from creativity to innovation: the role of female

INTERNATIONAL JOURNAL OF SOCIAL AND MANAGEMENT STUDIES (IJOSMAS)

Volume: 02 No. 02 https://www.ijosmas.org : 2775-0809 e-ISSN

© 2021, IJOSMAS http://www.ijosmas.org 66

From Creativity to Innovation: The Role of

Female Employees’ Psychological Capital

Masduki Asbari1*

, Agustian Budi Prasetya2, Priyono Budi Santoso

3, Agus Purwanto

4

1,2,3,4 Pelita Harapan University, Jakarta, Indonesia

*e-mail: [email protected]

Abstract - This study aimed to measure the effect of psychological capital and individual creativity on employee

individual innovation behavior of the female employees of a manufacturing industry in Tangerang. In this study,

individual creativity is mediating variable. Data was collected from 277 returned questionnaire of samples

taken by random sampling. Data was analyzed using SEM method with SmartPLS 3.0 software. The results of

this study showed that psychological capital had a significant effect on individual creativity, psychological

capital and individual creativity have a significant effect on individual innovation behavior, individual creativity

have a positive and significant effect on the relationship between psychological capital and individual

innovation behavior. Individual creativity functioned as a partial mediator. This new research proposed a

model for managing the individual innovation behavior among the female employees of the manufacturing

industry in Tangerang through developing psychological capital with individual creativity as a mediator. This

research could pave the way to improve employee readiness in facing the era of industrial revolution 4.0.

Keywords: Individual creativity; individual innovative behavior; industrial revolution 4.0; psychological capital.

I. INTRODUCTION

Innovation is a desired goal for a successful modern company. Most companies and organizations

recognize the need to be proactive in their efforts to “find” or be innovative. No exception manufacturing

industry organizations. Although there is a great deal of literature on innovative behavior in general, very

little research has been done on the unit of analysis for female employees called the manufacturing

industry (Masduki Asbari, Pramono, Kotamena, Liem, Sihite, et al., 2020; Sutardi et al., 2020; Yuwono,

Novitasari, et al., 2020; Yuwono, Wiyono, et al., 2020). Therefore, more research is needed on the potential

factors associated with innovative behavior from the perspective of female employees in research in the

manufacturing industry (M Asbari et al., 2020; Masduki Asbari, Chi Hyun, et al., 2020; Masduki Asbari,

Fayzhall, et al., 2020; Masduki Asbari, Hyun, et al., 2020; Masduki Asbari, Pramono, Kotamena, Liem,

Alamsyah, et al., 2020; Basuki et al., 2020; Fayzhall et al., 2020; Goestjahjanti et al., 2020; Purwanto et

al., 2020; Santoso et al., 2020; Zaman et al., 2020). However, it is important to note that, although

creativity is used synonymous with innovation, in this study the concept of creativity is separated from the

concept of innovative behavior.

For the above reasons, this study has three objectives. First, the aim and overall contribution is to study

innovative behavior from the perspective of female employees using industrial manufacturing

organizations. Second, according to the literature, innovative behavior is influenced by personal

characteristics (Kim & Park, 2015). This study discusses two personal characteristics, namely employee

creativity and psychological capital. According toYu et al. (2019) only a few studies have attempted to

determine the impact of psychological capital on employee creativity in the workplace context. In

particular, this study examines whether and how the influence of psychological capital is associated with

individual female employees' creativity and innovative behavior. By focusing on these three constructs, the

study contributes to the relatively little research domain of female employee innovation performance in the

manufacturing industry. This research report is structured as follows. First, the conceptual model is briefly

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described. Second, content and relationships between concepts are discussed. Third, methods, statistical

analysis and empirical hypothesis test results are presented. The last section contains the overall

conclusions of this study.

A. Individual Innovative Behavior

According to Fuglsang, innovation is a difficult phenomenon to define and study, and there is no consensus

on how to define innovation (Fuglsang, 2010). One of the earliest definitions of innovation was the

Schumpeter definition (Schumpeter, 2008). Schumpeter calls innovation a 'new combination' of services,

work processes, products and markets (Fritsch, 2017; Schumpeter, 2008). In literature, innovation can refer

to a new product or service, a new production process, or a new administrative structure or system (Asbari

et al., 2021; Fikri et al., 2020; Hutagalung et al., 2020; Novitasari, Kumoro, et al., 2020; Novitasari,

Yuwono, et al., 2020; Nugroho et al., 2021; Putra et al., 2020, 2021; Suprapti et al., 2020). These different

definitions of innovation show the various potential differences between different types of innovation.

Simply put, innovation can be realized anywhere in an organization. However, this study limits its focus to

innovations relevant to individual female employees. The type of innovation evaluated in this study is the

innovative behavior of individuals in the manufacturing industry. Individual innovative behavior regarding

the implementation of innovation that has the potential to benefit employee performance.

Individual innovative behavior is related to employee behavior and their ability to adopt and use new and

useful ideas in their work environment (Agistiawati et al., 2020; Hutagalung et al., 2020; Novitasari,

Kumoro, et al., 2020; Novitasari, Yuwono, et al., 2020; Suprapti et al., 2020). Thus, the individual's

innovative behavior does something new that represents a change in behavior or a discontinuity relative to

the usual patterns of organizational behavior in the past. Consequently, the domain of individual innovative

behavior is linked to day-to-day employee practices. Such innovation is implicitly a function of learning

and knowledge creation, which is integrated into daily work practices (Avby & Kjellström, 2019).

Additionally, there is no explicit focus on implementation timing. Innovations can be implemented either

as a one-time change (for example for conditional improvement in certain situations) or more permanently

(for example, a new extended procedure for all production processes). Innovation in a one-time situation is

analogous to the literary term ad hoc innovation (Gallouj & Weinstein, 1997). Similar to ad hoc innovation,

the individual's innovative behavior may include some transient innovations. However, the concept of

individual innovative behavior can include several elements that can be repeated in new situations, to be

implemented and generalized on a more permanent basis (Toivonen et al., 2007). Consequently, the

concept of individual innovative behavior in this study is open to various changes that are relevant to

employee performance. Thus, individual innovative behavior embraces and reflects a specific form of

change-oriented activity (Battistelli et al., 2013), which is explicitly shown to employees in the

implementation of new ideas and useful in a job role.

B. Individual Creativity

As shown in the conceptual model in Figure 1, individual creativity is one of the two personal

characteristics mentioned to impact an individual's innovative behavior. Individual creativity as a personal

characteristic reflects the idea that creativity is heterogeneous and distributed across individuals in the

organization. Creativity is flexible and dynamic and varies from employee to employee. Therefore,

individual creativity is a resource or individual ability to create (Agistiawati et al., 2020; Asbari &

Novitasari, 2020; Maesaroh et al., 2020; Novitasari, Kumoro, et al., 2020; Novitasari, Sasono, et al., 2020;

Novitasari, Yuwono, et al., 2020 ; Sudiyono et al., 2020; Yuwono, Wiyono, et al., 2020). Based on this, and

specifically for this study, individual creativity is defined as an individual employee effort in producing

new things, useful ideas or problem solutions.(Amabile et al., 2005). Individual creativity refers to the

process of making ideas or solving problems and actual ideas or solutions (Amabile et al., 2005).

Creativity is sometimes used synonymously with innovation. However, in this study, the authors separate

the concept of individual creativity from individual innovative behavior.Shalley et al. (2004)supports this

distinction, stating that it is "important to distinguish creativity from innovation". Creation refers to the

development of novel, potentially useful ideas. Although employees may share these ideas with others, it is

only when they are successfully implemented at the organizational or unit level that they are considered

innovations (Shalley et al., 2004). As the definition above suggests, individual creativity refers to the

production and development of new and potentially useful ideas. consequently, individual creativity






describes individual cognitive processes and thinking (refers to creative thinking) and potential related

activities such as (1) defining the problem to be solved, (2) gathering information, (3) generating ideas and

(4) evaluating ideas(Mumford et al., 1991). In contrast to individual creativity, the concept of individual

innovative behavior is related to behavior, which specifically refers to the behavioral implementation of

creative ideas. Consequently, there is a natural difference between individual creativity and individual

innovative behavior, even though the two concepts are closely related or interrelated.

Creativity is most often described as the need to 'put in' for innovation. Slåtten & Mehmetoglu (2015)

emphasizes the importance of creativity, characterizing it as the “ultimate source” of innovative behavior.

Gilmartin (1999) illustrates the importance of creativity by describing it as a "fuel for innovation". This is

because "the basis of the idea of innovation is creativity" as stated byVan de Ven (1986). Previous research

has found a positive relationship between creativity and innovation at the individual level (Slåtten &

Mehmetoglu, 2015). In line with previous research, this study looks for a positive relationship between

individual creativity and individual innovative behavior. Therefore the first hypothesis of this study is as

follows:

Hypothesis 1: Individual creativity has a significant effect on innovative behavior.

C. Psychological Capital

The psychological capital in Figure 1 is the second personal characteristic that can influence an individual's

innovative behavior (Purwanto et al., 2021). Psychological capital construction is taken from positive

psychology, and attention to "who you are" as a person (Luthans et al., 2007a). More precisely,

psychological capital focuses on the positive aspects and strengths of individuals and labels them

collectively as positive psychological sources for innovative processes (Luthans et al., 2007b). Luthans et

al. (2007b) describe psychological capital as a construct that includes four first-level positive psychological

resources: (i) hope, (ii) self-efficacy, (iii) resilience (resilience) and (iv) optimism (Luthans et al., 2007b).

The dimension of hope in psychological capital is a motivational state that describes the extent to which a

person can progress when facing obstacles. Self-efficacy is an individual's belief in someone, in the form

of "the ability to perform tasks successfully". Resilience (resilience) refers to the ability to manage

setbacks, pursue goals, and achieve good results. Optimism is a positive assessment of the future (Luthans

& Youssef-Morgan, 2017).

Previous research has linked individual psychological capital to work-related performance, including

individual innovative behavior. For example, Slåtten et al. (2019) found that psychological capital among

employees was positively related to innovative behavior. In another study, we found a positive relationship

between psychological capital and innovative performance as rated by supervisors among employees

employed in various fields (Abbas & Raja, 2015). In line with most of the previous research, psychological

capital is expected in such a construct "to provide the necessary storehouse of psychological resources

which help effectively innovative work-related ideas." (Abbas & Raja, 2015). Based on this, the second

hypothesis of this study is proposed as follows:

Hypothesis 2: Psychological capital has a significant effect on innovative behavior.

Although psychological capital has been suggested to have a direct impact on the innovative behavior of

individuals, it is also reasonable to assume that psychological capital has an additional direct impact on

individual creativity. Previous research has revealed that individual creativity is linked to personal factors

(Slåtten et al., 2019). In this study, psychological capital reflects these individual factors. In particular,

psychological capital is expected not to be limited to its positive impact on individuals, but also to trigger

individuals to be more creative. It is important to remember that individual creativity in the preceding

discussion is described in terms such as "primary source" (Slåtten & Mehmetoglu, 2015) and the

"foundation of innovation" (Van de Ven, 1986). In simple terms it can be said that, without creative

thinking, no innovative behavior will occur. Gilmartin (1999) supports this assumption, stating, "creativity

is the basic building block of discovery and innovation".

Each of the four sources of psychological capital is a potential provider and helps enhance individual

creativity. Creative thinking is not a quick solution, but it can involve extensive and intensive cognitive and






mental work. It is reasonable to assume that the mental labor of individual creativity requires some form of

a learning process of at least four steps. First, one must be aware of the problem or challenge that needs to

be resolved. Second, one must be interested and motivated to explore the nature of the problem ('what is

the real problem to be solved here?'). Third, identify potential solutions. In this section, there may be

several and sometimes even seemingly contradictory solutions, each with specific obstacles. Fourth,

among the list of alternative solutions, one must ultimately evaluate and identify the most appropriate and

practical solution. Based on the four-step process of individual creativity, it is easy to imagine that

individual creativity is a relatively demanding mental / cognitive process that can be frustrating, time

consuming and stressful. However, a person's psychological capital resources can increase their creativity.

Psychological capital is a core resource for achieving individual creativity because it is represented by a

positive assessment of the circumstances and the likelihood of success based on motivated and diligent

efforts. It is easy to imagine that individual creativity is a relatively demanding mental / cognitive process

that can be frustrating, time consuming and stressful. However, a person's psychological capital resources

can increase their creativity. Psychological capital is a core resource for achieving individual creativity

because it is represented by a positive assessment of the circumstances and the likelihood of success based

on motivated and diligent efforts. It is easy to imagine that individual creativity is a relatively demanding

mental / cognitive process that can be frustrating, time consuming and stressful. However, a person's

psychological capital resources can increase their creativity. Psychological capital is a core resource for

achieving individual creativity because it is represented by a positive assessment of the circumstances and

the likelihood of success based on motivated and diligent efforts (Luthans et al., 2007a).

Previous research has revealed that four sources or "ingredients" of psychological capital, both individually

and collectively, are associated with individual creativity (Rego et al., 2012). For example, previous

research has linked the expected source of psychological capital with a person's desire for creative

exploration (Luthans & Youssef-Morgan, 2017). The study explicitly states that hopeful employees will

"tend to be creative" (Luthans & Youssef-Morgan, 2017). Likewise, in terms of optimism Rego et al.

(2012) found that optimistic people tend to be more creative than their less optimistic counterparts.

Research on two other sources of psychological capital, self-efficacy and resilience, has also found that

they are positively related to aspects of creativity (Cohler, 1987; Tierney & Farmer, 2002). So, in

conclusion, the four sources of psychological capital are all potentially linked to individual creativity.

Based on previous research it is expected that the four dimensions of psychological capital will be

positively related to the individual creativity of female employees. The assumptions about this relationship

can be summarized in the third hypothesis of this study, namely as follows:

Hypothesis 3: Psychological capital has a significant effect on individual creativity.

Hypothesis 2 and hypothesis 3 above state that psychological capital has a direct impact on employees'

innovative behavior and individual creativity. However, as shown in the research model, it is also

expected that the relationship between psychological capital and individual innovative behavior is

mediated by individual creativity. This assumption is a third alternative in which psychological capital can

be linked to individual innovative behavior. The main argument for this third route of impact is in the core

role that individual creativity appears to have in individual innovative behavior. As emphasized above,

individual creativity in the literature is described as the "primary source." (Slåtten & Mehmetoglu, 2015)

and the "foundation of innovation" (Van de Ven, 1986). Hini implies that from the perspective of

individual employees, individual creativity is a necessary prerequisite for individual innovative

behavior. Based on the core role of individual creativity, the increased individual creativity of

employees due to their psychological capital can encourage employees to experiment and apply

creative ideas, if they see benefits for their work. As a result, individual creativity is expected to

mediate between psychological capital and individual innovative behavior. Therefore, the fourth

hypothesis in this study is as follows:

Hypothesis 4: Psychological capital has a significant effect on innovative behavior through individual creativity

as a mediator.

D. Research Framework




According to Sekaran & Bougie (2003) theoretical framework is the foundation on which the entire research

project is based. From the theoretical framework can be formulated hypotheses that can be tested to determine

whether the theory formulated is valid or not. Then then further it will be measured by appropriate statistical

analysis. Referring to previous theory and research, there is a relationship between the following variables:

psychological capital which refers to the research parameters Luthans & Youssef-Morgan (2017), individual

creativity refers to the research parameters George & Zhou (2001) and innovative behavior refers to research

parameters Janssen (2000) and Scott & Bruce (1994). For this reason, the authors build a research model as

shown in Figure 1 below:

Figure 1. Research Model

II. METHODS

A. Operational Definition of Variables and Indicators

The method used in this research is quantitative method. Data was collected by distributing questionnaires to all

female employees of a manufacturing companyin Tangerang. The instrument used to measure psychological

capital adapted from Luthans & Youssef-Morgan (2017) using 4 items (X1-X4). Psychological capital is defined

as ka state of positive psychological development of a person characterized by self-efficacy, optimism, hope and resilience

(Luthans & Youssef-Morgan, 2017). Variablepsychological capital This is explained in four items, namely: (X1) “I feel

confident that I can set goals for myself in my work area”; (X2) “I am optimistic about my future in this organization”; (X3)

“When faced with a challenge in my work, I can find an alternative solution to it”; (X4) “I can find an alternative way to

reach my goal”. Individual creativity instruments adapted from George & Zhou (2001)using 2 items (Z1-Z2).

Individual creativity is defined asgenerate / produce new ideas, useful ideas, or problem solutions from each employee.

This idea includes the process of making ideas and actual ideas(George & Zhou, 2001). This individual creativity variable is

described in two items, namely: (Z1) “I contribute creative ideas to solve challenges in my work”; (Z2) “I contribute creative

ideas to improve the quality of my work”. Instrument pinnovative behavior adapted from Janssen (2000) and Scott

& Bruce (1994) using 5 items (Y1-Y5). Innovative behavior (individual) is defined asEmployee behavior and its

ability to adopt and use new and useful ideas in their work (Janssen, 2000; Scott & Bruce, 1994). This individual innovative

behavior variable is described in five items, namely (Y1) “I create new ideas to solve problems in my work”; (Y2) “I am

looking for new work methods or techniques to complete my work”; (Y3) “I investigate and find ways to apply my ideas”;

(Y4) “I promote my ideas so that others can use them in their work”; (Y5) “I try new ideas in my work”. The research

model can be seen as in Figure 1. The questionnaire is designed closed except for questions / statements about

the identity of the respondent in the form of a semi-open questionnaire. Each closed question / statement item is

given five answer options, namely: strongly agree score 5, agree score 4, neutral score 3, disagree score 2, and

strongly disagree score 1. The method for processing data is by using PLS and using SmartPLS version 3.0

software as a tool.

B. Population and Sample

The population in this study are permanent employeesfrom one of the manufacturing industries in Tangerang,

amounting to 305 people. The questionnaire was distributed using simple random sampling technique. The

results of the questionnaire returned were 277 samples. So the sample size is 90.8% of the total population.



III. RESULTS

A. Sample Description

A total of 277 female employees participated. They have different age groups, ranging from under the age of 29

years 246%), 30-49 years (48%), and over 50 years of age (28%). Their employment status varies, of which

38% are permanent employees, 62% of whom are contract employees. The length of their work also varies, 34%

of them are under 5 years, 50% have worked between 5-10 years, and the remaining 16% have worked for more

than 10 years. The highest education level of the respondents is the majority at high school level (SMA / SMK),

namely 75%, and the remaining 23% are junior high school graduates and 2% undergraduate graduates.

Table 1. Sample Description

Criteria Qty. %

Age <29 yrs. 66 24%

30-49 yrs. 133 48%

> 50 yrs. 78 28%

The period of service as an employee <5 yrs. 94 34%

5-10 yrs. 139 50%

> 10 yrs. 44 16%

Highest diploma Junior High 64 23%

High school 208 75%

≥ S1 5 2%

Source: Processed Data (2021)

B. Test Results of the Validity and Reliability of Research Indicators

The measurement model testing stage includes testing for convergent validity, discriminant validity. Meanwhile,

to test the construct reliability, Cronbach's alpha and composite reliability were used. The results of the PLS

analysis can be used to test the research hypothesis if all indicators in the PLS model have met the requirements

of convergent validity, discriminant validity and reliability testing.

1. Convergent Validity Testing

Convergent validity test is done by looking at the loading factor value of each indicator against the construct. In

most references, a factor weight of 0.7 or more is considered to have sufficiently strong validation to explain

latent constructs (Chin, 1998; Ghozali, 2014; Hair et al., 2010). In this study, the minimum limit for the

accepted loading factor is 0.7, and provided that the AVE value of each construct is> 0.5 (Ghozali, 2014). After

going through SmartPLS 3.0 processing, all indicators have a loading factor value above 0.7 and an AVE value

above 0.5. The fit or valid model of this study can be seen in Figure 2. Thus, the convergent validity of this

research model has met the requirements. The value of loadings, Cronbach's alpha, composite reliability and

AVE for each complete construct can be seen in Table 2.

2. Disriminant Validity Testing

Discriminant validity done to ensure that each concept of each latent variable is different from other latent

variables. The model has good discriminant validity if the AVE squared value of each exogenous construct (the

value on the diagonal) exceeds the correlation between that construct and other constructs (values below the

diagonal) (Ghozali, 2014). The results of discriminant validity testing are by using the AVE square value,

namely by looking at the Fornell-Larcker Criterion Value obtained as shown in Table 3. The results of the

discriminant validity test in table 3 above show that all constructs have an AVE square root value above the

correlation value with other latent constructs (via Fornell-Larcker criteria). Likewise, the cross-loading value of

all items from an indicator is greater than the other indicator items as mentioned in Table 4, so it can be

concluded that the model has met discriminant validity (Fornell & Larcker, 1981).

Furthermore, a collinearity evaluation is conducted to determine whether there is a collinearity problem in the



model. To find the collinearity, the collinearity VIF statistic of each construct is needed. If VIF is more than 5,

then the model has collinearity (Hair et al., 2014). As shown in Table 4, all VIF scores are less than 5, i.e. hThe

result of the structural collinearity model reveals the VIF value below 2. This indicates that this research

model does not have a multicollinearity problem.

3. Construct Reliability Testing

The construct reliability can be assessed from the Cronbach's alpha value and the composite reliability of each

construct. The recommended composite reliability and Cronbach's alpha values are more than 0.7 (Ghozali,

2014). The results of the reliability test in Table 2 above show that all constructs have composite reliability and

Cronbach's alpha values greater than 0.7 (> 0.7). In conclusion, all constructs have met the required reliability.

Figure 2. Valid Research Model

Source: SmartPLS 3.0 Processing Results (2021)

Table 2. Items Loadings, Cronbach's Alpha, Composite Reliability, and Average Variance Extracted

(AVE)

Varables Items Loadings Cronbach's

Alpha

Composite

Reliability AVE

Psychological Capital (X) X1 0.938 0.931 0.951 0831

X2 0.955

X3 0.930

X4 0.815

Individual Creativity (Z) Z1 0.975 0.948 0.975 0.950

Z2 0.975

Innovative Behavior (Y) Y1 0.825 0.906 0.930 0.728

Y2 0894

Y3 0.855

Y4 0890

Y5 0.798


Table 3. Discriminant Validity

Variables X Y Z



Psychological Capital (X) 0.911

Innovative Behavior (Y) 0.691 0.853

Individual Creativity (Z) 0.662 0.728 0.975


Table 4. Collinearity Statistics Individual Creativity (VIF)

Variables X Y Z

Psychological Capital (X) 1,780 1,000

Innovative Behavior (Y)

Individual Creativity (Z) 1,780


Table 5. Value of R Square

Variables R Square R Square

Adjusted

Innovative Behavior (Y) 0.608 0.605

Individual Creativity (Z) 0.438 0.436


Table 6. Hypotheses Testing

Hypotheses Relationship Beta SE T Statistics P-Values Decision

H1 Z -> Y 0.482 0.071 6,813 0.000 Supported

H2 X -> Y 0.371 0.061 6,068 0.000 Supported

H3 X -> Z 0.662 0.038 17,642 0.000 Supported

H4 X -> Z -> Y 0.319 0.048 6,653 0.000 Supported


C. Hypothesis Test

Hypothesis testing in PLS is also called the inner model test. This test includes a significance test for direct and

indirect effects as well as measuring the magnitude of the influence of exogenous variables on endogenous

variables.To determine the effect of psychological capital on the innovative behavior of individual female

employees through individual creativity as a mediating variable, a direct and indirect effect test is needed. The

effect test was carried out using the t-statistic test in the partial least squared (PLS) analysis model using the

SmartPLS 3.0 software.With the boothstrapping technique, the R Square value and the significance test value

were obtained as shown in Table 5 and Table 6.

Based on Table 5 above, the R Square value of individual creativity (Z) is 0.438, which means that the

individual creativity variable (Z) can be explained by the psychological capital variable (X) of 43.8%, while the

remaining 56.2% is explained by other variables not discussed. In this research. Meanwhile, the R Square value

for innovative behavior (Y) is 0.608, which means that the variable innovative behavior (Y) can be explained by

the variable psychological capital (X) and individual creativity (Z) of 68.8%, while the remaining 31.2% is

explained by other variables which was not discussed in this study. Meanwhile, Table 6 shows the t-statistics

and p-values which show the influence between the research variables that have been mentioned.

D. Discussion

The results of data analysis show that: first, individual creativity has a positive and significant effect on

innovative behavior. This is evidenced bythe t-statistics value of 6.813 is greater than 1.96 and the p-value of



0.000 is smaller than 0.05. In conclusion, the hypothesis H1 is accepted. Second, psychological capital has a

positive and significant effect on individual creativity. Evidenced by the t-statistics value of 6.068 is greater than

1.96 and the p-value of 0.000 is smaller than 0.05. In conclusion, the H2 hypothesis is accepted. Third,

psychological capital has a positive and significant effect on innovative behavior. This is evidenced by the t-

statistics value of 17.642 which is greater than 1.96 and the p-value of 0.000 is smaller than 0.05. In conclusion,

hypothesis H3 is accepted. Fourth, psychological capital positive and significant effect on innovative behavior

through individual creativity. This is evidenced by the t-statistics value of 6.653 which is greater than 1.96 and the

p-value of 0.000 is smaller than 0.05. In conclusion, hypothesis H4 is accepted.

This study aims to improve understanding and application of the fundamentals of innovation in

manufacturing organizations. Contributions can be summarized in three parts. First, in contrast to most

previous studies on the level of organizational innovation, this study focuses on innovation from the

perspective of individual employees, particularly female employees. Thus, the results of this study deepen

and broaden the literature on understanding and innovative practices of female employees in the

manufacturing industry. Because in fact, in many manufacturing industries, especially in the area of

footwear and garment commodities, the majority of employees are female. Therefore, the creativity of

these female employees is the main source of innovation for the company. Second, researchpreviously

limited to the manifestation of innovative behavior or research so-called innovative behavior of

individuals. Although individual innovative behavior is an interesting aspect, this study extends previous

research as it increases our knowledge of the factors that impact employees, namely the cognitive

processes associated with individual innovative behavior. By incorporating the concept of individual

creativity, this research offers insight into the relationship betweenthe basic premise of individual creativity

and individual innovative behavior.

In line with previous research, the innovative behavior of individuals in this study is defined as "the

implementation of new and useful ideas in a job role." (Battistelli et al., 2013). As mentioned above, the

individual's innovative behavior includes various manifestations of “novel” behavior at work. In particular,

"novelty" ranges from incremental (minor) innovation on the one hand, to radical innovation (major) on

the other. Likewise, the aspect referred to as the “in” work role in the definition of an individual's

innovative behavior covers the various “times and places” where “novelty” or innovation occurs. In

particular, the term “in” job roles can include innovation by frontline employees (eg finding new ways to

manage packaging production) as well as 'in' backstage work (eg new administrative routines or internal

work processes). Thus, the definition of individual innovative behavior in this study touches on one of the

earliest definitions of innovation.Schumpeter (2008), which describes innovation in a broad sense as the

implementation of a combination of new services, workplace processes, products and markets. By

incorporating psychological capital, this study also provides new insights into how personal factors,

individually and collectively, can influence individual creativity and employees' innovative behavior.

IV. CONCLUSION

This study contributes to the understanding and practice of innovation in manufacturing industry

organizations from the perspective of individual female employees. In particular, this study reveals a

multifaceted association between psychological capital, individual creativity, and innovative behavior of

female employees in the manufacturing industry in Tangerang. Tit has been proven that (i) variable

individual creativity has a positive and significant effect on innovative behavior, (ii) psychological capital

positive and significant effect on individual creativity, (iii) psychological capital positive and significant effect on

innovative behavior, (iv) psychological capital positive and significant effect on innovative behavior through

individual employee creativity in the manufacturing industry in Tangerang.

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