Skill-based hiring is a methodology that emphasises and prioritises the knowledge, skills and abilities of candidates over conventional criteria such as academic credentials and years of experience (Khasni et al., 2023). Implementing skill-based hiring standards guarantees logical hiring choices grounded in quantifiable metrics rather than conventional credentials (Verheyen et al., 2016).

Today, firms are increasingly recognising that some professions do not require academic degrees or long experience but rather the presence of skills acquired via vocational training or actual job experience (Boyer & Griffith, 2023; Kotla, 2024). Organisations implementing this modern strategy ensure the selection of the most qualified personnel to fulfil the necessary responsibilities, tasks and roles. Fundamentally, skill-based hiring emphasises skills, knowledge and talents over formal credentials (Khasni et al., 2023). These principles depend on practical evaluation and alignment of candidates’ skills with the specific jobs they are expected to fulfil. Organisations employing skill-based hiring prioritise a candidate’s capabilities over their academic credentials or years of experience. Skill-based hiring employs advanced technology such as artificial intelligence and data-driven recruitment tools. Skill-based hiring demonstrably improves the inclusion of people from diverse backgrounds in organisations, removing unnecessary hurdles established by standard recruiting criteria (Albright et al., 2020). This staffing method improves objective initiatives and employee retention, strengthens training and development initiatives and ensures better alignment between the employee and the job, allowing for the effective execution of organisational roles, tasks and responsibilities and thereby reducing employee turnover. Skill-based hiring ensures that job descriptions are produced using a specific set of relevant skills, knowledge and abilities, while interviews are conducted based on the candidate’s attitudes and job suitability. Aritificial intelligence -powered evaluation tools ensure the monitoring and tracking of potential candidates. Choosing candidates based on objective data criteria can lead to more effective and equitable results (DeMark & Kozyrev, 2021). However, while AI is often perceived as objective, it can still reflect biases present in the data or algorithms used, which may inadvertently affect fairness in decision-making (RA.10, lines from 125–127). Our study draws on two reputable sources that have identified the most influential and subjectively informed approaches to hiring individuals according to their skills. The first study includes analysing how important academic credentials are and figuring out which jobs are best for skill-based hiring (Sigelman et al., 2024). Another research study aims to evaluate a dataset of one million Internet enterprises in the United Kingdom (Gonzalez & Stephany, 2023). Depending on those studies, the most effective models for practising skill-based hiring include the following elements: (1) Job descriptions requiring specific skills: This dimension assesses the extent to which your company prioritises skills over degrees or experience during the hiring process. (2) Skill assessment and evaluation: It checks how frequently the business uses practical or real-world skill evaluations to evaluate candidates’ skills. (3) Evaluations of work samples and portfolios: It examines how the organisation assesses candidates’ skills using case studies, previous project assessments or work samples. (4) Situational and behavioural interviews: They emphasise candidates’ problem-solving capabilities, adaptability and critical thinking skills rather than their academic qualifications or professional experience. (5) Interpersonal competencies: Encompassing effective communication and collaboration. Data-driven recruitment decisions pertain to the degree to which an organisation utilises artificial intelligence and performance metrics to evaluate talent objectively.

The notion of individual performance has attracted considerable focus across several disciplines, including applied psychology and HRM (Johari et al., 2018; Taamneh et al., 2021). The notion of employee performance assessment encompasses parameters like productivity, goal attainment and job quality. This study’s focus on skill-based hiring emphasises the significance of skills, knowledge and abilities pertinent to the job’s nature. While technical skills are significant, they do not constitute the primary criteria for organisational success; rather, soft skills such as teamwork, leadership and communication have a far higher influence (Bishop, 2017). Given these facts, it is more rational to adopt a holistic approach to the criteria for recruiting and performance evaluation to ensure organisational success. Hiring people with skills that improve overall employee performance is a top priority. At the same time, a lot of work goes into making a complete list of criteria that are necessary for employee performance (Islam & Periaiah, 2023; Shahi et al., 2023; Taamneh et al., 2022). The importance of assessing employee performance stems from the use of behavioural and technical criteria to guarantee that employees satisfy expectations. Researchers argue that the absence of a performance monitoring system, or the inability to adopt one, might create a difficult atmosphere for employees. This tough climate may reduce staff morale and cohesion, jeopardising the organisation’s long-term viability (Fauzi et al., 2023). One of the most significant goals of employee performance evaluation is to foster a culture of responsibility and continuous development, both of which are critical components in retaining a competitive edge for modern firms (Escolar-Jimenez, 2019; Jančiauskaitė & Lalienė, 2023). Performance evaluation literature has addressed several types of individual performance measuring methods. There is a scale that focuses on behavioural standards and advocates of this movement claim that it gives a more accurate picture of employee performance, particularly when behavioural standards are linked to performance outcomes (Fauzi et al., 2023; Taamneh et al., 2024). Organisations can, however, implement an individual performance measuring system that combines self-assessment and customer feedback (Hartati & Hikmah, 2022; Khan et al., 2017). According to researchers, in order for individuals to thrive in their positions, performance standards must be related to the skills and behaviours they encompass, as well as congruent with the strategic goals of businesses (Derebew et al., 2021; Lestari & Setya, 2018). This study’s major factors for evaluating job performance are the following: (1) Job knowledge and skills, (2) work quality, (3) work quantity, (4) communication skills, (5) teamwork and collaboration, (6) adaptability and flexibility, (7) initiative and invention, (8) customer service and relationship management, (9) goal achievement and (10) overall performance and growth (Lestari & Setya, 2018).

Continuous learning is defined as the ongoing acquisition of fresh skills and knowledge with the intention of improving individual performance. In the context of our study on skill-based hiring, continuous learning is defined as the voluntary and ongoing pursuit of knowledge, skills and abilities for professional progress (Nosike, 2022). Dealing with professional and technical developments and problems is the central focus of continuous learning in the workplace. This approach emphasises obtaining new or enhancing current abilities with the goal of securing the organisation’s capacity to compete, grow and prosper. At the same time, it seeks to ensure that personnel maintain their ability to fulfil the duties and activities allocated to them (Godbless & Obaro, 2022; Wateen et al., 2024). The banking sector’s rapid technological progress, as well as the rising intensity of competition, necessitates the adoption of the continuous learning concept and strategy. Continuous learning is a mindset that promotes self-development, reaching capacities and keeping the desire to gain fresh skills and knowledge outside of the framework of traditional learning (Godbless & Obaro, 2022; Terence & Cate, 2023). Continuous learning has the substantial benefit of enhancing employee engagement and job satisfaction. The competency acquired through continuous learning promotes the employee’s trust to perform the roles and tasks essential for one’s career path (Nosike, 2022). Continuous learning elements include self-directed learning, knowledge collaboration, skill development, feedback, formal and informal learning, technology adoption, organisational support and a growth mindset (Huang & Yu, 2019; Lestari & Setya, 2018).

The notion of skill-based hiring has lately gained popularity in academic circles, with job candidates’ practical skills becoming the primary hiring factor rather than academic degrees. Skill-based hiring has emerged as a critical recruitment technique, driven by the scarcity that many firms confront in assessing the abilities necessary to fill the position (Sarker et al., 2019; Soelistya, 2025). Several earlier research studies have proven that skill-based hiring, which prioritises skills and competencies above academic degrees, significantly improves employee performance across industries (Zayed et al., 2023). This approach is congruent with Khasni et al. (2023), who think that hiring methods based on developing a set of skills necessary to fill the position improve employee performance and organisational success (Stewart & Preiksaitis, 2023). According to Boyer and Griffith’s research, businesses are now better able to connect work requirements in job descriptions with the real skills necessary for the position in question. They no longer use traditional approaches based on academic degrees or years of experience. Their findings further suggest that the shift to skill-based hiring has helped address mismatches in the labour market. Furthermore, Wang and Cotton’s (2024) study found that using a skill-based hiring approach improves not only employee performance but also work team and institutional performance. In addition, past research has established the relevance of soft skills as a key component of the skill-based hiring method for improving individual performance and organisational success. These studies found that an employee’s capacity to communicate, evaluate issues, make decisions and cooperate is a critical component that contributes to excellent performance (Stewart & Preiksaitis, 2023). Consequently, the hypothesis is formulated as follows:

Both approaches (i.e. skill-based hiring and continuous learning) have been thoroughly examined, albeit separately. It is evident that addressing them collectively would benefit all parties (employees and employers). Focusing on job candidates’ skills and abilities rather than the traditional approach of relying on academic degrees and years of experience allows both the employee and the organisation to engage in continuous learning, particularly informal learning, to ensure that they acquire skills that they may not have been able to master through formal academic learning (Khandakar & Pangil, 2019; Muzam, 2022). Previous research has proven that hiring people based on their skills fosters an atmosphere conducive to continuous learning, particularly informal learning. These studies found a substantial positive association between the variables of skill-based hiring and continual learning (Khandakar & Pangil, 2019; Liu & Gopez, 2024). Continuous training and development are examples of best practices in human capital, which improve employee learning and retention (Bilan et al., 2020). This tendency is corroborated by the findings of Zwateen et al. (2024), who proved that continuous learning ensures employees’ competence and knowledge; hence, strengthening the relationship between skill-based employment and continuous learning. The changing job market requires companies to hire people based on their skills. This fits with Bilan et al.’s (2020) argument that it is important to value human capital and invest in it through ongoing learning. This will make employees more productive and help the company keep them. This is consistent with Zwateen et al.’s (2024) viewpoint, which states that continuous learning is essential for developing employees’ abilities and knowledge, which is why skill-based employment and continuous learning techniques are related. These arguments lead us to the following hypothesis:

A previous study has demonstrated a considerable interest in the critical role that continuous learning plays in increasing employee performance across all industries. According to research, continuous learning is crucial for employees and organisational development. Organisations that promote a culture of continuous learning have better employee and institutional performance (Mustafa & Lleshi, 2024). In a study on the relationship between continuous learning and job performance in India’s information technology (IT) industry, it was discovered that continuous learning practice had a significant positive impact on employee performance (Budhiraja, 2022). In the same vein, another study conducted in Ghana’s nursing business discovered that continuous learning in all forms is positively and closely related to employee performance. These studies suggest that lifetime learning in all of its forms not only improves employee performance but also fosters an atmosphere favourable to lifelong learning inside the business and supports individual achievement. According to Hasan’s study (2020), continuing education inside firms fosters a conducive work environment, which is critical for improving employee performance. In this context, Kapoor’s (2023) study revealed that learning platforms play an important role in resolving skill gaps and supporting results-based performance. It also indicated that this would improve the culture of skill development, eventually leading to higher employee performance. In a study on total quality management conducted by Fang (2023), it was shown that training programmes given to employees enhanced their acquisition of the necessary skills and knowledge, which led to improved job performance. Other previous studies indicated that a culture of continuous learning positively affects training outcomes and improves the level of job performance, and that continuous learning represents an important strategy for employee development and that adherence to it enhances both job and institutional performance (Kumar & Kumar, 2023; Mustafa & Lleshi, 2024). Numerous prior research studies have demonstrated that promoting continuous learning initiatives in various ways positively influences employee performance. Moreover, research demonstrates that the promotion of continuous learning methodologies fosters job happiness and dedication, which in turn enhances job performance (Adiansyah et al., 2021; Hendri, 2019). Numerous prior research studies have demonstrated that promoting continuous learning initiatives in various ways positively influences employee performance. Moreover, research demonstrates that the promotion of continuous learning methodologies fosters job satisfaction and dedication, which in turn enhances job performance (Adiansyah et al., 2021; Budhiraja, 2022; Hendri, 2019; Mustafa & Lleshi, 2024). Considering these arguments, we formulate the following hypothesis:

Prior research indicates that merely implementing skill-based hiring does not guarantee superior job performance. Continuous learning plays a crucial role as a significant catalyst in transforming the benefits of skill-based hiring into enhanced performance. This notion posits that continuous learning incentivises employees to participate in training and professional development programmes, which are crucial for improving employee performance (Budhiraja, 2021; Novrianto et al., 2024). Organisations that effectively foster a culture of continuous learning enhance employee satisfaction, job performance and stability. Organisations that promote continuous learning offer training programmes, initiatives and assistance that motivate employees to acquire and implement necessary skills and knowledge (Budhiraja, 2021; Novrianto et al., 2024). The mediating function of lifelong learning in the correlation between skill-based employment and work performance may be elucidated by its impact on enhancing employees’ abilities and knowledge. Consequently, increased participation in continuous learning initiatives and programmes enhances employees’ capabilities and skills in addressing problems and changes in their current positions (Pradhan et al., 2017). Additional research has demonstrated that learning, in its diverse manifestations, mediates the link between HRM practices and employee performance (Raj & Srivastava, 2013; Udin, 2023). Studies by Han et al. (2022) and Park and Choi (2016) indicated that both formal and informal learning significantly influence work performance. This affirms that continuous learning interacts with elements such as engagement and culture to foster an atmosphere conducive to elevated employee performance. Thus, we can formulate the following hypothesis:

The research evaluated variables utilising a 5-point Likert scale, with 1 denoting ‘strongly disagree’ and 5 indicating ‘strongly agree’. The questionnaire was derived from prior research to gather data from individuals employed in commercial banks. The 18-item questionnaire was utilised to assess skill-based hiring, as referenced in Bersin (2024) and Jørgensen and Christensen (2022). The employee performance scale with 10 items was selected from the research of Borman and Motowidlo (1997). The 12-item scale was used to evaluate continuous learning (Watkins & Marsick, 2019). We delivered 380 questionnaires to the indicated participants at the aforementioned banks and, with rigorous follow-up, obtained 365 questionnaires suitable for statistical analysis, yielding a 91% response rate. We conducted a thorough pre-testing procedure to ensure that the questionnaire was clear and relevant. We conducted this in two steps. Initially, researchers who were not biased based on gender checked the content to make sure it met academic standards and included all the needed parts. A pilot test with 25 participants from the target population provided insight into future enhancements. It gave information about the questionnaire’s practical features, such as the clarity and usefulness of its content. The ideas gathered from this pilot testing resulted in targeted enhancements to the questionnaire’s clarity and usability.

Table 1 presented the results of the descriptive analysis, high mean values indicate strong agreement among respondents, and high values of standard deviations reflect variability in their responses.

The first step in the analysis is to assess the measurement model in both convergent validity and discriminant validity. The results of the measurement model tests showed that convergent validity was confirmed when the factor loading was greater than or equal to 0.7, average variance extracted (AVE) equal to or greater than 0.5 and composite reliability (CR) equal to or greater than 0.7 (Hair et al., 2019). Table 2 showed that the results of Cronbach’s alpha and CR were above the 0.7 thresholds. The results of the AVE were above the 0.50 values.

The second step in the measurement model is to assess the discriminant validity. There are two methods to assess the discriminant validity; the first one is Heterotrait-Monotrait (Henseler et al., 2015), and the second one is Fornell-Larcker (Fornell & Larcker, 1981). The main alternative way to check the discriminant validity is Heterotrait-Monotrait (Henseler et al., 2015); the ratio of Heterotrait-Monotrait should be less than 0.90 as suggested by Henseler et al. (2015). All Heterotrait-Monotrait (HTMT) values shown in Table 3 are within the acceptable range. In addition, the Fornell-Larcker was satisfied as the square of each variable’s AVE is greater than the intercorrelations Table 4.

A structural model was applied to assess the inner model and as well as assessing the significance level of the (path coefficients-β) for hypothesis testing (Hair et al., 2019). The results in Table 5 and Figure 2 and Figure 3 showed that job performance is significantly and positively influenced by skill-based hiring (p = 0.000) and continuous learning (p = 0.000), and hence the hypotheses (H1 and H3) were accepted. In addition, the results also revealed that continuous learning is significantly and positively influenced by skill-based hiring (p = 0.048), and hence, hypothesis (H2) was also accepted. Finally, regarding the mediating effect of continuous learning, the results show that continuous learning has mediated the association between skill-based hiring and job performance, and hence, hypothesis (H4) was also accepted.