FACTORS RELATED TO LEARNING AGILITY: A SYSTEMATIC LITERATURE REVIEW

The current situation in the world is experiencing VUCA, where there are rapid and drastic changes in technology, economics, the environment, and other aspects. Every adult, especially employees and job seekers, needs to develop learning agility so that they can adapt and compete in today's era. This systematic literature review aims to identify the factors related to learning agility. Article searches were conducted from March to June 2022 using six databases, namely SpringerLink, Emerald Insight, ScienceDirect, SAGE, Scopus, and ProQuest, with keywords "Learning Agility" AND "Employee*" OR "Jobseeker*" OR "Student*". After the article screening process, a total of 10 studies were obtained and analyzed in this literature review. The results show that there are 11 factors related to learning agility, namely compensation, salary, internal marketability, digital competence, digital technologies, e-learning, career variety, work experience, outcome, learning engagement, dan turnover intention. The results of this study can be useful as a reference for future research to further examine the relationship of the above factors. The results of the study can also be practically useful for developing individual learning agility so that they have optimal potential to adapt agilely in the VUCA era.


Introduction
The world is rapidly changing today, both in terms of technology, economy, environment, and other aspects. This situation can also be referred to as VUCA, which stands for volatility (uncertainty), uncertainty, complexity, and ambiguity (Tamara et al., 2021). In the midst of this fast-paced world, especially in terms of technology, volatility, uncertainty, complexity, and ambiguity have become common situations in the business industry. This VUCA era has been known for several years and emerged as a result of the rapid flow of globalization that has spread throughout the world and influenced various aspects of life in society, including business processes, economy, and human resources (Bahri, 2022;Tamara et al., 2021). There are impacts of VUCA that affect the business sector in Indonesia, such as the unstable business rate due to technological advancements, developing and changing trends in society, and the unpredictable development of the business sector (Hendrarso, 2020).
In building a business, good human resources are needed to contribute to optimal business product outcomes (Anita, 2022). Companies that are able to successfully face the VUCA era are also companies that have employees who are sensitive to opportunities, risks, and challenges, and are able to build innovation for continuous development (Hendrarso, 2020). Therefore, employees as the drivers in companies and students or jobseekers as potential employees must have the ability to process decision-making quickly, innovate products or services, renew technology, and expand business scale.

Literature Review
One of the competencies needed to face the current situation is learning agility. In facing this VUCA situation, each individual is pushed to be more agile in facing changes, and this ability is called learning agility (Dank & Hellström, 2020). Learning agility enables individuals to adapt to the increasingly changing era. Learning agility is the ability and willingness of a person to learn from experience and apply the lessons learned to improve performance in the future (Derue et al., 2012). Research conducted by the Center for Creative Leadership (2014) showed that individuals who have high learning agility will have more active work behavior, creativity, the courage to express their opinions, optimism, resilience, and continuously develop and improve themselves (Mitchinson & Morris, 2014). Therefore, a systematic literature review is needed to provide an understanding of what factors are related to learning agility so that it can be a basis for developing learning agility as one of the important competencies to face the current VUCA era.

Methods
This study is a Systematic Literature Review (SLR) which reviews a number of predetermined research articles by identifying, evaluating, and interpreting all findings in research studies to answer the research objectives. The search for these articles was conducted from March to June 2022 using the following databases: SpringerLink, Emerald Insight, ScienceDirect, SAGE, Scopus, and ProQuest with the keywords "Learning Agility" AND "Employee*" OR "Jobseeker*" OR "Student*". The articles found based on these keywords were then synthesized and analyzed according to inclusion and exclusion criteria. The inclusion criteria include: (a) participants are adult individuals who are employees, students, or jobseekers, (b) the research was published in English and/or Indonesian, (c) the research is quantitative or qualitative, (d) the year of publication is within the last 10 years, from 2012 to 2022. The exclusion criteria are research studies that do not meet the inclusion criteria, have already been found in other publications, and full-text research papers are not available.
A total of 129 articles were obtained, then 58 articles were excluded because their titles and abstracts did not meet the criteria (n=35) and they were duplicate articles (n=23), resulting in a total of 71 articles. Based on the inclusion and exclusion criteria, 41 articles were excluded due to the sample not being suitable, the articles being literature reviews and meta-analyses, the quality of the journals being poor, and the research focus being more towards medical studies. A total of 30 articles remained, where 20 articles were excluded based on a check of the full text because the discussions were not comprehensive enough and did not fit the objectives of this study. As a result, there are 10 articles that will be further analyzed in this systematic literature review study.

Result and Discusssion Results
The following are the 10 articles reviewed to identify factors related to learning agility. Learning agility has a significant indirect effect on outcomes through a supportive culture as a mediator. Learning agility has a significant direct effect on outcomes.

Discussions
Based on the ten articles reviewed above, five groups were found consisting of factors related to and/or influencing learning agility, namely 1) compensation, salary, and internal marketability ; 2) digital competence, digital technologies, and e-learning; 3) career variety and work experience, 4) outcome and learning engagement; and 5) turnover intention.
Learning agility relates to internal factors that exist within the organization, such as compensation, salary, and internal marketability (Dai et al., 2013;Park et al., 2022). Individuals with high learning agility will be able to climb the career ladder and increase their income more quickly than individuals with low learning agility (Dai et al., 2013). Findings from Dai et al. (2013) also shows that managers and executive level employees with high learning agility will be able to learn from their experiences and increase their value to the organization so that this is appreciated by others and results in benefits at better levels of salary and compensation. Another research conducted by Park et al. (2022) demonstrated that the perceived internal marketability of individuals in organizations can be positively related to work-related learning processes. When organizations provide learning opportunities for individuals to improve their skills, individual perceptions of internal marketability will also increase. They will feel the eligibility to work and this is related to individual learning agility abilities (Park et al., 2022).
Digital technology and e-learning have also been shown to be positively related to learning agility in individuals Kim et al., 2018). In order for individuals to be able to actively adopt digital or technological approaches, they need good adaptability and flexibility which learning agility has. Individuals can have a positive perception of digital technology as a learning tool and integrate it into the work process because they have proactive intentions and good learning agility (Kim et al., 2018). On the other hand, e-learning technology is seen as an effective tool for increasing learning agility and enabling individuals to acquire new knowledge and skills according to their learning needs. Individuals with high learning agility are found to be able to perform better because they get adequate support to increase their knowledge through e-learning technology .
In addition to internal organizational factors and e-learning technology, learning agility can also continue to improve along with more career experience (Dries et al., 2012). Individuals who have more varied career experiences, both in terms of the large number of organizations and work domains they have worked on, will also have high learning agility (Dries et al., 2012). However, in terms of duration of work, research conducted by Ayu et al. (2021) shows that individuals who work for less than 2 years have higher learning agility. This can also be related to the age where younger individuals will have high learning agility so that they are more able to handle new changes smoothly compared to other older individuals (Ayu et al., 2021).
Individuals with high learning agility will have a tendency to produce something that has an impact, both in terms of performance in the organization (outcome) or attachment to the learning process (learning engagement) Jeon et al., 2022). Individuals with learning agility will be able to achieve organizational goals through limited resources and innovation, and the results also prove that learning agility can help individuals perform formal performance and fulfill responsibilities optimally . Individuals with high learning agility are also shown to be able to adopt an open perspective about others and are willing to control their behavior according to the environment. Therefore, learning agility can be considered as an important factor influencing individual performance and achievement as reflected in a high level of learning engagement (Jeon et al., 2022).
Optimal performance results during work lead individuals with high learning agility to have low levels of turnover intention (Tripathi et al., 2020). This is because when individuals have higher learning agility, they will tend to have stronger involvement in work and produce optimal performance where this leads to an increase in salary and compensation they get (Dai et al., 2013). That way, there is high individual involvement in the organization accompanied by an increase in satisfactory returns, so they will have the intention to remain in the organization so that internal turnover can decrease (Tripathi et al., 2020).

Conclusion
The factors found to be related to learning agility through the identification of ten literature articles in this study are: compensation, salary, internal marketability, digital competence, digital technologies, e-learning, career variety, work experience, outcome, learning engagement, and turnover intention. The results of this study can be useful as a reference for further research to be able to further examine the relationship of the factors above. The research results can also be of practical use for developing individual learning agility so that they have optimal potential to adapt agilely in the VUCA era.