Keywords

National Culture, Organizational Innovation, Organizational Learning Capability

Introduction

The constant pressure due to technological advancement and changes in consumers' preferences have forced organizations to keep on learning and adapting to their operating environment. To change and improve for the better organization has to learn from its past performance, experts in the respective fields, or other people/similar organizations that excel and perform better. This learning process can be done individually as well as the organization as a whole. The learning process done by an organization as a total is called organizational learning, which gains its popularity in 1990 after Peter Senge published, the fifth discipline.

To learn, an organization must make the environment within the organization conducive to learning. To be conducive, the organization and its management must have specific characteristics that facilitate organizational learning (Goh & Richards, 1997; Alegre & Chiva, 2008). In addition, several studies link organizational learning capability to company performance and innovativeness (Ona? et al., 2014; Gomes & Wojahn, 2017; Alegre & Chiva, 2008).

Faculty members are knowledge workers who provide education, research, and community services. The university gives the faculty members the freedom to set their syllabus and modify it if necessary, using a teaching method that suits them best and applies new teaching technology. The faculty members also have the autonomy to work on their research interests and publish their work and actively involve in their academic community (Camps et al., 2011). In addition, the faculty members often collaborate with their colleagues inside and outside their organizations to create new knowledge through joint research and seminars (Azagra-Caro et al., 2008; Camps et al., 2011). These are to show that universities are indeed practicing the facilitating factors of organizational learning.

The difference in one's national culture has been taken for granted for most of the study of the organization (Nazarian et al., 2014). However, the previous study showed that national culture impacts a country's innovation level (Herbig & Dunphy, 1988; Cox & Khan, 2017; Prim et al., 2017), organization performance (Rhyne et al., 2002), and learning (Kim & McLean, 2014; Beyene et al., 2016). On the other hand, other studies indicated that national culture inhibits Singapore's implementation of organizational learning and cultural attitudes compose a systemic barrier to learning and adaptation (Retna & Jones, 2005). So it is imperative to manage culture; when differences in cultures are manageable, it can lead to better and faster learning (Hoecklin, 1995).

Indonesia is a country that consists of more than 17 thousand islands and more than hundreds of ethnic and linguistic groups; as can be expected, there is a diverse culture that makes up the national culture of Indonesia. Jakarta is the capital city of Indonesia. It is a metropolitan city and has become the melting pot of diverse cultures as Jakarta has become the magnet and attracts people from other cities throughout Indonesia. Therefore, universities in greater Jakarta consist of faculty members and students of different cultural backgrounds.

The impact of national culture on other cultures, organizational learning, and organizational innovation has been tested. However, there is little study on the effect of national culture on organizational learning capability that leads to organizational innovation, particularly in higher learning institutions. Therefore, this study examines organizational learning capability as the mediator between national culture and organizational innovation of universities in greater Jakarta.

Theoretical Framework

Learning

To be considered a learning organization, an organization must place learning as the fundamental substance in its system. This learning has to take place at both the individual level, team level, and organizational level (Marquardt, 2002). Fiol and Lyles suggested the definition of learning as "development of insights, knowledge, and associations between past actions, the effectiveness of those actions, and future actions" (Fiol & Lyles, 1985). When change occurs at the skills, insights, knowledge, attitudes, and values of an individual resulting from learning through self-study, technology-based instruction, and observation, it is called individual learning. When the same thing happens in a group or a team, it is called team learning. It is called organization learning when it takes place by and within the group. (Marquardt, 2002) Many other definitions of learning would lead to several interpretations, but all of these definitions agreed that learning would improve performance at the end of the day.

Organizational Learning

Organizational learning is the method of sharing the knowledge gained from the total learning of each individual in the organization so that it becomes the organization's common knowledge. Organizational learning is essential for the organization, especially when change is an everyday occurrence. To cope with this change organization must have the ability to learn so that it can sense, act and adapt (Camps, Alegre & Torres, 2011).

Even though various definitions regarding organizational learning would lead to several interpretations, all of those definitions agreed that learning would improve individuals, groups, and organizations, including future performance (Fiol & Lyles, 1985). To be called a learning organization, an organization must establish a system to inspire and transmit to other members and preserve the shared learning norms (Lawrence & Dyer, 1983). Learning will occur when the corporate culture is conducive to learning. And the strategy of the firm permits flexibility so that the organizational structure makes innovativeness and new insights possible (Fiol & Lyles, 1985).

Organization Learning Capability

Organization learning capability is when organizations and management possess characteristics that encourage the learning process and enable organizations to learn (Goh & Richards, 1997). This capability would also mean that there is no distraction in the learning process in the organization (Camps & Alegre, 2011). According to Goh, organizational learning capability is used in various organizational functions such as strategic planning and information and knowledge management. Organizations use it to alter external knowledge and information into knowledge-based output (Goh, 1998).

Facilitating Factors of Organizational Learning

Scholars, such as Goh & Richards (1997), consider the importance of facilitating organizational learning success in studying organizational learning capability. They define enabling factors as something that helps facilitate the learning process. These facilitating factors would make the learning in the organization possible.

Supported by literature research findings, the five fundamental and most used organizational learning dimensions are experimentation, risk-taking, interaction with the external environment, dialogue, and participative decision-making. Commitment to learning is a factor that implicitly appears in all five dimensions. Another factor that is also implicitly present in all five dimensions is leadership (Chiva, Alegre & Lapiedra, 2007).

Experimentation

Experimentation is a situation in which the development of new ideas and offering suggestions are highly encouraged. Therefore, in this dimension, encouragement to develop new ideas and provide recommendations are included among the factors. Other factors in this dimension are the availability of continuous training or the desire to learn and improve. Therefore, many scholars adopted the experimentation dimension (Chiva, Alegre & Lapiedra 2007). For example, Nevis, et al., (1995) add curiosity, embrace change, and use different methods and procedures in problem-solving other than trying new ideas.

Risk-Taking

Risk-taking is the degree to which an organization or individual tolerates ambiguity and uncertainty and committing errors (Chiva, Alegre & Lapiedra, 2007). Therefore, the environment should be designed to facilitate organizational learning, an environment that tolerates risk-taking and mistake-making (Hedberg, 1981; Alegre & Chiva, 2008). Sitkin acknowledged that failure could be beneficial and a requirement for organizational learning. Failure means that problems are present and addressed and found (Sitkin, 1996 in Chiva, Alegre & Lapiedra, 2007). Succeeding Sitkin's finding, many works support that risk-taking and accepting mistakes are critical drivers for organizational learning (Popper & Lipshitz, 2000).

Interaction with the External Environment

An organization's external environment, such as competitors, economic conditions, and political and social environments, significantly influences organizational learning, especially in rapidly changing and unstable environments (Chiva, Alegre & Lapiedra, 2007). According to Hedberg (1981), the atmosphere is the critical driver of organizational learning. Therefore, the more unstable the environment is, the greater the need for organizational learning (Popper & Lipshitz, 2000).

Dialogue

Dialogue is a process that can be used to reach an agreement or common understanding. During this process, both parties need to uncover the hidden meaning of words (Schein, 1993). The development of a learning organization requires building a common understanding that starts with an individual who practices dialogue (Chiva, Alegre & Lapiedra, 2007). Only through dialogue and daily interaction between individuals learning occurred; therefore, meeting people will increase learning (Nevis et al., 1995).

Participative Decision Making

Participative decision-making is when an employee is taking part and influences the decision-making process (Cotton et al., 1988; Chiva, Alegre & Lapiedra, 2007). The advantage of involving employees in decision-making is that it will boost employee motivation, job satisfaction, and organizational commitment (Chiva, Alegre & Lapiedra, 2007). In addition, Nevis, et al., (1995); Goh (1997) agree that using participative decision-making in the organization as one aspect can make learning possible.

Hofstede Cultural Dimensions

The objective of this paper was to study the impact of different national cultures on organizational learning capability. Therefore, Hofstede's dimensions model is the appropriate model to use. Hofstede identified four cultural dimensions in national cultures (Hofstede, 1983).

Power Distance

 According to Hofstede, power distance is a condition where there is an unequal distribution of power between leaders and followers in an organization or institution (Hofstede, Hofstede & Mirkov, 2010). In a low power distance, cultures employees prefer to be involved in decision making because there is an equal relationship between leader and followers. In contrast, in high power distance culture, where there are unequal distributions of power, employees do not want to get into arguments with their bosses. In addition to that, the subordinate expect what to do (Czerniak & Smygur, 2017); thus, there won't be consultative decision-making (Hofstede, Hofstede & Mirkov, 2010). As for the superiors have problems trusting to delegate to their subordinates important works or decisions (Dorfman & Howell, 1988).

Individualism/Collectivism

The degree of relationship orientation in society, whether oriented toward the group or individual, where the group's interest is considered more important than the individual's good, is called collectivistic (Hofstede, Hofstede & Mirkov, 2010). Clearly, in a collectivistic culture, harmony in the group or organization is of utmost importance. (Hofstede, Hofsted & Mirkov, 2010) However, the drawback in this collectivistic society is that an individual is not encouraged to think creatively (Baah, 2013), such as give new ideas or provide a solution if it is not for the benefit of the group or organization (Kim, McLean, 2014). On the other hand, in an individualistic culture, since individuals are responsible for their self-interest, they are more comfortable deciding what is best (Hofstede, 1983).

Masculinity/Femininity

To indicate the extent to which the dominant values of society either masculine or feminine. Masculinity culture is identified with assertive and competitive behaviors (Hofstede, Hofstede & Mirkov, 2010; Kassa & Vadi, 2010). In addition, masculine societies are characterized by high achievement and high risk-taking (Hofsted, Hofsted & Minov, 2010) and long-term growth (?kerlavaj, 2013). An organization with masculine culture is more competitive than feminine culture (Baah, 2013). In feminine cultures, people prefer peace, cooperation, and consensus in the group (Hofstede, Hofstede & Mirkov, 2010).

Uncertainty Avoidance

To what extent people in societies tolerate uncertainty and ambiguity. People in high uncertainty avoidance are risk-averse. They do not like ambiguity and uncertain situations. (Hofstede, 1983) Those people are more comfortable with clear standard operating procedures, regulations, and instructions in the workplace (Hofstede, Hofstede & Mirkov, 2010). In low uncertainty avoidance cultures, people are risk-takers. They do not have problems with uncertainty and ambiguity (Hofstede, 1983); therefore, they prefer flexibility in doing things and will not feel threatened with different opinions (Hofstede, Hofstede & Mirkov, 2010).

Organizational Innovation

Innovation is when a new idea/service/product/behavior/process/technology is adopted in an organization (Wang & Ahmed, 2004; Daft, 1978; Zennounche, 2014). To innovate requires individuals to obtain knowledge already existing in the organization or outside the organization and then share it with others (Sanz-Valle 2011; Chang & Cho, 2008; Damanpour, 1991), and this knowledge sharing will create new insights (Nonaka, 1994).

Product innovation is marked with newness in the product offer to the market, which is different from the existing product (Szymanski & Henard, 2001). In addition, process innovation is the addition of a new element in the production or services (Damanpour & Gopalakrishnan, 2001). Behavior innovation when there is a sustained change in behavior in an organization concerning innovation (Avlonitis 1994).

Hypothesis Development

Societies with large power distance are endowed with the following characteristics: people in the family, group, or organization tend to rely on hierarchy. There are disparities of rights and powers between power holders and non-power holders. Leaders are directive and hold more power. Therefore, leaders and managers are respected because of the position that they have. Moreover, communication between leaders and followers is indirect. Their communication with lower power is indirect. Team members with lower power are expected to be obedient to their superiors and procedures (Hofstede, Hofstede & Minkov, 2010). There will be no initiative and new ideas coming from the workers on improving things or how they are carried out their work and how they carry out changes in their work, reducing creativity and innovation.

In a society with a large power distance, risk-taking would be low. People in this society are highly dependent upon people with higher authority to decide, set direction, and plan (Hofstede, 1983); as risk-taking is low, so does innovation, since risk-taking is a must for generating a new idea (Amabile et al., 1996). So it is unlikely that followers initiate interacting with their environments because they do not want to undermine their managers or leaders; subordinates likely wait for direction from their superior before interacting with their working environments. When it comes to dialogue, the characteristics of people come from high power distance cultures in when communicating is indirect and primarily one-way communication (the manager gives the order to workers). Followers have an unequal relationship with their leaders (Kim & McLean, 2014). Shared understanding and knowledge sharing are not expected in this kind of environment, especially when the leaders or managers are around.

Participative decision-making will not happen in high power distance cultures since decision-making comes from people with higher authority. Workers or people with less power or lower authority are always look up to their superiors to make a decision and speak up the voice for them. Moreover, the organizational structure is rigid, and employee participation in decision-making is low or non-existent (Beyene et al., 2016). As a result, innovation will be low since participative decision-making corresponds to increased involvement and commitment to innovation (Damanpour, 1991).

On the other hand, people in weak uncertainty avoidance embrace ambiguity and uncertainty (Hofstede, 1983); they are not wholly reliant on the procedures and comfortable doing something new or embracing changes, and tolerant to different opinions (Korsakiene & Gurina, 2012). Furthermore, they are also flexible, willing to look for new information, engage in experimental learning, and learn from failure (?kerlavaj et al., 2013). The leaders are transparent to their followers regarding the organization's direction, stimulating their stimulative insights (Prim et al., 2017). According to Shane (1993) society with a weak uncertainty avoidance have the most significant innovation.

According to Shipper, Hoffman & Rotondo (2007), feedback or giving out suggestions would be avoided in the high collectivist society because it would disturb the group's harmony. Concerning experimentation, collectivist cultures will give new ideas and provide recommendations only if they benefit the group. If the opinions or suggestions have a negative connotation to the group, they will be hidden. So, a reality that is beneficial to the organization but unfavorable to the group will be distorted and obscured (Kim & McLean, 2014).

In a collectivist society, the interaction between employees with the environment would be significant. Therefore, people from these high collectivistic cultures focus on building relations. In collectivistic cultures, harmony in the group is of the utmost importance (Hofstede et al., 2010); therefore, dialogue is most likely to happen. Group members can use dialogue to reach a shared understanding and a harmonious relationship both in and out of the organization (Kim & McLean, 2014). Knowledge sharing within a group happens in a collectivist society because smooth information flow frequently occurs (Michailova & Hutchings, 2006). Individualist society values freedom and autonomy, which is necessary for innovation (Herbig & Dunphy, 1998). Moreover, they possess a strong entrepreneurial orientation that is risk tolerance and innovative (Wang, 2008; Hofstede, 2001).

In feminine cultures, employees tend to think that cooperation with other people in and out of the organization is of importance (Kim & McLean, 2014). Therefore, people coming from feminine cultures are well verse in interaction with their environments. Furthermore, in the high feminine societies, decision-making is achieved through involvement (Hofstede, 1983). In feminist cultures, people's serenity and consensus at work are preferable and support collaboration, leading to high development and research activities (?kerlavaj 2013; Couto & Vieira, 2004). The organization which is tolerant to mistake-making, which is the characteristic of feminine cultures, is more innovative (Prim et al., 2017). Trust and low conflict in the feminine cultures create an environment conducive to the uncertainty resulting from new ideas (Nakata & Sivakumar, 1996). Thus it can be hypothesized as follow:

Hypothesis 1a: Large power distance has a negative influence on organizational innovation

Hypothesis 1b: Strong uncertainty avoidance has a negative influence on organizational innovation

Hypothesis 1c: Collectivist has a negative influence on organizational innovation

Hypothesis 1d: Masculinity has a negative influence on organizational innovation

Hypothesis 2a: Large power distance has a negative influence on organizational learning capability.

Hypothesis 2b: Strong uncertainty avoidance has a negative influence on organizational learning capability.

Hypothesis 2c: Collectivist has a positive influence on organizational learning capability

Hypothesis 2d: Masculinity has a negative influence on organizational learning capability

Hypothesis 3a: Organizational Learning Capability has a positive and significant influence on Execute New Idea

Hypothesis 3b: Organizational Learning Capability has a positive and significant influence on Execute New Process

Hypothesis 3c: Organizational Learning Capabilityhas a positive and significant influence on Execute New Behavior

Hypothesis 3d: Organizational Learning Capability has a positive and significant influence on Execute New Product

Hypothesis 3e: Organizational Learning Capability has a positive and significant influence on Execute New Service

Hypothesis 3f: Organizational Learning Capability has a positive and significant influence on Execute New technology

Hypothesis 4a: Organizational Learning Capability mediate the relationships between Power Distance and Organizational Innovation

Hypothesis 4b: Organizational Learning Capability mediate the relationships between Uncertainty Avoidance and Organizational Innovation

Hypothesis 4c: Organizational Learning Capability mediate the relationships between Collectivism and Organizational Innovation

Hypothesis 4d: Organizational Learning Capability mediate the relationships between Masculinity and Organizational Innovation

Methodology

Data Collection

The researcher distributed the questionnaires to the head of the department of universities in Jakarta, Indonesia, which has an A accreditation through personal email. A total of 164 heads of department were chosen proportionally out of 275. The survey consisted of questions regarding national culture, consisting of 12 questions adapted from (Dorfman & Howell, 1988). Dorfman & Howell designed the questions to measure dimensions of national culture that influence work-related values and the management process at the individual level by measuring an individual's belief in cultural values (Dorfman & Howell, 1988). At the same time, questions regarding organizational learning capabilities consist of 15 questions adapted from (Chiva et al., 2007), whereas questions on organizational innovation comprised of 8 questions adapted from (Susanto, 2017; Wang & Ahmed, 2004).

Item Measurement

The questionnaires consist of three sections, demographics, national cultures, and organizational learning capability. Four constructs to measure national culture were power distance, uncertainty avoidance, individualism/collectivism, and masculinity/femininity using the scale developed by Dorfman & Howell (1988). The organizational learning capability scales adopted from Alegre & Chiva (2008) consist of five constructs: experimentation, risk-taking, interaction with the external environment, dialogue, and participative decision-making. Six dimensions of organizational innovation are executing new ideas, executing new processes, executing new behavior, executing new products, executing new services, and executing new technologies. The adopted scale was developed by Santoso (2017); Wang & Ahmed (2004).

Research Model

To get more theoretical parsimony of the research model, we designed it as a hierarchical component using reflective-formative measurement for the national culture construct. It includes four observed Lower-Order Components (LOCs), followed by reflective-reflective measurement for organizational learning capability and organizational innovation construct, and it contains 11 observed Lower-Order Components (LOCs). Moreover, our conceptual research model (as shown in figure 1.) postulates the exogenous variables (i.e., national culture), mediating variable (i.e., organizational learning capability), and endogenous variable (i.e., organizational innovation). With several lower-order components such as power distance, uncertainly avoidance, collectivism, and masculinity for national culture. Experimentation, risk-taking, interaction with the external environment, dialogue, and participative decision-making for organizational learning capability. Execute new service, execute new ideas, execute new process, execute new behavior, execute new product and execute new technology for organizational innovation.

Data Analysis

In this study, the data were analyzed using the Partial Least Square - Structural Equation Modeling (PLS-SEM) method, assisted with the Smart PLS 3.3.3 application. The PLS-SEM analysis was carried out in two levels, namely first-order confirmatory factor analysis (first-order CFA) and second-order confirmatory factor analysis (second-order CFA).

Outer Model

The first stage in the factor analysis was to test whether the indicators used could confirm the constructs (variables) in this study, while the second stage was to analyze the latent constructs into the dimension constructs. The factor analysis aimed to identify the dimensions of the structure and then determine to what extent each dimension could explain each variable. This test used the repeated indicators approach, also called the hierarchical component model.

Reliability and validity indicators form the initial step to check and ensure that the related indicators have similarities captured by the latent construct (Wong, 2019). However, after assessing convergent validity by examining the outer loadings of each latent construct, 3 of the 24 indicators in the higher and lower national culture constructs were omitted due to having outer loading values lower than the threshold level of 0.5, as proposed by Hair et al. (2014). Meanwhile, 10 of the 30 indicators on the higher and lower organizational learning capability constructs measured lower than the threshold level of 0.5, so that they were nullified and excluded from the model. However, in the higher and lower organizational innovation constructs, all 16 indicators have values above the threshold level of 0.5.

The next test was done by observing the Variance Inflation Factor (VIF) value, where a high correlation is not expected between the indicators of the measurement model. In addition, a high correlation between items indicates colinearity, which is considered problematic (Hair et al., 2014). The researcher had examined the colinearity between the construct items by examining the Variance Inflation Factor (VIF) value. Thus, the inner VIF value was used to examine the colinearity problem. According to Hair, et al., (2017), the expected VIF value should be less than 7, while the research results showed that the VIF values of all predictor constructs were less than 7. Therefore, colinearity was not a problem between construct dimensions (Hair et al., 2014; Hair et al., 2011).

As there were no issues with convergent validity, the next step was to examine the discriminant validity for each construct by observing the correlation value between constructs in the model. In measuring discriminant validity, Andriani & Putra (2019) mentioned two testing steps: the Fornell-Larcker criterion and the HeteroTrait-MonoTrait ratio of correlations (HTMT). However, Henseler, et al., (2015) suggested prioritizing using the HTMT inference rather than the Fornell-Larcker criterion. This is based on the failure of the Fornell-Larcker criterion in identifying discriminant validity, especially for large cases or complex research models. For this reason, the researcher only used HTMT inference as a test to identify discriminant validity (Table 1).

Table 1 Discriminant Validity (HTMT Inference Analysis)
Original Sample (O)	Sample Mean (M)	2.5%	97.5%
Collectivism/Individualism [LOC] ->National Culture [HOC]	0.355	0.357	0.323	0.400
Masculinity/Feminine [LOC] ->National Culture [HOC]	0.119	0.118	0.099	0.139
National Culture [HOC] ->Organizational Innovation [HOC]	-0.029	-0.030	-0.131	0.068
National Culture [HOC] ->Organizational Learning Capability [HOC]	0.210	0.219	0.063	0.380
Organizational Innovation [HOC] ->Execute New Behavior [LOC]	0.873	0.872	0.810	0.917
Organizational Innovation [HOC] ->Execute New Ideas [LOC]	0.766	0.765	0.688	0.829
Organizational Innovation [HOC] ->Execute New Process [LOC]	0.849	0.850	0.785	0.899
Organizational Innovation [HOC] ->Execute New Product [LOC]	0.629	0.624	0.420	0.771
Organizational Innovation [HOC] ->Execute New Service [LOC]	0.776	0.773	0.671	0.846
Organizational Innovation [HOC] ->Execute New Technology [LOC]	0.652	0.645	0.488	0.758
Organizational Learning Capability [HOC] ->Dialogue [LOC]	0.679	0.679	0.536	0.792
Organizational Learning Capability [HOC] ->Experimentation [LOC]	0.874	0.873	0.808	0.917
Organizational Learning Capability [HOC] ->Interaction with external environment [LOC]	0.814	0.814	0.739	0.873
Organizational Learning Capability [HOC] ->Organizational Innovation [HOC]	0.742	0.739	0.626	0.825
Organizational Learning Capability [HOC] ->Participative Decision Making [LOC]	0.514	0.511	0.331	0.661
Organizational Learning Capability [HOC] ->Risk-taking [LOC]	0.376	0.381	0.254	0.501
Power Distance [LOC] ->National Culture [HOC]	0.318	0.316	0.273	0.354
Uncertainty Avoidance [LOC] ->National Culture [HOC]	0.331	0.329	0.285	0.368

Meanwhile, reliability was examined using the composite reliability test by observing all latent variable values in this study, having a composite reliability value of 0.7. It can be concluded that the construct has good reliability or that the questionnaire used as a tool in this study has been reliable or consistent.

The second stage of testing was carried out by running the second-order confirmatory factor, which was used to identify the dimensions of a structure and then determine to what extent each of its dimensions could explain each variable. All lower-order constructs that made up the higher-order constructs were found to have statistical t-values above 1.96 and p-values below 0.05; thus, it can be concluded that all dimensional constructs made up organizational innovation (Table 2).

Table 2 Testing of Significance Lower and Higher Order Construct
Original Sample (O)	T Statistics (|O/STDEV|)	P Values
Collectivism/Individualism [LOC] ->National Culture [HOC]	0.355	18.182	0.000
Masculinity/Feminine [LOC] ->National Culture [HOC]	0.119	11.565	0.000
Organizational Innovation [HOC] ->Execute New Behavior [LOC]	0.873	31.722	0.000
Organizational Innovation [HOC] ->Execute New Ideas [LOC]	0.766	21.069	0.000
Organizational Innovation [HOC] ->Execute New Process [LOC]	0.849	29.291	0.000
Organizational Innovation [HOC] ->Execute New Product [LOC]	0.629	6.962	0.000
Organizational Innovation [HOC] ->Execute New Service [LOC]	0.776	17.308	0.000
Organizational Innovation [HOC] ->Execute New Technology [LOC]	0.652	9.494	0.000
Organizational Learning Capability [HOC] ->Dialogue [LOC]	0.679	10.488	0.000
Organizational Learning Capability [HOC] ->Experimentation [LOC]	0.874	31.425	0.000
Organizational Learning Capability [HOC] ->Interaction with external environment [LOC]	0.814	23.408	0.000
Organizational Learning Capability [HOC] ->Participative Decision Making [LOC]	0.514	6.051	0.000
Organizational Learning Capability [HOC] ->Risk-taking [LOC]	0.376	5.937	0.000
Power Distance [LOC] ->National Culture [HOC]	0.318	15.018	0.000
Uncertainty Avoidance [LOC] ->National Culture [HOC]	0.331	15.871	0.000

Inner Model

After the estimated model had met the criteria of the measuring model (outer model), the next step was to test the structural model (inner model). According to Ghozali (2015), the evaluation of the structural model (inner model) aims to predict the relationship between latent variables. Hair, et al., (2017), as quoted in Ramayah, et al., (2017), suggest observing the coefficient of determination (R²), model fit, and predictive relevance (Q²) to assess the structural model (inner model). Evaluate the model with SEM-PLS began by observing the R-square (R²) for each endogenous latent variable. The R-square coefficient of determination shows how much the exogenous variable explains the endogenous variable.

The R-square has a range of zero to one. An R-square value close to one means that the independent variable provides all the information needed to predict the variation of the endogenous variable. On the other hand, a smaller R² value means a limited ability of the independent variable to explain the endogenous variable's variation. Measurement using R-square has a weakness. The value of R-square will increase every time there is an additional exogenous variable, even though the exogenous variable has no significant effect on the endogenous variable. However, if an adjusted R-square value is used (Hair et al., 2017), this coefficient can be a positive bias upwards in complex models where more paths lead to endogenous constructs. More importantly, the coefficient of determination needs to be assessed in the context of the research project discipline to assess whether the R-square value obtained is large enough. From the test results, it could be seen that the adjusted R-square (R²) value of the organizational innovation construct was 0.542. These results indicated that the endogenous organizational innovation variable with an R-square value of 0.542 could be explained by the exogenous variable of 54.2%, while other exogenous variables outside this study explained the remaining 45.8.2%.

Predictive relevance (Q²) for the structural model measures how well the observed values are generated. According to Hair, et al., (2017), if the value of Q² is greater than zero for certain endogenous latent variables, it shows that the PLS path model has predictive relevance for that construct. Based on the calculation of predictive relevance (Q²), all measurements showed values above 0.000, namely dialogue (0.236), execute new behavior (0.592), execute new ideas (0.577), execute new process (0.605), execute new product (0.380), execute new service (0.589), execute new technology (0.417), experimentation (0.523), interaction with external environment (0.373), national culture (0.527), organizational innovation (0.292), organizational learning capability (0.021), participative decision making (0.171) and risk-taking (0.096). Thus it can be concluded that the model has a relevant predictive value.

The evaluation of the fit model in this study was carried out using three test models, namely Chi2, Standardized Root Mean Square Residual (SRMR), and Normal Fit Index (NFI). According to Bentler & Bonett (1980), the model can be accepted if the Chi2 value exceeds 0.9 (Chi2>0.9). Hair, et al., (2014) suggest that the model is considered a good fit if the standardized root mean square residual (SRMR) is below or equal to 0.1. The results showed that the model in this study has a good fit, having been found to have a Standardized Root Mean Square Residual (SRMR) value equal to 0.1. However, the other goodness of fit criteria is not shown by the software. This is because the model in this study used a repeated-indicators model so that some goodness of fit criteria were not defined.

Table 3 Hyphotesis Testing
Hyphotheses	Original Sample (O)	T Statistics (|O/STDEV|)	P Values
H1a	-0.009	0.570	0.568
H1b	-0.009	0.573	0.567
H1c	-0.010	0.562	0.574
H1d	-0.003	0.569	0.569
H2a	0.067	2.712	0.007
H2b	0.070	2.531	0.011
H2c	0.074	2.547	0.011
H2d	0.025	2.540	0.011
H3a	0.568	10.358	0.000
H3b	0.630	12.050	0.000
H3c	0.648	11.555	0.000
H3d	0.466	5.584	0.000
H3e	0.575	9.611	0.000
H3f	0.484	6.779	0.000
H4a	0.050	2.847	0.004
H4b	0.052	2.677	0.007
H4c	0.055	2.690	0.007
H4d	0.019	2.688	0.007

Based on the results of hypothesis testing, it was found that power distance, uncertainty avoidance, collectivism, and masculinity had no direct effect on organizational innovation because the correlations have p-values above 0.05. So it could be concluded that increases or decreases in power distance, uncertainty avoidance, collectivism, and masculinity were unable to increase or decrease organizational innovation. From these findings, it can be concluded that H1a, H1b, H1c, and H1d are rejected.

Testing the H2a, H2b, H2c, and H2d hypotheses showed that the relationship between power distance, uncertainty avoidance, collectivism, and masculinity significantly affected organizational learning capability, with p-values below 0.05 and t-statistics values above 1.96. Similarly, the relationship between organizational learning capability to execute new ideas, execute new processes, execute new behavior, execute new products, execute new services, and execute new technology significantly affected p-values below the 0.05 and t-statistics values above 1.96.

The test continued by analyzing the mediating effect of organizational learning capability on the relationship between power distance, uncertainty avoidance, collectivism, masculinity, and organizational innovation. In the indirect relationship, it was found that organizational learning capability mediated the existing relationship with p-values below 0.05 and t-statistics values above 1.96. However, according to Capeda, et al., (2018), the role of mediation can be determined by comparing direct and indirect relationships, which can be analyzed as full mediation, partial mediation, and no mediation. This study found that the direct relationship between power distance, uncertainty avoidance, collectivism, masculinity, and organizational innovation did not affect. Still, the effect was found to change if mediated by organizational learning capability. It can be concluded that organizational learning capability fully mediates the relationship between power distance, uncertainty avoidance, collectivism, masculinity, and organizational innovation. Organizational learning capability is a variable that has an essential role in helping encourage the existence of a national culture that can affect organizational innovation.

Conclusion

Previous studies revealed that National Culture's dimensions, namely power distance, uncertainty avoidance, individualism/collectivism, and masculinity/femininity, influence innovation (Prim et al., 2017; Cox & Khan, 2017) have a significant effect on innovation. However, this study found no direct relation between National Culture dimensions and organizational innovation. Only through the mediating effect of Organizational Learning Capability then the relationship is established. The organizational learning capability has managed culture to achieve organizational innovation, for it significantly affects all dimensions of organizational innovation. In addition, organizational learning capability mediates power distance, uncertainty avoidance, masculinity/femininity, and individualism/collectivism on all dimensions of organizational innovation.

This study has a limitation that is limited to a specific national context and greater Jakarta in particular. In addition, the data collected were not large enough. It is suggested for future similar research that the research scale is broadened, which covers all provinces in Indonesia.

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57. Roy Pratikno received B.Sc., degrees in Computer Science, University of Minnesota, Twin Cities, U.S.A. and M.M. degree in International Business from Universitas Gadjah Mada, Yogyakarta, Indonesia.