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Volume LVI, Number 2

What are the Crucial Factors Explaining Job Satisfaction and Dissatisfaction in RMAs? Statistical Analysis Based on the Japanese Survey

 

Shin Ito, Ph.D., MBA
Institute for Future Initiatives, The University of Tokyo, Japan

Hiroaki Hanaoka, M.A.
Co-Creation Affairs Division, Department of Co-Creation Promotion, The University of Osaka, Japan

Norihiro Hirata, Ph.D.
Research Administration Center, Innovative Research and Liaison Organization, Shinshu University, Japan

Makiko Takahashi, Ph.D.
Graduate School of Innovation Management, Kanazawa Institute of Technology, Japan

 

Abstract

Research managers and administrators (RMAs) face several challenges due to the various tasks and roles required in university research management. One of the challenges is their workplace environment, including job satisfaction. However, little empirical research has statistically analyzed the relationships between job satisfaction and its factors among RMAs. This analysis divided job satisfaction into Job content satisfaction and Employment dissatisfaction. Regression analysis statistically verified the relationships using Japanese survey data of 245 individuals. The logistic regression results showed that if RMAs experience Esteeming work content after employment, they have high Job content satisfaction and low Employment dissatisfaction. Some characteristics of RMAs were also significantly related to Job content satisfaction. Another regression analysis confirmed that high Job content satisfaction and low Employment dissatisfaction had significantly positive relationships with Affective commitment. An additional interview survey enforced these results. Affective commitment generally predicts organizational performance and employee turnover reduction. Thus, the results imply that specific approaches to improve job content satisfaction and employment dissatisfaction are necessary for universities and other institutions that hire RMAs to enhance research activities. Furthermore, the results provide valuable suggestions for RMAs’ career development and emphasize the characteristics of RMAs as a profession.

Keywords: Research Managers and Administrators (RMAs); Job Satisfaction; Affective Commitment; Japanese Survey Data; Regression Analysis

 

Introduction

University research activities, which play an essential role in the knowledge economy, are growing and changing over time. In recent years, university researchers have expanded their roles not only to produce academic results but also to engage in various other activities, such as obtaining external funding, including from industry, managing projects, and disseminating and utilizing research results (Kyvik, 2013; Altamony et al., 2017). These changes require a highly diverse set of new professionals (Gibbs & Kharouf, 2020). This situation has led to an increase in the role of research managers and administrators (RMAs), who are professional personnel supporting research (Kerridge & Scott, 2018; Kerridge et al., 2023).

Research management and administration in universities is a growing area for effectively promoting research (Derrick & Nickson, 2014; Schützenmeister, 2010) and is associated with high research productivity (Beerkens, 2013). RMAs’ extensive duties include acquiring external research funds, budget management, contract negotiation, compliance with research ethics and laws, and planning research projects. RMAs with diverse titles are now present in universities and research institutions in various countries, and the RMA profession is growing worldwide and developing as a global profession (Kerridge & Scott, 2018; Kerridge et al., 2023).

RMAs constitute the foundation of research activities in universities and research institutions, but they also face several challenges: the tasks and roles required of RMAs are extensive (Tauginienė, 2009; Shelley, 2010; Shambrook & Roberts, 2011), and in many countries, their roles and functions are not clearly defined (Virágh et al., 2019). The boundaries of their operations also tend to be blurry. As a result, they do not receive sufficient recognition of their roles and tasks from the university executives and researchers, the direct stakeholders RMAs support (Poli, 2018; Virágh et al., 2019). Although the history of RMA, tracing its origins to the United States (Monahan et al., 2023), is more than 60 years old, it is still a developing profession.

Such difficulties for RMAs hinder the smooth execution of work and can have a negative psychological impact. In other words, RMAs may feel dissatisfied and find themselves unable to increase satisfaction due to work-specific circumstances.

Job satisfaction is one of the subjects that has drawn the highest interest from researchers in the field of organization management. The existing research indicates that job satisfaction affects employees’ behavior and cognition, such as organizational commitment (e.g., Patrick & Sonia, 2012; Koo et al., 2020) and retention (e.g., De Sousa Sabbagha et al., 2018). Many studies report that job satisfaction positively correlates with individual and organizational performance (e.g., Bakotić, 2016; Katebi et al., 2022; Platis et al., 2015). RMAs’ job satisfaction or dissatisfaction will also influence their activities and, in turn, the efficiency of research management and administration in the entire organization. However, only a few empirical studies have statistically analyzed the relationship between job satisfaction and its factors among RMAs (e.g., Volkwein & Parmley, 2000).

Employees’ satisfaction depends on job characteristics (Hackman & Lawler, 1971; Hackman & Oldham, 1975). Hackman and Oldham (1975) proposed a model with five core dimensions as job characteristics: skill variety, task identity, task significance, work autonomy, and feedback on results. After that, many studies have examined this job characteristic model. For example, Ali et al. (2014) verified the positive relationships between the five core dimensions and job satisfaction based on a survey of fast-food managers. Although the regression analysis results indicated that skill variety most explained the variance in job satisfaction, the researchers judged it derived from the job background. Similarly, Blanz (2017) used survey data from social workers in Germany and confirmed that all five core dimensions correlate with job satisfaction. 

Moreover, De Haan et al. (2012) added creativity as a job characteristic in a model. RMAs collaborate closely with researchers in universities and research institutions to improve the viability and efficiency of research activities (De Jong & del Junco, 2023). As RMAs’ tasks contain survey analysis and project planning that require creativity, their job characteristics are presumably linked to job satisfaction.

A notable characteristic of professionals is that they are firmly committed to the field of their expertise and technology rather than to the organization that employs them (Gouldner, 1957; Wallace, 1995). However, in the case of RMAs, a holistic perspective is necessary to coordinate with related parties inside and outside the university (Shambrook & Roberts, 2011). Namely, having a high level of professional and organizational orientation is desirable. The relationship between these job characteristics and job satisfaction remains blurry.

On the other hand, since RMAs work and collaborate with faculty, they require a high level of expertise and communication skills. Their stress as an interpersonal service has also been reported (Katsapis, 2012; Shambrook, 2012). The intensity of stress on professionals has been the subject of extensive empirical research in fields such as nursing, caregiving, teaching, and hospitality. In these fields of stressful interpersonal services, exploring factors improving job satisfaction is significant from both academic and practical perspectives.

In summary, RMAs face many challenges in performing their duties. The professional environment affects RMAs’ job satisfaction, which in turn can influence individual and organizational performance. Examining these relationships could play a decisive role in improving the management of organizations with RMAs.

Therefore, this study aims to clarify the relationship between job satisfaction or dissatisfaction and its factors among RMAs. The relationship between organizational commitment and job satisfaction or dissatisfaction will also be clarified. Although RMAs’ performance attracts attention, little research has examined organizational commitment that mediates between job satisfaction and performance. Specifically, this analysis will statistically verify these relationships using data from a Japanese questionnaire survey conducted by the Research Manager and Administrator Network Japan (RMAN-J).

The results of this study will not only fill a gap in academic literature but also help RMAs make specific improvements to achieve a more satisfying way of working. Increased job satisfaction might lead to smoother and more efficient research activities, ultimately contributing to improved research results and the development of the research institution. Furthermore, it will provide valuable suggestions for RMAs’ career development and emphasize the attractiveness of RMAs as a profession.

 

Theory

Concept of Job Satisfaction

Job Satisfaction

Job satisfaction is an umbrella concept that describes pleasing or positive feelings arising from an individual’s evaluation of or experience on the job (Locke, 1976). There is an accumulation of research on job satisfaction in areas such as management organization theory. Among them, Herzberg’s two-factor theory (Herzberg et al, 1959) is a framework for collecting long-term attention to understand job satisfaction. This theory divides factors into two categories: motivational factors (satisfiers) leading to job satisfaction and hygiene factors (dissatisfiers) leading to job dissatisfaction. Motivational factors include achievement, recognition, job content, responsibility, promotion, and growth potential. In contrast, hygiene factors cover supervision, company policy and management, working conditions, interpersonal relationships, position, job security, and salary.

Motivational and hygiene factors have different effects on job satisfaction. When hygiene factors are vital, employees feel dissatisfied, but this does not mean satisfaction improves if these factors disappear. On the other hand, when motivational factors are vital, employee satisfaction increases. Many studies have referred to the two-factor theory, and debates on its validity have continued today, both in support and in opposition (e.g., Diener, 1985; Gawel, 1996; Knight & Westbrook, 1999; Mehrad, 2020; Siruri & Cheche, 2021). One of the remarkable contrary arguments is that some hygiene factors, such as salary, work as motivational factors in specific professions (Gawel, 1996). For research incorporating the two-factor theory, it is necessary to consider the background circumstances and context of the research subject.

Job Characteristics

Job characteristic theory (Hackman & Lawler, 1971; Hackman & Oldham, 1975) states that job characteristics influence job satisfaction, motivation, and performance. Job characteristics refer to the specific elements or descriptions of an employee’s job. Job characteristics can also appear in employee attributes (age, gender, years on the job).

So far, many studies have attempted to understand how these job characteristics affect employees’ job satisfaction (Ali et al., 2014; Blanz, 2017; De Haan et al., 2012; Ehrhart, 2006; Raihan, 2020). These studies show that the main dimensions of job characteristics theory have paths to job satisfaction. For example, a high level of job variety, one of the five elements, allows employees to find new challenges and learning opportunities without boredom.

Furthermore, employees with high job diversity will find new challenges and learning opportunities without getting bored. Regarding RMAs, Ito and Takahashi (2023) indicate that perceived job attraction and acquired academic degrees after engagement have significantly positive relationships with the total experience years of research management. Different university professional staff have boosted cognition in their work contributions and deepened collaborations with faculty (Veles et al., 2023).

However, these relationships could depend on the context. For example, Zhao et al. (2016) analyzed the relationship between job characteristics and job satisfaction, focusing on interpersonal service characteristics. The data from hotel employees showed that skill variety, a core dimension in job characteristic theory, was negatively associated with job satisfaction. In certain interpersonal service professions, job variety may increase stress rather than interest or attractiveness of the job. Thus, there still appears to be considerable scope for research.

 

Organizational Commitment

Affective Commitment

Organizational commitment is a concept that describes an employee’s perception or attitude toward the organization. Employees are generally more committed to highly specialized professions. Researchers have proposed various definitions and measurements. Among them, the three components of affective, continuance, and normative commitment proposed by Allen and Meyer (1990) have diffused. Affective commitment indicates the degree of an individual’s sense of connectedness to the organization. Continuance commitment (utilitarian commitment) depends on the perceived benefits of continued participation and the perceived losses associated with leaving. Normative commitment is an activity that arises from an obligation or responsible connection.

Organizational commitment has attracted attention primarily because of its link to turnover and performance. It also gains social interest as the employment environment changes, such as workforce mobility. This study focuses on affective commitment as a factor that positively affects organizational performance.

Job Satisfaction and Affective Commitment

The relationship between job satisfaction and affective commitment has been an active theme in organizational behavior. Both concepts are related to employee involvement and loyalty to the organization and are critical managerial factors for organizations. Many past empirical studies have shown a positive relationship between job satisfaction and affective commitment (e.g., Patrick & Sonia, 2012; Koo et al., 2020). In other words, the more satisfied employees are with their jobs, the greater their affective commitment to the organization tends to be.

Diverse empirical studies have also progressed on the influence of other factors and circumstances on the relationship between job satisfaction and affective commitment. For example, Saha and Kumar (2018) confirm that organizational culture moderates the relationship between job satisfaction and affective commitment based on a questionnaire survey of Indian public sector employees.

Köse and Köse (2017) further examined the relationship between job satisfaction and organizational commitment by dividing job satisfaction into intrinsic and extrinsic. Continuance and normative commitment had significantly negative and positive relationships with extrinsic job satisfaction, respectively, while affective commitment had no significant relationship with intrinsic or extrinsic job satisfaction.

These empirical studies suggest that the relationship between job satisfaction and affective commitment is complex, as other factors and individual characteristics also influence the relationship. Thus, although employees with higher job satisfaction tend to have higher affective commitment, there remains room to study the relationship in light of other factors and contexts.

 

Occupational stress of RMAs

Job characteristics can be associated with specific stressors. Mark and Smith (2012) investigated the relationship between job characteristics, coping behaviors, and mental health conditions among 307 employees at a single UK university. The focal university employees included administrative staff, managers, professors, researchers, and lecturers. Using a questionnaire survey, the researchers found that university employees had significantly stronger tendencies toward anxiety and depression compared with 120 non-university participants in the general population. Regression analysis showed that job characteristics such as high job demands in the workplace and the heavy workload required to meet those demands were associated with high levels of anxiety and depression.

Some researchers have investigated the nature and role of RMAs (Tauginienė, 2009; Cole, 2010; Shelley, 2010; Nash & Wright, 2013). Schiller and LeMire (2023) highlighted the burden of RMAs engaged in post-award administration. Stress of RMAs also has been reported (Katsapis, 2012; Shambrook, 2012).

Tabakakis et al. (2020) conducted a statistical analysis of burnout and related factors through an international Internet survey. The survey received responses from 2,416 individuals from RMA-related organizations in four countries: the United States, the United Kingdom, Australia, and Canada. They classified burnout into three categories: interpersonal, work-related, and customer-related. As a result, many items such as work pace, role clarity, quality of leadership, work-family conflict, and justice and respect were significantly related to burnout in all three categories. This research highlights that burnout is a common issue academic research organizations should undertake.

In summary, job satisfaction has long been the subject of management research. Job satisfaction is positively related to affective commitment, an individual’s sense of belonging to the organization. Furthermore, many researchers have confirmed that job characteristics influence job satisfaction, but the relationship is context-dependent and leaves room for further research, especially in the RMA field.

 

Methods

This section proposes three emerging concepts arising from this project. To arrive at a set of concepts, the group met to discuss the objectives of each phase, share experiences, and read through the vignettes. Through a brainstorming session, the group finalized a list of emerging concepts, which are defined and exemplified in this section.

 

Questionnaire Survey

RMAN-J, established in March 2015, is the professional association representing RMAs in Japan. As of the end of June 2023, it had 36 organizational members, 656 individual members, and six supporting members, and it holds a national conference annually.

In Japan, the Ministry of Education, Culture, Sports, Science and Technology (MEXT) conducts an annual survey on industry-academia-government collaboration, using universities and other organizations as survey units. RMAN-J established a working group to consider the necessity of individual-level data complementary to the MEXT (2021) survey. The working group conducts questionnaire surveys for the members irregularly. This study utilizes the data from a survey conducted by RMAN-J in the 2022-23 Financial Year, which included questions on job satisfaction and career choices.

The survey was conducted from July to September 2022 and employed an online questionnaire using a Google form. The questionnaire was sent to all 637 RMAN-J individual members; participation was voluntary. In August, the survey working group reminded no-respondents to take the survey. As a result, the number of respondents reached 287 (response rate: 45.1%). Personal demographic information such as age, gender, and educational background was collected for all respondents. Respondents working in research administration (RA) or similar work, regardless of position title, were asked about their work experience, perceptions of their organization, employment conditions, and level of satisfaction. The attribute question items stem from those in RAAAP-2 (Kerridge et al., 2020; Poli et al., 2023), an international survey by research management/administration-related organizations in various countries.

The number of respondents engaging in RMA or similar work was 247. This analysis excluded the two respondents with missing values in the focal items and, as a result, focused on the 245 responses. The type of affiliation of the subjects was 162 (66.1%) national universities, 10 (4.1%) public universities, 40 (16.3%) private universities, 15 (6.1%) inter-university research institutes, 12 (4.9%) national research and development corporations, and 6 (2.4%) companies and others.

 

Selection Bias

As mentioned earlier, the dataset is comprised of responses from RMAN-J individual members. The survey was free to join. Thus, there is an inherent selection bias. The gender differences between the Japan subset of RAAAP-2 data (Kerridge et al., 2022) and this dataset indicated no statistical significance: χ2 (1) = 161.61, P = 0.704. Another test on age distribution between the MEXT (2021) survey and the dataset indicated a significant difference: χ2 (3) = 25.974, P < 0.001. The dataset includes younger ages than the MEXT survey. Therefore, one must consider the selection bias and interpret the results carefully.

 

Objective Variables

Job Satisfaction

Based on the discussion after Herzberg’s two-factor theory (Herzberg et al., 1959), this study measures satisfaction with job content as a motivational factor and dissatisfaction with working conditions as a hygiene factor. The respondents answered job satisfaction on a 5-point Likert scale ranging from “very satisfied” to “not satisfied at all.” A dummy variable indicating Job content satisfaction was created by assigning 1 to the “very satisfied” and “somewhat satisfied” responses and 0 to the “neither satisfied nor dissatisfied,” “not very satisfied,” and “not satisfied at all” responses. Similarly, another dummy variable indicating Employment dissatisfaction was created by assigning 1 to the “not at all satisfied” and “not very satisfied” responses and 0 to the other responses. Both became objective variables.

Affective Commitment

For the affective commitment, the questionnaire selected three items from Allen and Meyer (1990): “I would be very happy to spend the rest of my career with this organization,” “I want to introduce my organization to people outside it,” and “I feel emotionally attached to this organization.” The item “My current organization is a place where I can grow” was an additional question about the place of career development. The wording has reflected the recent discussion that employees see their organizations as a place to grow and develop their knowledge and skills (e.g., Manuti et al., 2017). The respondents rated their perception of their organization on a 5-point Likert scale from “Applicable” to “Not applicable” for the four items. Factor analysis generated the objective variable Affective commitment from these four items.

 

Explanatory Variables

Job Characteristic Variables

Researchers have long discussed Job characteristics as a factor in job satisfaction (Hackman & Lawler, 1971). This study created the URA position and Research activity dummy variables to reflect the job characteristics of RMAs. In Japan, individuals in diversified positions carry out RMA work and similar tasks. Therefore, the questionnaire survey asked about official positions with a wide range of options: URA (university research administrator), a faculty member, a professional at a university or other institution, a traditional university administrator, a corporate researcher, a corporate employee except researcher, an executive officer at a university or other institution, and other. URA is a growing position descriptor and title in Japan, and the position generally differs from that of a faculty and traditional administrator. Assigning 1 to the respondents holding a URA position and 0 to any other position created the URA position as an explanatory dummy variable.

RMAs may wish to conduct research as part of their work to utilize their research experience. Since some RMAs in Japan officially allocate part of their work to research, the questionnaire included an item with three options: “allowed to conduct research activities,” “not allowed to conduct research activities,” and “other.” The Research activity dummy explanatory variable was created by assigning 1 if the research activity was allowed and 0 if not.

Experience in Multiple Organizations

Another question addressed the number of institutions to which they had ever belonged as RMAs as an explanatory variable. An increase in the number of institutions one has worked for may improve satisfaction and performance because of the variety of experiences one has gained. On the other hand, if required knowledge is highly organization-dependent, moving from one organization to another may result in a decline in satisfaction and performance due to the inability to utilize previous knowledge. In the past, Japan had a strong culture, system, and practices supporting lifetime employment in both the corporate and public sectors. Although they have been weakening in recent years, they remain deeply rooted.

For this reason, the number of organizations an employee enrolled in could likely connect to job satisfaction and dissatisfaction in Japan. This analysis generated the dummy variable Experience in multiple organizations for the number of institutions by assigning a value of 1 when the number of institutions was two or more and a value of 0 otherwise.

Crucial Item to Continue RMA

The RMAN-J survey had a section asking about what respondents had valued most in their decision to continue working as RMAs. The choices followed RAAAP-2 (Kerridge et al., 2020; Poli et al., 2023). The composition of responses was as follows: job content 123 respondents (50.2%); attractiveness of their organization 14 (5.7%); benefits (salary, length of employment) 16 (6.5%); location 16 (6.5%), research support position using research experience 42 (17.1%), utilization of qualifications and experience 10 (4.1%), and others 24 (9.8%). In this analysis, assigning 1 to responses for job content and 0 to all other responses generated a dummy variable of Esteeming work content.

 

Control Variables

Control variables arose from the questionnaire items regarding respondents’ attributes. The age options consisted of six levels: every ten years for ages 20-59 and 60 or older. One respondent (0.4%) was aged 20-29, 42 (17.1%) were 30-39, 85 (34.7%) were 40-49, 73 (29.8%) were 50- 59, and 44 (18.0%) were 60 and older. Putting those Ages under 40 as a reference category created three dummy variables for the Ages 40-49, Ages 50-59, and Age 60 or older.

Prior research (Ito & Watanabe, 2020) confirmed the link between academic qualifications and RMA skills. The RMAN-J survey also included a question about the highest academic qualification. The analysis contained 130 respondents (53.1%) with a doctorate, 71 (29.0%) with a master’s degree, 39 (15.9%) with a bachelor’s degree, and 5 (2.0%) with other such as junior college. This educational item created a dummy variable Doctorate by assigning 1 to the respondents with a doctorate and 0 to the others.

Since the working environment differs between Japan and overseas, such as Europe and the United States, the RMAN-J survey incorporated experience working overseas into the questions. A dummy variable, Experience working abroad, was assigned 1 if the respondent had worked abroad (61 respondents, 24.9%) and 0 otherwise (184 respondents, 75.1%).

Considering that work arrangement flexibility also affects job satisfaction, the RMAN-J survey asked about work arrangements. The analysis included 128 (52.2%) fixed full-time, 29 (11.8%) flexible and full-time, 83 (33.9%) discretionary work, and 5 (2.0%) part-time and other. To create a dummy variable for Discretionary or flexible work, in this analysis, 1 was assigned to flexible full-time and discretionary work and 0 to all others.

In addition to full-time RMA duties, some Japanese RMAs have educational and research or traditional administrative duties. The sample included 195 (79.6%) full-time duty, 22 (9.0%) concurrently engaged in education and research duties, 25 (10.2%) concurrently engaged in administrative duty, and 3 (1.2%) in other duties. In the analysis, a dummy variable, Full-time RMA duty, with those reporting RMA as a full-time duty being assigned 1, and all others 0.

The questionnaire measured the respondents’ career duration by the Cumulative work years as an RMA. The item set up several classes: in 1-year increments from less than 1 to 6 years, 7 to 9 years, 10 to 14 years, and 15 or more years. The median years replaced each class, and the class of 15 years or more was represented by 20 years. Although this control variable is strictly an ordinal scale, it was treated as an interval scale because the number of years contained ten steps.

In the gender category, 101 (41.2%) women and 144 (58.8%) men responded. However, the item was excluded from this analysis because their correlations with the objective and main explanatory variables were weak, and the insertion did not change the regression analysis results.

 

Regression Model

Based on the previous studies and the meanings of the variables, this analysis statistically evaluated a model with Job content satisfaction as the objective variable first and then a model with Job content satisfaction as the explanatory variable and Affective commitment as the objective variable. Since Job content satisfaction is a binary variable, a binary logistic regression analysis was selected for the model with Job content satisfaction as the objective variable. The estimation method was the maximum likelihood method. Ordinary least squares (OLS) regression analysis with robust standard errors proceeded. The statistical analysis was conducted using SPSS version 29.

 

Figure 1. Method Flowchart

 

Supplemental Interview Survey

Interviews were conducted from October to November 2023 to reinforce the questionnaire survey. The focal group consisted of 18 individuals with high Job content satisfaction and low Employment dissatisfaction among those willing to cooperate with the follow-up survey. As a consequence, 12 individuals agreed to be interviewed (response rate: 66.7%). The approach was a semi-structured interview based on a short version (20 items) of the Minnesota Satisfaction Questionnaire (MSQ, Weiss et al., 1967). The respondents selected all the statements that applied to them from the employment (8 items) and job content satisfaction (12 items) sections. The interview questionnaire slightly modified some items for RMAs.

 

Results

Pre-Data Analysis

At first, the distributions of the objective variables were checked. As for the job content satisfaction measured on a 5-point Likert scale, the most frequent response was “somewhat satisfied” at 47.8%. The distribution of the variable was unimodal and showed no ceiling or floor effects. Similarly, the most frequent response to employment satisfaction was “somewhat satisfied” at 35.9%. The distribution exhibited a unimodal and no ceiling or floor effects. All four items to measure affected commitment on a 5-point Likert scale did not follow normality but were unimodal and indicated no ceiling or floor effects. The most frequent responses were “neutral” about “I would be very happy to spend the rest of my career with this organization” and “I want to introduce my organization to people outside it.” As for “I feel emotionally attached to this organization” and “My current organization is a place where I can grow,” “somewhat applicable” was the most frequent response.

 

Factor Analysis

An exploratory factor analysis (EFA) using the maximum likelihood method determined the factor structure of the four items used to measure affective commitment. One factor had an eigenvalue greater than 1.0 (eigenvalue of 2.452), indicating a one-factor structure. Factor loadings ranged from 0.538 to 0.858. Cronbach’s alpha coefficient, which indicates reliability for these four items, was calculated to be 0.778, confirming a high degree of internal consistency and meeting the reliability criterion of 0.6 or higher (Bagozzi & Yi, 1988). The factor scores of the first factor became the objective variable, Affective commitment.

 

Descriptive Statistics

Table 1 shows the descriptive statistics of the variables analyzed. All variables except for Affective commitment and Cumulative work years are dummy variables. Affective commitment derived from factor scores was a variable centered with a mean of 0.

 

Table 1. Descriptive statistics

Variables	Average	S.D.	Min	Max
Affective commitment	0.000	0.915	-2.588	1.377
Job content satisfaction	0.702	0.458	0	1
Employment dissatisfaction	0.273	0.447	0	1
Ages 40-49	0.347	0.477	0	1
Ages 50-59	0.298	0.458	0	1
Age 60 or older	0.180	0.385	0	1
Doctorate	0.531	0.500	0	1
Experience working abroad	0.249	0.433	0	1
Discretionary or flexible work	0.457	0.499	0	1
Full-time RMA duty	0.796	0.404	0	1
Cumulative work years	7.312	5.753	0.500	20.000
URA position	0.653	0.477	0	1
Research activity	0.384	0.487	0	1
Experience in multiple organizations	0.376	0.485	0	1
Esteeming work content	0.502	0.501	0	1

 n = 245. S.D., Standard deviation.
All variables are dummy items apart from Affective commitment and Cumulative work years as an RMA.
The reference category of the three age dummy variables is Age under 40.

 

Logistic Regression Analysis

Table 2 shows the results of the logistic regression analysis with Job content satisfaction and Employment dissatisfaction as the objective variables. Models 1 and 2 have Job content satisfaction as the objective variable, while Models 3 and 4 have Employment dissatisfaction as the objective variable. Models 1 and 3 have only control variables, while models 2 and 4 have all control and explanatory variables. In both models, the input variables’ VIF (variance inflation factor) values were below 2.1, indicating that the models were unaffected by severe multi-collinearity. The results of the Hosmer-Lemeshow test, an indicator of model goodness of fit, showed that the range of significance probabilities for models 1 to 4 was 0.166 to 0.374, which is above 0.05, and the goodness of fit was considered good.

Models 1 and 2 show that the control variable, Age 60 or older dummy, had a significant (p<0.05) relationship with high Job content satisfaction. In Model 2, the URA position, Research activity, and Esteeming work content had significant relationships with high Job content satisfaction. In contrast, Experience in multiple organizations had a significant association with low Job content satisfaction. In particular, the odds ratio for Esteeming work content was as high as 3.280.

Models 3 and 4 indicate that the control variable, the Age 60 or older dummy, had a significant relationship with low Employment dissatisfaction. In contrast, the coefficient of Experience working abroad was significant with high Employment dissatisfaction. In Model 4, the URA position and Experience in multiple organizations had significant links to high Employment dissatisfaction. Conversely, Esteeming work content was significantly related to low Employment dissatisfaction. Research activity had no significant relationship.

The goodness of fit in Model 2 improved concerning the correct response rate, the NagelkerkeR2 pseudo coefficient of determination, and the -2 log-likelihood. Similarly, Model 4 was better than Model 3 in the goodness of fit.

 

Table 2. Logistic regression on Job content satisfaction and Employment dissatisfaction

	Model 1					Model 2					Model 3					Model 4
Variables	B	S.E.	p	Odds		B	S.E.	p	Odds		B	S.E.	p	Odds		B	S.E.	p	Odds
Ages 40-49	0.583	0.419	0.164	1.792		0.728	0.446	0.102	2.071		-0.174	0.429	0.685	0.840		-0.311	0.453	0.492	0.733
Ages 50-59	-0.145	0.419	0.729	0.865		0.040	0.445	0.928	1.041		-0.444	0.458	0.332	0.641		-0.568	0.475	0.232	0.566
Age 60 or older	1.397	0.558	0.012	4.042		1.911	0.615	0.002	6.760		-1.443	0.588	0.014	0.236		-1.425	0.613	0.020	0.241
Doctorate	0.120	0.305	0.694	1.128		0.275	0.348	0.429	1.317		-0.027	0.315	0.933	0.974		-0.313	0.344	0.362	0.731
Experience working abroad	-0.434	0.336	0.196	0.648		-0.462	0.356	0.195	0.630		1.038	0.337	0.002	2.824		1.098	0.353	0.002	2.998
Discretionary or flexible work	-0.244	0.308	0.428	0.783		-0.502	0.350	0.151	0.606		0.052	0.317	0.869	1.054		0.094	0.343	0.784	1.099
Full-time RMA duty	-0.300	0.376	0.425	0.741		-0.545	0.431	0.206	0.580		0.077	0.373	0.835	1.081		-0.304	0.425	0.474	0.738
Cumulative work years	0.023	0.027	0.393	1.023		0.048	0.032	0.131	1.049		0.034	0.027	0.208	1.034		0.032	0.031	0.303	1.032
URA position						0.794	0.372	0.033	2.212							0.816	0.388	0.035	2.262
Research activity						0.741	0.375	0.048	2.097							0.110	0.363	0.761	1.117
Experience in multiple organizations						-0.756	0.345	0.029	0.470							0.772	0.345	0.025	2.165
Esteeming work content						1.188	0.333	<0.001	3.280							-0.796	0.328	0.015	0.451
Constant	0.749	0.485	0.122	2.114		-0.368	0.575	0.522	0.692		-1.187	0.500	0.018	0.305		-1.215	0.594	0.041	0.297
Correct rate	68.6					70.2					73.5					73.5
NagelkerkeR2	0.095					0.232					0.096					0.183
-2 log-likelihood	281.5					254.7					270.6					254.3
Hosmer-Lemeshow test	0.374					0.208					0.179					0.166

B, non-standardization coefficient; S.E., standard error; p, significance probability; Odds, Odds ratio

 

OLS with Robust Standard Error

Next, an OLS regression analysis with robust standard errors used Affective commitment as the objective variable. The regression resulted in Table 3. The same variables as the control and explanatory ones in the logistic regression are used in Model 1. Model 2 added Job content satisfaction to Model 1, and Model 3 added Employment dissatisfaction to Model 1. Model 4 includes both Job content satisfaction and Employment dissatisfaction. In all models, the VIF value of each variable was less than 2.2, indicating no severe effects due to multi-collinearity. Regarding the overall significance of the models, the results of the F-test were all significant (p<0.05).

Models 2 and 4 indicate that Job content satisfaction had a positive and significant relationship with Affective commitment. Similarly, in Models 3 and 4, Employment dissatisfaction had a negative and significant relationship with Affective commitment. Comparing the adjusted R2 coefficient of determination, Models 2 and 3 were better than Model 1, with Model 4 having the highest adjusted R2.

Cumulative work years and Affective commitment possessed positive and significant relationships for all models in Table 3. Discretionary or flexible work was significantly positively related to Affective commitment only in Models 2 and 4.

 

Table 3. Multiple regression on Affective commitment

B, non-standardization coefficient; S.E., standard error; p, significance probability

 

Interview Survey Results

The supplemental interview survey followed the questionnaire survey. Tables 4 and 5 show the question items and answers. The following interpretation reflects the results of the interview survey.

 

Table 4. Items selected by respondents with high Job content satisfaction

Items

A

B

C

D

E

F

G

H

I

J

K

L

Total

The opportunity to work that makes use of my capabilities

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

9

The feeling of achievement that comes from the work

Yes

Yes

Yes

Yes

4

Being able to work a lot

0

Good rapport among co-workers

Yes

Yes

2

Opportunity to experiment with my own way of working

Yes

Yes

Yes

3

The opportunity to work independently

Yes

1

Being able to work without conflicting my conscience

Yes

Yes

2

Being praised for doing a good job

Yes

Yes

Yes

Yes

4

The opportunity to do things for others

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

8

The opportunity to become a respected person in the workplace

0

The way supervisors treat their subordinates

0

The capability of the supervisor to make decisions

Yes

1

 

Table 5. Items selected by respondents with low Employment dissatisfaction

Items

A

B

C

D

E

F

G

H

I

J

K

L

Total

The opportunity to be promoted in this job

Yes

Yes

2

The opportunity to give directions to others

Yes

1

Operating policies indicated by the university or department

Yes

1

The salary and the workload and duties

Yes

Yes

Yes

Yes

4

The freedom to act on my own judgment

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

10

The workplace provides stable employment

Yes

Yes

Yes

3

The opportunity to do a variety of works from time to time

Yes

Yes

Yes

Yes

Yes

Yes

Yes

7

The working conditions

Yes

Yes

Yes

Yes

4

 

Interpretation of Results

Characteristics of URA Positions

Logistic regression analysis showed that URA position among job characteristics related to high Job content satisfaction and Employment dissatisfaction. In other words, compared to other RMAs, such as university faculty members and administrative staff, individuals holding a URA position are attracted to the job content but dissatisfied with employment conditions. Specific causes of dissatisfaction could be compensation, employment status, and criteria for promotion. Regarding employment conditions, many of Japan’s URAs are employed on fixed-term contracts (Takahashi & Ito, 2023).

Using Research Experience

Among the job characteristics, the Research activity connected with high Job content satisfaction but did not have a significant connection with Employment dissatisfaction. These results are consistent with the two-factor theory of Herzberg et al. (1959). In other words, for RMAs, conducting research as part of their job provides an opportunity to utilize their research experience. It increases satisfaction, but being unable to conduct research does not increase dissatisfaction. The increase in satisfaction would be because many RMAs have research experience, and using their past professional research experience leads to satisfaction.

As specific reasons for job content satisfaction (Table 4), “The opportunity to work that makes use of my capabilities” was selected the most frequently among the 12 items. The feeling of meaningfulness derived from using the skills and knowledge through previous work and research experience and the sense of responsibility for planning and carrying out projects led to job satisfaction. This result is in common with research findings (Hackman & Oldham, 1975) that job characteristics create psychological states of meaningfulness and responsibility, which lead to job satisfaction and performance.

In the interviews, the respondents stated the following: “I was able to improve the facility based on my experience as an experimental researcher” (E); “Transferring from the industry, I gained a deeper understanding of research as an RMA and doctorate student. I was able to proceed with my work from both industry and academia’s perspectives” (C); “I was able to utilize my experience and skills in editing and planning books and videos in my previous job” (L).

Esteeming Work Content

Next, Esteeming work content was associated with high Job content satisfaction and low Employment dissatisfaction. In other words, respondents who selected job content as the most important reason for continuing to work had higher Job content satisfaction and lower Employment dissatisfaction. There could be several reasons why Esteeming work content after employment as an RMA led to high Job content satisfaction and low Employment dissatisfaction.

One clue is that “The opportunity to do things for others” was selected frequently in the interview survey (Table 4). RMA is considered a professional occupation based on advanced knowledge and skills. Hall (1968) proposed five elements for the attitudes and behaviors of these professional workers: (1) independent action, (2) self-control, (3) conformity to the professional group, (4) contribution to the public interest, and (5) dedication to the profession, and “The opportunity to do things for others” is related to the elements (4) and (5).

There was diversity in how the expression “do things for others” was perceived; some said it is satisfying to do work that pleases company employees, university faculty, and students (C, J, and L). In contrast, others said that RMAs could change social systems through universities with a public status (D) and that RMAs do something for others (F), emphasizing the social nature of RMAs.

Furthermore, the positive linkage between esteeming work content after employment and high job content satisfaction could derive from the attractiveness of flexibility in research management and administration work. In the interview survey results, “The freedom to act on my own judgment” was often selected as a reason for low Employment dissatisfaction (Table 5). This result could reflect the autonomous behavior cultivated through their research experience. Autonomous behavior is one of the characteristics of professionalism. It refers to the right of individuals to make decisions about the means and goals of their work based on their professional judgment (Bartol, 1979a, 1979b; Miner, 1980).

In the interview survey, the related comments are: “Job discretion and flexibility lead to satisfaction” (L); “Although responsibility is involved, I was able to act entirely on my judgment” (C); “Regarding my work in institutional research, I have the discretion to decide how to proceed with my task, and I work in collaboration with my team members” (H); “I can decide to some extent how to proceed with my work before consulting with the executive director, and I can set my own priorities within a broad scope of work” (I).

Multiple Factors on Job Satisfaction

The respondent attribute variables indicate that Job content satisfaction declines and Employment dissatisfaction increases when the number of organizations the respondent has enrolled in is two or more (Experience in multiple organizations). One could interpret the results in various ways. First, it reflects the local working environment. Japan highly depends on knowledge, such as peculiar organizational rules, to do the job. Changing jobs forces one to rebuild knowledge and experience. Thus, even though RMAs have accumulated experience, they need additional time to engage in advanced work. This situation increases the cost of changing organizations.

The other factor is Japanese employment and work assignment practices. RMAs in Japan, especially URA positions, tend not to have detailed job descriptions, even though they are professionals. Due to organizational circumstances, such as a small budget, RMAs tend to be assigned more varied tasks.

The second most frequently selected reason for low Employment dissatisfaction in the interview survey was “The opportunity to do a variety of works from time to time” (Table 5). In general, professionals are satisfied with becoming more proficient in specific tasks. However, respondents with low Employment dissatisfaction viewed more diversified tasks as preferable. Given these results, RMAs with high Employment dissatisfaction may be too focused on being a “specialist” and, therefore, unable to adapt to multitasking. An interviewee stated that he considered himself good at doing diversified jobs and connecting people rather than concentrating on one job (D).

Difference between Job Satisfaction and Dissatisfaction

Next, a regression analysis treated Affective commitment as the objective variable and Job content satisfaction and Employment dissatisfaction as explanatory variables. Job content satisfaction was positively associated with Affective commitment, while Employment dissatisfaction was negatively associated with Affective commitment. This result is in line with the findings of previous studies (e.g., Patrick and Sonia, 2012; Koo et al., 2020) that show a positive relationship between job satisfaction and affective commitment. Little research has statistically examined the relationships between job satisfaction and affective commitment among RMAs. This study divided job satisfaction into Job content satisfaction and Employment dissatisfaction as variables, which were significantly related. Affective commitment generally predicts organizational performance and employee turnover reduction. The results suggest that approaches to improve RMAs’ Job content satisfaction and Employment dissatisfaction may enhance research management and administration for universities and other institutions.

In the research, the variables of job satisfaction and dissatisfaction were operated based on the Two-Factor Theory (Herzberg et al., 1959). The Allen and Meyer (1990) scale employed to measure Affective commitment is a highly reliable tool used for an extended period in many studies. The definite paths from Job content satisfaction and Employment dissatisfaction to Affective commitment will support the validity of creating the variables of job satisfaction and dissatisfaction.

 

Conclusion and Contribution

This study aimed to clarify the relationships between job content satisfaction, employment dissatisfaction, their factors, and affective commitment among RMAs supporting research at universities and other institutions. The survey data from 245 individuals engaged in research management and administration or similar work in Japan validated the relationships. First, logistic regression analysis used Job content satisfaction and Employment dissatisfaction as objective variables. Least squares regressions with robust standard errors proceeded, putting Affective commitment as the objective variable. An additional interview survey followed the questionnaire survey.

Although RMAs are a growing global professional workforce and job satisfaction and affective commitment are essential factors affecting organizational performance, few empirical studies have statistically analyzed the relationships between job satisfaction, its factors, and affective commitment among RMAs. The study revealed the relationships between job characteristics and personal attributes of RMAs and job satisfaction. The analysis classified job satisfaction into Job content satisfaction and Employment dissatisfaction. Furthermore, significant relationships between Job content satisfaction and Affective commitment were also confirmed.

 

Implications

The findings of this study advance not only academic research in the field of research management but also offer unique insights for practical operations. By enhancing job satisfaction and affective commitment among RMAs, the study paves the way for more vibrant research activities at universities and other institutions, leading to expanded research outcomes and overall organizational development. Moreover, the study deepens our understanding of the professional characteristics of RMAs, thereby aiding in their career progression.

This analysis provides some practical implications, particularly for managers of RMAs. First, they should carefully consider the diversity of work, which is an RMA’s job characteristic. Based on the positive association between URA positions and job satisfaction in the regression analysis and the interview survey results, RMAs with high satisfaction have a positive attitude toward job diversity. This result is the opposite trend of the hotel employees surveyed by Zhao et al. (2016). It would be meaningful for managers to entrust RMAs with work in new fields that they are likely to be interested in or that will lead to their growth.

Second, assigning work for RMAs to utilize their research experience is worthwhile. The Research activity followed a path to high Job content satisfaction. The interviews also revealed RMAs’ desires to utilize their experience. Independent researchers can autonomously carry out tasks from problem discovery to solution. In order to make the most of these abilities, it is possible to make RMAs responsible for the project from the planning stage to the final one. That role allows them to see the overall picture. In job characteristic theory, this increases task identity.

Finally, hiring and developing RMAs from a long-term perspective is essential. The regression analysis showed that URA positions correlated to Employment dissatisfaction. A unique Japanese situation where most positions are fixed-term employment may impede career planning and skill development. Flexible systems would be preferable to allow RMAs to update their knowledge in the research fields and develop their interpersonal service skills during working hours. In addition, it would also be effective to encourage them to participate in professional societies, take training courses, and obtain qualifications and additional degrees. These approaches will likely lead to improved performance for RMAs and organizational performance through improved job satisfaction among RMAs.

 

Limitations and Future Research

One should be cautious in interpreting the results of this study. First, the data for this study was responses from individual members of RMAN-J. Respondents were highly educated and relatively middle-aged. In addition, Japan’s social structure and culture regarding employment may have influenced the relationship among the variables. For example, in Japan, job descriptions are often less detailed than in the West. Grasping some behavioral principles and practices requires long-term work at the same organization. As a result, turnover is often a high barrier for workers. The relationship between RMAs and the faculty also depends on the culture and customs of the country. Further empirical research in other countries with different social and cultural backgrounds would be beneficial.

Since there are other concepts related to job satisfaction, such as organizational culture, turnover intention, job performance, and empowerment, in addition to the variables in this study, future research could examine these concepts. Due to the cross-sectional data, it is impossible to identify a causal relationship between job satisfaction and affective commitment with the findings of this study. Further, longitudinal studies are needed to obtain evidence of a causal relationship.

 

Declarations and Acknowledgments

Acknowledgments

We gratefully thank the participants of the 2022 Research Manager and Administrator Network Japan (RMAN-J) member survey and the 2023 supplemental interview survey.

Funding

This work was supported by JSPS KAKENHI Grant Numbers JP19H01692, JP23K01602, and JP23K25678.

Disclosure Statement

The authors have no conflicts of interest to declare.

 

Shin Ito, Ph.D., MBA
Institute for Future Initiatives
The University of Tokyo, Japan
The current affiliation: National Institute of Science and Technology Policy, Ministry of Education, Culture, Sports, Science and Technology, Japan

Hiroaki Hanaoka, M.A.
Co-Creation Affairs Division, Department of Co-Creation Promotion
The University of Osaka, Japan

Norihiro Hirata, Ph.D.
Research Administration Center, Innovative Research and Liaison Organization
Shinshu University, Japan
The current affiliation: Research Strategy and Promotion Division, Department of Research Strategy, Headquarters for Co-creative Future Sciences, Hiroshima University, Japan

Makiko Takahashi, Ph.D.

Graduate School of Innovation Management
Kanazawa Institute of Technology, Japan

Corresponding Author

Correspondence concerning this article should be addressed to Shin Ito, National Institute of Science and Technology Policy, Ministry of Education, Culture, Sports, Science and Technology, 3-2-2 Kasumigaseki, Chiyoda-ku, Tokyo, 100-0013 Japan, shin.ito@nistep.go.jp

 

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