Comparison of Public College Librarians' Performance, Competence, and Work Design in Indonesia and Malaysia

Over the last few decades, the format of libraries has shifted. What was previously a traditional library is now automated into a digital library. The nature of libraries and their services has changed drastically in dynamic ways (Harris, 2015; Lau et al., 2020; Li et al., 2019; S. Liang & Wu, 2019; Stejskal & Hajek, 2015; Xu & Du, 2019). It can be seen that the role of libraries cannot be separated from the information needs, which currently become the priority for all segments of societal development. Changes in the work environment are users' expectations in responding to the challenges of information and communication technology (ICT) advancements. Following the changes in the work environment of the library, particularly in the college libraries, librarians face not only internal challenges but also user demands and expectations. User expectations always seem to exceed the library's capacity regarding infrastructure facilities, finances, staff, etc. Therefore, libraries must always try new alternatives to provide the best possible service for their users. The efforts that should be considered to maintain the libraries' existence in information fields include professionalism, proactiveness, and the readiness to pose as an information provider. History records that university libraries play an important role in the development of human resources and the progress of a nation. The method, which has proven effective in increasing the rankings of several public universities in both countries, involved giving more spotlight and attention to librarians who work in public college libraries. The literature on work design is very limited in library studies. However, work design is not a new topic among researchers in other fields. The significance of work design has been statically tested to improve the work environment. Therefore, little is known about the work design situation in the library sector, especially research related to design and work competence. Shupe et al. (2015) state that the measurement of task performance in the library field is still incomplete. No researcher has ever tried to connect it with design and job competence. Available studies by Robinson et al. (2015) provide empirical evidence on librarians regarding professional role-based competency practice. This is confirmed in Khan's (2020) research, which comprehensively discusses the relationship between competence and performance, although no work design dimensions are included. Based on the explanation that has been described, the researchers see that there is still room for further research related to task performance and design, especially regarding librarians. Apart from that, comparative research between work performance (WP), competence (COM), and work design (WD) between college librarians in Malaysia and Indonesia has never been carried out before. Previous research only discussed one area. In the performance dimension, several performance models in previous research always focused on behavior, not work results (Motowildo et al., 1997). In the context of this research, the proposed dimensions should represent the work environment of university librarians. Appropriate dimensions will improve the quality of data collection. As mentioned in the definition of WP, the most comprehensive study of WP was conducted by Koopmans et al. (2014). The dimensions chosen are suitable to represent the nature of WP among university librarians. This is because most of the performance of university librarians is measured by fulfilling the tasks given. Griffin et al. (2000) and Kahya (2009) claim that job and contextual performance are behavioral dimensions that independently contribute to organizational effectiveness. The explanation of the selected competency dimensions must be generalized to suit university libraries in Malaysia and Indonesia. The proposed competency dimensions are not specific to a particular division because this study does not focus on a specific division in the library. Also, the nature of the work environment in Malaysia and Indonesia is based on job rotation. Thus, the proposed competencies should not focus on details of the scope of work. To develop this research competency, researchers refer to Khan and Bhatti (Khan, 2015; Khan et al., 2015; Khan & Bhatti, 2017; Masrek et al., 2012). Accordingly, previous research has examined WD from various perspectives. WD studies create a better understanding of what motivational factors influence team member performance. Based on literature searches, discussion about WD and librarians is very limited. There is not much empirical evidence that researchers can refer to as a guide. However, some dimensions of WD seem to fit the work environment of university librarians. The dimensions chosen to measure WD among university librarians are well-suited to address the research objectives. As mentioned by Campion et al. (2005) and Parker et al. (2017), WD will promote positive values such as increasing WP, competence, and well-being.This study provides a new dimension that may be applied to study WP, COM, and WD. In this study, two of the four dimensions of WP by Koopmans et al. (2014) seem to fit the purpose of this study. Again, based on the literature review, it’s found various studies have proposed task performance and contextual performance as the main dimensions of the WP model (Diaz-Vilela et al., 2015). The first WP dimension used to test public college librarians' performance is task performance. Task performance can be defined as proficiency, the technical core of behaviors, and effectiveness in adding value and performance to the given task. Although task performance is the most visible dimension in WP theory and models, Koopmans et al. (2014) define contextual performance as behavior that supports a psychological, organizational, and societal environment in which the technical core is fully operated. Bekenova (2015) believes that additional roles, although not directly related to the main job or task, still support the main task. Besides, there is no standardization of competence for college librarians in Malaysia and Indonesia. In that sense, the explanation of the selected competency dimensions must be generalized to suit university libraries in Malaysia and Indonesia. Consequently, the proposed competency dimensions are not specific to a particular division because this study does not focus on a specific division in the library. For example, the first dimension is emotional intelligence. Khan (2020) defines emotional intelligence as the ability to understand, recognize, influence, and control the emotions of another individual. In addition, emotional intelligence can increase job satisfaction, which in turn can result in effective performance (Khan et al., 2017). The second deals with cognitive abilities, which are the ability to learn research and apply knowledge and process, including reason, analysis, and decision. Third, library leadership is one of the aspects of COM proposed in previous research by Khan (2020), Maduka et al. (2018), and Special Library Association (2016). It can be said that leadership is the basis that must be owned by each librarian. Fourth is collection management, which revolves around collection development, acquisition, sharing, protection and preservation of resources, proper management, assessment, and control of collections. Fifth is technology management, which must keep up with the times. Thanuskodi (2015) believes that as information professionals, librarians should be able to master basic technical skills in terms of hardware and software applications for library services and facilities. Sixth, research and reference services require academic librarians to excel in helping library users get information. In previous studies, COM and reference services are one of the core performance and competencies that are pivotal for librarians (Special Library Association, 2016). Seventh, content organization and structure related to cataloging, metadata, and classification activities. However, the most prominent WD dimensions are job characteristics and knowledge characteristics. And the first dimension of job characteristics is autonomy. White (2018) defines autonomy as a scenario where workers can exercise choices and preferences in their work. Second, job variation refers to the tasks other than the main job. Third, the significance of work that can impact an individual's work to others. Fourth, job identity is the extent to which the employee does all the work that has been assigned. Knowledge characteristics are also one of the important dimensions in the WD study (Hernaus & Vokic, 2014; Morgeson & Humphrey, 2006). Likewise, the first dimension of knowledge characteristics is the work complexity, which is assessed by the work's difficulty level. Second, Information procession can be defined as the degree to which the job requires information to fulfill the given tasks. Third, problem-solving can assist users in providing solutions and creativity in completing their work as librarians. Fourth, the variety of skills can be interpreted as the skills employees need to fulfill the given job. This research's novelty is comparing public college librarians' performance, competence, and work design in Indonesia and Malaysia. Also, the originality of this research lies in its theory and the methods used. Because the theory fits the study's goal, which is to compare how librarians work in both countries. To do this, it refers to performance, skills, and work methods suitable for college librarians in Indonesia and Malaysia. In terms of research methods, previous studies mostly used a descriptive quantitative approach, which explained each dimension: performance, competency, and work design. The explanatory quantitative approach in previous research emphasized the study of the relationship, influence, and impact of each dimension. Thus, it is very rare, and in fact, there has been no research that has carried out comparisons between state university librarians from these two countries, with a fairly large number of respondents, such as 380 state university librarians with details 231 librarians from Malaysia and 149 librarians from Indonesia.

This study used an explanatory quantitative method approach. Explanative research aims to find an explanation of why a symptom may occur, which will later describe a cause-and effect relationship and compare two or more samples. However, the sample in this study couldn’t be determined using probability sampling because the sampling frame is not available, and the exact number of the total population is unknown. Therefore, this study used purposive sampling, a non-probability method for taking population samples. The total sample size was 380 librarians, consisting of 231 from Malaysia and 149 from Indonesia. This research compares public college librarians in Indonesia and Malaysia with the independent sample t test p-value used to determine whether there is a difference. The data collection was done by distributing questionnaires through Google Forms. The questionnaires that have been scattered are then coded to classify the respondents' answers. A Likert scale was used to calculate data, as seen in the table. Table 1. Likert scale Score Value 7 6 5 4 3 2 1 Strongly agree Agree Somewhat agree Not both Somewhat disagree Disagree Strongly disagree Data analysis used is (i) descriptive statistics, (ii) general method variance, and (iii) Structural Equation Modeling (SEM), which were divided into measurement models (or confirmatory factor analysis) and structural model analysis. The analysis commonly used in the descriptive analysis is a measure of the central tendency and a measure of the dispersion. Likewise, the measure of central tendency includes the mean, median, and mode, while the measure of the dispersion includes the standard deviation, variance, range, and coefficient of variation (Elifson et al., 1990; Hadi, 1993; Hasan, 2003; Johnson & Bhattacharyya, 1985; Malo, 1986; Supranto, 1986). Then, the study used the mean to measure the central tendency of the research variables and the standard deviation to measure the dispersion. Structural Equation Modeling (SEM) is a powerful technique for capturing and explaining multifaceted relationships in social science. At the same time, a Confirmatory Factor Analysis (CFA) or measurement model describes how the measured variables logically and systematically represent constructs in the model. Thus, the questionnaire has undergone pre-testing and a pilot study to ensure quality and accurate research results. Accordingly, the data analysis method used is descriptive statistical analysis and inferential statistics with the t-test. Descriptive statistics were applied for mean, median, mode, and standard deviation. The t-test was used to test the research hypothesis, and the pooled variance (n1 = n2) formula was used to analyze the results of the independent sample test (t test) with the help of SPSS. Before testing the hypothesis, the data underwent the assumption test using the SPSS, which was proven normal according to Kolmogorov-Smirnov and Shapiro Wilk tests. Similarly, it was also proved to be homogeneous after the test, according to Levene's statistics.

Demographics of the Respondents Table 2. Demographics of the respondents Nationality Frequency Percent Malaysia 231 60.8 Indonesia 149 39.2 Aged Frequency Percent Less 25 6 1.6 26-29 23 6.1 30-34 60 15.8 35-39 79 20.8 40-44 86 22.6 45-49 59 15.5 50 above 67 17.6 Academic Qualification Frequency Percent Bachelor degree 199 52.4 Master degree 158 41.6 PhD 5 1.3 High School (SMA_SMK) 8 2.1 Diploma 2 4 1.1 Diploma 3 6 1.6 Length of Service Frequency Percent Less than one year 4 1.1 1-5 years 64 16.8 6-10 years 98 25.8 11-15years 99 26.1 16-20 years 57 15.0 More than 20 years 58 15.3 Source: processed primary data, 2022 This section shows the demographics in this study. Of 380 respondents, 39.2% came from Indonesia, while 60.8% came from Malaysia. Furthermore, most respondents (22.6%) were aged between 40-44, followed by those aged 35-39 (20.8%). The lowest number comes from those under 25 years old. Respondents were also asked about educational qualifications; the majority indicated they had obtained a bachelor's degree (52.4%). In comparison, 41.6% had obtained a Master's degree, and in terms of length of service in college libraries, 99, or 26.1%, answered that they have been working for between 11 and 15 years, followed by those who have been working between 6 and 10 years (25.8%). Performance Variables, Competence, and Work Design of Public College Librarians Table 3. Variable recapitulation No Variables Score Categories 1. Performance Task performance 5.95 Very good Contextual Performance 6.02 Very good 2. Competence Emotional Intelligence 5.99 Very good Cognitive Ability 5.99 Very good Library leadership 6.05 Very good Collection management 5.90 Very good Technology management 5.66 Very good Research and reference service 5.62 Very good Content organization and structure 5.67 Very good 3 Work Design 3a Job Characteristics Autonomy 5.86 Very good Task Variety 5.91 Very good Task significance 5.91 Very good Task identity 5.99 Very good 3b Knowledge Characteristic Work Complexity 4.79 Good Information processing 5.99 Very good Problem Troubleshooting 5.72 Very good Skill Variety 5.83 Very good Average 5.81 Very Good Source: processed primary data, 2022 Furthermore, table 3 reveals the results of recapitulating the independent sample t-test for each variable. Table 4. Independent Sample t-Test Recapitulation p-value Variables Levene's Test for Equality of Variances F Sig. t df Sig. (2-tailed) Performance Task performance Equal variances assumed .968 .326 -.118 378 .906 Equal variances not assumed -.114 281.168 .909 Contextual performance Equal variances assumed .052 .820 -.244 378 .807 Equal variances not assumed -.234 272.613 .815 Competence Equal variances assumed .194 .659 -1.284 378 .200 Equal variances not assumed -1.213 257.243 .226 Work Design Task characteristic Equal variances assumed 1.198 .274 1.444 378 .150 Equal variances not assumed 1.375 264.466 .170 Knowledge Characteristic Equal variances assumed 3.302 .070 4.944 378 .000 Equal variances not assumed 4.814 287.562 .000 Source: processed primary data, 2022

Librarians are the front guards of information that enters and develops in society. In the current situation, college librarians are an important element in improving human resources in a nation and are responsible for presenting information according to users’ needs. The performance, competence, and work design variables can support research objectives on public college librarians in Indonesia and Malaysia. The comparison of librarians’ performance in the two countries regarding task performance and contextual performance scored above 0.05 for all p-values, indicating no difference between librarians in Indonesia and Malaysia. Secondly, competence shows the same results with no significant difference because it has a p-value=0.2. Third, there is no significant difference in job characteristics because the p value is 0.150. At the same time, there is a significant difference between the knowledge characteristics of librarians at public universities in Indonesia and Malaysia at p=0.000. It can be said that based on the variables of performance, competence, and work design in terms of job characteristics, there is no significant difference between librarians at public universities in Indonesia and Malaysia. In contrast, regarding knowledge characteristics, there is a significant difference between librarians at public universities in Indonesia and Malaysia.