Does participative decision making affect lecturer

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Does participative decision making affect lecturer performance in higher education?

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D.S. Sukirno and Sununta Siengthai

Received June 2010 Accepted July 2010

School of Management, Asian Insititute of Technology, Pathumthani, Thailand Abstract Purpose – The relationship between participation and job performance has captured the interest of not only business researchers but also education researchers. However, the topic has not gained significant attention in the educational management research arena. The purpose of this paper is to empirically examine the impact of participation in decision making on lecturer performance in higher education. Design/methodology/approach – Mail survey was used to collect the data. Open-ended questionnaires were distributed to the lecturers in Yogyakarta Province in Indonesia. A total of 347 usable questionnaires were obtained which is about 46.3 percent rate of return. Factor analysis was used to identify the constructs. All Cronbach’s alpha values are more than 0.7 and factor loading is more than 0.50. Regression analysis was employed to test research hypotheses. In addition, t-test and ANOVA test were also conducted to investigate the different impact of demographic data on the job performance of the lecturers. Findings – This study finds that participative decision making and academic rank have significant effect on lecturer performance. This finding implies that involving lecturers in educational decision making would be useful to improve not only lecturer performance but also organizational performance. In addition, among all demographic variables taken into account, only academic rank significantly affects lecturer performance. Research limitations/implications – This study assumes constant the reward system and performance appraisal factors that might affect the relationship between participation and lecturer performance. The research findings urge the Indonesian government to immediately set an order of a participative decision making system to facilitate the realization of a better quality of Indonesian higher education performance. Originality/value – Participative decision making is a tool to align an organization’s vision and a lecturer’s objectives. The higher the level of lecturer’s participation in decision making the higher the lecturer’s commitment to the organization’s vision and the higher the lecturer’s performance will be. Keywords Participative decision making, Lecturer performance, Higher education, Indonesia, Performance levels, Employee participation Paper type Research paper

International Journal of Educational Management Vol. 25 No. 5, 2011 pp. 494-508 q Emerald Group Publishing Limited 0951-354X DOI 10.1108/09513541111146387

Introduction Higher education plays its main role in creating expertise and acts as a center of excellence for knowledge creation and developing human resources necessary for a country’s development. Higher education is the engine that drives the economy and the vaccination against the worst effects of globalization (Creech, 2000; Brodjonegoro, 2009). Further, higher education affects every area of national development and deserves requisite attention (Chauhan, 2008). Many strategies have been implemented by developing countries such as Indonesia to improve their higher education performance.

Job performance is a significant factor affecting organizational performance. In an educational setting, lecturer performance has a strategic role and is the main factor determining student performance and hence university performance. Kingdon and Teal (2003) mentioned that teachers are a central actor in the learning process that takes place in schools. Studying factors affecting lecturer performance in higher educational institutions from different settings is very useful for not only enriching and refining theory but also for developing reasonable recommendations to increase quality of higher educational institutions. Since 1980s, considerable attention was placed on enhancing teacher professionalism primarily through increasing teacher participation in decision making regarding issues affecting teachers’ schools and classrooms (Rice and Schneider, 1994). Employee participation has been primarily initiated from the industrial and business domains; but only recently it is evident in schools (Conway, 1980, p. 41). In the USA, teacher participation becomes central to many schools restructuring projects. The term “restructuring” suggests fundamental educational change in response to the need to comprehensively redesign schools (Lipman, 1997, pp. 3-4). Dimensions of managing the teaching-learning process developed by Pozo (2006) mentioned that there are many principal components determining successfulness of teaching-learning process, one of them is giving teacher a chance to participate in decision making. Participation in decision making is becoming a controversial issue to find a fit between lecturers and universities’ objectives. Such researches have been conducted in developed as well as developing countries but still very limited in Indonesia. Moreover, the previous research shows lack of consistent and conclusive evidence about the impact of participative decision making on teaching performance in higher education. The empirical evidence shows that research in this area is still an equivocal topic. The purpose of this research was to ascertain empirical evidence and gain insights about the impact of participative decision making on lecturer performance in higher education in Indonesia. Literature review Although job performance is commonly used in business and education fields of studies, its concept is still poorly defined. Different definitions of the concept might be given by different scholars in different fields. For instance, in education, technical engineering and business, we will find different definitions of job performance. Bernardin et al. (1995) defined job performance as the outcomes of work because they provide the strongest linkage to the strategic goals of the organization, customer satisfaction, and economic contributions. Campbell et al. (1970) conceptualized job performance as behavior and it does not have to be directly observable actions of an individual. It can consist of mental production such as answers or decisions. Whatever justification given by the leadership of colleges in Indonesia, with the university rankings in Indonesia started in the order of 78 in Asia-Pacific according to Time magazine, it still could be a reflection of underdevelopment of the higher education quality in Indonesia (Heriyono, 2009). By having such a condition, it would be still very difficult for Indonesian universities to compete internationally with other foreign universities. Heriyono exposed that improving lecturer performance might

Lecturer performance

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become a strategic approach for alleviating the educational problems. Therefore, identifying and facilitating factors influencing lecturer performance in higher education has become a paramount priority for Indonesia government. Linking participative decision making to lecturer performance Educators, practitioners, and researchers from various disciplines of knowledge have studied factors affecting performance. One of the prominent factors affecting performance is participative decision-making (Drummond and Reitsch, 1995; Lipman, 1997; Clinton and Hunton, 2001). Increasing level of teacher participation in making decisions and extending their involvement in the overall decision making process make school policy and management more responsive to societal needs (Pashiardis, 1994). Further, Pashiardis (1994) described that teachers can take a greater role in the overall success of the school when they are committed to being active participants in the decision-making process. Participation has an important role not only in the business or industrial sector but also in the educational sector. Participation in school decision making can enhance teachers’ commitment, expertise, and effectiveness (Marks and Karen, 1997, p. 246). Lipman (1997, p. 11) asserted that teacher participation was to re-energize schools, unleash teachers’ initiative and creativity, and get them to buy into the restructuring agenda. Besides, it has become a key component of recent efforts to restructure and reform schools in Indonesia. Teacher participation in school decision making has been advanced for many reasons (Smylie, 1996, p. 181) including the belief that it will enhance communication among teachers and administrators as well as the quality of educational decision making and quality of teachers’ work life. Participation may also enhance teacher’s sense of responsibilities, shared culture, and teacher commitment (Lipman, 1997, p. 4). In addition, Lipman stated that teacher participation is related to the implementation of programmatic decisions and creates opportunities for instructional improvement. Smylie (1996) stated that participation would improve teachers’ opportunities in acquiring new knowledge and insights. These opportunities can enhance respectively instructional improvement and student outcomes. Mualuko et al. (2009) investigated the extent to which teachers are involved in school decision making process in comparison to their desired extent of participation. They found that teachers desire greater involvement in decision making. They therefore recommended that by involving lecturers in decision making, the quality of decisions and their morale in their performance of duty will be higher. According to the above theoretical background, it is expected that providing lecturers a space for participating in decision making has positive impact on lecturers’ performance in teaching, research, publications, public services and managerial involvement activities: H1. Participative decision making is positively related to lecturer performance or in other words the more participative decision making, the better lecturer performance in higher education institutions will be. Linking demographic characteristics and lecturer performance Level of education and work experience are among the most commonly studied characteristics of entrepreneurs and educators. Cursory examination of empirical studies relating to the impact of education and experience on performance suggests that there are contradictory findings. Tremblay et al. (2001) confirmed that class-level

variables that positively affect performance are experienced teachers who were comfortable with the curriculum. In their business research, Kennedy and Drennan (1998) asserted that higher education and management experience in large organizations is associated with higher performance. Their arguments centered on the fact that experience improves teaching skills while pupils learn better at the hands of teachers who have taught them continuously over a period of years. Several studies have been conducted, yet there is not a single conclusion regarding gender equality on the job performance. Ackah and Heaton (2003) explored whether the acquisition of a human resource professional qualification has the same impact upon career progression for male and female managers. The findings suggested that the careers of men and women do differ, with men receiving more internal promotions while women were more likely to seek career progression in another organization and to be less successful in terms of earnings. In contrast, Watson (2003) had studied gender-based differences in the financial performance and business growth of small and medium-sized Australian enterprises and had found that female lecturers tend to perform better than male lecturers. In 2008, Adeyemi’s study revealed that teachers’ teaching experience had a significant impact on students’ learning outcomes. Schools having more teachers with teaching experience of five years and above achieved better results than schools having more teachers with less than five years of teaching experiences. Recently, Kadri et al. (2009) found that gender and experience of lecturers affected lecturer performance. In Indonesia, public universities, in general, are regarded as being much more prestigious and more favored by students than their private counterparts. Therefore, Indonesian private institutions are also more vulnerable in an increasingly competitive environment. This argument is supported by research evidence revealed by Chien-ern et al. (2008) in Taiwan higher education system. Their administrators are more eager than their public counterparts to try new strategies for getting out of the predicament. Indonesian government financial and non-financial support is perceived as the most influential determinant for public universities. Due to the lack of financial support and potential market demand, it was reported that about 40 percent of private universities (1,080 universities) in 2008 are going out of business (Sinar Indonesia Baru, 2008). Such salient different conditions may cause lecturer performance variation between public and private universities. Based on the literature review, it is then hypothesized as follows: H2. Demographic characteristics (i.e. age, gender, experience, educational level, academic rank, and school background) are related to lecturer performance of public universities and private universities in Indonesia. Research methods Sample and data A number of lecturers working in different public and private universities in Yogyakarta province participated as respondents in this research. Sampling frame was determined based on the publication of Indonesian Higher Education Department (http://evaluasi.or.id/index.php). A total of 750 questionnaires were distributed to the respondents by using snowball sampling method. After being verified, about 347 of returned questionnaires are usable which is about 46.3 percent rate of return. Detailed description of the demographic data is given in the Table I.


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Table I. Profiles of the sample respondents

Variable

Group description

Male

University status

Public Private Total

90 120 210

Age

#41 years .41 years Total

Experience

Gender Female

Total

%

45 92 137

134 212 347

39 61 100

79 131 210

79 58 137

158 189 347

46 54 100

#12 years . 12 years Total

89 121 210

77 60 137

166 181 347

48 52 100

Education level

Bachelor degree Master degree Doctoral degree Others Total

45 150 12 3 210

42 91 2 2 137

87 241 14 5 347

25 70 4 1 100

School background

Engineering Business and economics Medical sciences Education Others Total

52 27 7 80 44 210

22 34 28 35 18 137

74 61 35 115 62 347

21 18 10 33 18 100

Academic rank

Associate professor Assistant professor Instructor Others Total

51 78 48 32 210

24 37 53 23 137

75 115 102 55 347

22 33 29 16 100

In total, there are 347 lecturers from 34 different universities in Yogyakarta Province who participated in this research. About 60 percent (i.e. 210) of the sample are male and 40 percent (i.e. 137) are female. It is found that 39 percent of the respondents work in the public universities while 61 percent in the private universities. There are two main age groups of respondents in which 46 percent are 41 years old or less and 54 percent of them are more than 42 years old. Data also show that about 48 percent of respondents have been working as a lecturer for 12 years or less and 52 percent of respondents have their experience as lecturers for more than 12 years. Based on the lecturers’ educational attainment level, the majority, i.e. 70 percent of lecturers hold a master’s degree and many, i.e. about 25 percent have obtained bachelor’s degree and only about 4 percent of lecturers hold doctoral degree and the rest about 1 percent of the lecturers hold only diploma degree or lower. The demographic data indicate that 48 percent of the lecturers have worked for at least 12 years and 52 percent have more than 12 years of work experiences. Research participants come from many different backgrounds of knowledge. About 21 percent of respondents are working in engineering, 18 percent in business and economics, 10 percent in medical sciences, 33 percent in education, and 18 percent in other different faculties.

In the sample of this study, there are many of the lecturers (i.e. 45 percent) who have no academic rank teaching in the public and private universities. Such lecturers may become a guest or adjunct lecturer in the universities. They might be a practitioner, financial analyst, technician, business people or others who voluntarily participated in delivering their practical knowledge to the students. About 33 percent are assistant professors and 22 percent are associate professors. Since there is a limited number of professor and it is difficult to request their participation, no single professor has participated in this study. Variable measurement A two section questionnaire is used to collect the data. The first section asks the respondents about their demographic data. In the second section, the respondents are requested to indicate their own level of participation in decision-making and performance on various items, using a five-point Likert scale ranging from 1 to 5. An instrument of participative decision-making developed by Marks and Karen (1997) is adopted here. There are four participative decision-making domains used. These are school operations and management, students’ school experiences, teachers’ work life and control over classroom instruction. Data for lecturer performance is obtained by an instrument using six items from Smeenk et al. (2008). It questions the respondents about their quality of research, teaching, publications, public engagement and managerial involvement performance. Results Exploratory factor analysis and reliability test Exploratory factor analysis (EFA) and reliability test were conducted in the beginning before regression and ANOVA test were conducted. Based on the EFA, all items have significant factor loading as expected on the main factor. Table II indicates that all factor loading values are more than 0.5 as suggested by Hair et al. (2006). Based on the KMO test, as a measure of sampling adequacy, the results showed that KMO for overall variables are 0.831 greater than 0.50 (suggested by Hair et al., 2006), so that exploratory factor analysis could be continued. The probability associated with the Bartlett test for this research was p , 0.000 less than the level of significance (0.05) as it was required. Cronbach’s alpha coefficients of participative decision-making and lecturer performance instruments are respectively 0.868 and 0.863. As these are higher than 0.70, it could be concluded that the instruments are reliable (Nunnally, 1978; Hair et al., 2006). Comparative analysis on demographic data This section provides information regarding comparison analysis based on the demographic data on the lecturer participation in decision making and their performance. Based on t-test results listed in Tables III and IV, it is found that gender status does not distinguish level of lecturer participation and performance. Both male and female lecturers perform and participate in decision making. Further, this research proves that gender discrimination in work is definitely improper policy in an academic position in the university. This finding is confirmatory to several previous studies but contradicting with that of Watson’s (2003) which states that female lecturers perform better than their male


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Description

1

Participative decision making 1.1 Planning the building and budget 1.2 Determining the teaching schedule 1.3 Determining specific professional and teaching assignments 1.4 Establishing the curriculum 1.5 Hiring new professional personnel 1.6 Determining the content of practical subject 1.7 Determining student behavior codes 1.8 Disciplining students 1.9 Setting policy on a class size 1.10 Selecting textbooks and other instructional materials 1.11 Selecting content, topics and skills to be taught 1.12 Selecting teaching techniques

Component 2

0.533 0.693 0.754 0.711 0.677 0.620 0.700 0.616 0.604 0.569 0.563 0.559

Lecturer performance 2.1 Teaching performance (holding a degree, as a thesis advisor, student advisor, tutorial/teaching, writing a textbook, module, or practical manual, developing learning media, etc.) 2.2 Research performance (individual or group) 2.3 Publication performance (publishing an article/paper, translating/editing a book, patenting technological product, etc.) 2.4 Public engagement performance (conducting society training/illumination, as a member of governmental board, etc.) 2.5 Miscellaneous (seminar participant, achievement award, professional organization member, representativeness of organization in any event, a member of a governmental/university project, etc.) 2.5 Overall performance Eigenvalues Total variance explain Cummulative variance explained Alpha Table II. Exploratory factor analysis and reliability test

0.784 0.689 0.786 0.838 5.407 30.039 30.039 0.868

KMO and Bartlett’s test Kaiser-Meyer-Olkin measure of sampling adequacy Bartlett’s test of sphericity approx. chi-square df Sig.

Variable

Category

Gender

Male Female Public Private # 12 years . 12 years # 41 years . 41 years

University status Table III. T-test of participative decision making based on demographic data

0.667 0.795

Experience Age

3.118 17.324 47.364 0.853 0.842 2,998.731 153 0.000

n

Mean

SD

210 137 134 212 166 181 158 189

3.145 3.085 3.088 3.136 3.078 3.161 3.115 3.127

0.745 0.797 0.699 0.802 0.813 0.719 0.817 0.721

t

df

Sig.

0.710

345

0.478

2 0.578

344

0.564

2 1.001

345

0.317

2 0.152

345

0.880

counterpart. Santos et al. (2006), based on their study confirmed that there were no significant differences on mathematics achievement when considering gender. Based on their research findings, Shaffril et al. (2010) also claim that both male and female youth have a similar level of acceptance towards contract farming. Omirin (2007) reveals that there is no significant difference between the academic performance of male and female students in the Nigerian Universities. Based on the t-test results (Table III), there is no significant difference on lecturer participation in decision making and lecturer performance between the two different groups of university status, experience, as well as age. This research result implies that lecturer’s experience or age could not explain lecturer’s participation level in decision making and lecturer performance. It is also found that there is no difference between public and private universities in term of lecturer participation in decision making and performance. These contradict with the previous research findings obtained by Adeyemi (2008), Kadri et al. (2009) and Chien-ern et al. (2008). However, when demographic characteristics are used to explain the difference in the lecturer performance, it is found that “university status” is significantly related to lecturer performance, i.e. at the 0.10 level. The mean values indicate that lecturers working in public universities tend to have a better performance compared to those who work in the private universities. Several chronic problems faced by private universities make them more vulnerable in a high education business competition. The chronic problems are resulted from the lack of funding support, less of qualified staff members, stress on a bigger class, lack of facilities and training and development program, insecure job and less rigorous recruitment program. Another similar evidence is observed; Varghese (2004) found that many private universities in Africa rely heavily on part-time teachers and operate with a limited number of facilities and staff members, self-financing, and less chances to have educational advancement for their staff. Recently, Ashraf et al. (2009) asserted that almost all private universities in Bangladesh are founded on rented space and buildings, research facilities are also underdeveloped. Most of the universities did not have research bureaus, and publication facilities were also limited. Due to the lack of adequate supporting facilities and human resources, it is impossible for the teachers’ and the students’ performance in the private universities to reach a satisfactory level. Examining variation or differences among multiple groups of lecturers in participative decision making reveals that there is no significant difference among educational levels, academic ranks and school backgrounds (see Table V). It implies Variable

Category

n

Mean

SD

Gender

Male Female

210 137

3.645 3.613

0.581 0.572

University status

Public Private

134 212

3.703 3.587

Experience

#12 years .12 Years

166 181

Age

#41 years . 41 years

158 189

t

df

Sig.

0.506

345

0.613

0.530 0.602

1.830

344

0.068

3.581 3.680

0.590 0.562

21.588

345

0.113

3.606 3.654

0.577 0.578

20.768

345

0.443


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Table IV. T-test of lecturer performance based on demographic data

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that level of education, academic rank as well as school background have no effect on the level of participation of the lecturers in decision making process. Table V also shows that lecturer performance among different educational levels are found statistically not different. This finding might be interpreted that a higher degree of education of lecturers could not be used as a guarantee that they would show a better performance. Unreliable practical performance appraisal system and reward system have motivated many lecturers to find another job beyond the campus for their better expectation. On the other hand, the results of the ANOVA test (see Table VI) show that lecturer performance are significantly different among different groups of academic ranks and school backgrounds. Table VI suggests that based on the t-test results, instructor’s and assistant professor’s performance is significantly different from that of associate professor. Associate professor has a higher performance compared to his/her counterparts. Nevertheless, there is no difference between the assistant professor’s and instructor’s performance. Next, Table V also suggests that school backgrounds distinguish lecturer performance significantly (F ¼ 6:194; Sig: ¼ 0:000) (Figure 1). Based on post-hoc test, this study finds that lecturers working in schools (disciplines) such as engineering, medical sciences, business and economics tend to have a worse performance compared to those working in school of education or others. Statistically, there is a significant difference on Indonesian lecturer performance in school of education and school of engineering, medical sciences, business and economics. In more details, the following graphical presentation using mean bars shows that lecturers working in school of education had the highest performance compared to the lecturers working in the other different schools. Linking participation and demographic characteristics to lecturer performance By entering all demographic data and lecturer participation onto the regression model, this study finds that participative decision making and academic rank have a significant impact on lecturer performance (see Table VII). It is widely understood that academic

Table V. ANOVA results based on demographic data

Factor

Dependent variable

F

Sig.

Education level

Participative decision making Lecturer performance

0.548 0.607

0.650 0.611

Academic rank


1.388 2.758

0.238 0.028 *

School background


1.029 6.194

0.392 0.000 *

Academic rank Table VI. T-test results of lecturer performance based on academic rank

Assistant prof. – Instructor Assistant prof. – Associate prof. Instructor – Associate prof.

n

Mean

Mean difference

t

Sig.

115 and 152 115 and 75 152 and 75

3.613 - 3.544 3.613 - 3.813 3.544 - 3.813

0.069 2 0.200 2 0.270

0.976 22.373 23.450

0.330 0.019 0.001


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Figure 1. Mean bars of lecturer performance based on school background

Variable Constant Gender (G) University status (US) Age (A) Marital status (MS) Education level (EL) Experience (E) Academic rank (AR) Lecturer’s participation (PAR) R2 Adjusted R 2 F

Base model (1) 3.117

0.165 * 0.048 0.045 17.383 *

Model a Model a1 Model a2 (2) (3)

Model b Model b1 Model b2 (4) (5)

3.898 20.025 20.049 20.045 0.170 * * 20.038 0.013 20.090 * *

3.985 20.029 20.052 20.125 0.174 * * 20.041 0.025 20.101 * *

0.045 0.025 2.276 *

3.452 2 0.016 2 0.069 2 0.040 0.141 2 0.026 0.008 2 0.078 0.148 * 0.082 0.061 3.788 *

0.048 0.028 2.425 *

3.488 2 0.017 2 0.072 2 0.096 0.140 2 0.029 0.020 2 0.081 * * 0.144 * 0.083 0.061 3.815 *

Notes: *p , 0.000; * *p , 0.050; Model a ¼ Age and experience variable are classified in six groups; Model b ¼ Age and experience variable are classified in 2 groups; (1) Perf ¼ 3.117+0.165 Per *; (2) Perf ¼ 3.898 2 0.025G 2 0.049US 2 0.045A+0.170MS * * 2 0.038EL+0.013E 2 0.090AR * *; (3) Perf ¼ 3.452 2 0.016G 2 0.069US 2 0.040A+0.141MS 2 0.026EL +0.008E 2 0.078AR+0.148PAR *; (4) Perf ¼ 3.985 2 0.029G 2 0.052US 2 0.125A+0.174MS * * 2 0.041EL+0.025E 2 0.101AR * *; (5) Perf ¼ 3.488 2 0.017G 2 0.072US 2 0.096A+0.140MS 2 0.029EL+0.020E 2 0.081AR * *+0.144PAR *

rank will be directly related to lecturer performance. To be promoted to the higher rank, lecturers need more teaching credits, research projects, publications, public services and other managerial activities. It means that they have performed better for their jobs. This finding supports the previous results of studies done by several researchers (Drummond and Reitsch, 1995; Lipman, 1997; Clinton and Hunton, 2001). It suggests that providing lecturers a space to participate in decision-making process will definitely improve not only lecturer commitment, expertise, and effectiveness, responsibilities and shared culture but also lecturer performance (Marks and Karen, 1997; Lipman, 1997; Drummond and Reitsch, 1995; Lipman, 1997; Clinton and Hunton, 2001).

Table VII. Regression matrix on lecturer performance

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A three-model of regression analysis is conducted to examine the impact of participative decision making and demographic characteristics on lecturer performance. In the first step (base model), it is found that participative decision making affect significantly on lecturer performance (b ¼ 0:219; p , 0.000). Gender and experience are classified in six dummy variables (model a1) or two groups (model b1), both models show that marital status and academic rank are significantly related to the lecturer performance. Marital status shows a positive and significant impact on the lecturer performance ( p , 0.050) while organization rank is negatively related to lecturer performance ( p , 0.050). Model a2 and b2 are simultaneous regressions of demographic characteristics and participative decision making on lecturer performance. Regression results based on the model a2 show that none of the variables except participative decision making has a positive and significant impact on lecturer performance (b ¼ 0:197; p , 0.000). Academic rank and participative decision making have a significant impact on lecturer performance in model b2. However, surprisingly, academic rank shows a negative impact on the lecturer performance. It is most likely, based on casual observations, that ineffective reward system and performance appraisal system are the explanation. As it was predicted by Bennell (2004) that regardless of development status, the teaching force in most countries has never enjoyed full professional status. It is widely noted that incentives to enhance schools and teacher performance are frequently weak due to ineffective incentives design and interventions. This is particularly the case when teachers cannot be effectively disciplined for unacceptable behavior (absenteeism, lateness, poor teaching, abusive behavior towards pupils) by school management because it is very difficult to dismiss them. In addition, pay and promotion are largely unrelated to actual performance. In short, Bennell (2004) declared that where teacher’s pay is very low, there is normally de facto recognition that the “labour process” in school has to be organized in such a way that enables teachers their autonomy to generate additional income. In line with the earlier findings, regression coefficients and their significance presented in Table VII (model a2 and b2) displays that gender status, university status, age, experience, marital status and education level do not have significant effect on lecturer performance. These findings support a relevant study conducted by Gunbayi (2007) from a sample of 204 teachers from nine urban high schools in the center of Afyon and Usak cities in the west of Turkey. He found that there was no significant difference in the organizational clarity and standards, commitment, autonomy, intimacy and support, member conflict and rewards according to the gender, marital status, educational levels and seniority levels of the teachers. Later on, Akiri and Ugborugbo (2008) also proved that there was no significant difference in the productivity of male and female teachers in secondary school teachers in Delta State, Nigeria, although the male teachers were generally more productive than their female counterparts and that female teachers were more influenced by location than the male teachers. In term of teaching experience, Alexander (2004) in his study of teacher performance in Texas separated years of experience into four ranges of experience. These categorical ranges are: 0-5 years, 6-10 years, 11-20 years, and greater than 20 years. He found all the ranges of experience produced a negative coefficient, but none were significantly distinguishing teacher performance in Texas. What was revealed by Alexander is definitely similar to this present study.

Conclusion and recommendations This study empirically examines the impact of lecturer participation on lecturer performance in higher education institutions in Indonesia. There are several conclusions based on the research findings described in the previous section. First, this research finds that academic rank positively affects lecturer performance. Surely, in Indonesia, engaging more in research, teaching, publications, public service and other managerial activities becomes an academic requirement and prerequisite for the lecturers to get a higher academic rank. Secondly, gender status, university status, age, experience, marital status and education do not have significant effect on lecturer performance. These findings suggest that it is of high priority that the Indonesian government immediately set a better performance appraisal system and reward system to obtain a better lecturer performance. Thirdly, this research finds that participative decision making has a significant impact on lecturer performance in higher education institutions in Indonesia. This finding strongly recommends educational leaders to encourage a higher level of their lecturer involvement (engagement) both emotionally and physically in making decisions related to school operations and management, students’ school experiences, teachers’ work life and control over classroom instruction. By doing so, this policy is expected to increase lecturer and university performance. Fourthly, this research has partially failed to support research hypotheses related to the effect of several demographic characteristics. It is contradictory to the findings of Eyupoglu and Saner (2009), Kennedy and Drennan (1998), Adeyemi (2008), and Kadri et al. (2009) and Chien-ern et al. (2008). Since not only local but also central government have allocated a numerous facilities to the public universities, it is recommended to expeditiously administer a profound examination on factors affecting the research anomalies regarding university status, academic rank, educational level and teaching experiences. Finally, to capture a deeper explanation of factors affecting lecturer performance in higher educational institution in Indonesia, it is suggested for future research to take into account other personal and organizational factors such as motivation, recruitment system, performance appraisal system and reward system into their research model.

References Ackah, C. and Heaton, N. (2003), “Human resource management careers: different paths for men and women?”, Career Development International, Vol. 8 No. 3, pp. 134-42. Adeyemi, T.O. (2008), “Teachers’ teaching experience and students’ learning outcomes in secondary schools in Ondo State”, Nigeria Educational Research and Review, Vol. 3 No. 6, pp. 204-12. Akiri, A.A. and Ugborugbo, N.M. (2008), “An examination of gender’s influence on teachers’ productivity in secondary schools”, Journal of Social Science, Vol. 17 No. 3, pp. 185-91. Alexander, C. (2004), “Does teacher certification matter? Teacher certification and middle school mathematics achievement in Texas”, paper presented at the Annual Meeting of the American Educational Research Association San Diego, CA, April 12, available at: www. sedl.org/pubs/policyresearch/resources/AERA-2004.pdf (accessed 3 August 2010).


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interest areas are in human resources management, educational measurement, financial management and managerial accounting. D.A. Sukirno is the corresponding author and can be contacted at: [email protected] Sununta Siengthai is an Associate Professor in Human Resource Management at the School of Management Asian Institute of Technology. She received her MA and PhD degrees from the University of Illinois at Urbana Champaign; both are in the area of labor and industrial relations. Her research interests are in human resources management, industrial relations, performance management and measurement and international human resources management.

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