Learning Agility and Organization Learning Culture: Validating the Scale of Learning Agility and Organization Learning Culture Cross-Cultural

Benedikta Gaudensia Sura^1*, Reny Yuniasanti², Nina Fitriana³

^1,2,3Universitas Mercu Buana Yogyakarta, Depok, Special Region of Yogyakarta, Indonesia

Email: chalistahibaratu14@gmail.com¹, reny.yuniasanti@mercubuana-yogya.ac.id², nina@mercubuana-yogya.ac.id³

Abstract: The concept of learning agility has become a crucial tool in the selection, recruitment, and development of individual potential within organizational environments to address VUCA (volatility, uncertainty, complexity, and ambiguity) conditions. Learning agility encompasses aspects such as transformation, innovation, adaptation, and flexibility. This study aims to adapt and validate the BLAI (Burke Learning Agility Inventory) and OLC (Organization Learning Culture) scales within the Indonesian context.The research employs a cross-sectional design with six stages of cross-cultural adaptation: forward translation, synthesis, back-translation, expert assessment, scale trial, and reporting of adaptation results. The findings indicate that the BLAI scale, with its nine dimensions, and the OLC scale, with its two dimensions, exhibit good validity and reliability within the Indonesian context.The study concludes that these adapted measurement tools can be used to evaluate learning agility and learning culture in Indonesian organizations. These tools assist organizations in enhancing the effectiveness of recruitment and employee development processes in facing a constantly changing and uncertain work environment.

Keywords: Learning Agility, Organization Learning Culture, Cross-Cultural.

INTRODUCTION

The concept of learning agility, or can be referred to as learning agility is a concept that in recent years has been used as a way to select, recruit, and develop individual potential in an organizational environment (Burke, 2018). Learning agility is used as one of the key factors in dealing with conditions milieu work that is constantly changing and unpredictable or known as VUCA (volatility, uncertainty, complexity, and ambiguity) (Ferry, 2015). Volatility or volatility refers to the level of rapid fluctuations or changes in the business environment, Uncertainty or uncertainty relating to a lack of reliable information or predictions regarding the future. Complexity or complexity refers to the many complex factors and relationships in the business environment and Ambiguity or ambiguity refers to ambiguity or confusion regarding the information received (Manders, 2014). (Harvey & De Meuse, 2021) explained that learning agility is an important context for organizations in facing VUCA and the acceleration of change or hypercharge as a result of technological advancements. Learning agility is an analogy combining ideas such as transformation, innovation, adaptation, flexibility, change, reinvent, re-engineer, shift, pivot, renew and so forth. The concept of learning agility was first introduced by (Lombardo & Eichinger, 2000) The study highlights the concept of learning agility and finds a relationship between learning agility and leadership potential. (Lombardo & Eichinger, 2000) argues that an individual's potential cannot be fully detected from the things shown by an individual in his or her work, it is better for individuals to do something new and different which involves learning new skills, being given the opportunity to face new conditions and situations that have never been experienced before. The study also explains that the difference between a person and others can be seen from the individual's ability to learn from the experiences experienced, which is what distinguishes individuals with high potential and success from others. Therefore, learning agility is defined as an individual's willingness and ability to learn from experience and apply that learning to new conditions and different or difficult situations. (Lombardo & Eichinger, 2000) Introducing the dimensions that make up learning agility, namely people agility, mental agility, change agility and result agility. Research on learning agility continues to develop. Several studies have produced other instruments to modify the dimensions of learning agility considering that readability measures are not acceptable in all regions of the world (Gravett & Caldwell, 2016). Different instruments will be required for different regions, as efficient measuring tools in the global economy/market need to take into account the organizational culture in a particular region (Askarno & Nendi, 2023).

Thus the development of the four dimensions of research (Lombardo & Eichinger, 2000) where (De Meuse et al., 2011) Then add a new dimension to the pre-existing dimension, namely the self-awareness dimension. Then research (Derue et al., 2012) which defines learning agility as flexibility and speed and explains that learning agility can be understood by processes and behaviors. In this regard, Burke, 2018 then developed a new, simpler measurement from a behavioral standpoint with an orientation toward understanding that individuals can learn in any variety of situations that can result in positive performance changes over time. Although it is related to behavior, Burke, (2018) explained that the development of the measuring tool is based on the approach (De Meuse et al., 2010), but limit the construction of the aitem to observable behavior. Burke, 2018 explained that learning agility is a set of behaviors that can be developed that requires an examination of the individual's personal characteristics before learning agility as well as social contextual elements that can increase or decrease the individual's ability to act in an agile way. The measurement developed by Burke, 2018 is known as BLAI (Burke Learning Agility Inventory). The dimensions developed in the measurement are 1) the dimension of flexibility, the ability of individuals to be open to new ideas and propose new solutions.; 2) the speed dimension, the ability of individuals to adapt quickly to changes in situations and respond flexibly to new information received; 3) the dimension of experimenting, the ability of individuals to try new behaviors, such as approaches or ideas, to determine which ideas or approaches are effective.; 4) the dimension of performance risk-taking, which is the ability of individuals to seek out new activities, such as tasks, assignments, or roles, which provide opportunities to be tested and challenged; 5) the interpersonal dimension of risk-taking, which is the ability of individuals to deal with differences with others in a way that leads to learning and change; 6) the collaborating dimension, the ability of individuals to find ways of working with others that result in unique opportunities for learning; 7) the dimension of information gathering, the ability of individuals to use various methods to stay up to date in their field of expertise; 8) the dimension of feedback seeking, the ability of individuals to ask for feedback from others regarding their ideas and overall performance; 9) Reflecting Dimension, ability individuals to slow down the process, evaluate their own performance, and consider ways to be more effective.

Problems regarding learning agility often occur. This is evidenced by more than 50% of employees do not have agility and 30% have low agility (Brecheisen et al., 2018). Previous research estimates that only 15% of the global workforce is highly agile learners or have high learning agility (Swisher, 2013). This means that as many as 85% of the global workforce has low learning agility. Previous research found that the learning agility of millennial generation employees is in the medium category based on the length of work, i.e. the longer they work, the lower the learning agility (Surya & Yuniasanti, 2023). According to the results of the 2023 World Economic Forum survey, as many as 33% of respondents said that agility, resilience and flexibility skills are the most prioritized skills to be developed in Indonesia in the next five years, namely 2023-2027 (World Economic Forum, 2023). This means that the development of learning agility in Indonesia needs to be carried out because low learning agility will negatively impact the decline in company performance ((Dries et al., 2012). Yadav & Dixit explained that other studies have suggested that learning agility is a better predictor of high performance compared to IQ and personality traits (Wardhani et al., 2022)). According to (Derue et al., 2012) that sThe higher the learning agility of employees, the greater the contribution to the company's performance in the future. And with high performance, it will maintain the continuity of the company. (Dries et al., 2012) It found that the use of learning agility in identifying employees with great potential is better than using job performance. According to a study conducted by the Korn Ferry Instute (Knight & Wong, 2017) It was found that individuals with high learning agility were promoted twice as fast compared to individuals with low learning agility, it was also found that companies with highly agile leaders had 25% higher revenue margins than similar companies and also leaders with high learning agility had five times greater tolerance for ambiguity, empathy and social fluidity.

There are two main factors that affect learning agility: environmental factors and individual factors. According to (De Meuse et al., 2010) Environmental factors that affect learning agility are 1) organizational culture, that an organizational culture that is too restrictive will inhibit individual motivation to learn. On the contrary, a supportive culture, supporting individual independence and interaction between superiors and subordinates, will foster learning and learning agility; 2) Self-fulfillment, that individuals have the ability to influence an individual's potential simply by marking the person as a person with potential. (Derue et al., 2012) added that other environmental factors that affect learning agility include: 1) characteristics of previous experiences, the nature of the experience itself can have a strong influence on whether certain individuals show learning agility; 2) Learning culture, a dimension of organizational culture that focuses on the extent to which learning is well articulated as a norm and exemplified in an organization that helps trigger an individual's fundamental ability to learn quickly and flexibly, thus encouraging a greater demonstration of learning agility in the organization. According to (De Meuse et al., 2010) Individual differences that affect learning agility are 1) Past experiences experienced by individuals, that individuals who have lived for a certain period of time from various locations and worked in various work environments will be more likely to be open-minded and have a tendency to learn than individuals who remain in the same environment; 2) self-awareness, referring to the ability to have personal insight and form an accurate self-perception; 3) the ability of individuals to handle difficult situations, leadership development is essentially the development of leadership complexity. Complex leadership roles require a complex of thought, observation, and appropriate action (Azzahra et al., 2024). According to (Miller, 2018) Learning agility is influenced by two individuals, namely cognitive ability factors and personality factors; Plonka; (Derue et al., 2012)Presenting individual factors that affect learning agility in the workplace, namely belief and attitude factors which include emotions and positive attitudes towards change and positive attitudes towards repetitive learning and self-development (Petermann & Zacher, 2020).

According to (Derue et al., 2012) One of the antecedents of learning agility is organizational culture. Talking about organizational culture, it is inseparable from the organization through culture playing a role in advancing and developing individual learning with the aim of achieving good or productive individual learning which can then be applied to group learning or organizational learning so that it can contribute to organizational performance (Rebelo & Gomes, 2011). Therefore ((Rebelo & Gomes, 2011)Introducing a measurement that measures how far an organization contributes to the learning culture in an organization. This measurement tool is called organization learning culture (OLC). OLC consists of two dimensions, namely integral integration and external adaptation. These two dimensions are the most recent developments in the theory developed by Rebelo and Gomes. Previously, there were 4 dimensions, namely External orientation); (2) Autonomy and empowerment, (3) Leadership support, and (4) Learning incentive. The OLC scale was developed in 2000 based on six semi-structured interviews and learning culture frameworks proposed by Schein (1992, 1994), Hill (1996), Marquardt (1996) and Ahmed et al. (1999) (Rebelo & Gomes, 2011). With the initial number of items is 40 items which are then continued to be researched and reduced so that until now there are 20 OLC items.

There are several Western studies that use BLAI and OLC as measuring tools. However, the development of BLAI and OLC measurements in the eastern context, especially in Indonesia, has never been carried out, so adapting the scale to the eastern context is necessary due to differences in language, culture, and time span. The existing BLAI and OLC scales have been considered valid and reliable, however, to the knowledge of the researcher, there are limitations in terms of instruments that can be used to assess BLAI and OLC in the Indonesian context. Therefore, this study aims to adapt and validate the BLAI and OLC scales to suit the Indonesian context.

RESEARCH METHODS

Research Design

This study uses a cross-section design, where all actions are carried out at the same time. Researchers make cross-cultural adaptations by referring to the guidelines (Beaton et al., 2000) which consist of 6 stages: forward translation, synthesis, backward translation, expert committee meeting, pretesting, and submission of cross-cultural adaptation reports. In this study, the researcher used the following stages: forward translation, synthesis of translation results, and backward translation, the scale was synthesized and expert judgment was carried out, scale trials were carried out on the subjects, and reports on the results of cross-cultural adaptation were made.

Subject

The subjects of this study consist of two groups. The first group consisted of 6 experts in the field of psychology and English. A total of 5 out of 6 experts were recruited to do cross-cultural adaptation and one other person was recruited to conduct expert judgement.

The second group in this study consists of 100 employees aged 23-44 years (46 males or 46% and 54 females or 54%) from seven provinces in Indonesia, who were selected using the convenient sampling method. Partial Least Square (PLS-SEM) is used to assess the validity and reliability of the BLAI and OLC scales, which were adapted using the Smart-PLS version 3.0 application. Sample demographic data are presented in Table 1.

Table 1. Subject Characteristics

Characteristics of Respondents	Category	Frequency	Percentage
Age Range	23-26 Years	38	38%
	27-31 Years	38	38%
	32-36 Years	18	18%
	37-40 Years	2	2%
	41-44 Years	4	4%
Sum		100	100%
Gender	Man	46	46%
	Woman	54	54%
Sum		100	100%
Job Field	Finance	13	13%
	Education	29	29%
	Health	18	18%
	Economics	19	19%
	Law	6	6%
	Technician	13	13%
	Art	2	2%
Sum		100	100%
Education	High School/Vocational School	7	7%
	Diploma	12	12%
	Bachelor	72	72%
	Master	9	9%
	Doctor	0	0%
Sum		100	100%
Length of Work	3 - 11 Months	18	12%
	1-3 Years	31	21%
	More than 3 Years	50	33%
Sum		99	66%
Province	Special Region of Yogyakarta	21	21%
	East Nusa Tenggara	32	32%
	Riau Islands	7	7%
	Jakarta	23	23%
	West Java	7	7%
	East Java	5	5%
	Central Java	5	5%
Sum		100	100%
Income	Less than 1,000,000	8	8%
	IDR 1,000,000 -IDR 2,000,000	26	26%
	IDR 3,000,000 - IDR 4,000,000	35	35%
	Greater than IDR 4,000,000	31	31%
Sum		100	100%

Measure

In this study, the researcher adapted the BLAI and OLC scales developed by Burke, (2018) and Rebelo & Gomes, (2011) in the context of Indonesia. The BLAI scale has 38 items with 9 dimensions. Where the first and second dimensions, namely flexibility and speed, are measured using 5 items, while the third to seventh dimensions are experimenting, performance risk-taking, interpersonal risk-taking; collaborating, information gathering, feedback seeking, and reflecting Measured using 4 items. The measurement range of this scale uses 7 points from 1 "never" to 7 "very often". Burke, 2018 indicates that the BLAI scale is a valid, reliable, and unique construct. Research (Catenacci-Francois, 2018) reported that the BLAI scale has good reliability. Meanwhile, the OLC scale has 20 items with 2 dimensions, the first dimension is internal integration which is measured using 12 items and the second dimension, namely external adaptation is measured using 8 items. The measurement range used is 5 points of 1"hardly applicable" to 5 "almost all of them apply". Rebelo & Gomes, (2011) indicates that the BLAI scale is a valid and reliable scale. The reliability test values for each dimension are as follows: (α = 0.92 for internal integration and α = 0.90 for external adaptation). Some studies that used the OLC scale reported good reliability values such as (Saputra et al., 2018) and (Tripathi et al., 2020).

Data Analysis

Construct Validity Test

According to Jogiyanto, a strong correlation between the construct and the question items and a weak relationship with other variables is one way to test the validity of the construct (Hamid & Anwar, 2019). Construct validity testing in PLS-SEM consists of convergent validity and discriminatory validity.

Convergent validity is related to the principle that measurements of a construct should be highly correlated, Jogiyanto said (Hamid & Anwar, 2019). The validity test of reflective indicators with the Smart-PLS program can be seen from the loading factor values for each construction indicator, Ghozali & Latan (Haryono & Wardoyo, 2012). The Rule of Thumb to assess convergent validity is that the loading factor value must be greater than 0.7 for confirmatory studies and the average variance inflation factor (AVE) value must be greater than 0.5. (Hamid & Anwar, 2019).

The validity of discrimination is related to the principle that different construction measurements should not be highly correlated, Jogiyanto said (Hamid & Anwar, 2019). Discriminatory validity describes how far a construct/variable constructed differs from other constructs/variables ((Yamin, 2021). According to Ghozali & Latan, the way to test the validity of discrimination with reflective indicators is to look at the cross-loading value. This value for each variable must be greater than 0.70, Ghozali & Latan (Hamid & Anwar, 2019). According to (Yamin, 2021), discriminatory vagility testing is carried out at the level of variables and indicators. At the indicator level, cross-loadings are used and at the variable level is the Fonell-Lacker Criterion, which compares the root of AVE with the correlation between variables.

Reliability Test

Reliability tests are used to prove the accuracy, consistency, and precision of the instrument in measuring constructs, Ghozali & Latan, ((Hamid & Anwar, 2019). Measuring the reliability of a construct with reflective indicators can be done in two ways, namely with Cronbach's alpha and composite reliability. The rule of thumb is used to assess the reliability of a construct, and the composite reliability value must be greater than 0.70. However, using Cronbach's alpha to test the reliability of a construct will give a lower value (underestimate) so it is more advisable to use composite reliability, Ghozali & Latan in ((Hamid & Anwar, 2019).

RESULTS AND DISCUSSION

Result

The results of this research are presented in the form of a table that explains the evaluation of the measurement model, namely the validity of convergence and validity of discrimination as well as the reliability of the construct. Here's the explanation:

Learning Agility Scale

The following Table 1 is the results of the outer loading test. According to Ghozali & Latan's rule of thumb, the loading factor value must be greater than 0.7 for confirmatory studies and the average variance inflation factor (AVE) value must be greater than 0.5. (Hamid & Anwar, 2019).

Convergent Validity

Table 2. First trial outer loading value

Variable		Aitem	Outer Loadings	Conditions	Information
Learning agility	Flexibility	FBA1	0,831	>0.7	Valid
		FBA2	0,824	>0.7	Valid
		FBA3	0,871	>0.7	Valid
		FBA4	0,882	>0.7	Valid
		FBA5	0,828	>0.7	Valid
	Speed	SDA6	0,810	>0.7	Valid
		SDA7	0,875	>0.7	Valid
		SDA8	0,896	>0.7	Valid
		SDA9	0,880	>0.7	Valid
		SDA10	0,906	>0.7	Valid
	Feedback Seeking	FSA11	0,815	>0.7	Valid
		FSA12	0,846	>0.7	Valid
		FSA13	0,889	>0.7	Valid
		FSA14	0,811	>0.7	Valid
	Information gathering	IG15	0,867	>0.7	Valid
		IG16	0,889	>0.7	Valid
		IG17	0,883	>0.7	Valid
		IG18	0,885	>0.7	Valid
	Performance Risk Taking	PRA19	0,923	>0.7	Valid
		PRA20	0,318	>0.7	Invalid
		PRA21	0,246	>0.7	Invalid
		PRA22	0,932	>0.7	Valid
	Interpersonal Risk Taking	IRA23	0,786	>0.7	Valid
		IRA24	0,855	>0.7	Valid
		IRA25	0,891	>0.7	Valid
		IRA26	0,215	>0.7	Invalid
	Collaborating	CA27	0,875	>0.7	valid
		CA28	0,881	>0.7	Valid
		CA29	0,845	>0.7	Valid
		CA30	0,886	>0.7	Valid
	Experimenting	EXA31	0,871	>0.7	Valid
		EXA32	0,884	>0.7	Valid
		EXA33	0,835	>0.7	Valid
		EXA34	0,784	>0.7	Valid
	Reflecting	RA35	0,800	>0.7	Valid
		RA36	0,855	>0.7	Valid
		RA37	0,854	>0.7	Valid
		RA38	0,841	>0.7	Valid

In the first test, the items PRA20, PRA21 and RA26 were eliminated due to the outer loading value being smaller than 0.7. Meanwhile, the remaining 35 items were retested. The results of the second scale trial can be seen in Table 2 below:

Table 3. Outer loading value and AVE second trial

	Aitem	Dimension	Outer Loadings	Average Variance Extracted (AVE)
Learning agility	FBA1	Flexibility	0,831	0,718
	FBA2		0,824
	FBA3		0,871
	FBA4		0,882
	FBA5		0,828
	SDA6	Speed	0,810	0,764
	SDA7		0,874
	SDA8		0,896
	SDA9		0,879
	SDA10		0,906
	FSA11	Feedback Seeking	0,815	0,707
	FSA12		0,846
	FSA13		0,888
	FSA14		0,811
	IG15	Information gathering	0,867	0,776
	IG16		0,889
	IG17		0,883
	IG18		0,885
	PRA19	Performance Risk Taking	0,934	0,866
	PRA22		0,927
	IRA23	Interpersonal Risk Taking	0,789	0,720
	IRA24		0,861
	IRA25		0,893
	CA27	Collaborating	0,875	0,760
	CA28		0,881
	CA29		0,846
	CA30		0,886
	EXA31	Experimenting	0,871	0,713
	EXA32		0,884
	EXA33		0,835
	EXA34		0,784
	RA35	Reflecting	0,800	0,702
	RA36		0,855
	RA37		0,854
	RA38		0,841

Based on the second trial above, 35 items of the learning agility scale have an outer loading value > 0.7. And the AVE value > 0.5, then the convergent validity test meets the criteria.

Validity of Discrimination

Table 4. Cross Loading

	Collaborating	Feedback Seeking	Flexibility	Informatization Gathering	Interpersonal Risk Taking	Performance Risk Taking	Reflecting	Speed	experimenting
FBA1	0,554	0,671	0,831	0,649	0,626	0,726	0,653	0,545	0,712
FBA2	0,559	0,535	0,824	0,505	0,594	0,558	0,621	0,502	0,587
FBA3	0,579	0,572	0,871	0,543	0,595	0,616	0,619	0,582	0,671
FBA4	0,611	0,665	0,882	0,571	0,695	0,632	0,617	0,617	0,702
FBA5	0,614	0,674	0,828	0,627	0,602	0,639	0,581	0,665	0,663
SDA6	0,597	0,612	0,583	0,605	0,587	0,464	0,656	0,810	0,617
SDA7	0,559	0,599	0,615	0,677	0,531	0,494	0,636	0,874	0,683
SDA8	0,622	0,629	0,628	0,680	0,603	0,531	0,617	0,896	0,655
SDA9	0,585	0,660	0,569	0,638	0,611	0,440	0,623	0,879	0,637
SDA10	0,584	0,659	0,613	0,694	0,617	0,498	0,648	0,906	0,661
FSA11	0,588	0,815	0,547	0,615	0,719	0,529	0,631	0,578	0,601
FSA12	0,617	0,846	0,628	0,652	0,619	0,689	0,643	0,553	0,602
FSA13	0,650	0,888	0,694	0,708	0,648	0,680	0,614	0,610	0,677
FSA14	0,547	0,811	0,608	0,698	0,709	0,517	0,550	0,690	0,679
IG15	0,524	0,725	0,605	0,867	0,552	0,585	0,592	0,684	0,677
IG16	0,687	0,749	0,622	0,889	0,624	0,675	0,731	0,715	0,741
IG17	0,562	0,706	0,648	0,883	0,527	0,691	0,675	0,598	0,737
IG18	0,545	0,617	0,537	0,885	0,512	0,585	0,655	0,660	0,693
PRA19	0,591	0,693	0,705	0,702	0,588	0,934	0,728	0,528	0,659
PRA22	0,585	0,646	0,691	0,639	0,581	0,927	0,674	0,506	0,630
IRA23	0,618	0,713	0,744	0,589	0,789	0,592	0,589	0,555	0,647
IRA24	0,649	0,660	0,548	0,557	0,861	0,473	0,569	0,617	0,684
IRA25	0,678	0,657	0,571	0,452	0,893	0,528	0,637	0,543	0,654
CA27	0,875	0,701	0,628	0,603	0,768	0,626	0,693	0,548	0,771
CA28	0,881	0,561	0,528	0,569	0,592	0,524	0,710	0,594	0,710
CA29	0,846	0,523	0,528	0,543	0,573	0,441	0,610	0,576	0,722
CA30	0,886	0,691	0,705	0,586	0,720	0,599	0,642	0,633	0,768
EXA31	0,727	0,674	0,729	0,744	0,662	0,589	0,661	0,640	0,871
EXA32	0,733	0,688	0,696	0,675	0,709	0,587	0,694	0,663	0,884
EXA33	0,809	0,674	0,598	0,688	0,640	0,600	0,701	0,618	0,835
EXA34	0,605	0,528	0,641	0,621	0,627	0,565	0,694	0,592	0,784
RA35	0,639	0,528	0,640	0,582	0,640	0,600	0,800	0,645	0,715
RA36	0,675	0,634	0,606	0,661	0,652	0,601	0,855	0,626	0,720
RA37	0,611	0,625	0,591	0,636	0,508	0,673	0,854	0,516	0,637
RA38	0,623	0,638	0,606	0,649	0,563	0,655	0,841	0,647	0,651

The data presentation in Table 3 above shows that each item in the dimension has the largest cross loading value in the dimension it forms, compared to the cross-loading value in other dimensions. Based on the results obtained, it can be stated that the items used in this study have good discriminant validity in compiling their own constructs.

Fonell-Lacker Criterion value (root of AVE)

Table 5. Fonell-Lacker Criterion value

	Collaborating	Feedback Seeking	Flexibility	Informatization Gathering	Interpersonal Risk Taking	Performance Risk Taking	Reflecting	Speed	experimenting
Collaborating	0,872
Feedback Seeking	0,715	0,841
Flexibility	0,689	0,738	0,848
Informatization Gathering	0,661	0,796	0,685	0,881
Interpersonal Risk Taking	0,765	0,800	0,735	0,630	0,849
Performance Risk Taking	0,632	0,720	0,751	0,722	0,628	0,931
Reflecting	0,761	0,724	0,729	0,755	0,707	0,754	0,838
Speed	0,675	0,723	0,689	0,755	0,675	0,556	0,727	0,874
experimenting	0,853	0,762	0,789	0,809	0,781	0,693	0,813	0,745	0,844

Table 3 shows that based on the Fonell-Lacker criterion, the AVE root of the collaborating dimension is 0.873, higher than the correlation with the feedback seeking dimension of 0.715. Likewise with each AVE root of each individual.

Reliability

Table 6. Reliability

	Cronbach's Alpha	rho_A	Composite Reliability
Flexibility	0,902	0,903	0,927
Speed	0,922	0,923	0,942
Feedback Seeking	0,861	0,863	0,906
Informatization Gathering	0,904	0,906	0,933
Performance Risk Taking	0,845	0,846	0,928
Interpersonal Risk Taking	0,804	0,803	0,885
Collaborating	0,895	0,898	0,927
experimenting	0,865	0,868	0,908
Reflecting	0,858	0,859	0,904

Based on Table 5 above, it shows that the value of the composite reliability (CR) of the learning agility dimension, where each dimension has a CR value of > 0.7, so it can be concluded that the learning agility construct has a high reliability value.

Figure 1. Learning Agility Construction Model

Learning Culture

Convergent Validity

Table 7. Learning Culture First Trial

		Aitem	Outer Loadings	Conditions	Information
Learning Culture	Internal Integration	II1	0,409	>0.7	Invalid
		II2	0,717	>0.7	Valid
		II3	0,773	>0.7	Valid
		II4	0,750	>0.7	Valid
		II5	0,751	>0.7	Valid
		II6	0,764	>0.7	Valid
		II7	0,750	>0.7	Valid
		II8	0,819	>0.7	Valid
		II9	0,824	>0.7	Valid
		II10	0,802	>0.7	Valid
		II11	0,766	>0.7	Valid
		II12	0,745	>0.7	Valid
	External Adaptation	EA13	0,788	>0.7	Valid
		EA14	0,762	>0.7	Valid
		EA15	0,815	>0.7	Valid
		EA16	0,795	>0.7	Valid
		EA17	0,845	>0.7	Valid
		EA18	0,769	>0.7	Valid
		EA19	0,786	>0.7	Valid
		EA20	0,801	>0.7	Valid

In the first test, aitem II1 was eliminated because the outer loading value was smaller than 0.7. Meanwhile, the remaining 19 items were retested. The results of the second scale trial can be seen in Table 6 below:

Table 8. Second Trial

	Dimension	Aitem	Internal integration	External Adaptation	AVE
Learning Culture	Internal Integration	II2	0,717		0,595
		II3	0,760
		II4	0,748
		II5	0,753
		II6	0,763
		II7	0,758
		II8	0,819
		II9	0,826
		II10	0,804
		II11	0,773
		II12	0,755
	External Adaptation	EA13		0,788	0,663
		EA14		0,762
		EA15		0,815
		EA16		0,795
		EA17		0,845
		EA18		0,769
		EA19		0,785
		EA20		0,801

Based on the second trial above, 19 learning culture scale items have an outer loading value > 0.7. If the AVE value > 0.5, then the convergent validity test meets the criteria.

Validity of Discrimination

Cross loading

Table 9. Cross Loading

	Internal integration	External Adaptation
II2	0,717	0,564
II3	0,760	0,643
II4	0,748	0,570
II5	0,753	0,631
II6	0,763	0,653
II7	0,758	0,650
II8	0,819	0,712
II9	0,826	0,665
II10	0,804	0,671
II11	0,773	0,619
II12	0,755	0,558
EA13	0,655	0,788
EA14	0,614	0,762
EA15	0,629	0,815
EA16	0,653	0,795
EA17	0,672	0,845
EA18	0,707	0,769
EA19	0,652	0,785
EA20	0,628	0,801

Based on the data presentation in Table 3 above, it shows that each item in the learning culture dimension has the largest cross-loading value in the dimension it forms, compared to the cross loading value in other dimensions. Based on the results obtained, it can be stated that the items used in this study have good discriminant validity in compiling their own constructs.

Reliability

Table 10. Composite reliability

	Cronbach's Alpha	rho_A	Composite Reliability
Internal integration	0,932	0,933	0,942
External Adaptation	0,917	0,917	0,932

Based on Table 9 above, shows that the value of the composite reliability (CR) of the learning culture dimension, where each dimension has a CR value of > 0.7, so it can be concluded that the learning culture construct has a high-reliability value.

Figure 2. Learning Culture Construction Model

Discussion

This research was carried out with the main goal of adapting the BLAI and OLC scales into Indonesian. This research is very important because it is still rare to find a scale to measure BLAI and OLC in the Indonesian context. Therefore, the main contribution of this study is to provide a measuring tool that can help researchers study and assess learning agility and learning culture in non-Western contexts, especially in Indonesia. Researchers carried out cross-cultural adaptation by applying forward and back-to-back methods with the support of several experts. Cross-cultural adaptation is carried out due to language and cultural differences from the original version of the measuring instrument that cannot be used as it is in the Indonesian context without any cultural adaptation.

Referring to the results of the study above, the learning agility scale, which originally consisted of 38 items, has changed to 35 items, and the learning culture scale from 20 items to 19 items remaining due to the outer loading value that does not meet the rule of thumb. The learning agility measure provides a comprehensive assessment of various factors and dimensions, which can be used to develop leadership abilities (Gravett & Caldwell, 2016). Doing so will help organizations avoid mistakes by not delegating certain tasks to the wrong individuals. Understanding of learning agility in organizational culture, especially in Indonesia, to increase understanding of the concept of learning agility practitioners in the recruitment process, to increase the effectiveness of the process of hiring and retaining talented talents in Indonesia, and to stimulate additional scientific research. An essential leadership attribute is the ability to remain open to new ways of thinking and constantly learn new skills. Past understanding has created a revolution in terms of looking at leadership potential. Predictions of an individual's potential in the past are viewed for future success only based on past performance and demonstrated skills and abilities (Joiner, 2007). However, the approach inherently has its drawbacks. Research shows that fundamentally different behaviors are necessary at all levels of the organization and that effective behaviors at one level do not necessarily lead to success at the next level, especially being a leader (Joiner, 2019). Agile is said to be a process of finding, managing, and learning from new experiences. Agile learning looks at current performance and long-term potential. Learning agility has been used to describe individuals with skills such as openness, willingness to learn, and flexibility. In addition, agile learners are curious about the world and highly tolerate ambiguity, good people skills, vision, and innovation.

This research has several implications for employees and other researchers, namely learning agility can be a measurement tool used to recruit and develop employees in facing the current VUCA condition. Over the past few years, the popularity of the concept of learning agility has increased drastically in the business sphere (K. P. De Meuse, 2017). Survey (Potential: Who’s Doing What to Identify Their Best?, 2015) It was found that 62% of subjects said that learning agility is the most commonly used criterion to measure leadership potential compared to Intelligence (IQ) by 13%, culture fit by 28%, emotional intelligence by 24% and personality by 14%. According to research (Church et al., 2015) It found that more than half of the companies sampled used Agile/Ability as an assessment to identify high-potential talent (56%) and select senior executives (51%). This condition proves that in the face of today's uncertain work environment, learning agility is needed to obtain a qualified workforce that can be invited to "run" to maintain the company's sustainability in the future. Companies with employees who have high learning agility will be faster and adaptive so that employees are always ready for future changes, which of course, employees will produce better performance ((Church et al., 2015). In theory, organizational learning is an important factor that affects learning agility behavior in individuals in organizations. So that the understanding of organizational learning is necessary today, considering that currently, the company needs to create a different work environment because generational change is the benchmark, if not done then the current generation of employees can easily leave the organization Organizations with a learning culture have the ability to help employees in turning challenges into opportunities (Watkind & Marsick in (Gregory et al., 2022). A learning culture is needed to help employees adapt and grow. Employees tend to maintain job satisfaction and loyalty, and performance remains high when facing transitions in the company (Lin & Huang, 2020a). In an environment driven by a learning culture, employees will be motivated to acquire, distribute, integrate, create, and transfer information and knowledge to colleagues and be open to various possibilities for the formation of continuous transformation for the better. (Sidani & Reese, 2018). When employees in a certain division or workgroup face new tasks and tasks that cannot be overcome, then these employees or groups can collaborate and build communication with employees or groups from other divisions (Lin & Huang, 2020b).

Tripathi et al., (2020) said that providing a good learning culture in the organization will help employees increase learning agility in the era of technological change. Learning culture encourages and facilitates employees to learn, disseminate and share knowledge to improve organizational performance. Learning culture also plays an important part in spreading the learning culture to employees, which not only helps in improving employees as an organization to face new changes that appear in the market but also encourages employees to learn new skills, which are important for individual and organizational development (Tripathi et al., 2020).

CONCLUSION

This study aims to adapt learning agility and learning culture measurement tools so that they can be used in Indonesia. Based on the results of the analysis of the measurement model test, it can be concluded that the BLAI instrument can measure learning agility through nine dimensions: flexibility, speed, experimenting, performance risk-taking, interpersonal risk-taking; collaborating, information gathering, feedback seeking, and reflecting. Also, the OLC scale can measure learning culture in two dimensions: internal integration and external adaptation. The results of this study show that there is evidence of good and adequate validity and reliability, but it can still be improved by making certain modifications so that it can be a better measurement tool when applied to look at the phenomenon of learning agility in employees. In addition, it can also be done by obtaining a larger number of samples from this test to be able to obtain better validity.

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