workplace impact the development of its learning organizations? Considering the wide implementation of E-Learning Systems in South Korea that lack empirical support, this study was situated in three Korean companies with the intention to improve the effects and efficacy of the E-Learning System.

Method

Research Setting and Participants The research setting consisted of workplaces in South Korea. All data were collected via an online survey. Since the purpose of this study is to investigate the impact of the E-Learning System on the development of learning organizations, all data were collected from companies that are using the E-Learning System. Through convenience sampling, this study targeted three companies in South Korea, which are in the IT service industry and the media service industry. Generally, employees who work for service companies tend to be transferred to separate workplaces among various job locations. Through technology, three companies can share a great amount of information. Employees (i.e., entry level positions, assistant managers, managers, and senior managers) who have at least more than one-year of work experience in these three companies were invited to participate in this study. However, executives from the three companies were excluded due to conflicts of interest. Their participation is strictly voluntary. Respondents were fluent in Korean, the language in which the survey was translated. Study site A

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Company A, comprised of 1350 employees in South Korea, was selected as the site for studying the information and communication technology service industry. Starting in 1998, the employees used the E-learning System. The average learning expenditure spent per employee was $2,000 (per year). Generally, 1000 E-learning courses have been offered to employees, and they have spent at least 120 to 150 hours a year for their work-related learning. The average hour of learning depends on employees’ position. The portion of E-learning has been growing (70%) compared to that of face-to-face training (30%). In 2011, the reason for this change could be accounted for by the characteristics of the IT industry. Specific courses, such as leadership and IT courses were provided as E-learning courses. Study site B Company B is an information communication and technology service. It employs 580 members of staff. The company offers various services, such as systems management, mobile services, data center service, system integration, and information strategic consulting. Employees of Company B have a right to learn at least 40 hours per year for their job-related development. Generally, E-learning courses were shared from a conglomerate and more than 200 E-learning courses are offered per month. The conglomerate has a plan to update the E-Learning System. Study site C A regional media service company of 890 employees in South Korea was selected as the site for this study. The media service company has been utilizing the E-Learning System as a training tool because it has major offices in Seoul, Incheon, Changwon and Masan, Kimhae and Pusan city. This company spent approximately one billion dollars in 2010 to train employees. The company spent $1000 on each employee to learn per year and/or participate in training programs. Since 2001, 30% of the training expenditure was used for E-learning. The average number of learning hours for each employee was around 80 per year. The company offered around 900 E-learning courses, and each employee is encouraged to take at least one E-learning course a month. An average of 30 to 40 employees take E-learning courses through the intranet every month. See Table 1 for the comparison among the three companies.

Insert Table 1

Instrumentation

The online survey questionnaire, based on a 7-point Likert scale, consisted of (1) learning organization, (2) the behavioral intention to use and the acceptance towards E-Learning System, and (3) participants’ demographic information. See Appendix A.

The dimensions of the learning organization questionnaire (DLOQ) This instrument was developed to measure the extent to which a company meets certain criteria as a

learning organization (Watkins & Marsick, 1996, 2003). The instrument was supported by strong reliability and validity in prior studies (Ellinger et al., 2002; Harnandez, 2003; Kumar & Idris, 2006; McHargue, 2003; Yang, 2003; Yang, et al., 2004; Zhang et al., 2004). See Table 2. DLOQ has also been validated in a Korean context (Park, 2008; Song, et al., 2009). In this study, the short version of the DLOQ with 21 items was used due to its high reliability score (Alpha = .93) (Yang, 2003).

Insert Table 2

UTAUT Instrument UTAUT was applied to measure the technology acceptance levels toward ELS. UTAUT is measured by

eight constructs, which includes performance expectancy (4 items), effort expectancy (4 items), social influence (4 items), facilitation conditions (4 items), anxiety (2 items), self-efficacy (4 items), attitude towards using technology (4 items) and behavioral intention (3 items). See Table 3 for construct definitions. The reliability and validity of the instrument has been reported by numerous studies (Oshlyansky et al., 2007; Venkatesh & Davis, 2000) with strong reliability (Alpha > .80) (Venkatesh et al., 2003). In addition, the instrument has been validated in cross-cultural settings (Oshlyansky et al., 2007).

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Insert Table 3 Data Collection The data were collected for eight weeks in early 2012 via online surveys. The survey was distributed to 1150 employees within the three companies by their Human Resource Development (HRD) staff and 334 surveys were returned (response rate 29%). See Table 4 for details on the number of participants and response rates among the three companies.

Insert Table 4 Data Analysis The data analysis consisted of the following steps. First, the data were evaluated to check normality (Hair, & Rolph, 1998). Second, descriptive analyses were conducted to study the demographic information of the participants and understand the characteristics of the data, such as means, standard deviation, frequency, and distribution. Third, a data reduction analysis was conducted, which included factor analysis and reliability testing. Fourth, to answer the research question, the data were analyzed using multiple regressions. Participants’ gender, age, positions held, educational level, work experiences, and their E-Learning Systems experiences were controlled to remove potential influences of the aforementioned independent variables on the relationship between technology acceptance toward E-Learning System and learning organizations (Newton & Rudestam, 1999).

Results Of the 334 returned datasets, two cases were deleted due to errors. A normality test and Lavene’s test were performed to further exclude five cases. In the end, 327 completed datasets were used for further analyses. See Table 5 for participants’ demographics.

Insert Table 5

Exploratory Factor Analysis and Reliability

UTAUT toward E-Learning System

Principal Component Analysis (PCA) was applied to validate and reduce the variables. An initial factor extraction with a varimax method was performed and three factors remained. The PCA (KMO =. 920) extracted four components with eigenvalues greater than 1.00 and accounted for 69.2% of the variance. To verify the four factors (See Table 6), a parallel analysis (PA) was conducted. Two factors (16 items) were eventually retained for further data analysis. The overall reliability (Cronbach’s Alpha) of UTAUT toward the E-Learning System is .94 with the internal consistencies of the instruments varying from 0.93 to 0.94. See Table 7.

Insert Table 6

Insert Table 7

The Dimensions of Learning Organizations A principal component analysis (PCA) of DLOQ was conducted to validate and reduce the variables. An initial factor extraction was conducted according to PCA (KMO = .951), and rotated according to the varimax method. The PCA extracted two components with eigenvalues greater than 1.00 and accounted for 59.9% of the variance. To verify the two factors, a parallel analysis (PA) was conducted (Watkins, 2010). Only one factor (10 items) was eventually used for further analysis. See Table 8. The overall reliability (Cronbach’s Alpha) of DLOQ is 0.929, which is satisfactory. See Table 9.

Insert Table 8

Insert Table 9 Descriptive Statistics The mean score of the learning organizations was 4.81 (7 Likert-scale), Factor 1 (Identity/trust) and factor 2 (Structure) showed a relatively high score (4.46, 4.76, respectively). Factor 2 (Facilitating Conditions/Effort Expectancy) of E-Learning Systemshowed a relatively high score (5.03).

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Insert Table 10

Results Based on Data from All Three Companies Overall, the participants’ perceptions of E-Learning System, as an independent variable based on UTAUT affected the perceived learning organization (R²=.214). In particular, factor 1 (Performance Expectancy/Attitude) and factor 2 (Facilitating Condition/Effort Expectancy) influenced the perceived dimensions of a learning organization. Thus, the results indicated that employees’ perceptions of E-Learning Systems might influence perceptions toward the development of learning organization (see Table 11).

Insert Table 11

Results Comparison among Individual Companies A total of 80 datasets from each company were randomly selected via SPSS to conduct this comparison. The datasets from each company were examined to answer the research question. As Table 12 shows, employees’ perceptions of E-Learning System in Company A affected the learning organization (F=3.480, df =3,76, p <. 05). In particular, factor 2 (Social Influence) significantly affected the learning organization (Beta = .184).

Insert Table 12

As Table 13 shows, employees’ perceptions of E-Learning System in Company B, however, did not affect the perceived learning organization (F=2.445, df =2,77, p =.09). Thus, employees’ perceptions of E-Learning System did not influence the perceived dimensions of a learning organization in Company B.

Insert Table 13

Finally, employees’ perceptions of E-Learning System in Company C did affect the learning organization perceptions (F=41.605, df =1,78, p <.05). In particular, factor 1(performance expectancy/Effort expectancy/facilitating condition) significantly affected the perceived learning organization (Beta = 0.847). Thus, the results indicated that employees’ perceptions of E-Learning Systeminfluenced the perceived dimensions of a learning organization in Company C. See Table 14.

Insert Table 14

Results Comparison Even though each company is part of the service industry, individual companies showed very different results based on EFA. The results of Company A and Company C indicate that employees’ utilization of E-Learning Systems affected the learning organization in Company A and Company C but not Company B. It is interesting that the results of Company B do not affect the development of the learning organization. In particular, Company A and Company C showed that employees’ acceptance toward E-Learning Systems influenced the learning organization, which are statistically significant (R²=.121 for Company A, R²=.348 for Company C). Notably, Company B and Company C showed different results, even though they are from the same subsidiaries of a conglomerate in South Korea. They both follow similar educational policies and offer similar E-learning contents as well as similar E-Learning Systems, except for job specific contents.

Insert Table 15

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Discussion

This study sought to investigate the effect of E-Learning Systems on fostering the development of learning organizations in three companies in South Korea. Three sites were chosen in the service industry because employees in the service industry are accustomed to being divided into separate workplaces. Therefore, information technology, such as E-Learning Systems, is a critical media used to communicate, aid in learning, and develop employees within organizations. The results based on all data points from the three companies indicated that employees’ perceptions of E-Learning Systems could influence their perceived dimensions of a learning organization. Some differences emerged when comparing the results among individual companies. The results of Company A and Cmpany C showed that E-Learning Systems promoted the development of their learning organizations. However, in Company B, E-Learning System did not seem to contribute to the development of a learning organization. Prior studies support the significant relationships indicated by Company A and Company C as technologies are enablers of the development of a learning organization. Studies found that using E-Learning Systems can positively influence the development of learning organizations (Kane, & Alavi, 2007; Keane, Barber, Munive-Hernandez, 2007; ChattiJarke, & Frosch-Wilke, 2007). Ashworth, Mukhopadhyay, and Argote (2004) examined the relationship between information systems and organizational learning in a bank and revealed that using information technologies to facilitate knowledge sharing can increase organizational learning. In addition, Kane and Alavi (2007) found that knowledge management tools such as electronic communities of practice or knowledge repositories might affect and enhance organizational learning. The findings of this study align with previous findings. It contributes to existing research, regarding similar E-Learning Systems, and learning organization relationships in South Korean organizations. The insignificant result evidenced by Company B showed that E-Learning System did not affect the learning organization within the company. Previous studies too have reported that employees appear not to share their knowledge, although organizations have placed a lot of effort into facilitating employees’ knowledge sharing (Ciborra & Patriota, 1998; Ford & Chan, 2003; Scarbrough, 2003; Szulanski, 1996). There are several reasons that might explain the results of Company B. According to Edwards, Fraser, & Weitel (2009) and Sykes, Kenkatesh & Grosain (2009), social influence is the critical factor that affects employees' utilization of technology in the workplaces. Peers or supervisors of Company B may not faciliate employees' learning. Moreover, social influence within Company B may not be a critical factor because employees learn to keep their expertise for personal asset. Employees in high-tech firms tend to learn job-specific contents. However, the E-learning contents that Company B offers seem to be associated with general competencies, such as presentation skills, communication skills, or leadership. Thus, employees in Company B might think that using E-Learning System may not be appropriate for their knowledge sharing or learning. The results of this study also imply that E-Learning Systems’ strategies might not be aligned with the learning and development strategies and policies of Company B. Company B seemed to underestimate the role of technologies, such as E-Learning System, which also explains why it does not integrate E-Learning System into employees’ learning and performance systems. Thus, employees’ perceptions of E-Learning Systems may not have strongly affected the development of learning organizations directly due to this disconnection. As a result of such misalignment, employees in Company B may have perceived, through their culture, that minimal utilization of E-Learning System was acceptable. Further, recent studies (Conley & Zheng, 2009; Yoon & Lim, 2010) showed that this disconnection seems to be replicated in the use of information technologies within organizations. Based on the findings of this study, learning oranizations of South Korea are defined as companies that can utilize E-Learning Systems to distribute a company's values, policies, and business strategies to employees. At the same time, it offers learning culture that facilitates employees' learning and development within the company.

Conclusion

This study showed the critical role of E-Learning Systems for the development of learning organizations within the workplace (Ardichvili, 2008; Barab et al., 2004; Huang & Chen, 2001; Jian & Jaffres, 2006; Wenger, 1998). Furthermore, this study demonstrated that a holistic perspective is necessary to integrate technologies into the workplace for the creation and sustainability of a learning organization. Adopting information technologies can be a viable intervention for organizational development and can bring a variety of changes at the individual, team, and

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organizational levels. However, there seems to be a problem where technology is overlooked in the change management process. Wang, Wang, Ma, and Liang (2009) emphasized that adopting technology is a very complex process that is related to psychological, organizational, and systems variables. Executives, managers, and human resource development (HRD) professionals have yet to recognize its real value (De Long & Fahey, 2000). This means that HRD professionals should consider creating specific roles that would contribute to creating a stronger workplace culture through technology. This would allow employees to enjoy their learning and apply what they learn to their jobs for improved job performance. Based on the findings of this study, the researcher proposes the following suggestions to HRD professionals who desire to incorporate technologies within their organizations. Effective knowledge sharing and learning through technologies cannot be enforced or mandated upon employees. However, HRD professionals can foster safe learning environments where employees voluntarily participate in using these technologies. Moreover, HRD professionals need to reveal the barriers, and create a link between interventions and technologies, which enhance the creation of a learning environment with their organizations. Adopting and implementing E-Learning Systems may be performed in various ways based on the organization’s situation E-Learning Systems practices may have variations and differentiations, depending on the organization. Thus, an alternative strategy is to diagonose the organizations’ situations by identifying the specific groups that need extra interventions, as well as determining which interventions are needed to fill in the gaps to integrate the technologies. Based on the diagnosis, HRD should actively provide support resources and feedback to employees and decision makers with updated regarding the implementation of technologies. For example, the results of this study showed that in Company B, E-Learning Systems did not seem to be working properly in the development of the learning organization. This means that the utilization of E-Learning Systems may not be appreciated or recognized in this particular workplace. This study conducted quantitative data from on-line surveys. A more thorough explanation might be added if qualitative questions were asked. Future research might considerably improve our understanding of technology adoption for employees’ learning. Therefore, further studies need to be conducted to investigate the impact of technology on learning cultures in the workplaces of different industries.

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Table 1: Study sample sites

Site (industry)

Total numb er of employees

Total training expenditure ($ for an

employee)

The average training hours per

employee

Year ELS used

Company A (IT service)

1,350 24 billion (2,000 $)

120(2011) 1998

Company B (IT service)

580 N/A 40(2009) 2001

Company C (Media Service)

890

1 billion (1000 $)

80(2008) 2003

Table 2: The Dimensions of Learning Organization

Dimension Definitions

Creating continuous learning opportunities

Continuous learning requires employees to be willing to change, adapt, grow, and take control of work-related decisions.

Promote inquiry and dialog

People gain productive reasoning skills to express their views and the capacity to listen and inquire into the views of others; the culture is changed to support questioning, feedback, and experimentation.

Encourage collaboration and team learning

Work is designed to use groups to access different modes of thinking; groups are expected to learn together and work together; collaboration is valued by the culture and rewarded.

Create system to capture and share learning

Both high and low technology systems to share learning are created and integrated with work; access is provided; systems are maintained.

Empower people toward a collective vision

People are involved in setting, owning, and implementing a joint vision; responsibility is distributed close to decision making so that people are

motivated to learn toward what they are held accountable to do. Connect the organization

to its environment People are helped to see the effect of their work on the entire enterprise; people scan the environment and use information to adjust work practices; the organization is linked to its communities.

Provide strategic leadership for learning

Leaders model, champion, and support learning; leadership uses learning strategically for business results

Key results financial performance

State of financial health and resources available for growth

Knowledge performance Enhancement of products and services because of learning and knowledge capacity

Table 3: The UTAUT constructs (Venkatesh et al., 2003)

Construct Definitions

Performance Expectancy The degree to which an individual believes that using the system will help him or her to attain gains in job performance.

Effort Expectancy The degree of ease associated with the use of the system. Attitudes An individual's positive or negative feelings about performing the target

behavior.

Social Influence The degree to which an Individual perceives that important others believe he or she should use the new system.

Facilitating Conditions The degree to which an individual believes that an organizational and technical infrastructure exists to support use of the system.

Self-efficacy Judgment of one’s ability to use a technology to accomplish a particular job or task

Anxiety Evoking anxious or emotional reactions when it comes to performing a behavior

Behavioral Intention to use The degree to which an individual wants to use technology and will use what is learned in the work context

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Table 4: The Number of Participants and Response rate

Study site Industry Time Span

Number of Participants/distributed number

Response rate

Company A Information Technology (IT) Service

4 weeks (March)

100/350 29%

Company B Information Technology

(IT) Service

4 weeks

(March)

121/300 40%

Company C Broadcasting service 4 weeks (Feb)

113/500 23%

Total Service industries 8 weeks 334/1150 29%

Table 5: Descriptive statistics of participant demographic information

Frequency (Percent)

Total Company A Company B Company C

Gender Male 148(45.3) 42(42.0) 55(46.2) 51(47.2)

Female 59(18.0) 35(35.0) 14(11.8) 10(9.3) Missing 120(36.7) 77(77.0) 50(42.0) 47(43.5) Total 327(100.0) 100(100.0) 119(100.0) 108(100.0)

Age Less than 20 1(0.3) 0(0.0) 0(0.0) 1(0.9) 20 – 29 28(8.6) 14(14.0) 6(5.0) 8(7.4)

30 – 39 113(34.6) 38(38.0) 44(37.0) 31(28.7) 40 – 49 64(19.6) 24(24.0) 19(16.0) 21(19.4) Over 50 1(0.3) 1(1.0) 0(0.0) 0(0.0) Missing 120(36.7) 23(23.0) 50(42.0) 47(43.5)

Total 327(100.0) 100(100.0) 119(100.0) 108(100.0)

Work experience

Less than 1 year 12(3.7) 5(5.0) 3(2.5) 4(3.7) 1 – 5 years 85(26.0) 29(29.0) 27(22.7) 29(26.9) 6 – 10 years 60(18.3) 15(15.0) 29(24.4) 16(14.8) 11 – 15 years 33(10.1) 14(14.0) 8(6.7) 11(10.2) 16 – 20 years 16(4.9) 14(14.0) 1(0.8) 1(0.9) Over 20 years 1(0.3) 0(0.0) 1(0.8) 0(0.0) Missing 120(36.7) 23(23.0) 50(42.0) 47(43.5) Total 327(100.0) 100(100.0) 119(100.0) 108(100.0)

Job

function

Sales/ Marketing 56(17.1) 28(28.0) 4(3.4) 24(22.2)

Product/ Technician 43(13.1) 0(0.0) 26(21.8) 17(15.7) Support 51(15.6) 29(29.0) 3(2.5) 19(17.6) Research 14(4.3) 9(9.0) 5(4.2) 0(0.0) Service 4(1.2) 0(0.0) 4(3.4) 0(0.0)

Others 35(10.7) 10(10.0) 25(21.0) 0(0.0) Missing 124(37.9) 24(24.0) 52(43.7) 48(44.4) Total 327(100.0) 100(100.0) 119(100.0) 108(100.0)

Position Employee 36(11.0) 2(2.0) 13(10.9) 21(19.4) Assistant Manager 63(19.3) 19(19.0) 23(19.3) 21(19.4)

Manager 61(18.7) 27(27.0) 22(18.5) 12(11.1) Senior manager 31(9.5) 15(15.0) 10(8.4) 6(5.6) Supervisor 15(4.6) 13(13.0) 1(0.8) 1(0.9) Missing 121(37.0) 24(24.0) 50(42.0) 47(43.5)

Total 327(100.0) 100(100.0) 119(100.0) 108(100.0)

Education Level

High school graduate 4(1.2) 0(0.0) 0(0.0) 4(3.7) Certificate or associates degree 10(3.1) 3(3.0) 1(0.8) 6(5.6) Undergraduate degree 161(49.2) 57(57.0) 60(50.4) 44(40.7) Graduate degree (Master) 30(9.2) 15(15.0) 8(6.7) 7(6.5)

Ph.D. 1(0.3) 1(1.0) 0(0.0) 0(0.0) Missing 121(37.0) 24(24.0) 50(42.0) 47(43.5) Total 327(100.0) 100(100.0) 119(100.0) 108(100.0)

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Table 6: Actual and Random Eigenvalues (Parallel Analysis: PA)

Factor Actual eigenvalue Average eigenvalue Standard Dev

1 11.947 1.5386 .0446 2 2.874 1.4584 .0367 3 1.350 1.3917 .0321 4 1.130 1.3323 .0286

Table 7: Item Statistics and Reliability (N=327)

Component Item (16 items) Mean (Std. Deviation)

Cronbach’s Alpha if item deleted

Cronbach Alpha

1 Attitude2 4.74(0.97) .935

.940

Attitude3 4.50(0.98) .934 Attitude4 4.55(1.00) .935 PerformanceExpectancy3 4.76(0.99) .934 PerformanceExpectancy2 4.61(0.97) .935

Attitude1 5.40(0.87) .935 PerformanceExpectancy4 3.95(1.14) .940 PerformanceExpectancy1 5.02(0.98) .935 Effort Expectancy 1 4.62(0.94) .934

2 Facilitating Conditions 4 4.77(1.11) .940 Facilitating Conditions2 5.07(0.97) .936 Facilitating Conditions1 4.90(0.98) .935 Social Influence 4 5.14(1.08) .936

Effort Expectancy 3 5.21(0.91) .935 Effort Expectancy 2 5.02(0.99) .936 Effort Expectancy 4 5.10(0.91) .936

Table 8: Actual and Random Eigenvalues (Parallel Analysis: PA)

Factor Actual Eigenvalue Average Eigenvalue Standard Dev

1 11.430 1.4783 .0463

2 1.121 1.3956 .0360

Table 9: Item Statistics and Reliability

Component Item (10 items) Mean (Std. Deviation)

Cronbach’s Alpha if item deleted

Cronbach Alpha

1 Strategic leadership (O21) 4.86(1.21) .917 .929 Team learning (T8) 4.94(1.29) .919 Strategic leadership (O19) 4.99(1.28) .918

Team learning (T9) 4.84(1.26) .919 Inquiry and dialog (I6) 4.73(1.26) .922 Inquiry and dialog (I5) 4.79(1.17) .925 Team learning (T7) 4.74(1.36) .927 System connection (O18) 4.84(1.27) .922 Inquiry and dialog (I4) 4.58(1.23) .923 Strategic leadership (O20) 4.77(1.26) .920

Table 10: Descriptive Statistics of Remained Factors (N=327)

Mean(S.D) All Three Companies

Company A Company B Company C

UTAUT ELS Factor 1

(Attitude/Performance expectancy)

4.68(0.78) 4.56(0.73) 4.65(0.74) 4.84(0.78)

Factor 2 (Faciliating Conditions/Effort Expectancy)

5.03(0.78) 5.16(0.82) 4.82(0.67) 5.13(0.81)

Learning Organization

Factor 1 (Individual, Team, Organizational) 4.81(0.98) 4.78(0.85) 4.63(0.96) 5.04(1.08)

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Table 11: Regression Model

Model Beta t Sig. df F R²

(Constant) 7.01 .000 3,323 29.26 .214 ELS Factor 1 .220 3.14 .006* ELS Factor 2 .344 4.54 .000**

ELS Factor 3 -.083 -1.16 .179

a. Predictors: (Constant), ELS factor 1, 2, 3 b. Dependent Variable: Learning Organization

Table 12: How Employees’ Perceptions on ELS Affect the Learning Organization of Company A

Beta t Sig. Df F R²

1.Constant 4.912 .000 3,76 3.480* .121

Factor 1 (Attitude/Effort Eexpectancy) -.235 -1.592 .115

Factor 2 (Social Influence) .342 2.321 .023*

Factor 3 (Faciliating Conditions) .183 1.415 .161

a. Independent variable: factor 1, factor 2, factor 3

b. Dependent variable: learning organization c. *p<.05 **p<.001

Table 13: How Employees’ Perceptions on ELS Affect the Learning Organization of Company B


1.Constant 4.035 .000 2,77 2.445 .060

Factor 1 (Attitude/Performance Expectancy) .224 1.478 .144

Factor 2 (Social Influence) .028 0.028 .854

a. Independent variable: factor 1, factor 2 b. Dependent variable: learning organization c. *p<.05 **p<.001

Table 14: How Employees’ Perceptions on ELS Affect the Learning Organization of Company C


1.Constant .277 .420 .675 1,78 41.605** .348

Factor 1 .847 6.450 .000**

a. Independent variable: factor 1 b. Dependent variable: learning organization c. *p<.05 **p<.001

Table 15: The Differences among Company A, B, and C’ Results

Company Company A Company B Company C

Results R²=.121 (F=3.480*) R²=.060 (F=2.445) R²=.348 (F=45.605**)

a. *p<.05 **p<.001

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Can E-Learning System Enhance Learning Culture in the Workplace? A Comparison among Companies in...

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