Soft skill competency and employees’ capacity as the intervening factors between training effectiveness and health workers’ performance

Abstract

This study aimed to determine the role of soft skill competency (SSC) and employees’ capacity (EC) in mediating the effect of training effectiveness (TE) on health workers’ performance (HWP). A quantitative approach was conducted by using the Structural Equation Modeling (SEM)-Amos version 23 analysis, with data obtained through accidental sampling from 222 health workers who filled out online questionnaires and were declared complete. The results showed that TE improved SSC and HWP, although it did not have a direct effect on increasing EC. This indicated that SSC was needed to mediate the relationship between these two variables. SSC and EC also mediated the effect of TE on HWP. These results were expected to enrich the limited references in explaining the relationship between human resources (HR) planning and HWP, specifically during the COVID-19 pandemic.

Keywords:

• training effectiveness
• soft skill competency
• employees’ capacity
• health workers’ performance

1. Introduction

Globalization is considered a tremendous challenge in organizational management, where difficulties have been increasingly encountered in the realization of employees’ performance, which is an absolute demand in every company. In this case, consistent and continuous efforts are highly required, specifically during the present COVID-19 pandemic. These difficult problems are reportedly experienced by several Arab countries with good health systems (United Nations, 2020a). Indonesia and some Southeast Asian nations are also experiencing similar challenges (United Nations, 2020b). In addition, a frightening study emphasized the assumption of an economic recession, which threatened the world (Bohoslavsky, 2020).

Based on these problems, a clear drug capable of curing the COVID-19 disease is highly needed. Besides medicine, the readiness of human health resources is also essentially required in handling emergencies. According to several study experts, good human resources (HR) planning was helpful to many organizations in handling changing environmental situations (Chakraborty, 2019), with Artificial Intelligence-based HR planning aiding human resource practices (Pandey, 2020). This showed that HR planning was able to improve organizational human resource performance, regarding various reports within private and public organizations. However, only a few of these analyses examined the performance of human resources in the health sector. This was in line with the data of Open Knowledge Maps, where only six publications prioritized the performance of health workers during 2019–2021 (Open Knowledge Maps, 2021). Based on the results, more analyses were still required despite the help of these publications on health organizations, where human resources were adequately prepared to overcome the present conditions.

Several experts also agreed that the developmental patterns of organizational employees’ systems are very crucial to the improvement of employees’ performance. From this context, training is the most common HR development considered to improve competency (Aci et al., 2021; Mislia et al., 2021) and employees’ capacity (EC) toward the enhancement of performance. Based on various studies, training contributed to the improvement of employees’ performance (Asfaw et al., 2015; Cooney et al., 2002; Khan et al., 2016; Onyango & Wanyoike, 2014; Rajeswari & Palanichamy, 2014; Thevanes & Dirojan, 2018) and service (Nurung et al., 2019, 2020).

Although some reports showed that training improved performance, different perspectives were still observed for others (Häfner & Stock, 2010), with the development element not emphasizing significant improvements. These perspectives triggered the curiosity of many experts in reexamining the contribution of training, specifically effective teaching processes to health workers’ performance (HWP) heavily affected by the present COVID-19 pandemic. Despite many reports emphasizing this development plan, more analyses are still needed regarding the patterns by which training effectiveness (TE) emphasizes HWP. Based on several experts, the low influence of training on improving performance depends on two factors, namely (1) ineffective teaching processes, and (2) the need for determinants capable of strengthening the impact between the two variables.

This study used conceptual framework models of soft skill competency (SSC) and EC, whose establishment is mostly promoted by effective training. The collaboration of these variables subsequently triggers an improvement in HWP. Therefore, this study aims to determine the role of SSC and EC in mediating the effect of TE on HWP. In this context, a conceptual framework is elaborated based on human capital theory, with assumptions emphasizing the intervention of HR TE. This condition is prioritized because the intangible assets existing in each organizational individual are increased to improve employees’ performance (Amankwah-Amoah et al., 2016; Crook et al., 2011; Nafukho et al., 2004; Strober, 1990). From this description, the intangible assets focus on competency, specifically soft skill and EC (Bontis & Fitz-Enz, 2002; Bontis et al., 2007). The intervention is also considered TE promoting employees’ skill toward the improvement of performance. Meanwhile, EC is obtained from TE, leading to performance development. The results obtained are expected to enrich the references needed to strengthen human health resources toward the improvement of performance.

2. Literature review

2.1. Theoretical background and hypothesis development

Training is generally considered a heated debate due to being an alternative solution in the improvement of performance (Azas et al., 2019; Nasri et al., 2018; Salama Tamsah & Natsir, 2017), regarding the reports in several countries (Asfaw et al., 2015; Cooney et al., 2002; Khan et al., 2016; Onyango & Wanyoike, 2014; Rajeswari & Palanichamy, 2014; Thevanes & Dirojan, 2018). Based on the perspectives of engagement theory, various antecedent levels of TE were prioritized (Sitzmann & Weinhardt, 2018). This hierarchically described the processes at every organizational level, which influenced each other and interacted with the success or failure of training. The temporal nature of this theory also supported the consideration of each analyzed process before the preparation, conceptualization, and completion of training (Kearsley et al., 1998; Sitzmann & Weinhardt, 2018). Furthermore, a sequence model of independent and combined effects of establishing objectives, priorities, and continuity was proposed (Sitzmann & Weinhardt, 2019; Toth et al., 2021). Effective training also produced a series of outputs needed in organizational development based on continuous HR improvement.

SSC is an output produced by participants from effective training (Umar et al., 2020), and is increasingly echoed in this millennial era. It also indicates personal competencies such as social talent, communication and language skills, hospitality, ability to work in groups and organizations, etc (Dwi Riyanti et al., 2016; Mahfud et al., 2017; Sain & Wilde, 2014; Seetha, 2014; Sisson & Adams, 2013). These skills are strategic for success in professional and personal life, specifically during a job acquisition (Cimatti, 2016). Furthermore, resource management is used in the recruitment stage and during a professional appointment as an employee. External, organizational, and service quality, as well as employees’ standard of living, are also strongly supported by the soft skill possessed at every level (Luk & Layton, 2004; Mahfud et al., 2017). The skill serves as the bedrock for the quality assurance of human capital job performance in the company (Cimatti, 2016). From this context, employees often turn out focused and effective when self-efficacy is applied in carrying out specific activities (Mensah & Lebbaeus, 2013; Orgambídez et al., 2020; Çetin & Aşkun, 2018). In addition, employees with high self-efficacy are more capable, resistant, and active in printing results and obtaining planned learning outcomes.

This study produces several factors including the perception of progress towards goals and potential consequences, such as existing business regulations (Bandura, 2015; Wood & Bandura, 1989). This explains that self-efficacy is obtained from self-confidence, regarding an individual ability to succeed during job performance. Besides this, employees with high self-efficacy also achieve the maximum level of skill to efficiently conduct daily duties and responsibilities (Çetin & Aşkun, 2018). This level of self-efficacy is observed from their SSC due to the easier achievement of performance (Dean & East, 2017; Ibrahim et al., 2017; Shafie et al., 2014; Wilks & Hemsworth, 2011). Based on these relationships, the following hypotheses are proposed:

H1:

Training effectiveness significantly and positively affects soft skill competency

H2:

Soft skill competency significantly and positively influences employees’ capacity

H3:

Soft skill competency significantly and positively impacts health workers’ performance

Involvement is also needed to hierarchically interrelate the training processes at various organizational levels, while contributing to the achievement of goals (Anitha, 2014; Lockwood, 2007). In this process, employees are expected to focus on achieving the objectives of program completion, which should be adequately and thoughtfully conducted to improve knowledge and skills (Alainati et al., 2010). Besides, the success of training is also determined by the initiative, independence, and cognitive abilities of the adhering employees (Sitzmann & Weinhardt, 2019). From this context, training clarity is expected to increase when there is clear communication between HR system and employees. Effectiveness is also increasingly anticipated when training is demonstrated as a primary goal (Ostroff & Bowen, 2000). This is capable of strengthening the communication between HR system and employees.

In performance, competency and soft skill are commonly improved by directly targeting their functions. For example, working methods training highly support the growth and development of employees’ abilities (Alainati et al., 2010; Chen & Naquin, 2006; Kamen et al., 2010). Soft skill is also transferred from one environment to produce different benefits and develop employees (Avanzi et al., 2014). Moreover, learning is always used as the most effective method of training. The ability and need to adapt to new tasks are also responsible for activating the knowledge of desired thoughts and perspectives. This is carried out by strengthening cognitive and emotional self-regulation in learning (Hautamäki et al., 2002), while increasing employees’ work creativity (Kamen et al., 2010; Liu et al., 2020). From this description, employees with high creativity are expected to efficiently complete tasks (Cook, 2018) and design appropriate work methods to achieve effectiveness and efficiency (Cook, 2018; Ohly, 2018). This proves that employees with work experience and training at various levels are capable of producing competent creativity to adequately complete the job performance (Baer, 1991, 1994; Gong et al., 2018; Qureshi, 2016). Based on these relationships, the following hypotheses are proposed:

H4:

Training effectiveness positively and significantly affect employees’ capacity

H5:

Employees’ capacity significantly and positively influence health workers’ performance

Setting training goals and priorities is a causal mechanism that triggers all the behaviors to be motivated (Locke & Latham, 2002). This explains that the first step for employees to attend training is to set goals and focus on achieving specific objectives, such as the attempt to timely complete the teaching process and increase productivity (Gambo, 2015). From this context, knowledge and skills are often increased (Ostaszewski et al., 2018; Yusof et al., 2012) while establishing new performance goals (Asfaw et al., 2015; Dermol & Čater, 2013; Dos Santos, 2019; Karimi & Nejad, 2018; Khan et al., 2016). These goals are generated for organizational effectiveness by the initiative, independence, and cognitive abilities obtained from training outputs (Asfaw et al., 2015; Rahman et al., 2013; T. C. Huang, 2001; Truitt, 2011).

The prioritization of continuous HR development with the best soft skill is also very essential (Karwowski & Soszynski, 2008; Rahman et al., 2013; Truitt, 2011). This ability develops publicly available forms or outcomes of competition and enables many organizations to work effectively and efficiently during the coordination of organizational programs (Borate & Borate, 2016; Liu et al., 2020; Rahman et al., 2013). From this description, increasingly effective soft skill support requires more than technical abilities, even in technology-intensive industries. Furthermore, coordination and collaboration between business owners and employees are essential to achieve a competitive level of quality (Cimatti, 2016). In this case, HR management is found to play a role in the recruitment process for employees, regarding their existence within the professional organizational duties. The qualities of employees’ products, organization, service and life also prioritize the soft skill possessed by the personnel at any level (Cinque, 2016, 2017). Based on these relationships, the following hypotheses are proposed:

H6:

Training effectiveness significantly and positively affects health workers’ performance

H7:

Training effectiveness significantly and positively influences health workers’ performance through soft skill competency and employees’ capacity

H8:

Training effectiveness significantly and positively impacts health workers’ performance through soft skill competency

H9:

Training effectiveness significantly and positively affect health workers’ performance through employees’ capacity

2.2. Conceptual framework

Figure 1 shows the references used in building the relationship between variables regarding the hypotheses developed in the conceptual framework, while Table 1 presents the measurement of variables and indicators.

Figure 1. Conceptual Framework.

Table 1. Measurement of variables

Variable	Indicator	Items
Training Effectiveness (TE)	additional knowledge (TE1)	I always have additional knowledge after every training I always have additional work skills after every training
	ability to remember (TE2)	I can remember the activities carried out during the training I can understand activities carried out during training
	ability to practice (TE3)	I can apply the training outputs in my present job I can put into practice the experience gained from training in my current work
Soft Skill Competency (SSC)	searching for information (SSC1)	I can find the latest information to add skills
	orientation on efficiency (SSC2)	I have simple work skills and always prioritize efficiency at work
	systematic planning (SSC3)	I can make systematic plans and steps in my work
	problem-solving (SSC4)	I am responsive, alert to problems, and able to always find a solution faced by the work team
	the persuasive ability (SSC5)	I can communicate ideas and convince others to follow what I want
Employees’ Capacity (EC)	employees’ cooperation (EC1)	I can work well with fellow employees to increase work capacity
	employees’ commitment (EC2)	I have a high commitment to work through a capacity development
	employees’ involvement (EC3)	I always prioritize employee involvement as a whole to increase work capacity
	employees’ capacity building initiatives (EC4)	I always initiate businesses or activities in the context of developing employees’ capacity
Health Workers’ Performance (HWP)	responsiveness (HWP1)	I have high responsiveness, specifically about work, to improve my performance
	availability (HWP2)	I always maintain attendance and availability of time for work
	productivity (HWP3)	I always maintain and prioritize work productivity to improve performance
	use of competence (HWP4)	I always improve my competence to improve my performance

3. Methods

3.1. Sample criteria

This study was conducted on health workers in South Sulawesi Province during the COVID-19 pandemic. As the largest province in eastern Indonesia, the number of patients was also very high. Therefore, the analysis of health workers performance in handling a pandemic was very important during this period. In this study, all the South Sulawesi health workers at 18,240 were the study population, with the determination of the samples emphasizing Hair et al. (2010). From this context, a minimum of 100 people was implemented for the models using structural equations with five or more variables. By using the Soper sample size calculator for structural equation modeling (Soper, 2022), the appropriate number of samples was determined through a statistical power level of 0.95. This indicated that the sample size of the 4 latent and 16 observed variables should be 137 at a probability level of 0.05.

Data collection was also carried out through the distribution of online questionnaires, which were filled out by 222 participants within two months. The data instrument consisted of several professions, namely Doctors (n = 13), Nurses (n = 49), Midwives (n = 35), Physiotherapists (n = 12), Dentists (n = 25), Health Analysts (n = 15), Sanitarians (n = 9), Nutritionists (n = 9), Radiographers (n = 10), Medical Record Experts (n = 10), Public Healthcare Graduates (n = 35), and Electromedical Scholars (n = 2). The participants also had the following education level, namely Diploma 1–3 (n = 83), as well as Bachelor’s (n = 106) and Master’s (n = 33) Degrees. Furthermore, 97 (43.69%) and 125 (56.31%) of the entire sample were male and female, respectively, with their ages ranging from 20–30 (n = 31), 31–40 (n = 75), 41–50 (n = 91), and 51–60 (n = 25) years old. From these descriptions, the number of participants had exceeded the required minimum sample size.

3.2. Measurement

Table 1 shows the data obtained from the participants’ answers to statement items, which were measured by a 7-point Likert scale (1 = strongly disagree, 2 = disagree, 3 = moderately disagree, 4 = neutral, 5 = moderately agree, 6 = agree, 7 = strongly agree). TE was also measured by additional knowledge, ability to remember, and subsequent study practice (Perdue et al., 2002; Wilson et al., 2002) in public organizations (Umar et al., 2020). For SSC, measurement was conducted by searching for information, orientation on efficiency, systematic planning, problem-solving, and persuasive ability (Dwi Riyanti et al., 2016; Umar et al., 2020; Wikle & Fagin, 2015). Meanwhile, EC was measured by cooperation, commitment, involvement, and capacity-building initiatives (Kimutai et al., 2013), with HWP being analyzed through responsiveness, availability, productivity, and use of competence (Kimutai et al., 2013; Lutwama et al., 2012).

The data collection process underwent two testing stages before measuring the effect between variables. Firstly, the Confirmatory Factor Analysis (CFA) was used to confirm that each indicator was capable of accurately measuring its latent variables (Ghozali, 2017). In this stage, an indicator is declared measurable and appropriate when loading factor and Critical Ratio coefficients greater than 0.5 and 2 are observed, respectively. CFA was also responsible for the construct validity assessment of the conceptualized measurement theory, by using the CR (Construct Reliability) and Average Variance Extracted (AVE) values. Based on the CR and AVE values, the validity of the data on a construct was greater than 0.7 and 0.5, respectively. From these results, the measurement of variables were obtained from a sample describing the actual population score.

Secondly, a model fit testing was carried out to determine the extent to which the data obtained confirmed the conceptualized framework (Anderson & Gerbing, 1988). From this context, the Goodness of Fit (GoF) value indicated various outcomes through the AMOS output. This showed that the model data were declared to have conformity when the GoF criterion had a small expected Chi-Square value, RMSEA<0.08, GFI>0.90, AGFI>0.90, the Degree of Freedom<2.0, as well as CFI and TLI>0.95.

4. Results

4.1. CFA and model fit testing

From the obtained data, Table 2 shows the CFA and model fit outputs.

Table 2. Statistical result

Variables	Indicators	Standardized Estimate	Estimate	Standard Error	Critical Ratio	P-Value	Construct Reliability (CR ≥ 0.7)		Average Variance Extracted (AVE ≥ 0.5)
Training Effectiveness (TE)	additional knowledge (TE1)	.826	.935	.060	15.701	***	.89		.73
	ability to remember (TE2)	.850	.951	.058	16.409	***
	ability to practice (TE3)	.887	1.000	-	-	***
Soft Skill Competency (SSC)	searching for information (SSC1)	.754	1.000	-	-	***	.88		.61
	orientation on efficiency (SSC2)	.786	.953	.079	12.013	***
	systematic planning (SSC3)	.857	1.104	.082	13.408	***
	problem-solving (SSC4)	.850	1.088	.082	13.245	***
	the persuasive ability (SSC5)	.669	1.019	.101	10.055	***
Employees’ Capacity (EC)	Employees’ cooperation (EC1)	.813	1.000	-	-	***	.90		.70
	Employees’ commitment (EC2)	.873	1.110	.072	15.372	***
	Employees’ involvement (EC3)	.734	.961	.081	11.841	***
	Employees’ capacity building initiatives (EC4)	.748	1.102	.090	12.273	***
Health Workers’ Performance (HWP)	responsiveness (HWP1)	.817	1.000	-	-	***	.87		.62
	availability (HWP2)	.738	.810	.067	12.162	***
	productivity (HWP3)	.818	.867	.063	13.829	***
	use of competence (HWP4)	.793	.810	.061	13.387	***
Model Fit Testing		Cut of Value				Result		Remark
Chi-Square		df = 98, X2 = 122.107				164,095		Marginal
Significance		0.05				.000		Marginal
CMINDF		2				1,674		Fit
GFI		0.90				.917		Fit
AGFI		0.90				.885		Marginal
TLI		0.95				.969		Fit
CFI		0.95				.974		Fit
RMSEA		0.03–0.08				.055		Fit

Note: *** (Significant at Level p < 0.01)

Based on Table 2, each indicator had a loading factor value>0.5, critical ratio>2, and p-value<0.05, proving their abilities to measure the validity of latent variables. The CR and AVE values were also 0.7 and 0.5, respectively, indicating an excellent reliability level from the data obtained (Ghozali, 2017). Furthermore, the model structurally complied with the fit testing approach, where the GoF value met the suitability standard. This was specifically observed for the values of CMIN/DF, GFI, TLI, CFI, and RMSEA at 1.674 (≤2), 0.917 (≥0.9), 0.969 (≥0.9), 0.974 (≥0.9), and 0.05, respectively. From these results, the suitability of the conceptualized model was confirmed from a modelling perspective.

According to data processing, TE was analyzed by three indicators, namely additional knowledge (TE1= .826), ability to remember (TE2= .850), and capability to practice (TE3= .887), with the reliability analysis showing CR = 0.89 and AVE = 0.73. Furthermore, SSC was measured by information search (SSC1= .754), efficiency orientation (SSC2= .786), systematic planning (SSC3= .857), problem-solving (SSC4=.850), and persuasive ability (SSC5= .669), with the reliability test indicated by CR = 0.88 and AVE = 0.61. EC was also analyzed by cooperation (EC1= .813), commitment (EC2= .873), involvement (EC3= .734), and capacity building initiatives (EC4= .748), where the reliability analysis emphasized CR = 0.90 and AVE = 0.70. Meanwhile, HWP was measured by responsiveness (HWP1=.817), availability (HWP2= .738), productivity (HWP3= .818), and use of competence (HWP4= .793), where the reliability test prioritized CR = 0.87 and AVE = 0.62. Based on these results, the final model is shown in Figure 2

Figure 2. Structural equation model.

4.2. Hypothesis testing

By using a feasible data, the hypothesis testing outputs are shown in Table 3.

Table 3. Hypothesis Testing

Hypothesis	Standardized estimate	Estimate	Standard Error	Critical Ratio	P-Value	Result
H1: Training Effectiveness →Soft Skill Competency	.839	.396	.035	11.434	***	Supported
H2: Soft Skill Competency Health Workers’ Performance	.243	.255	.131	1.943	.052	Not Supported
H3: Soft Skill Competency → Employees’ Capacity	.793	.725	.115	6.315	***	Supported
H4: Training Effectiveness → Employees’ Capacity	.078	.034	.048	.696	.487	Not Supported
H5: Employees’ Capacity → Health Workers’ Performance	.586	.672	.117	5.734	***	Supported
H6: Training Effectiveness → Health Workers’ Performance	.190	.094	.042	2.245	.025	Supported
H7: Training Effectiveness →Soft Skill Competency & Employees’ Capacity → Health Workers’ Performance	.640	Estimates/Bootstrap (two-tailed significance-BC)			.011	Supported
H8: Training Effectiveness → Soft Skill Competency → Employees’ Capacity	.665	Estimates/Bootstrap (two-tailed significance-BC)			.014	Supported
H9: Soft Skill Competency → Employees’ Capacity → Health Workers’ Performance	.465	Estimates/Bootstrap (two-tailed significance-BC)			.008	Supported

Note: *** (Significant at Level P < 0.01)

Based on Table 3, the AMOS output showed that TE positively and significantly affected SSC (ƴ = .839; p-value = .000), leading to the acceptance of H1. However, SSC positively and insignificantly influenced HWP (β = .243; p-value = .052), causing the rejection of H2. The AMOS output also proved that SSC positively and significantly impacted EC (β = .793; p-value = .000), confirming the acceptance of H3. From the results, rejection was subsequently observed for H4, as TE did not significantly affect EC (ƴ = .078; p-value = .487). EC and TE also positively and significantly influenced HWP (β = .586; p-value = .000 and ƴ = .190; p-value = .025), leading to the acceptance of H5 and H6, respectively. According to Estimates/Bootstrap (two-tailed significance-BC), the relationships between TE & HWP and TE & EC were mediated by SSC at p-value = .011 and .014, causing the acceptance of H7 and H8, respectively. The relationship between SSC and HWP was also mediated by EC at p-value = .008, confirming the acceptance of H9.

5. Discussion

Based on the results, the ability to practice was the most significant indicator that provided a measurement of TE, leading to the encouragement of SSC. These results were in line with several previous reports, where training and practice played essential roles in improving personal abilities, specifically in the health sector (Ahmad et al., 2022; Calavia et al., 2023; Taddio et al., 2022). As a series of efforts to improve HR quality, TE was also demonstrated by increasing knowledge, as well as the abilities to remember and practice the process, causing the encouragement of soft skill improvements in employees. This result was supported by various recent studies, where the importance of training was confirmed for the development of skills (Gomez et al., 2023). It was also in line with Dammert and Nansamba (2023), where training strengthened messages in achieving long-term organizational goals by improving the soft skill possessed by HR. These results are essential for the medical workers primarily handling new cases in the health sector. Based on the soft skill measurement, systematic planning was the primary indicator providing the largest contribution. This showed that TE promoted HR to have systematic planning abilities. The soft skill was subsequently expected to support the readiness of health workers, regarding the confrontation of future challenges. In this case, the ability to systematically plan and solve problems was the component mainly considered in increasing the assessment of soft skill and improving HWP.

From the results, soft skill did not significantly adjust the impact of training on HWP. According to Cimatti (2016), this element showed several interpersonal skills, namely talent, language and communication skills, friendly nature and teamwork ability, etc. This indicated that the skills were advantageous in the interpersonal relationships involving everyone within multiple organizations. Although they were needed everywhere, soft skill still showed all the abilities and skills that are not directly related to work attributes or tasks. This result was not in line with Ibrahim et al. (2017), where different organizations need to understand HR capabilities, such as SSC, to obtain good performance. By identifying the soft skill possessed by HR, multiple companies need to provide appropriate training to encourage and improve organizational performance. The result also showed that any increase in SSC promoted EC, whose indicators included commitment, collaboration, capacity-building initiatives, and engagement. The contribution of systematic planning and problem-solving also promoted the development of EC in establishing SSC. These conditions subsequently illustrated the extent to which employees performing systematic planning promoted organizational commitment and cooperation. This was in line with Cimatti (2016), where soft skill was one of the most influential factors in measuring a person’s ability level at work. Y. Huang et al. (2014), Layuk et al. (2017), and Mendes and MacHado (2015) also confirmed that employees were capable of applying their abilities more systematically through the good soft skill to drive better performance.

According to the relationship between TE and EC, the ability to practice and remember, as well as additional knowledge, did not significantly impact increasing EC, specifically commitment and cooperation, which play major measurement roles. However, each increase in the indicators provided a significant improvement in HWP. The occurrence of TE is often observed when targeted outputs are realized and employees are satisfied with the teaching experience, leading to the improvement of motivation, knowledge, and skills (Sitzmann & Weinhardt, 2018). From this context, a transfer of knowledge and skill commonly caused significant changes in post-training work after participation. Training is also effective when most participants complete the process and the company obtains a return on their investment in increased organizational performance (Ployhart et al., 2014; Sitzmann & Weinhardt, 2018). Although EC is not affected by TE, some observations were still emphasized regarding the failure to acquire knowledge and skill in the teaching process. Based on these results, the transfer of knowledge and skill was not perfectly conducted due to low motivation in training participation. This was because employees considered the training objectives irrelevant or monotonous, causing boredom. Subsequently, these conditions are the reason employees do not complete the training process.

According to Table 3, employees’ commitment was the main indicator providing the most important measurement of EC. This indicated that the growing commitment of health workers promoted the improvement of performance, specifically their productivity and ability to respond to duties and responsibilities. These results were in line with several previous studies, where the development patterns of HWP were observed with increased EC (Kimutai et al., 2013; Latif, 2012). It also stated that an increase in EC only occurred when the authority or HR department invested in developing HR performance. Since HR is an essential capital for the organization, HR quality development should be highly considered by the management. Based on these results, training was considered one of the main focuses in measuring HWP (Sellers et al., 2019). Although it had a significant effect, the standardized estimate value still showed a minimal effect of TE on HWP. This study was understandably carried out during the COVID-19 pandemic, where many health workers were unprepared to handle various situations. In this case, previous training processes had not significantly influenced HWP in handling COVID-19 patients. Despite all limitations, the efforts of health workers were still appreciated during the pandemic period. This led to the encouragement of the special training processes for health workers in handling unexpected conditions and having extensive impacts.

From these results, training is capable of effectively improving performance when appropriately implemented by health workers (Dieleman & Harnmeijer, 2006). According to previous studies, the practical ability of these workers determined the level of TE and increased performance (Khan et al., 2016; Onyango & Wanyoike, 2014; Patri & Suresh, 2018; Ramadevi et al., 2016). These results were reinforced by Dammert and Nansamba (2023), where no strong relationship was observed between training intensity and the improvement of HR performance. Furthermore, TE improved SSC and EC as a trigger for HWP. This showed that SSC and EC were good mediators in the relationship, as the contribution of TE toward the improvement of performance was directly or indirectly optimal. Therefore, SSC was a mediator affecting EC, with training playing a good role in improving performance when HR adequately transferred the teaching process outputs into daily activities. This result subsequently aligned with several previous studies (Asfaw et al., 2015; Sitzmann & Weinhardt, 2018, 2019). SSC also indirectly improved HWP through EC, showing that the contribution of soft skills consistency toward employee capacity development was decisive in improving health worker performance. From this context, EC was considered an important variable that was used to increase HWP through SSC development. This proved that health workers with improved soft skill were capable of improving their work capacity and performance.

6. Conclusion and implications

Based on the results, TE improved SSC and HWP, although it indirectly improved EC. Besides, it also optimally improved HWP through SSC and EC. This indicated that soft skill consistency contributed to the improvement of employee capacity, while highlighting the need to directly improve HWP. It also confirmed that the enhancement of HWP was achieved through EC. Although SSC indirectly improved HWP, it still optimally contributed to EC. The results also showed that EC importantly promoted HWP due to the enhancement of SSC. This proved that health workers with improved soft skill were motivated toward possessing better capacity and performance. Besides indirectly improving and triggering health worker performance (HWP), soft skill consistency (SSC) also promoted the development of employee capacity (EC). This development condition showed that EC was a good mediator. From this context, the direct contribution of TE was optimal in promoting HWP improvement. Meanwhile, indirect inputs were observed to be better through SSC and EC. Based on these results, SSC and EC were good mediators in improving HWP.

Overall, the findings in this study show that human resource development has a huge role in dealing with very precarious situations such as a pandemic. Good management of training results is the key to human resource development in order to boost employee capacity and further encourage performance improvement. Theoretically, this research reinforces human capital theory, where effective training contributes significantly to human resource development. This research shows that training contributes to improving the intangible assets of each individual in the organization, which can further encourage performance improvement. Managerially, it can be explained that training is needed in order to improve soft skills. Therefore, HR development managers must pay attention to improving training management because only effective training can contribute to employee performance, especially in health organizations.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest regarding the study, authorship, and/or publication of this article.

ORCID iD

Hasmin Tamsah https://orcid.org/0000–0002–9570–9658

Acknowledgments

The authors are grateful to the health workers who filled out the questionnaire despite the COVID-19 pandemic. The authors are also grateful to the leadership and the academic community at their institution.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The author(s) obtained no financial support for this study, authorship, and/or publication.

Notes on contributors

Hasmin Tamsah

Hasmin Tamsah is an Assistant Professor at Department of Management, STIE Amkop Makassar, Indonesia. His research interest include Human Resources Management, Human Development Theory and Environmental Economics. His research that has been carried out includes Poverty Analysis, Poverty Alleviation Model, Economic Valuation of Coral Reefs and others. His current project is Calculating regional assets with an economic valuation approach

Gunawan Bata Ilyas

Gunawan Bata Ilyas is an AssociateProfessor at Departement of Management, STIE Amkop Makassar, Indonesia. His research interest include Marketing Management, Human Resource and Business Management.

Jumiaty Nurung

Jumiaty Nurung is an Assistant Professor at Department of Management, STIE Amkop Makassar, Indonesia. Her research interest include Human Resources Management, Human Capital and Business Administration.

Ekafadly Jusuf

Ekafadly Yusuf is an Assistant Professor at Department of Management, STIE Amkop Makassar, Indonesia. His research interest include Management, Human Resource, Economics and Public Administration.

Sri Rahmi

Sri Rahmi is an Assistant Professor at Department of Management, STIE Amkop Makassar, Indonesia. Her research interest include Marketing, Management, Consumer Behavior, Human Resource and Digital Information.